The influence of social media promotion mix on the car insurance purchasing of residents in Mahikeng JN Ndeudjeu orcid.org/0000-0002-2694-7492 Dissertation accepted in fulfilment of the requirements for the degree Master of Commerce in Marketing Management at the North West University Supervisor: Prof M Potgieter Graduation ceremony: May 2021 Student number: 26195658 DECLARATION I, Ndeudjeu Joseline Nadia, declare that the dissertation entitled “Influence of the social media promotion on the car insurance purchasing of residents in Mahikeng” is my work in design and execution and has not been submitted for any degree purposes at this or any other university. I declare that all materials and sources used or quoted in this work have been duly acknowledged by means of complete references. Signature: .............................Date: …………………………… i DEDICATION This study is dedicated to my parents, my late father, Mr Ouelanuech Emil who left me the greatest inheritance of loving school and my mother Ndjimen Marie-Claire for her love and care. I also recognize my brothers A. Kameni, J. Njossi and B. Kwemo. A special dedication goes to my carrying and lovely fiancé Djamfa Mbiakop William and our lovely daughter Djamfa Mbiakop Njiane Nayza. ii ACKNOWLEDGEMENTS ‘‘A dream doesn’t become reality through magic; it takes sweat, determination and hard work’’ – Colin Powell. These three elements are correct but without the support of the following pillars in my life, completing my master’s programme would not have been possible:  My supervisor, Prof Marius Potgieter, whose expertise, support and patience added considerably to the completion of my study. I appreciate his continuous assistance with the writing of every chapter and the endless amount of time spent editing and improving my writing.  My family, for their encouragement and overwhelming support in my education.  My friends, for being there and motivating me every step of the way.  Lastly, thanks to the Lord for helping me every step of the way, through difficulty and joy. Psalm 118: 22 – The stone that the builders rejected has become the cornerstone. iii ABSTRACT Over the past four years, the number of uninsured cars on the South African roads has increased by 65% due to the fact that consumers do not trust the insurance providers, the excessive rate of premiums and they found insurance needless as they have never been involved in accidents. The use of social media would be extremely beneficial to educate consumers, as the use of marketing via social media would be another opportunity of interacting with people, but still in a large extent unexploited by the insurance industry. In the light of the aforementioned, it is important for insurance companies to integrate social media in their marketing, as well as interacting with consumers in order to create awareness. Ethically, the research raises serious questions about the influence of the social media on the car insurance purchasing decisions of residents in Mahikeng. To answer this question, the study was conducted through the utilization of an online questionnaire completed by residents in Mahikeng through email and company platforms. Respondents are car owners, who may have subscribed or not to a short-term car insurance service. For this study, the presentation of the results starts firstly with a descriptive analysis and a cross-tabulation to describe the demographic and economic variables in relation to car insurance purchase decision. The results showed that most respondents had their cars insured and expressed a strong interest to social media. Secondly the study makes use of the Chi- square to test the significant relationship between each construct and the online purchase decision. The results show that attitude, service quality, perceived trust and social media are significantly associated with online purchase decision. Lastly, logistical regression was employed to investigate the effect of the online purchase decision and social media promotion mix. The results show that the social media significantly influenced the purchase decision of car insurance online. From a safety perspective, the government should make third party car insurance compulsory and this will emphasize the need for insurance companies to take into account social media to create awareness and educate car owners in Mahikeng. This implies that car insurance companies must focus on social media such as live video, sponsored events, personal selling and advertisement in order to influence residents in Mahikeng to purchase car insurance via social media. The insurance companies should also educate their consumers on the available insurance discounts, claim process while creating experiences for consumers through event and newsletters. By doing so, insurance companies will be able to build trust, reduce complaints and enhance consumer loyalty. In conclusion, insurance companies should invest iv more effort on their marketing campaigns, in order to increase the number of insured cars on the South Africans roads. In addition, insurance companies should not consider credit scores when calculating premiums as this unfairly penalizes lower-income car owners. Key words: Car insurance, integrated marketing communication (IMC), purchase decision making, promotion mix, social media. v TABLE OF CONTENTS DECLARATION..................................................................................................................... i DEDICATION........................................................................................................................ ii ACKNOWLEDGEMENTS ................................................................................................ iii ABSTRACT ........................................................................................................................... iv LIST OF TABLES ................................................................................................................ xi LIST OF FIGURES ........................................................................................................... xiii LIST OF ABRREVIATIONS…...………………………………...………………………………xvi CHAPTER ONE ...................................................................................................................... 1 INTRODUCTION OF THE STUDY ................................................................................... 1 1.1 Introduction ........................................................................................................................ 1 1.2 Background of the study .................................................................................................... 2 1.3 Problem statement .............................................................................................................. 4 1.4 Research objectives and questions ..................................................................................... 5 1.4.1 Research objectives ......................................................................................................... 5 1.4.2 Research questions .......................................................................................................... 6 1.5 Research hypothesis ........................................................................................................... 6 1.6 Motivation of the study ...................................................................................................... 7 1.7 Literature review ................................................................................................................ 8 1.8 Research gap .................................................................................................................... 10 1.9 Conceptual framework ..................................................................................................... 11 1.10 Research methodology ................................................................................................... 12 1.10.1 Study area.................................................................................................................... 13 1.10.2 Sampling process ........................................................................................................ 13 1.10.3 Research design .......................................................................................................... 16 1.10.4 Pretesting the questionnaire ........................................................................................ 17 1.10.5 Data collection ............................................................................................................ 18 1.10.6 Data analysis ............................................................................................................... 18 1.11 Delimitation ................................................................................................................... 19 1.12 Definitions of key terms ................................................................................................. 19 1.12 Ethical consideration ...................................................................................................... 21 1.13 Chapter outline ............................................................................................................... 21 vi CHAPTER TWO ................................................................................................................... 24 MARKETING AND INTEGRATED MARKETING COMMUNICATION ................ 24 2.1 Introduction ...................................................................................................................... 24 2.2 Marketing ......................................................................................................................... 25 2.2.1 Marketing philosophies ................................................................................................. 27 2.2.2 Marketing mix components .......................................................................................... 31 2.3 Marketing communication ............................................................................................... 42 2.3.1 The nature of marketing communication ...................................................................... 42 2.3.2 Communication process ................................................................................................ 43 2.3.3 Components of the marketing communication mix ...................................................... 45 2.4 Integrated service marketing communication (IMC) ....................................................... 57 2.4.1 Social media and integrated marketing communication ............................................... 58 2.4.2 Integrated marketing communication strategic planning process ................................. 59 2.5 The importance of integrated marketing communication in the insurance ...................... 63 2.6 Summary .......................................................................................................................... 65 CHAPTER THREE ............................................................................................................... 66 SOCIAL MEDIA AND CONSUMER BEHAVIOUR ...................................................... 66 3.1 Introduction ...................................................................................................................... 66 3.2 Internet penetration in South Africa ................................................................................ 67 3.3 Overview of social media ................................................................................................ 70 3.4 Short-term insurance in South Africa .............................................................................. 74 3.5 Digital technology in short-term insurance companies ................................................... 77 3.5.1 The importance of social media for short-term insurance ............................................ 78 3.5.2 A different form of social media used for short-term insurance ................................... 79 3.6 Consumer behaviour ........................................................................................................ 85 3.6.1 Overview of consumer behaviour ................................................................................. 85 3.6.2 Online consumers in South Africa ................................................................................ 88 3.6.3 Online consumer engagement and decision making ..................................................... 90 3.7 Conceptual framework ..................................................................................................... 94 3.7.1 Perceived behavioural control....................................................................................... 96 3.7.2 Perceived usefulness ..................................................................................................... 96 vii 3.7.3 Attitude ......................................................................................................................... 97 3.7.4 Social influence ............................................................................................................. 98 3.7.5 Purchase intention ......................................................................................................... 99 3.8 Factors influencing online purchase intentions.............................................................. 100 3.8.1 Trust ............................................................................................................................ 101 3.8.2 Promotion mix ............................................................................................................ 102 3.8.3 Perceived security ....................................................................................................... 103 3.8.4 Perceived tangibility ................................................................................................... 103 3.8.5 Service quality ............................................................................................................ 104 3.8.6 Social media platform ................................................................................................. 105 3.9 Summary ........................................................................................................................ 106 CHAPTER FOUR ................................................................................................................ 107 RESEARCH METHODOLOGY ..................................................................................... 107 4.1 Introduction .................................................................................................................... 107 4.2 Research philosophy ...................................................................................................... 108 4.2.1. Realism research philosophy ..................................................................................... 109 4.2.2. Interpretivist research philosophy .............................................................................. 109 4.2.3. Pragmatism research philosophy ............................................................................... 109 4.2.4. Positivism research philosophy.................................................................................. 110 4.3. Research approach ........................................................................................................ 111 4.3.1. Qualitative research approach .................................................................................... 111 4.3.2. Quantitative research approach .................................................................................. 111 4.3.3. Mixed research approach ........................................................................................... 112 4.3.4. Research approach used in this study ........................................................................ 112 4.4. Research design ............................................................................................................ 113 4.5. Study area...................................................................................................................... 113 4.6. Sampling design ............................................................................................................ 115 4.6.1. The target population and sampling ........................................................................... 115 4.6.2. Select the sampling frame .......................................................................................... 116 4.6.3. Select sampling method ............................................................................................. 116 4.6.4. Determine sample size ............................................................................................... 119 4.7. Data collection procedure ............................................................................................. 122 viii 4.7.1. Identify information types and sources ...................................................................... 122 4.7.2. Research instrument ................................................................................................... 123 4.7.3. Data collection method .............................................................................................. 134 4.8. Data analysis and statistical techniques ........................................................................ 137 4.8.1. Checking of the questionnaire ................................................................................... 138 4.8.2. Data editing and screening ......................................................................................... 139 4.8.3. Coding ........................................................................................................................ 140 4.8.4. Data entry ................................................................................................................... 141 4.8.5. Data cleaning ............................................................................................................. 141 4.8.6. Statistical technique for data analysis ........................................................................ 141 4.9. Ethical considerations ................................................................................................... 146 4.10. Summary ..................................................................................................................... 147 CHAPTER FIVE ................................................................................................................. 148 RESULTS AND DISCUSSIONS ...................................................................................... 148 5.1. Introduction ................................................................................................................... 148 5.2. Univariate test statistics ................................................................................................ 149 5.2.1. Demographic characteristics of cars owners related to car insurance in Mahikeng .. 150 5.2.2. Social media access and usage among cars owners in Mahikeng ............................. 156 5.2.3. Demographic and economic variables in relation to insurance purchasing decision 159 5.3. Bivariate test (Chi- square) ........................................................................................... 168 5.3.1. Association between the demographic, economic variables and online purchasing decision ................................................................................................................................ 168 5.3.2. Association between social media usage, social promotion mix, consumer behaviour and online purchasing decision ............................................................................................ 170 5.4. Multivariate test (Stepwise logistic regression test) ..................................................... 176 5.5 Summary ........................................................................................................................ 180 CHAPTER SIX .................................................................................................................... 182 CONCLUSIONS AND RECOMMENDATIONS ........................................................... 182 6.1. Introduction ................................................................................................................... 182 6.2. Motivation and objectives of the study ......................................................................... 182 ix 6.3. Summary of the marketing and integrated marketing communication for insurance companies ............................................................................................................................ 183 6.4. Summary of social media and consumer behaviour over car insurance in South Africa .............................................................................................................................................. 184 6.5. Summary of the methodology used in this study .......................................................... 185 6.6. Summary of the findings ............................................................................................... 186 6.6.1. Research question one: What are the demographic and socio-economic characteristics of cars owners in Mahikeng? ............................................................................................... 186 6.6.2. Research question two: What is the relationship between demographic, economics variables and online purchasing decision of cars insurance in Mahikeng? ......................... 187 6.6.3. Research question three: What is the relationship between social media usage, online promotion mix, consumer behaviour variables and online purchasing decision of cars insurance in Mahikeng? ....................................................................................................... 188 6.6.4. Research question four: What is the impact of social media promotion mix on online purchasing decision of cars insurance in Mahikeng? .......................................................... 189 6.7. Policy recommendations and implications ................................................................... 190 6.7.1 Conceptual framework ................................................................................................ 190 6.7.2 Policy recommendations emanating from social media promotion mix and online purchasing decision .............................................................................................................. 191 6.7.3 Policy recommendations emanating from consumer behaviour and online purchasing decision ................................................................................................................................ 193 6.7.4 Policy recommendations emanating from income and online purchasing decision ... 194 6.8 Practical significance of the study ................................................................................. 194 6.9 Limitations of the study ................................................................................................. 195 6.10 Opportunities for further research ................................................................................ 195 6.11 Conclusion ................................................................................................................... 196 REFERENCES .................................................................................................................... 197 x LIST OF TABLES Table 1.1: Conceptual analysis (TAM and TPB) 10 Table 1.2: Study population and rational 14 Table 1.3: Sample plan 16 Table 1.4: Secondary objectives and data analysis 19 Table 2.1: Marketing described 26 Table 2.2: The service marketing mix 33 Table 2.3: Nature of marketing communication 43 Table 2.4: Public Relation techniques 52 Table 2.5: Direct marketing definitions 55 Table 3.1: The evolution of the World Wide Web 71 Table 3.2: Social Media described 72 Table 3.3: Social media characteristics 73 Table 3.4: Strengths and weaknesses of SA Short-Term insurance 77 Table 3.5: The nature of Consumer Behaviour / What consumer behaviour is 86 Table 3.6: Advantage and Disadvantage to purchase insurance online 88 Table 3.7: Multiple dimensions of consumer engagement 91 Table 3.8: Influencing consumer decision making 92 Table 3.9: Independent variables 101 Table 4.1: Sample plan for the study 121 Table 4.2: Measurement scale 126 Table 4.3: Summary of the scales used in the questionnaire 128 Table 4.4: Reliability statistics 131 Table 4.5: Selection of best items to include in the study 132 Table 4.6: Example of data code in Excel spreadsheet 140 Table 4.7: Secondary objectives and data analysis 142 Table 4.8: Different types of descriptive techniques 143 Table 5.1: Demographic characteristics of car owners 151 Table 5.2: Car insurance status and practices of respondents 153 Table 5.3: Demographic characteristics of respondents in relation to car insurance status 155 Table 5.4: Social media usage 157 Table 5.5: Average time spend on social media sites per day 159 xi Table 5.6: Association between the demographic, socio-economic and social media usage and online purchasing decision 169 Table 5.7: Reliability test of social media usage 171 Table 5.8: Validity test of social media usage 171 Table 5.9: Reliability test of social media promotion mix and consumer behaviour 172 Table 5.10: Validity test of social media promotion mix and consumer behaviour 173 Table 5.11: Relationships between Online Purchasing Decision and the other variables 175 Table 5.12: Omnibus test 177 Table 5.13: Model summary 177 Table 5.14: Hosmer and Lemeshow test 177 Table 5.15: Logistic regression 178 xii LIST OF FIGURES Figure 1.1: Chapter outline 2 Figure 1.2: Conceptual framework (TAM and TPB) 12 Figure 2.1: Chapter outline 25 Figure 2.2: Marketing philosophy outline 27 Figure 2.3: Marketing orientation 28 Figure 2.4: Marketing mix components 31 Figure 2.6: The ten Ps of service marketing 34 Figure 2.7: Main types of car insurance in South Africa 35 Figure 2.8: Marketing communication strategy 42 Figure 2.9: Social media communication process 44 Figure 2.10: The marketing communications mix 46 Figure 2.11: Online advertisement message 48 Figure 2.12: Online sale promotion 49 Figure 2.13: Sales promotion strategy 50 Figure 2.14: Digital personal selling process 54 Figure 2.15: Digital marketing 57 Figure 2.16: The IMC planning process 60 Figure 2.17: A conceptual model of IMC process for Car Insurance 64 Figure 3.1: Chapter outline 67 Figure 3.2: World Internet Penetration Rates: geographic Regions Mid-Year 2020 68 Figure 3.3: E-Commerce use amongst internet users 69 Figure 3.4: Insurance penetration across Sub-Saharan Africa in 2017 75 Figure 3.5: South African short-term insurance market in 2018 (annualised premiums, in ZAR billions) 76 Figure 3.6: Number of social network users in South Africa from 2017 to 2023 (in millions) 83 Figure 3.7: The most-used social networks site 84 Figure 3.8: Consumer behaviour outline 85 Figure 3.9: Insurers satisfaction and complaints over insurance provider 90 Figure 3.10: Conceptual framework 95 Figure 4.1: Chapter Outline 108 Figure 4.2: Study area 114 Figure 4.3: Steps to select a sample 115 xiii Figure 4.4: Sample methods 117 Figure 4.5: Sample categories 121 Figure 4.6: Information source 122 Figure 4.7: Letter of approval from the Department of Economic Development, Environmental Conservation and Tourism 136 Figure 4.8: Online message posted 137 Figure 5.1: Layout of the chapter 149 Figure 5.2: Frequency of login into social media sites 158 Figure 5.3: Gender and purchasing decision 160 Figure 5.4: Age group and purchasing decision 161 Figure 5.5: Monthly income and purchasing decision 162 Figure 5.6: Vehicle insured and online purchasing 163 Figure 5.7: Media triggers your intention to purchase insurance and purchasing decision 165 Figure 5.8: Number of times respondent accesses social media and purchasing decision 166 Figure 5.9: Time spent on social media and purchasing decision 167 Figure 6.1: Constructs affecting the purchase decision of car insurance online 191 xiv LIST OF ABBREVIATIONS AAAA: American Association of Advertising Agencies AIE: African Insurance Exchange AMA: American Marketing Association ARPA: Advanced Research Projects Agency ASA: Advertising Standards Authority ENATIS: Electronic National Administration Traffic Information System FMCGs: Fast Moving Consumable Goods GWP: Gross Written Premium IMC: Integrated Marketing Communication IRB: Institutional Review Board KPMG: Klynveld Peat Marwick Goerdeler NMMDM: Ngaka Modiri Molema District Municipality OECD: Organisation for Economic Co-operation and Development PMD: Prime Meridian Direct PR: Public Relation PRSA: Public Relations Society of America PWC: Price Waterhouse Coopers SAIA: South African Insurance Association SPSS: Statistical Package for Social Science xv TAM: Technology of Acceptance Model TPB: Technology of Perceived Behaviour TRA: Theory of Reasoned Action xvi CHAPTER ONE INTRODUCTION OF THE STUDY 1.1 Introduction Short-term insurance can make use of the social media promotion mix to influence the car insurance purchase decision of residents in Mahikeng if they are knowledgeable about those influences. For insurers, social media brought about a total transformation in social interaction, making consumer more aware of options, such as the insurance domain. Insurance is an enterprise based on trust where the consumer pays a subscription to a service provider, believing to acquire value from that enterprise at a later stage (Blake, 2018). Consumers use social media differently, and this has opened varying doors to a myriad of possibilities for insurers and car owners. Hence, there is a need to study the influence of the social media promotion mix on car insurance purchase decision-making. Currently, there is limited research measuring the influence of the social media promotion mix on car insurance. Sherman (2019) said that the emergence of social media has revolutionized traditional media, and thus resulted in consumers believing that the promotion mix of social media is much more trustworthy compared to traditional media. In recent years, there have been an increasing number of uninsured cars in South Africa (Hippo, 2017; Moonstone, 2018; Statistics South Africa, 2016). In the year 2010, the Constitutional Court of South Africa issued a judgement on the abolition of Law No 19 of 2005, which stipulated that “anyone injured in a motor vehicle accident could receive compensation from the Road Accident Fund” (Barendse, 2012). As a result, the situation exposed road users to exorbitant expenses and gives the insurance company the possibility to design insurance cover for potential risks. Finding the right car insurance policy is often a challenging task for consumers as they have no idea of what ought to be looked for and where to look for it. Consequently, many consumers consider only a few key points before making a final decision while others base their choice on recommendations and the past experiences of family and friends (Gerber, 2016; Wheels24, 2018). To address these challenges, selected factors that may influence car owners to purchase insurance online were examined by this study and two models, the technology of acceptance model (TAM) and the technology of perceived behaviour (TPB), were used to explore the extent to which social media influence consumer decision making. The layout of this chapter is graphically expressed in the following figure. 1 Figure 1.1: Chapter outline BACKGROUND OF THE STUDY PROBLEM STATEMENT RESEARCH OBJECTIVE RESEARCH METHODOLOGY CHAPTERS OUTLINE 1.2 Background of the study A historical retrospection of insurance companies in South Africa dates back to December 1835 and was discovered in the Cape Colony (Pearson & Yoneyama, 2015; Verhoef, 2012). The period between the 1950s and 1970s witnessed a period of transformation whereby Santam revolutionised the insurance industry by launching its Multiplex policy (Greyling & Verhoef, 2017; Santam, 2016). South Africans were able to have a single short-term insurance policy, covering all their assets under a unified system. The insurance company’s main goal consisted of collecting premiums from subscribers in order to protect them against the risks (Mokebe, 2018; Still & Stokes, 2016). A report based on 10 insurance companies, according to Price Waterhouse Coopers (PWC) (2014) and Santam (2016), revealed a 6% annual growth rate of insurance companies for the year 2013. Similarly, a report by the South African Insurance Association (2017) indicated that the following insurance companies witnessed a short term growth rate: Sanlam being the largest short-term insurer with 18.9% of gross premiums, followed by Guardrisk (6.4%), Absa (3.1%), Budget Insurance Company (2.5%) and the American International Group (2.1%), thus indicating the importance of these companies in the South African society. It is worth stating that the South African insurance sector is the largest in Africa, based on written premium volume and assets under management (Akinlo & Apanisile, 2014; Moodley, 2019). The industry is well-established and had a penetration rate 2 CHAPTER ONE: INTRODUCTION of 14% in 2014 and 16.99% in 2017, which ranked it amongst the highest in the world (Price Waterhouse Coopers, 2018). However, the short-term insurance industry in South Africa has been one of the slowest industries to realise the importance of going digital (Moodley, 2019; Insight Survey, 2019). Studies have shown that proper integration of the social media platform and content marketing had a significant impact on consumer behaviour. Different studies have demonstrated that insurance companies have become more conscious by including social media in their activities for a better chance of success (Chong, 2017; Kaplan & Haenlein, 2010; Vinerean, Dumitrescu & Tichindelen, 2013). A growing number of businesses are currently using social media websites to plan their marketing and the insurance market has not been left behind (Wheels24, 2018). Buying car insurance is no longer a simple task for motorists, neither for insurers, as they need to understand how the purchase journey has become complex and critical in order to maximize sales and retain consumers (Youngman, 2014). However, access to information have contrived consumers to feel more empowered, which can be the main factor influencing their purchase and digital platform preferences. For instance, Price Waterhouse Coopers (PWC, 2014) highlighted that 68% of consumers are more likely to download information from their insurance provider while 67% of consumers, in order to receive a discount in premiums, are willing to have a device connected to their car, and finally 50% of consumers are prepared to provide additional information to their insurers to enable them to seek the best deal. Roesler (2015) did a comparative study between USA and SA on the influence of social media on consumer-buying decisions. His study revealed that 32% of consumers and 19.4% of car owners are influenced by social media respectively, and these claims were supported by Mawson (2016). A growing number of consumers is discovering the benefits of comparing and buying insurance products online, as stated by Hippo (2017). In order to optimize their sales and prioritize consumer needs, it is important for insurance providers to understand at what stage potential consumers tend to abandon their online purchases and adapt their communication strategies while creating additional alternatives (Benady, 2014; Youngman, 2014). From a marketing perspective, social media is viewed as a medium with which consumers will engage, as 35% are willing to receive offers through social media whilst only 26% buy insurance online (Automobile Association of South Africa, 2018). Therefore, there is a need to research the likeliness that the social media promotion mix has a definite influence on consumers’ purchase decision-making, specifically those in Mahikeng. 3 1.3 Problem statement The Road Traffic Act 1988 encourages all motorists to insure their cars (Barendse, 2012; SAIA, 2017). Although car insurance is required by almost all countries, car insurance is not compulsory in South Africa. Nevertheless, South African insurance companies are facing severe competition in such a way that consumers are able to cancel or transfer an insurance policy to a competitor with immediate effect (PWC, 2014). However, with the emergence of social media marketing, South African insurers are increasingly challenged to know how to use and influence the purchase decision-making of consumers (Pfukwa, 2015; Rhys, 2013). In 2016, the number of uninsured cars in Ireland increased by 85% (Raidió Teilifís Éireann, 2016) while the percentage of uninsured cars in the United States of America continued to be on a steady decline, dropping from 14.9% in 2003 to 13% in 2015 (Leefeldt, 2017). Meanwhile the number of uninsured cars in the United Kingdom fell by 33% in 2018 (Be Wiser Insurance, 2019). A numerical investigation was conducted by SAIA to determine the number of insured vehicles on South Africa’s roads and the results revealed that only 35% of vehicles in South Africa are sufficiently insured, indicating a concerning low coverage in the automobile sector (SAIA, 2017). These findings are consistent with the report of Fin24 (2017) and Wheels24 (2018) which revealed that, the number of uninsured vehicles on the South Africa’s roads continues to increase, as it is the case in 2017 where the number of uninsured vehicles rose from ten to twelve million (70%) in 2018. Several authors have drawn conclusions from these findings by assuming that: cars on South Africa’s roads are uninsured, firstly, due to the excessive rate of premium policies; secondly, car owners think insurance is needless as they are not likely to be involved in accidents; and finally, consumers do not trust the providers (Aglionby, 2016; Bowen, 2019; Prime Meridian Direct, 2018). According to the Electronic National Administration Traffic Information System (ENATIS, 2019), there were 43 969 licensed vehicles in the Mahikeng municipality with 30 778 vehicles uninsured in 2018. Evidence from Mawson (2016) highlighted that 19.4% of car owners register their car insurance online, while 24.6% only look at the process and 23.9% affirmed that they would not acquire insurance online as websites are too slow. The use of social media would be extremely beneficial to educate consumers, generate competitive intelligence, and cause the creation of networks through which messages can be aimed at consumers (Harris-Ferrante, 2012; Rhys, 2013). In the light of the aforementioned, it is important for insurance companies to integrate the social media promotion mix in their marketing, as well as interacting with consumers in order to create awareness. 4 To explore the most influential applications of social technologies in the global economy, Manyika et al. (2011) stated that marketing via social media would be another perspective of interacting with people but it is to a large extent still unexploited in the car insurance industry. For the purpose of attracting and retaining consumers from an insurance company perspective, the problem identified in this study is that there is uncertainty concerning the influence of the social media promotion mix and this calls for a study to explore the influence of the social media promotion mix on car insurance purchase decision-making in Mahikeng. Due to the nature of the service provided, this study explored how a combination of social media promotion and purchase decision-making are considered and implemented on behalf of short- term insurance companies in Mahikeng. 1.4 Research objectives and questions A change in consumer behaviour because of social media is one of the most intriguing aspects of contemporary marketing and research. This study was motivated by the need to take into consideration the fact that 65% of vehicles on South Africa’s roads are uninsured, as mentioned in the problem statement. The research objectives are divided into two categories; that is primary and secondary objectives. 1.4.1 Research objectives The aim of this study is to understand and obtain insight on the purchasing decision-making of car insurance in Mahikeng within the context of the social media promotion mix. From the research aim, the following primary and secondary objectives are put forward: 1) Primary objective The main objective of this study is to investigate the influence of the social media promotion mix on the purchase decision-making for short term insurance by car owners in Mahikeng. 2) Secondary objectives To ensure that the primary objective of the study is reached, the secondary objectives formulated are:  To obtain a demographic description of car owners in Mahikeng. 5  To test the association between socioeconomic variables and purchasing decision-making.  To determine the relationship between social media platforms usage, online promotion mix, consumer behaviour and purchase decision-making amongst car owners in Mahikeng.  To investigate the impact of the online promotion mix on car owners’ purchasing insurance decision-making in Mahikeng. 1.4.2 Research questions The study objectives described above assist in addressing the research questions which guided this study. 1) Primary research question This research was guided by one central research question which is: ‘How are car owners influenced by the social media promotion mix to purchase short term car insurance online? 2) Secondary research questions The secondary research questions of this study are as follows:  What is the demographic description of car owners in Mahikeng?  What is the attitude of car owners in Mahikeng towards social media platforms?  Is there a relationship between the social media platforms and purchase decision-making among car owners in Mahikeng?  What are the factors influencing car owners when purchasing short-term insurance through social media in Mahikeng?  Is there a relationship between the online promotion mix and the purchase decision-making among car owners in Mahikeng? 1.5 RESEARCH HYPOTHESIS Based on the aim and objectives of this study, the following hypotheses are formulated to guide the study: H01: There is no relationship between socioeconomic variables and purchasing decision. 6 H02: There is no relationship between the online social media platform usage and purchase decision-making. H03: There is no relationship between the online promotion mix and purchasing decision- making. H04: There is no relationship between the consumers’ behaviour and their purchasing decision- making. H05: The online promotion mix does not influence car owners’ purchasing insurance decisions in Mahikeng. 1.6 Motivation of the study The technological advancement and the ever increasing impact of social media are the biggest trends shaping the insurance industry (Kruger, 2017). However, insurance companies should not only focus on building new products but should also build relationships with their consumers (Kotler et al., 2015). A similar study by Rhys (2013) asserts that insurance companies should focus on changing consumer demand while adopting new technology that will allow them to sustain their competitiveness over the short term. This usually can be done in both short and long term basis. Studies by Aglionby (2016) and PWC (2014) found that short-term premiums in South Africa accounts for almost 80% of all premiums in sub-Saharan Africa with a penetration rate of 15.4% of the Gross Domestic Product. This study fills in the research gap in unravelling various consumer attributes and perceptions which can influence their decision-making to purchase car insurance through social media, and the effect of the promotion mix on their decision-making process. As a contribution to the body of knowledge, a conceptual framework base on the integration of the technology of acceptance model and the technology of perceived behaviour was used to add value on the subject. This study makes a contribution towards the marketing of car insurance by means of a set of recommendations, which should be considered by car insurance marketers. As contribution of the study to the policy makers, the present study identifies a decrease in the number of car operating on South African roads. The empirical findings and recommendations of the study can serve as evidence for car insurance companies on the importance of the social media promotion mix as a marketing tool and to initiate further research in other sectors related to the social media promotion mix. 7 1.7 Literature review A literature review is referred to by Leedy and Ormrod (2014) as any other research which surrounds the phenomenon under study. Over the past three decades, researchers have paid substantial attention to determining the conditions or factors that can facilitate the integration of technology in the business environment (Manyika et al., 2011). Models have been developed and tested to help predict the acceptance of technology. Among these models is the theory of reasoned action (TRA) and its extensions (such as the theory of planned behaviour and the technology of acceptance model) which have been applied extensively in analysing a wide range of human behaviours (Ajzen, 1991; Ajzen, 1985; Davis, 1986; Fishbein & Ajzen, 1975). Executing the research objective associated with this study required the use of valid models. The technology of acceptance model (TAM) and the technology of perceived behaviour (TPB) were adapted for the purpose of this study. Conferring with Wang (2017), TAM can be used to examine the purchase intentions of online users, since they have dual characteristics of being both traditional and information system users. However, TPB has been one of the most influential theories in explaining and predicting behaviour, and it has been shown to predict a wide range of behaviours (Armitage & Conner, 2011; Karimy et al., 2015; Sheppard et al., 1988). The objective is to examine the antecedent of the social media promotion mix and the intention to purchase insurance policy online. A reported number of studies were conducted using the original TAM model to investigate the adoption of new technologies on consumers’ behaviour (Lim &Ting, 2012; Pinho & Soares, 2011). On the other hand, various researchers have only focused on the factors that influence online purchasing decision-making (Lim et al., 2016; Putro & Haryanto, 2015; Ye & Zhang, 2014) but with little or no work on the social media promotion mix on consumers. A study by Hakkak et al. (2013) extended the TAM model by adding the following variables to the model: enjoyment, trust and risk. Very few researchers attempted to incorporate consumer behaviour and the impact of social media on consumer purchase decision-making (Akar et al., 2015; Hajli, 2014; Maoyan et al., 2014). Besides these, the TAM model was extended to predict consumers’ intention to purchase online (Lee &Paris, 2013; Miranda et al., 2014; Nistor, 2011; Tripathi, 2014). TPB has been widely recognized and applied in food related studies (Aziz & Chok, 2013; Bashir et al., 2019; Lim & Goh, 2019) and online shopping behaviour (Amaro & Duarte, 2015; Lim et al., 2016; Yang et al., 2017). Other interesting work focused on building complex models based on TPB (Chen &Tung, 2014; Karimy et al., 2015; Md Husin & Ab Rahman, 8 2016; Pan & Truong, 2018; Shi et al., 2017; Wang et al., 2016;). All of these studies show that there is a relationship between consumer attitude towards social media and the intention to purchase using social media platforms. This study adopted previous findings on social media and consumers’ behaviour, it should be noted that most of these studies concentrated on Fast Moving Consumable Goods (FMCGs). The provisional framework developed for this study is based on an extensive concept-analysis as presented in Table1.1 and is a compendium of a selection of previous studies. Table 1.1 presents the different constructs used by previous researchers based on the TAM and TPB models. The integrated model of the TAM and the TPB has rarely been adopted with regards to car insurance purchase decision-making; although the two models have been found to predict and explain the intention to use technology in several studies while providing a clear foundation to interpret and understand the relevance of the model (Cheng, 2019; Chin, 2016; Putra, 2018; Safeena et al., 2013; Sentosa & Mat, 2012; Yu et al., 2018). For the present study, TAM and TPB were extended by adding four constructs which include: promotion mix, perceived security, perceived tangibility and service quality. Trust and website characteristics were selected based on previous studies. The questionnaire was used to test each construct and the results are presented and explained in Chapter Five and Six. Table 1.1: Conceptual - analysis (TAM and TPB) Dimensions Perceived usefulness X X X X X X X X Perceived Ease of Use X X X X X X X Perceived Behavioural control X X X X X X X X Subjective Norm X X X X X X Attitude X X X X X X X X X X X X Purchase intention X X X X X X X X X X X 9 Ajzen (1985) Davis (1986) Maoyan et al. (2014) Tripathi, (2014) Ye and Zhang, (2014) Amaro &Duarte, (2015) Chin, (2016) Md Husin et al. (2016) Putra, (2018) Bashir et al. (2019) Cheng, (2019) Present study Perceived value X X Perceived risk X X X X Social media marketing X Trust X X X X Perceived attractiveness X Website characteristics X X Sales promotion X Awareness X X Buying behaviour X X Perceived relative advantage X Perceived complexity X Perceived compatibility X Communicability X Knowledge X Exposure X self-esteem X Online complaints X Promotion mix X Perceived security X Perceived tangibility X Service quality X 1.8 Research gap After reviewing literature, it became clear that the TAM and TPB models, which were developed to explain and predict individual computer usage behaviour, intention and actual computer adoption behaviour, is regarded as the most suitable models for this type of study, as suggested by Ajzen (1985) and Davis (1986). Studying consumer behaviour in an online context has been an essential research area for researchers such as Amaro and Duarte (2015), Bashir et al. (2019), Putra (2018) and Ye and Zhang (2014). This study incorporated areas that lack research, and it is important to investigate the influence of the promotion mix on social media with reference to car insurance in Mahikeng. 10 The focus of this study is to determine how the social media promotion mix influences consumer purchase decision-making in the short-term insurance market. To achieve this, a conceptual model is presented below with the purpose of optimizing the social media promotion mix, the attitude of consumers towards social media platforms, as well as the various factors affecting online purchase decision-making. 1.9 Conceptual framework Different scholars investigated numerous factors that can affect the purchasing behaviour of online consumers (Bashir et al., 2019; Chin, 2016; Putra, 2018). The conceptual framework used for the purpose of this study shows that a diverse range of factors indicate that many consumers do struggle with online technology, which in turn affects their decisions to purchase online (Athapaththu, Kulathunga & Mawatha, 2018; Khan-AM & Rangsom, 2014). Several researchers have studied the factors resulting from the TAM and TPB models because these are closely related to a consumer’s intention to adopt new technology (Wang, 2017; Lim et al., 2016b; Hattangadi, 2014; Maoyan et al., 2014; Ye & Zhang, 2014). By implementing the present study, the conceptual framework provides an understanding to short-term insurance, that there is a need to invest more into information technology economy because the gains would spread to other sectors of the economy. Amongst other theories pertinent to this type of work, two were selected as they provide a better understanding of consumer behaviour which are the theory of acceptance model and the theory of planned behaviour. In keeping with the general proposition from previous studies, the TAM and the TPB models were extended for the purpose of this study by: ● Proposing four additional key constructs (promotion mix, perceived security, perceived tangibility and service quality). ● Modifying some of the existing relationships in the original conceptualisation of TAM and TPB. ● Adapting the existing moderators. The conceptual framework developed for this study is presented below as Figure 1.2. 11 Figure 1.2: Conceptual framework (TAM and TPB) Source: Adapted from Ajzen (1991); Davis (1986) The framework proposed by this study will assist short-term insurance companies and marketers to adopt social media as an effective and efficient marketing strategy. The framework also suggests that for an organisation to reap the benefits of social media, there is a need to better understand the online behaviour of car owners. 1.10 Research methodology Tlapana (2017) is of the opinion that research methodology is a way of solving a research problem in a scientific manner, as described by Wild and Diggines (2013). The philosophical orientation of a researcher should be unknown in research according to Creswell (2014). A brief overview of each aspect of the research method and what each of it involves are elucidated below. 12 1.10.1 Study area Mahikeng local municipality is the smallest of the five municipalities but the most densely populated area with 78 people per square kilometre in the Ngaka Modiri Molema District Municipality (NMMDM) among other Ditsobotla local municipality, Ramotshere Moiloa local municipality, Tswaing local municipality and Ratlou local municipality (Mahikeng Local municipality, 2020b). The empirical focus of this study is on the Mahikeng local municipality, which is a Category B municipality, located within the Ngaka Modiri district in the North West province, South Africa. The Mahikeng municipality is divided into 28 wards which comprises of 102 villages and suburbs, with approximately 75% of the area being rural and these rural areas are in the southern and western parts of the municipality. The largest population group in Mahikeng local municipality is black African with 95%. The last recorded population in 2011 was 291 527, and in 2016 was 314394 with 24.4% representing population under 15 years, 71.3% representing population between 15 years and 64 years and only 4.3% representing population over 65 years (Municipality of South Africa, 2020). 1.10.2 Sampling process In order to understand the factors that influence car owners in Mahikeng to use social media as a medium to purchase car insurance online, a clear identification of the target population and sampling is presented below. 1.10.2.1 Target population The population of a research study, according to Creswell (2014) and Govender (2014), involves a broader group of participants from whom data will be obtained by means of a survey or interview. Furthermore, Cooper and Schindler (2014) explain that a research population is the entire group of elements to be studied. The target population for this study, according to the Electronic National Administration Traffic Information System (ENATIS, 2019) is 46463 vehicles, which comprises car owners in Mahikeng who have subscribed or not to an insurance policy. The objectives of a study normally specify the target population and Mahikeng municipality will be the geographic location for this study. The sample selection will take place online (Company platform, Facebook, WhatsApp, Email). 13 The target population for this study consists of four parts (Silver, Stevens, Wrenn & Loudon 2012), namely: elements, sampling units, extent and time, which are presented in Table 1.2. Table 1.2: Study population and rational Elements Description Rational Sampling Ngaka Modiri Car’s owner unit Molema district municipality Extent The study focuses on Mahikeng municipality only. Time 1 November 2019 to April 2020 Data were collected following the ethical clearance and the questionnaire were pre-testing Source: Silver et al.(2012) 1.10.2.2 Sampling frame Sampling is the process of selecting subsets of a population to be included in a research study (O’Leary, 2010). Creswell (2014) describe sampling design as the method or technique used to select a subgroup from a population to participate in a study. It would be superlative to include the whole population in some form of study, but in most instances it is not feasible to include any subject because the population is virtually finite. The sample frame of this study consists of car owners who are contracted or not to short term insurance company. A link to the questionnaire together with an invitation message were sent via social media to consumers who were requested to forward it to their family, friends and the greater Mahikeng community on Facebook, requesting car owners to participate in the online survey. 1.10.2.3 Sampling technique This study adopted a quantitative research technique where data generated from the questionnaire among car owners were captured into a database before being analysed using descriptive statistics. Since this study had a sample to be implemented, a non-probability sampling method was selected. To select the participants, a purposive sampling was used to 14 reach the appropriate subgroup (Hair et al., 2013b). Which, in this case included car owners who are insurance and non-insurance subscribers. Brown et al. (2013) and Wilson (2014) outlines purposive sampling as a technique where a sample is logically assumed to be representative of the population. However, purposive sampling does not eliminate under representation of persons who are difficult or reluctant to participate. Mahikeng is the largest municipality compared to the other four local municipalities located within the jurisdiction of the Ngaka Modiri-Molema district and was thus selected as ideal from which to generate the sample. Having determined the sampling method, the sample size is subsequently discussed. 1.10.2.4 Sampling size McDaniel and Gates (2015) explain the sample size as the number of elements or individuals to be included in the final sample. As the sample frame is required for the purpose of this study, the mode of selection of participants vary depending on the goals and scope of the study. After the sampling methods has been chosen and the target population identified, the next step is to define the suitable sample size. As state earlier, among the total population of 314394, the total number of vehicle in Mahikeng local municipality is 46463. To determine the sample size that is required for the purpose of this study, the ROASOFT software which include a 90% confidence level with 5% margin of error and 50% of response distribution rate was used. Based on the total population of vehicle in Mahikeng municipality, a sample size of 263 respondents at a confidence level of 90% was considered. In conclusion, the summary of the sample plan for this study is presented in Table 1.3. 15 Table 1.3: Sample plan Sample plan Target population Males and females, older than the age of 18 who owns a car. Sample frame Total license vehicle population in Mahikeng municipality is estimate to 46 463 Total licence vehicle population in Mahikeng and Mmabatho is estimate to 8467 Sampling method Non-probability sampling which include purposive sampling. Method of sample size ROASOFT calculation Expected sample size 263 1.10.3 Research design Selecting the research design consists of a number of actions that contribute to the overall research. The aim of the survey consists of finding out why, where and how the social media promotion mix influence individuals in the process of decision-making. Gray (2013) and Wild and Diggines (2013) explain that research design provides the overall structure to be followed for an investigation, through the planned and systematic collection, analysis and interpretation of data. Kesharwani et al. (2018) outline descriptive research as a method that describes the characteristics of the population being studied. Therefore, the research design highlights the research questions by answering when the data will be collected and how it will be analysed. The descriptive research design was adopted for the purpose of this study and the main advantage of this approach is that, accurate data can be collected to provide a clear picture of the research topic (Kumar, 2019). 1.10.3.1 Quantitative research design The quantitative method is a process of research that provides a numeric description of trends, attitudes or opinions of a population by studying a sample of the population (Creswell, 2014). The quantitative research essentially refers to the presentation of systematic steps of methodical research while using quantitative properties in research (Edmonds & Kennedy, 2016). Various 16 quantitative research methods are available and this study used an online surveys. A descriptive research design was used to collect and provide empirical fact to the research questions in the course of this study. It is however not possible to generalize the findings of quantitative research conducted on a purposive sample but this study was designed according to the guidelines of scientific research to obtain a true as possible reflection of the selected sample to understand the population under study (Kesharwani et al., 2018). 1.10.3.2 Information needs Information is the result of data processing and is the end result when data are turned into something useful (Berndt & Petzer, 2012). According to Neelankavil (2015), there are two types of information that provide research information to solve problems, namely: primary and secondary information. A secondary source of information involves collecting data from already published sources. In contrast to this is primary data which are specifically gathered to solve a particular problem identified (Kumar, 2019). Kesharwani et al. (2018) describe primary information as direct evidence of an event, which is not yet analysed and performed to meet specific objectives. Primary data were collected by means of the questionnaire among car owners in Mahikeng. Neelankavil (2015) presents secondary data as information that has already been collected by other researchers and agencies and has been processed. For the purpose of this study, secondary data were obtained through published articles, academic textbooks, journals, magazines, reports, books, websites and various online databases. 1.10.4 Pretesting the questionnaire Once the questionnaire were developed, the questionnaire was pre-tested through a pilot before the actual data was collected to test the relevance and accuracy of the questions included in the questionnaire. A pilot study considered by Babin and Zikmund (2016) to be a small-scale preliminary study aimed at assessing the feasibility, duration, adverse effects and improving the design of the study before conducting a large-scale research project. A pilot study was conducted on selected friends who are car’s owners in Mahikeng during the month of February 2020. Normally about five to ten respondents are included in the pre-testing phase (Burns et al., 2017; Lukka & James, 2014). The researcher agreed to enrol 25 car owners male and female aged from 18 years and over by sharing the link of the online questionnaire through their 17 different social media. Among the 25 questionnaires sent, only 20 questionnaires were received and grouped into car’s owners insured and car’s owners uninsured in order to balance the two group for analysis. The pilot study comprised several components which are to determine the feasibility of the study, recruitment of subjects, testing the measurement instrument, data entry and analysis (Hassan, Schattner & Mazza, 2006). The coefficient alpha is the first measure to assess the quality of an instrument (Brown et al., 2013) and the higher the coefficient alpha, the more reliable the instrument is (Taber, 2018). The data collected from the pilot study was used to assess the measurement scale reliability using coefficient alpha and to assess the uni- dimensionality of the scales. 1.10.5 Data collection Data collection refers to the steps involved in collecting information for a study. Primary and secondary information are the two sources of information in most scientific research (Neelankavil, 2015). In this study, primary information was collected quantitatively by means of an electronic questionnaire with close-ended questions. The questionnaire used in this study was designed based on the different types of scale responses. The questionnaire was designed with a five-point Likert scale, which ranged from strongly agreed to strongly disagree, as well as dichotomous responses with a ‘Yes’ or ‘No’ response type. Data was obtained from both available literature and the empirical investigation. The information obtained was used to determine if the social media promotion mix do influence consumers’ purchase decision- making regarding short-term insurance in Mahikeng. 1.10.6 Data analysis The data analysis is used to provide meaning to basic data. Data analysis implies the interpretation of data in order to draw outcomes that mirror the ideas, interests and theories that instigated the research (Babbie, 2013; Kumar, 2019). There are a number of methods that can be used to analyse quantitative data, ranging from univariate analysis to more complex multivariate analysis (such as regression analysis, correlation, linear regression, Anova, Chi- square, cluster analysis and structural equation modelling) (Babbie, 2013; Cant, 2011; Kesharwani et al., 2018; Kumar, 2019). The data collected were analyzed using the statistical software program Statistical Package for Social Sciences (SPSS) version 24, with particular 18 emphasis on multivariate analysis and structural equation modelling (Malembo, 2015). For the purpose of this study, the following statistical techniques were utilised for the purpose of this study as specified in Table 1.4: Table 1.4: Secondary objectives and data analysis Objectives Statistical technique To describe the socioeconomic characteristic of car Descriptive analysis owners in Mahikeng. (Univariate) To investigate the relationship between the demographic, Chi-Square (Bivariate). socio-economic and socio-media usage and purchase decision making amongst car owners in Mahikeng. To determine the relationship between social media usage, Chi-Square (Bivariate). social media promotion mix, consumer behaviour and online purchasing decision in Mahikeng. To investigate the impact of online promotion mix on the Logistic regression purchase decision making amongst car owners in (Multivariate) Mahikeng. 1.11 Delimitation The focus of this study is on the short-term insurance users in Mahikeng, specifically car owners. The social media tools Facebook, Twitter, LinkedIn, YouTube and Corporate blogs are employed as the most commonly used platforms in South Africa. Regarding the marketing communication mix elements, advertising, sales promotions, public relations, personal selling and direct marketing will be included. 1.12 Definitions of key terms Subsequently is an explanation of the key ideas related to the topic in order to clarify the way in which it will be used in this study. 19 Car insurance According to the National Association of Insurance Commissioners (2012), insurance is an economic device transferring risk from an individual to a company and reducing the uncertainty of risk via pooling. Car insurance is one of the most popular types of insurance. Barone (2019) and Kagan (2018) explain that car insurance is a policy purchased by vehicle owners to mitigate costs associated with getting into a car accident. Car insurance services require satisfaction, trust and commitment to create a quality relationship with car owner (Pfukwa, 2015). Integrated marketing communication (IMC) Kotler et al. (2015) said Integrated Marketing Communication is a way of looking at the marketing process from the point of view of the consumer. IMC is a marketing communication activity meant to create a single positioning of a brand by delivering a consistent message through various communication channels (Finne & Grönroos, 2017; Seric et al., 2016; Valos et al., 2016). IMC is a concept adopted by companies to assure that all their marketing communication tools deliver a clear and competitive message about the organisation and its know-how (Jobber & Ellis-Chadwick, 2016). Promotion mix Promotion mix is one of the four basic elements of the marketing mix, and refers to consumer awareness regarding a service or product in order to generate sales and create brand and consumer loyalty (Kotler et al., 2015). The promotion mix is the specific combination of promotional tools such as personal selling, advertising, sales promotions, public relations and direct marketing (Belch & Belch, 2018; Koekemoer, 2014). Promotional tools used adequately build a relationship while communicating value to the consumer by positioning the company in the mind of the consumer (Barnard et al., 2017; Cunningham, 2018). Purchase decision making Consumers seek items to satisfy their needs and desires. Khatib (2016) describes the consumer purchase decision as a stage where consumers identify their needs, collect information, evaluate alternatives, and then make a purchase decision. Consumer purchase decision-making is generally acknowledged as the “behaviour patterns of consumers, intention to buy a specific product or service which they have chosen after a certain evaluation in order to satisfy their 20 need” (Kotler et al., 2015). Armstrong and Kotler (2013) define purchase decision as the decision-making process individuals engage in when needs and desires occurs. Social media Social media refers to a set of web based interactive technology applications, allowing people to generate and share information known as ‘Web 2.0’ (Kaplan & Haenlein, 2010). Social media is not just an activity; it is an investment of valuable time and resources. Social media are the online means of communication, conveyance, collaboration and cultivation among interconnected and independent networks of people (Tuten & Solomon, 2015). Pütter (2017) posits social media as "consumer-generated media covering a wide variety of new sources of online information, created and used by consumers’ with the intention of sharing information with others regarding any subject of interest”. 1.12 Ethical consideration Ethical consideration, according to Marshall and Rossman (2011), is more than just ensuring informed consent and protecting a participant’s anonymity. It also entails anticipating challenges that will occur. This calls for a researcher to be emotionally firm and continuously evaluate own behaviour. In order to conduct this study, the ethical standards of academic research were adhered to and this entails gaining clearance for this study from the North-West University in accordance with the research policy of the university. All sources consulted and quoted are dually acknowledged. Participants’ privacy was respected and this is reflected in their interaction and the information gathered. All general research ethics and conventions were observed and honoured during the course of this study. 1.13 Chapter outline At the end of this study, a final report was compiled as a master’s dissertation, which comprises six chapters as explained below. 21 Chapter 1: Introduction to the study The first chapter introduces the entire study with emphasis on the background of car insurance and social media for short-term insurance. The purpose of the study is to investigate the influence of the social media promotion mix on car insurance for short-term insurance companies in South Africa. The chapter provides the problem statement, research objectives, research questions and hypotheses of the study. A brief elaboration on the literature review, research gap and the conceptual framework are presented. Finally, the research design and methodology according to which the research was conducted, the delimitation of the study, ethical considerations and lastly the definition of terms are presented in this chapter. Chapter 2: Marketing and integrated marketing communication The focus of this chapter is on an explanation of marketing, and also integrated marketing communication (IMC) and its components, to provide a better understanding of the research topic. Communication through the marketing mix which consists of defining the marketing communication process and the extended marketing communication mix are highlighted. The evolution of IMC and its benefits for short-term insurers are provided. Moreover, an in-depth discussion on the implementation of IMC for short-term insurance is included and a marketing communication model is also proposed. Chapter 3: Consumer behaviour and social media Chapter three provides a narrative on consumer behaviour regarding the use of social media. A relevant literature review is provided about South African consumers and the factors affecting their online purchase decisions, followed by the importance of social media and the type of social media used by short-term insurers. An in-depth explanation of the TAM and TPB theories are provided, followed by a proposed conceptual framework based on previous models related to the field of study and the factors influencing online consumer decision-making. Chapter 4: Research design and methodology The focus of this chapter is on the research methodology employed for the purpose of this study. It describes the research design carried out to investigate car owners in Mahikeng and the effects of the social media promotion mix on their purchase decisions, it further explains the research hypothesis and instruments used to collect the data required. A detailed description 22 of the statistical methods used in analysing the data is presented. The chapter also describes the various tests performed to ensure that the data are suitable for factors analysis and interpretation. The structure of the questionnaire and the measures are included in this chapter. Chapter 5: Research results Chapter five provides the results and discussions obtained from the study as per the planned research methodology and data collected. The study’s findings are presented, interpreted and discussed in this chapter in a form of figures, tables, and also discussions with reference to the findings of other studies. The descriptive analyses includes the online consumer demographic description and their social media usage, followed by the reliability, validity and chi-square analysis. Lastly, multivariate analysis and structural equation modelling were applied to test the relationships and the research hypotheses. Chapter 6: Conclusion and recommendation The final chapter presents a review of the entire study and provides conclusions of both the literature and empirical studies, together with the recommendations emanating from the findings of this study. The recommendations and managerial implications associated with the objectives and hypotheses shaped in Chapter One are presented. Suggestions for further research are made and limitations that could accrue during the research are pointed out in order to assist future researchers to overcome and avoid the same limitations. 23 CHAPTER TWO MARKETING AND INTEGRATED MARKETING COMMUNICATION 2.1 Introduction It was established in Chapter one that, the aim of the study is to determine the influence of social media promotion on car owner’s in Mahikeng. Currently, there seems to be a limited knowledge on the factors that may contribute towards the decision for consumer to purchase insurance policy online. By identifying those factors, it may offer valuable assistance to short- term insurance companies, as they will have a better understanding of the factors which might result in more decision to purchase car insurance online. In order for the marketing concept to be fully implemented throughout insurance industry, management must enthusiastically embrace and endorse the concept and encourage its use in every department. It is necessary to obtain a comprehensive understanding of the type of marketing used by short- term insurance companies. Thus this Chapter focuses on marketing, which is recognized as an important business function to the success of any company. The chapter begins by exploring the marketing philosophies, marketing communication and the communication mix components. It further addresses the concepts of understanding the integrated marketing communication and its importance for short-term insurance companies. Derived from the generic elements of IMC, the chapter concludes with a conceptual model of IMC for car insurance. The road map of the chapter is presented in Figure 2.1. 24 Figure 2.1: Chapter outline MARKETING MARKETING COMMUNICATION INTEGRATED SERVICE MARKETING COMMUNICATION THE IMPORTANCE OF INTEGRATED MARKETING COMMUNICATION IN INSURANCE 2.2 Marketing History points out that without suitable marketing (CIM, 2015) companies cannot understand the needs and preferences of their consumers, which also applies to short-term insurance companies. However, where a service provider fails to satisfy the target market, competitors will poach such consumers and maximize their profits. Many companies embraced the marketing concept since the 1950s (American Marketing Association, 2014) and in recent years, companies became consumer and competitor oriented with the aim of satisfying consumers better than their competitors (Hasan, 2014). Sometimes people assume that marketing depends on advertising and selling (CIM, 2015). However, every product we purchase, every media message we receive and the choice we take as a consumer have been fashioned by the marketing efforts. There are many descriptions and definitions of marketing. For the purpose of this study, a selection as indicated in Table 2.1, reflect some of the key ideas of what marketing entails. 25 MARKETING AND INTEGRATED MARKETING COMMUNICATION There are many descriptions of marketing, for the purpose of this study, a selection as indicated in Table 2.1 reflects some of the key ideas of what marketing entails. Table 2.1: Marketing described Descriptions Source “Marketing is the activity, set of institutions and processes American Marketing for creating, communicating, delivering, and exchanging Association (2014) offerings that have value for consumers, consumers, partners, and society at large”. Marketing is “a process whereby an organization in its Cant and Van Heerden drive to meet its organization goal, focuses on meeting (2017) customer needs and wants, by offering the right product, at the right price, at the right place and by using the right marketing communication channels.” Marketing is “the management process for identifying, Chartered Institute of anticipating and satisfying consumer requirements Marketing (2009) profitability” Marketing is ‘‘a set of activities that have values for Kotler (2014) consumers.’’ Marketing is a societal and managerial process by which Kotler and Keller (2012) individuals and organisations obtain what they need and want through creating and exchanging values with others” The key terms emanating from these descriptions are: consumers; value exchange; relationships between the consumer and the organisation, and the appropriate marketing communication channels. The marketing communication and the relationships between insurance industry and consumers also form the key themes of this chapter. Considering the different descriptions of marketing and the fact that there is no universally accepted description of the term ‘marketing’, the definition of Cant and Van Heerden (2017) will account for the purpose of this study. Marketing plays a vital role in the insurance industry and serves to increase sales while maintaining market share (Sanders, 2017). A general rule of thumb is that 26 the higher the level of service, the greater the demand (Duan, 2012). Thus, if demand for insurance services decline, marketers should find the cause and take immediate actions to eliminate it (Slack & Brandon-Jones, 2018). Tay and Diener (2011) in their study mentioned that as a person satisfies one need, a higher-level need becomes more important. Considering fulfilment, insurance companies should aim for a continuous level of satisfaction so that car owners can become loyal supporters (Cunningham, 2018) who recommend the service to all in their networks. Figure 2.2: Marketing philosophy outline PODUCTION ORIENTATION SALES ORIENTATION MARKETING MARKET ORIENTATION PHIILOSOPHY SOCIETAL MARKETING ORIENTATION RELATIONSHIP MARKETING ORIENTATION 2.2.1 Marketing philosophies Organisations endeavour to build a bond with consumers which will foster a sound union between the organisation and its target consumers, which ideally will result into a symbiotic relationship between both parties. However, there are several marketing orientation stages which constitute the marketing philosophies that can influence an organisation’s marketing process towards achieving its goals and objectives over a period of time. Nevertheless, each of these marketing orientations has a set of unique and distinct principles to ensure consumer satisfaction. As depicted in Figure 2.3, each of the five marketing orientations are presented and explained (Armstrong, Adam, Denize & Kotler, 2014; Cunningham, 2018). 27 Figure 2.3: Marketing orientation Production Societal Relationship Sales Market orientation marketing orientation orientation marketing orientation orientation Source: Adapted from Armstrong, Adam, Denize and Kotler (2014) and Cunningham (2018) Subsequently is a synopsis of each one of the marketing orientations. 1) Production orientation Production orientation is the first stage and focuses on the internal manufacturing capabilities of the organisation rather than the needs and wants of consumers (Cunningham, 2018). Insurance companies face many conflicting threat (Ismail, 2017) as they fail to deliver value to consumers, yet insurance consumers do not have complex requirements (Lake, 2017; Naujoks, Darnell, Schwedel, Singh & Brettel, 2018). Insurance agencies offer a wide variety of services at a reasonable price (Quain, 2018). In the year 2017, about 49,3% formal complaints associated with car insurance providers was evaluated by the Ombudsman (Du Plessis, 2019). Cant and Van Heerden (2017) stated that “Generally, production orientation is used only when the demand for a service is greater than the supply”. The main advantage of a production- oriented approach is that organisation are constantly revising and improving product to be the best it can be at the lowest price possible (Armstrong, Adam, Denize, & Kotler, 2014). Madubanya (2015) infers that in an insurance company, policies are not shaped by consumers but by the companies and then sell through representatives, advertising and other sales systems. To succeed in a competitive market, organisation must start by identifying what the market wants and then produce it, rather than focusing on what the company considers as best for the market (De Meyer-Heydenrych, Human, Maduku, Meintjes & Nel, 2017). 28 2) Sales orientation In the 1960s, sales techniques for products and services became more advanced (Lake, 2017). Although the production orientation was fruitful for some time, many businesses recognised that aggressive sales methods might be useful to increase sales and positive returns, according to Lazarri (2018). Sales orientation is seen as an intuitive reaction to the problems of production-oriented in which, (Cunningham, 2018) the organisation and its sales staff will use strong and aggressive techniques to persuade consumers to buy. The idea behind a sale orientation is to look at different aspect of buyer’s behaviour as they may not want the services sold (Lake, 2017). Sales orientation is necessary for service providers in a competitive market such as insurance companies. Whether insurance consumers need it or not, insurance providers are tempted to push their service towards consumers (Cant, Wiid & Kallier, 2015), by using technique that suggest a two-in-one offer where the second product is free in order to increase sales and thus return on investment (Harker, Brennan, Kotler & Armstrong, 2015). Insurance is a necessity product that requires sales orientation to educate and drive purchases from consumers by applying promotions and outbound sales efforts to drive revenue. For the purpose of this study, sales orientation will be applicable to the current study as the insurance industry is competitive and largely dependent on sales orientation (Lazzari, 2018). 3) Market orientation Market orientation can be described as a strategy used to attain a sustainable competitive advantage, Cant and Van Heerden (2017) suggested that organisations should identify the needs and wants of consumers, then modify their products or services to meet those needs and desires. Cunningham (2018), represents market orientation as the organisational culture that most creates the necessary behaviours for the creation of superior value for the buyers and, as a result, a superior endless performance for the industry. In other words, market orientation is delineated as a philosophy and behaviour to perceive and determine the needs of the target and meeting the needs of consumers; creating a competitive advantage (Jandaghi et al., 2011). In their study on market orientation and corporate performance of insurance companies in Nigeria, Ogbonna and Ogwo (2013) revealed that progress was recorded by insurance companies that engaged in market orientation, while those that did not apply the market orientation concept, experienced low performance. Market orientation includes three components which are: customer-orientation, competitive orientation and coordination that reflects the extent to which a company introduces a marketing concept as the heart of the company (Khoshku & Farahani, 29 2018). For the insurance industry to achieve high performance, market orientation must be vigorously pursued as a tool among other strategies by researching what consumers want and need in a car insurance policy rather than produce an insurance policy that does not follow the consumers expectation (Catlin, Duncan, Fanderl & Lorenz, 2017). Since the advent of the internet, the consumer knows much more about the market, and one of the key goals of any insurance is to build meaningful relationship with the audience (Bassig, 2019) by driving higher engagement levels on social media. Social media leads can be a valuable resource for insurers and consumers who are looking for an insurer not only to sell them a policy, but also as expert they can trust to protect their assets (Bedgood, 2016). 4) Societal marketing orientation The societal marketing orientation calls upon marketers to incorporate social and ethical considerations into their marketing practices. The societal marketing orientation resulted after the implementation of the marketing concept whereby organisations adopted the need to give back to society by producing better products for the well-being of society, as indicated by Bhasin (2017). De Meyer-Heydenrych et al. (2017) acknowledged that, an organisation exists not only to meet organisational objectives and satisfy consumer needs; but, also to improve the lasting best interests of individuals and society. Many insurance companies are committed to social responsibilities to ensure that, the communities and the environment are safer place for all. Insurance companies take their social responsibility seriously by helping people and businesses in a philanthropic way while creating a positive change internally (Davis, 2018). Insurance today is woven into the social circles of daily living, it protects consumers against loss, personal liabilities, and offers various benefits in most aspects of a person’s daily life (Hose, 2018). Chan (2012) mentioned that societal responsibility helps in building a better image for a company and raise the standard of living of people in society by, for example, creating a long-term relationship with insurance holders. 5) Relationship marketing orientation Enlightened marketers came to the realisation that focusing on building long-term relationships with consumers provides an enhanced value rather than pursuing mere short-term transactions. Relationship marketing orientation is an approach designed to foster loyalty, interaction and long-term commitment of consumers by providing them with information that is tailored to their specific needs and interests while promoting open communication (Karimi, 2014). 30 According to De Meyer-Heydenrych et al. (2017), organisations that successfully implement relationship marketing, undoubtedly benefit from repeat sales and referrals, which ultimately lead to increased sales, bigger market share, and profit maximisation. By enabling consumers to create quotes that match their needs and situations, insurers are able to create a lasting relationship which will attract and retain consumers (Cunningham, 2018; Stokes & Still, 2016). The sustainability of the insurance industry is based on expanding the confidentiality of consumers (car owners as in this case) toward insurance company. Hence insurance companies ought to focus on building a climate of trust in order to retain their consumers (Madubanya, 2015). A relationship marketing approach allows insurance companies to tailor the service in response to needs generated by the consumer, based on experience and information collected over time (Bazini et al., 2012). Insurance companies are believed to commercialise under rivalrous conditions due to the fact that insurance policies are, becoming commoditized (Girdlestone, 2018). After elaborating on marketing philosophy, several marketing orientation stages were identified and insurance companies can use different approaches for different products line. The challenge is for marketers to respond to the marketing environment by adopting the appropriate strategy marketing depending on competitors actions. Figure 2.4: Marketing mix components THE TRADITIONAL MARKETING MIX MARKETING MIX COMPONENTS THE EXTENDED MARKETING MIX 2.2.2 Marketing mix components The mix was presented as an integrated set of marketing tactics to achieve the organisational goals and create valuable relationship with consumers. In marketing, the mix is considered as the process of designing and integrating various elements of the marketing such as the 4Ps, 7Ps and the 10Ps in order to achieve the company’s objectives (Aarnio, 2017; Ryan, 2017; 31 Tekletsion, 2019). The marketing mix is the voice of the business world because it is used to connect with consumers and stakeholders. Perceived as a collection of tactics, service marketing anticipates consumer demand for an intangible product according to Prachi (2019). Marketers need to be aware of the elements that make up the marketing mix and the options involved in each element, and how these elements can be used in different combinations so that an effective marketing strategy is provided (Belch, 2017). The marketing mix consists of a set of controllable marketing tools which involves placing the proper product in the right place, at the right price and at the right time (Borden, 1964). Twelve elements of the marketing mix were originally identified (Borden, 1964) and later reduced by McCarthy (1960) into the four P’s traditionally known as: Product, Price, Place and Promotion. The marketing mix was said to be “the design and integration of marketing elements into a program that are based on the assessment of market forces, which best achieve the objectives of a company at a given time” (Baker & Hart, 2016). Durett (2016) determined that the 4Ps as identified, included all important features of marketing, but did not pay attention to the current context, characterized by hyper- personalization and a consumer buying behaviour. By reviewing the marketing mix, Kareh (2018) and George (2017) stated that it is becoming a routine to summarize the marketing mix elements in the four P’s, and suggested that the service element should be taken into consideration. Over time, the traditional four P’s have received a wide acceptance in the marketing domain, but some suggestions was made in order to improve the marketing mix. Most suggestion was made due to the fact that the four P’s do not address all marketing situations. A summary of the extended elements of the marketing mix by different authors is presented in Table 2.2. 32 Table 2.2: The service marketing mix Mix elements 1 Product          2 Price          3 Place          4 Promotion          5 Physical      evidence 6 Process     7 People        8 Packaging   9 Positioning   10 Partnership    The newly identified sets of P's, as presented in Table 2.2, raises the question whether all of these P’s are viable and practical to the short term insurance industry. The main concern is that the majority of these views were not published in high-quality academic and scientific journals or tested empirically for reliability and validity. In addition to the 7P’s, Packaging, Positioning and Partnership are taken into consideration in order to constitute the 10P’s which will be used for this study. 33 McCarthy (1960) Booms & Bitner (1981) Ster Van der (1993) Botten & McManus (1999) Kotler & Keller(2016) Srilal (2016) Londre (2017) Markgraf (2018) Service Marketing Figure 2.6: The ten P’s of service marketing Product Partnership Promotion Positioning Price Place Packaging People Process Physical evidence 2.2.2.1 The traditional marketing mix To continually evaluate and re-evaluate their business activities, insurance company should take into consideration the 10P’s of marketing as presented in Figure 2.6. The purpose of the ensuing section is to firstly demonstrate the relevance of the traditional marketing mix to car insurance industry. 1) Product/service The ability of an organisation to meet and satisfy the needs of consumers better than the competition is not an easy task. Products offer consumers specific benefits and are traditionally a combination of tangible and intangible attributes pooled to create value in exchange (Naujoks et al., 2017). The American Marketing Association (2017) describes services as an “intangible element that cannot be separated from the person providing it”. Services usually involve consumer to participate in some way, and cannot be sold in the sense of ownership transfer, and possess no title”. A service is regarded as any non-material, non-stackable economic activity that does not result in a transfer of ownership (Baker & Hart, 2016; Cant & Van Heerden, 2017). There are often items that people buy out of a sense of fear or danger, and car insurance is one of these. Insurance policy is considered by Claessens (2017) as an unsought product, which can be described as a product that the consumer may or may not consider buying 34 under normal conditions. The leading insurance companies offer innovative and different products and services that meet the needs and preferences of thereby improving consumer satisfaction (Collomb, 2017; Madubanya, 2015). Insurance products are financial arrangements as the insurer announces its guarantee to cover costs, the consumer in return agrees to pay a monthly premium as expected (Kokemuller, 2017; Prime Meridian Direct, 2019; Wheels24, 2018). Consumers frequently require support with the service they have purchased, whether it is information on how to use or how to assemble those (Naujoks, Brettel, Singh, Darnell & Schwedel, 2017). Some of the main types of car insurance, according to Bosari (2013), Hippo (2017), PMD (2019) and Wheels24 (2018) are presented in Figure 2.7. Figure 2.7: Main types of car insurance in South Africa Comprehensive car insurance • covers the vehicle for accidental damage, hail or hijack, as well as injury to others or damage caused to third party property. Third party, fire, and theft • is seen as the cheapest comprehensive cover. This policy covers accidental damage to another person’s car or property. Accidental damage to the vehicle will only be covered if it is a fire. Theft and hijackings are also included. Third party insurance • this policy covers damage to the property of a third party. This policy is usually the least expensive and profitable if the car is not very expensive, but the owner of the car should keep in mind that the vehicle is not covered. Source: Bosari (2013); Hippo (2017); PMD (2019) and Wheels24 (2018) 2) Price Price, from a marketing point of view, consists of establishing a fair value that meets the company and the buyer’s expectations, thus enabling us to evaluate the buyer’s performance (Cunningham, 2018; Deepak & Jeyakumar, 2019). Some motorists may argue that car insurance in South Africa is too expensive, but it is vital for car owners to be covered (Wheels24, 2018). Price according to Kotler and Keller (2012) is the only marketing mix element that produces revenues. Price, is the monetary value of a product or service set by a 35 supplier or producer, which can also be set by the buyer when they possess some monopsony power (Kotler et al., 2015; McDaniel, Lamb & Hair, 2011). The current insurance market in South Africa is sometimes considered too expensive for consumers, as over 45% of consumers request insurance quotes in the hope of getting insurance in the form of a reduced premium (Davis, 2018). Khoshku and Farahani (2018) opine that insurance companies have long used factors such as gender, age, the type of car, location, and driving record to determine rates. When purchasing car insurance, a set of guidelines and regulations are adopted to set the rates and car insurance could be considered as a grudge purchase (Bosari, 2013; PMD, 2019). Cunningham (2018) stated that premiums are used to attract consumers by adding an incentive to their purchase. For existing insurance holders, the renewal of their contract focuses on premium prices over competitive premiums (Hyppo, 2020; Masuku, 2018), as Compare (2019) promotes the easy way of obtaining comparative quotations online. 3) Place The marketing of services refers to place as distribution. Location refers to the place where the service is available for the consumer to purchase (Baker & Hart 2016), also called the distribution channel, which ensures that the right service is available at the right place at the right time (McDaniel, Lamb & Hair, 2013). The purpose of a place as a distribution channel is to give car owners effective access to purchase insurance efficiently (Khoshku & Farahani, 2018). Most producers do not sell goods directly to end users, instead use intermediary distribution channels to reach end users (Belch & Belch, 2018; Kotler & Keller, 2012). There are two categories of distribution channels available and the choice of the company is determined by its structure, policy and location in the market. The insurers market a variety of insurance cover, either directly or indirectly (Sanders, 2017). In order to enhance value for the consumer, provider develops relationships with intermediaries (Kotler & Amstrong, 2012). To make the lives of car owners easier, intermediaries perform a variety of functions and Bosari (2013) identified these as insurance agents, call centres agents, independent agents, and lastly brokers. It is clear that to ensure synergy within the channel, the selection of the channel and the intermediaries are crucial to bringing value to the distribution channel and ensure its efficient management (Christotoua, 2017; Cunningham, 2018). 36 4) Promotion It is difficult for companies to sell something that consumers do not know about. As mentioned by Cant and Van Heerden (2017), promotion is perceived as the use of communication tools such as verbal and non-verbal skills to inform consumers of a company’s services. This is done by placing the service on the consumers mind through communication in order to generate a channel of exchange with the targeted consumer (Fourie, 2014). Unlike retailers, insurance companies are traditionally limited in their interactions with consumers, and many consumers rarely think of their insurance provider until their final statement arrives (Chibvura, 2017; Dan Gavriletea, 2015) or when they need assistance. Due to the nature and characteristics of the services, promoting the services is very difficult and service providers have to be creative (Cunningham, 2018). Speaking of promotions, companies have different expectations and these expectations are developed to better position themselves in the consumer’s mind. Brown (2017) and Cant and Van Heerden (2013) identified those expectations as follows: Building awareness: include the selection of promotional activities that help inform consumers about the company and its services. To promote insurance awareness, insurance companies need to publicize the various insurance products available for consumers by including awareness campaigns, social media promotions and road-shows (Saraswathy, 2016). Creating interest: Car insurance is of a particular importance to citizens, and to create consumer interest, the insurance industry make use of online promotion which is becoming a very innovative area in providing creative services to policy holders (Khoshku & Farahani, 2018; Landini, 2012). The target consumer must feel that the company is reaching out to them using advertisements, website content, emails and the sales process to generate interest. An article from the Oxford Business Group (2016) states that the lack of certainty in the insurance industry stems from the idea that insurers need to develop completely new technologies in order to innovate and create value for their consumers. Differentiate service: Kopp (2019) opines service differentiation as a marketing strategy in which a company focuses on differentiating its offers to consumers in order to gain a competitive advantage. For insurance companies to survive and grow, they need to be able to differentiate themselves from their competitors (Kopp, 2019). The insurance industry is too smart to rely solely on price as a point of differentiation, since Organ (2014) strongly recommended the use of relationship marketing to gain the trust of potential consumers before 37 being invited to become a consumer. Depending on the response capacity of their competitors, the ability to properly handle a claim gives the insurance company a real opportunity to differentiate themselves (Cholak, 2015; Dunn, 2018) With the advent of social media, the marketing mix is important for insurance companies as it clearly outlines how they will find new consumers and promote their services to ultimately get more sales. The following seven elements deal with the part of the extended marketing mix that relates specifically to the marketing of services, such as car insurance. 2.2.2.2 The extended service marketing mix The traditional marketing mix has proved extremely useful for a substantial product, however, these are some of the seven new ones and how they can be applied to car insurance. 1) Packaging Several commercial insurance policies are package policies. Cunningham (2018) describes packaging as an action taken by a company to design and create a container to distribute and sell its product. A report from Wheels24 (2018), mentioned that, the insurance industry is highly competitive and insurers are trying as much as possible to differentiate their packages to become more competitive in the market. Several risk coverages are to be taken into account, such as civil liability and real estate’s risk, which when combined together allow companies to pay lower prices than they should have taken out for a distinct policy and risk (Kagan, 2018). This is because commercial packaging policies are available to a wide range of companies and can be tailored to their specific needs. 2) Positioning It is a well-known fact that consumers, partners and employees decide on connecting with companies that speak the same language as their peers. The concept of positioning refers to the strategy used by a company to occupy a place in the minds of the targeted consumer while distinguishing itself from the competition (Richards, 2018). Rouse (2013) describes positioning as a way to identify an appropriate market place for a service or brand and establish it in that environment. A mobile application was developed by the South African Insurance Association (SAIA) to help consumers better understand short-term insurance while encouraging financial literacy in short-term insurance (Moonda, 2013). The SAIA (2017) report has shown that 38 consumers are uneducated and insurance companies are unable to position themselves in the market and minds of consumers which can be explain by the fact that merely 35% of motor vehicles in South Africa are insured. Bedgood (2017) believes that many consumers do not fully understand the concept of insurance and provider should be able to educate them, in doing so, find opportunities to increase brand loyalty and retain policy holders. Numerous insurance companies are competing for a share in the South African short-term insurance industry. Based on Gross Written Premium (GWP), Santam insurance positioned itself in the short-term insurance market with 24%, while Mutual and Federal insurance have reserved R5 billion for the next three or five years to increase its reach (Maharaj, 2016; PWC, 2013; Santam, 2018). 3) People People make up a large part of marketing, (Harvey, 2017) and they are described as the human side of service and experience (Pride et al., 2012). People concept is considered by Richardson and Gosnay (2010) as an important marketing asset. According to the Oxford Dictionary, peoples are humans that form a group with a common interest. People will be loyal to an insurance provider depending on the relationship they have built with the salesperson. Lovelock and Patterson (2015) indicates that the difference between one service provider and another depends on the attitude and competence of their front-line employees. To efficiently offer a unique culture and work environment, insurance companies need to diversify their market and staff profile with the right capabilities (Cascio & Montealegre, 2016). Since no one wants to work in the insurance industry (Heyhoe, 2018; Parrick, 2018), it is essential for insurance providers to hire, attract and develop talented employees (Harvey, 2017; Heyhoe, 2018). Insurance companies need to make their culture the foundation of the organisation and recognize the importance of their people in creating a successful work place (Fourie, 2014; Patel, 2017a). Presented as those involved in service delivery, Kotler and Keller (2016) identifies two set of people (internal and external people) which are critical to marketing success. The area of service experience however identifies three types of people as mentioned by Baker (2014) Cant (2011) and Cunningham (2018): the employee providing the service; the consumer receiving the service; and other service users who may be affected by previous service experience. A number of employees are listed as being extremely important in insurance companies, but it should be noted that not all of these insurance companies have the same number of employees, according to Bonner (2018) and Parrick (2018). 39 4) Physical evidence Insurance products are basically invisible, and as such, physical evidence plays a considerable role as proof of the service to be delivered. Physical evidence is therefore described as the tangible aspects of delivering a product to consumers (Kotler & Amstrong, 2012) or the atmosphere of the service process and any tangible support that is used to market the product (Cunningham, 2018). In the service industries, the physical evidence of a service delivery has to do with how the service is perceived in the market (Harvey, 2017). A statement from Kotler and Armstrong (2012), suggested that the physical setting of an exchange may be described as atmospherics, which are: Visual dimension: appearance of vehicles, uniforms, staff, printed materials and other visible evidence for quality services. Aural dimensions: volume, pitch, ambient music tunes used by the call centre, the quality of the advert played. Tactile dimensions: softness, smoothness and temperature, brochures, equipment, layout of the store, fixture and signage perceptions. Appearance of the employees is an important physical evidence of any insurance company. The physical ambience is the behaviour of the insurance staff on the phone and in person, but the best physical evidence in case of insurance policies can be provided to insurance consumers in the form of policy certificate and premium payment receipt (Shameen & Gupta, 2012). 5) Process The process features all the creative, control and structure that has been brought into marketing management (Bernt & Tait, 2013; Kotler & Keller, 2016). Regarded as the backbone of the service offered, Lovelock and Patterson (2015) noted in their book “Service Marketing” that employees often rely on effective backstage processing systems to provide high quality service. In the same observation, Cunningham (2018) describes the process as the way in which the service is delivered and relates to the role of the consumer, employees, deadlines and any service equipment. The manner in which services are provided by insurance companies affects the conditions under which people buy as well as their propensity to buy. Cant and Van Heerden (2017) claim that the service process is divided into three categories: 40 Before sales: Insurers rarely communicate with their consumers, and the communication begins when there is a demand for an insurance product followed by the purchase decision (Netland & Powell, 2016). This means that consumers communicate by looking for web-based learning, companies’ websites, comparison websites and recommendation from friends. During sales: consumer support is important throughout the sale process and insurers need to integrate trust, from expert communication channels using digital option (Fan Bi, 2017). Throughout the process, the insurance company informs the consumer of the risks and the need to protect themselves, followed by the transfer of the product’s ownership to the consumer such as the documentation of the service offered and its membership card. After sales: refers to various processes in which policy holders are satisfied or not with the service offered in order to spread a positive word of mouth (Netland & Powell, 2016). At a time when insurers are unable to differentiate themselves from the competition through the products they offer, consumer experience is becoming important in providing a competitive advantage for companies (Buttle & Maklan, 2019; Fan Bi, 2017). This process involves human interaction, which provides opportunities to improve consumer loyalty. 6) Partnership Partnership between insurance companies and technology became more common since 2017 (Accenture, 2017; Organisation for Economic Co-operation and Development, 2017). Partnership can be described as an arrangement between two or more brands, working together through strategic marketing campaigns to help each other achieve their goals (Accenture, 2017; Cristal, 2017). Insurers can enhance their chances of finding the right partners by carefully considering their position (McKinsey & Company, 2017), which is how an insurance company will offer its ideal service to supplement a secondary brand while using the target audience to improve its value proposition. The partnership enables the product to reach a part of the population that would have been difficult or impossible to find without a partner connected to the target market while developing new offers (Agrawal, 2020). These partnerships can play an important role in improving efficiency, consumer experience and data capabilities (Simpson, 2018). In terms of innovative technologies, Sanlam insurance is recognized as a market leader, becoming the first African partner to join Insuretech Plug and Play to connect the South African ecosystem to Silicon Valley (Banderker, 2018). 41 It is not advisable to regard one or the other elements of the marketing mix as more important than the other. The insurance marketers are tasked with the responsibility of testing out all element of marketing until they discover the most suitable combination for their business. Marketing mix enables the development of relationships by carefully examining the needs and wants of consumers. The focus of this study is on one of the component of the marketing mix, namely: the marketing communication mix. Subsequently the ensuing discussion explores the concepts of marketing communication and integrated marketing communication (IMC) further. 2.3 Marketing communication The nature of marketing communication is to influence the target market, and without marketing communication, insurance companies may not reach their goals and lose sales opportunities in the meantime. Consistency in informing consumers about what is available and beneficial to them is crucial in helping insurance companies identify the most appropriate communication strategy for their target market (Eiman, 2017). Figure 2.8 illustrates the marketing communication strategy. Figure 2.8: Marketing communication strategy Nature of The marketing Communication marketing communication process communication mix components 2.3.1 The nature of marketing communication It is essential to start by presenting the nature of what marketing communication is and it should be borne in mind that there is no universally accepted description of what marketing communication is. The nature and origin of marketing communication is depicted in Table 2.3 as follow. 42 Table 2.3: Nature of marketing communication Descriptions Source “Marketing communication encompasses all the messages, Cunningham (2018) media, and activities that an organisation uses to communicate with the market while persuading target audiences to purchase their products or services, in a manner to position themselves in the mind of the target audiences.” Marketing communications is a management process through Fill and Turnbull (2016) which an organisation engages with its various audiences. Marketing communication involves the processes of creating Kanibira, Saydanb and communication opportunities, the sending and the reception of Nartc (2014) messages from consumers, to generate the desired ideas in the target audience. Marketing communication is the process by which firms Kotler and Keller (2012) attempt to directly or indirectly inform and remind consumers regarding the products or services they offer. The above description highlights the idea that a company that decides to deliver its services through a particular channel of communication sends a distinct message to the market. The description made by Cunningham (2018) on marketing communication will account for this study, because it raises the idea that messages sent by marketing experts are measured and developed using different communication channels. Any form of promotion requires a communication to take place, therefore communication involves more than just spreading the message and receiving it physically. In the next section, the communication process is presented in detail. 2.3.2 Communication Process Defined as a process, communication is the way of exchanging verbal and non-verbal information, ideas and feelings with one or more individual (Fill & Turnbull, 2016; Hurn, 2014). Basically, the communication process involves a step-by-step task, as depicted in Figure 2.9. To facilitate a better understanding of how marketing communication works, it is essential 43 to start with the communication process, because it gives meaning to marketing communication and enables managers and marketing experts to take advantage of available opportunities. Figure 2.9: Social media communication process Source: Adapted from Baker (2014); Garcia (2011) and Klepek and Starzyczná (2018) Due to the rapid adoption of social media by marketing experts, it is necessary to consider how social media has affected the communication process. The social media message must be viewed as a “strong and attractive” source of information so that the recipient can identify it and reproduce it for the services that are the subject of the campaign (Baker, 2014). The message is how a company promotes it’s services on social media. The sender generates a message and encodes it to the receiver through a channel who then decodes the message. Furthermore, the sender makes use of symbols to convey the message and produce the required response. For an example, the marketing manager and the team create an advert that captures and highlights advantages of car insurance. The receiver decodes the message and sends the feedback to the sender thereby making the communication process to be complete. Once the message is received, car owners interpret the message by determining which insurance company offers a better service. 44 The interaction uses two-way communication between brands and people present on social media (Hutchinson, 2017). A proactive interaction is a super powerful tactic for some brands to connect with the public and find prospects. The insurance company should consider interacting to create a presence for their social network, consolidate the voice of its brand and promote events. The feedback is an important element of the communication process. The feedback is the receiver’s reaction to the message (Bell & Taheri, 2017). It helps the sender in confirming the correct interpretation of the message by the decoder. The exposure is a means used to transmit the message (Fill & Turnbull, 2016). The insurance company should choose an appropriate medium for transmitting the message else the message might not be conveyed to the desired recipients. The present study makes use of social media through which the promotion mix is applied in order to transfer the message. Sharing information on social media networks allows insurance companies to stay connected with their potential consumers. For a safe online sharing, insurance companies need to be relevant, use visuals and add personality to their content. Impersonal relationship has consequences, and according to Sander (2017), this is due to the fact that insurance companies are traditionally limited in their interactions with consumers. However, it is important to build a long-term relationship with policy holders, by rewarding and recognizing the value of the relationships as well as improving the effectiveness of their communications (Gavriletea, 2015). When choosing the type of communication to adopt throughout the marketing stimulation program, the insurance company should analyse the advantages and disadvantages of each components of the promotion mix and allocate the budget between the mix to determine the different components to collectively form the ideal combination (Keegan. 2014; Percy, 2014). There is a number of promotion mix that a company can use and they will be discussed in the next section. 2.3.3 Components of the marketing communication mix The marketing communication mix, also known as the promotional mix, is used for this study and it is important to note that the marketing communication mix includes the promotion used by the company to communicate with consumers. In some cases, consumers purchase the 45 service before hearing about it, while others purchase the service after the company advertises it’s in a form of promotion to increase the value for purchasing the service (Fourie, 2014). Promotions are particularly effective when the marketing manager is sensitive to the needs and wants of the consumer, while striving to persuade, inform or remind consumers of the company’s product and service (Cunningham, 2018). There are several marketing communication mix that a company can use to communicate with the target audience. An illustration of varying marketing communication mix is shown in Figure 2.10 below. Figure 2.10: The marketing communications mix Source: Andrews and Shimp (2017); Belch and Belch (2018) and Koekemoer (2014) The six common components of marketing communication are described below: 2.3.3.1 Advertising Advertising is the first component of the marketing communication mix, as illustrated in Figure 2.10, it is universally acknowledged as any paid form of nonpersonal communication for an organisation, product, service or idea by an identified sponsor (Belch & Belch, 2018; Prasetyo & Nuzula, 2015). Advertising is the introduction of unspecified products or services through 46 various operators to build information, awareness and influence the view of the targeted audience (Grewal & Levy, 2012; Koekemoer, 2014; Kotler, 2014). Currently, insurance advertisements take up a lot of space on television and media, emphasizing creativity and awareness. Media advertising is the most practical way to reach a large number of consumers to involve them in the buying process (Amstrong & Kotler, 2014; Belch & Belch, 2018). A report by McKinsey and Company (2013) revealed that advertising spending for digital media in 2017 media will be three times higher than newspaper advertising and will almost match the share of television followed by a rapid increase in mobile advertising according to ZenithOptimedia (2015). Due to the flexibility of the internet, online advertising for Hsuan and LiYazdanifard (2014) became a powerful tool in the insurance industry, allowing advertisers and agencies to interact and market the service as consumers now spend more time online. Duneva-Stoyanova (2019) states that marketing experts are always concerned about the quality of their advertisement, as great advertising is about quality and the following characteristic can be observed:  Pervasiveness: advertising allows the seller to repeat the message several times and allows the buyer to receive while comparing the messages from different competitors.  Amplified expressiveness: advertising gives a chance to marketers to embellish the company and its product through the judicious use of print, sound and colour.  Impersonality: the public does not feel compelled to pay attention or respond to the advertising, as it is not an interaction with the audience. For a company to reach its target audience, the advertisement should be done according to a specific criteria such as purpose, target audience, geographic area and medium (Koekemoer, 2014). An example of an online advertisement for car insurance is presented in Figure 2.11. 47 Figure 2.11: Online advertisement message Source: King Price Insurance (2019) According to the SAIA (2013), advertisements must comply with the ethics of the Advertising Standards Authority (ASA), while the interest of consumers should be taken into account and must not in any way be misleading. 2.3.3.2 Sales Promotions The next variable in the promotion mix is sale promotion. The American Marketing Association (AMA) (2013), describes sales promotions as a “media and non-media marketing pressures applied for a predetermined time frame to different target audience, thus consumer, retailers and wholesalers in order to stimulate trial, increase consumer demand and improve product viability”. Generally perceived as a marketing activity, sale promotion provides short- term incentives or rewards to initiate a desired response from the target audience (Amstrong & Kotler, 2014; Belch & Belch, 2018; Pride & Ferrell, 2013). AMA’s point of view on sales promotion is articulated and targeted on a specific audience, Belch’s on the contrary emphasizes the aspect of short-term incentive tools aimed at stimulating a sale. Marketing experts have learned with the help of the African Insurance Exchange (AIE) to achieve their goals by using additional promotional methods in combination with advertising to create synergies and serve their consumers in the best ways possible (Dangaiso, 2014; Knoesen, 2019). Compared to other components of the marketing communication mix, sales promotion typically operates on a shorter time line and contributes significantly to profitability (Amstrong & Kotler, 2014). Figure 2.12 below shows the type of sale promotion used by OUTsurance. 48 Figure 2.12: Online sale promotion Source: OUTsurance (2011) Consumers have accepted sales promotion as part of their purchasing decision criteria and the company must use all means possible to communicate the effectiveness of their service (Odunlami & Emmanuel, 2014; Sakara & Alhassan, 2014). While consumer promotions aim to increase sales, Salesforce promotions aim to carry out the company’s sales process which depends on different objectives linked to different types of sales promotion as Figure 2.13 present below. 49 Figure 2.13: Sales promotion strategy Consumer-Oriented Trade-Oriented Contests, dealer Samples incentives Coupons Trade allowances Point-of-purchase Premiums displays Price-off deals Training programs Loyalty programs Trade shows Bonus packs Cooperative advertising Event marketing Source: Dangaiso (2014); Kotler and Amstrong (2012) and Lamb (2012) As shown in Figure 2.13, sales promotion can be grouped into two major categories: consumer oriented which is part of a promotional pull strategy and trade-oriented which is part of a promotional push strategy. According to the SAIA (2013), the two main categories are used in the insurance company and the following standards are applied for all insurance transaction:  Terms and language ought to be clear and not confusing.  The member must make all reasonable efforts to ensure that the consumer understands the policy documents, the specific terms and conditions.  In all cases, consumer information will remain confidential and will only be shared as required by law and approved by the consumer.  The process must be conducted in a fair, honest and transparent manner. SAIA and its members agreed to make an active contribution to ensure that short-term insurance industry remains relevant, inspires the confidence of stakeholder and offers products and solutions for the insurance industry (Saia, 2017). 50 2.3.3.3 Public Relations To maintain their reputation, insurance companies typically invest in good public relation strategies. Public relations (PR) is depicted as “the deliberate, planned and sustained effort to establish and maintain mutual understanding between companies and their internal and external publics” (Cunningham, 2018). The Public Relations Society of America (PRSA) describes “public relations as a strategic communication process that builds mutually beneficial relationships between organisations and their public” (PRSA, 2012). A Public relations (PR) is the discipline that deals with reputation, to gain understanding, support, influencing on opinion and behaviour (Chartered institute of public relation, 2015). The public image today represents 63% of the value of most companies, professionals help insurance companies maintain a good reputation with the public through traditional media and social media (Forsey, 2018; Pahwa, 2018; Sarno, 2012). The use of PR through press releases, community newspaper, mainstream media or social media sites helps insurance companies depending on their target market, to make consumer feel confident about calling them to get insurance rates and information (Pahwa, 2018; PRSA, 2012). The implementation and completion of public relations strategies require particular techniques to communicate with target audiences and a number of techniques as presented in Table 2.4 can be used to achieve public relations goals and objectives (Armstrong & Kotler, 2014; Theaker, 2012). 51 Table 2.4: Public Relation techniques PR techniques Definitions Examples Media relations Refers to links with media A new line of car insurance coverage to entities such as writing show how the company improves its press releases and services and offerings. featuring articles. Corporate image Help create a familiar By using the logo, brochures, uniforms corporate image with the and company cars, insurance service and raise companies market their services to the awareness. public. Community Many companies and Insurance companies help students involvement individuals strengthen obtain an insurance degree and are their public image by committed to the development of getting involved in the careers in the insurance industry. local community. Internet Is a way by which Insurance companies use their website companies can to address issues and provide disseminate public information about the services. relations information? Special event When special events Special event coverage can provide occur, customers may be liability insurance for personal injury notified by the firm’s. caused by an accident. Source: Compiled from: Armstrong and Kotler (2014); Hippo (2017); PMD (2018) and Theaker (2012) The above mentioned public relations techniques help insurance companies to enhance consumer loyalty. In the next section, the use of personal selling by the insurance company will be discussed. 52 2.3.3.4 Personal selling Selling intangible services as goods has always been challenging. The American Marketing Association (2017) refers to personal selling as “the personal or impersonal process of persuading a prospect to buy a commodity or service and to act favourably upon an idea that has commercial significance to the seller”. Koekemoer (2014) highlights personal selling as a personal act through which the seller learns the needs of the potential buyer, and seeks to satisfy them by offering appropriate goods or services. In Cunningham (2018) point of view, personal selling is the process of persuading a prospective or potential consumer to purchase a product or service. In an increasingly digitalized world, the “people factor” should not be underestimated as companies and insurers are questioning what value personal sales consultations offer to the institution and its consumers (Gehrig, 2018). It is important to note that the traditional sales strategies that rely on pushing consumers into closing sales will no longer work in digital age (Olivier, 2018). By using the right digital tools, sales representatives can facilitate decision-making, enhance the purchasing experience and help consumers connect with the brand (Gehrig, 2018). The present study assesses the effectiveness of personal selling as part of the marketing communication mix in creating awareness for insurance industries. To persuade a prospect from the early stage of awareness to a closed sale, salespersons have to follows a personal selling process in a sequence of five steps as presented in Figure 2.14. 53 Figure 2.14: Digital personal selling process • Salespersons introduce themselves using the Step 1: Approach popular search engine. • Once the seller has successfully started the Step 2: Need discovery commercial interaction, he must discover the specific needs and desies of the prospects. • Success here depends on the seller's ability to Step 3: Sales presentation come up with a solution for the prospect. • Closing the deal requires the seller to mobilize contacts from previous sales using social Step 4: Closing the sale media platforms to collect and publish testimonials. • Regarded as an overlooked part of a successful sales process, the seller emphasizes Step 5: Follow up communication, in order to obtain referrals for future sales. Source: Amstrong and Kotler (2011); Andzulis, Panagopoulos and Rapp (2012); Cunningham (2018); Koekemoer (2014); Van Heerden and Drotsky (2014). The digital personal selling process used in this study is a sequence of five steps that the salesperson follows to persuade a prospect from the early stage of awareness to a closed sale (Amstrong & Kotler, 2011; Andzulis, Panagopoulos & Rapp, 2012; Cunningham, 2018; Koekemoer, 2014; Van Heerden & Drotsky, 2014). A study by Harvard Business Review (HBR) has shown that companies with a standardized sales process see their turnover increase by up to 28% for those who follow the sales process, according to the Objective Management Group, 68% of all sellers do not follow the sales process at all (Plaksij, 2019). 54 2.3.3.5 Direct marketing Today, the changing needs of consumers have led insurance companies to use direct marketing strategies instead of relying solely on field agents (Ernest-Jones, 2019). With the advent of technology, several authors have defined direct marketing and Table 2.5 briefly presents them. Table 2.5: Direct marketing definitions Definitions Source Direct marketing is a marketing method used by insurance Belch and Belch brokers and companies to find new consumers. (2018) Direct marketing is the combination of advertising, sales Cunningham (2018) promotion and personal selling where the company attempts to reach the target audience directly, without the assistance of a middle man. Direct marketing is an advertising strategy that relies on the Kenton (2019) individual distribution of a sales pitch to potential consumers. Direct marketing for insurance company is the use of television, Pearson (2017) radio, print, website and social media advertising to attract consumers. Source: Belch and Belch (2018); Cunningham (2018); Kenton (2019) and Pearson (2017). Table 2.5 reflects that more insurance companies are adopting a direct to consumer approach, and Pearson’s (2017) description on direct marketing mirror the principal objective of this study which consist of understanding the influence of social media promotion mix on consumer purchase decision. Since consumers are more likely to “know” about the service offered before making a purchase decision, they are faced with the somewhat impenetrable nature of the insurance market (Blakeman, 2018; Ernest-Jones, 2019). Many companies use consumers databases and consumers are taking steps to block insurance companies as they become aware of how data is used to target them with digital advert (Augustyniak, 2019). Direct marketing for insurance companies can be quite effective when handled properly, as there are several 55 benefits of using direct marketing to sell insurance services (Las Vegas Color Graphics, 2014). Unlike most marketing campaigns, direct marketing campaigns do not rely on advertising in mass media; instead, direct mail postcards and letters are two types of traditional direct mail which are popular for insurance marketing; other types of direct marketing used by the insurance sector include telemarketing, radio, television and digital (Augustyniak, 2019). Insurance companies are now realizing that if they want to build a long-term relationship with their consumers, they should move away from third parties and talk to consumers directly. The following discussion will be on digital marketing. 2.3.3.6 Digital marketing Digital marketing encompasses all marketing efforts that use an electronic device (Cunningham, 2018). The new advance in technology has had a huge impact on the way in which insurance companies communicate and interact with their consumers. Perceived as the marketing of the future, digital marketing use numerous channels to connect with consumers online, where they spend most of their time (Dewdney & Ride, 2014; Miryala & Reddy, 2015). Marketing has always been about connecting with their audience, which means insurance industry need to meet consumer where they spend time: on the internet (Andrus, 2020; Hill, 2015). Digital and online media make it easier for companies to collect consumer data and track online habits through the use of cookies, and companies need to be open about how they collect and use information in order not to influence their privacy (Bowden, 2014; Hill, 2015). Insurance company can get a better idea of which marketing methods is appropriate and how it should be applied, Figure 2.15 briefly gives a list of digital marketing that can be used. 56 Figure 2.15: Digital marketing Content marketing Social Marketing media automation marketing Digital marketing Email Website marketing Inbound Afflialiate marketing marketing Source: Lunderberg (2019) and Simplilearn (2020) By leveraging digital advancements and multi-channel platforms, insurers can deliver impressive results and have a positive impact on how they interact with their target audience in marketing and distribution. Therefore, it is of necessity for a marketer to determine the appropriate blend of these promotional elements into an ideal mix to effectively market the company’s good/services. All forms of communications and messages are carefully interwoven and the subsequent discussion deals with integrated marketing communication, why it is important for insurance companies and how to go about delivering an integrated approach. 2.4 Integrated service marketing communication (IMC) The term integrated marketing communication (IMC) was coined in the mid-1990s (Marcinkiewicz, 2011) and this aroused the need for marketers to coordinate their 57 communication channels and the promotional components. Not too many years down the line, the perception of IMC shifted from a narrow view into a more holistic view, which consisted of ensuring that all components of the communication mix are linked (Vongkhamheng, 2017). However, it is necessary to coordinate the various components and communication channels so that a message sent by a company is consistent (Cunningham, 2018), irrespective of the component(s) and/or channel(s) used. The core dimension of a discipline is the agreement on its definition. One of the first cited definitions of IMC was proposed by the American Association of Advertising Agencies (AAAA) in 1989: “A concept of marketing communications planning that recognises the added value of a comprehensive plan that evaluates the strategic roles of a variety of communication disciplines, and then combines these disciplines to provide clarity, consistency and maximum communication impact”. Kotler et al. (2015) depict IMC as “the concept under which a company carefully integrates and co-ordinates its many communications channels to deliver a clear, consistent and compelling message about the organisation and its services”. Kotler highlights the objective of IMC, which is to deliver clear and persuasive messages to multiple audiences through multiple channels. For any communication initiative, insurance companies should determine who their main audiences are and then develop relevant messages through the media that are appropriate and effective in reaching that particular group (Armstrong & Kotler, 2013; Cunningham, 2018). The IMC concept can influence the purchasing behaviour of consumers by transmitting messages via several marketing communication channels (Kattiyapornpong & Yu, 2019; Pluta-Olearnik & Organizations, 2018). In addition, to influence consumers purchasing behaviour, IMC is also being developed to reduce the marketing budget as IMC could allow the insurance company to reduce their advertising costs and minimise the duplication of advertising designs and photography (Pluta- Olearnik & Organizations, 2018; Vongkhamheng, 2017). Therefore, IMC is recommended as a crucial marketing approach for small and medium enterprises, such as many insurance companies, as it enables them to gain access to target audiences directly with a lower marketing cost (Armstrong & Kotler, 2013; Cunningham, 2018; Mapheto et al., 2014). 2.4.1 Social media and integrated marketing communication Integrating social media into businesses is considered as one of the most important activities in today’s business environment, as the main functions of businesses depend on social media (Rogala, 2015), and they allow companies to access and communicate simultaneously with a 58 large group of consumers (Qualman, 2011). Insurance marketers should pay attention to consumers’ attitude towards online comments and reviews since consumers today do consider the online reviews of other consumers before deciding to purchase products or services (Bothma, 2018). Social media is one of the many mediums that can be used as an IMC component when marketers are designing marketing communication strategies. In the context of social media incorporation into integrated marketing communication, it is essential to elaborate on the opportunities and challenges of IMC. The effective use of social media can bring great opportunities for businesses, but will require some thought and planning. However, insurance companies need to be knowledgeable about what they can put on social media, and what would be realistic to expect in return when they incorporate, and maybe replace traditional media with social media. 2.4.2 Integrated marketing communication strategic planning process The strategic planning process is viewed as the development of a platform that serves as a channel for ideas and skills while recognizing the experience of people, as well as key traits such as tenacity and willpower (Saia, 2017). The strategic planning process for integrated marketing communication must be guided by the organisation’s strategic marketing plan, which in turn is guided by the insurance company’s overall strategic priorities (Bell & Taheri, 2017). Delivering IMC means certifying that all communication and media used are in line with the needs of target audiences in terms of messages, needs and preferences. Figure 2.16 illustrates how the marketing mix is recognised as a process to deliver an integrated communications program. 59 Figure 2.16: The IMC planning process Marketing communications Positioning IMC components: strategies advertising, sales Audience promotion, PR, direct marketing, Creative personal selling, sponsorship... Media Source: Bell and Taheri (2017) To help an insurance company develop an integrated marketing communication strategy, the following four steps implement a cohesive and integrated marketing strategy to produce a better result. Step 1: Positioning Baker (2014) describes positioning as a marketing concept that outlines what a business should do such as creating a mental image to market its services to its consumers. Brand positioning is important for the company because it represents the company’s services and makes them more visible and recognizable for consumers (Shimp & Andrews, 2013). Positioning a service is an essential element for a complete marketing strategy, since the development and communication of the service features are made available for consumers and done in different ways (Lauren, 2019). Based on the target market, the marketer fashions an image of their service and the focus of this study is on car insurance and online promotion mix. The starting point for any discussion on positioning is a thorough understanding of the target market and several marketing elements which must be taken into account to increase awareness (Baker, 2014; Bell & Taheri, 2017). Positioning a service is an essential element for a complete marketing strategy and several types of positioning strategies (Bell & Taheri, 2017; Guettler, 2019; Shimp & Andrews, 2013) are identified as follows: 60 Service benefits: short-term insurance can associate their service with certain beneficial value such as roadside assistance, cash back bonus and flexible premiums. Service price: short-term insurance associates their services with competitive pricing by providing affordable monthly cost for car servicing. Service quality: short-term insurance associates their service with high quality as the claim service time. Competitors: a highly competitive auto insurance marketplace is making coverage more widely affordable for all drivers, making consumers think that the insurance service is better than that of the competitors. Given the competitive nature of the South African short-term insurance market, OUTsurance and Santam have successfully positioned themselves (Christotoua, 2017) as domestic brands in the minds of South African consumers. Step 2: Audience A target audience includes a targeted set of consumers for whom it directs its marketing efforts (Kotler et al., 2015). The insurance industry needs to understand consumer service preferences to increase efficiency while creating a proper marketing communication practices for their audience (Lam et al., 2014). Within an organisation, there can be many types of audiences both outside and inside an organisation identified as primary audiences (car owner) and the secondary audiences (employees with income, adults and company). Below are the three distinct group of service marketing strategies identified by Bell and Taheri (2017); Klepek and Starzyczná (2018) and Pluta-Olearnik (2018);.  Pull strategies: to reach consumers where the focus is on communicating directly with end-users. Here, car owners are considered as the primary target audiences.  Push strategies: to reach members of marketing channels where the aim is to move service offers through these channels. The most significant audience in this case is trade and other insurance intermediaries.  Profile strategies: to reach all relevant stakeholders where the aim is to develop, build and grow long term relationships and to maintain a positive reputation. 61 Once the audience has been identified, it is then useful to gather information that can help the insurance provider to define the content that will most effectively target its audience. Step 3: Creative The marketing manager should not overload the audience but provide them with enough information to take action. The creativity of a message is one of the necessary steps for IMC because the message presents what the insurance company wants to project to its target audience (Percy, 2016). It also describes exactly what an insurance company would want their target audiences to think, feel and how to react after deploying the IMC components (Bell & Taheri, 2017; Kotler et al., 2015). Step 4: Media The last step of the strategic planning process consists of selecting the appropriate media. Today’s insurance consumer shops across various digital channels, turns to social media for recommendations and often uses different mobile devices during the entire purchasing journey (Bedgood, 2016). Since insurance is all about trust, the media image of the insurance industry and the insurance companies are essential for stability. As per Bell and Taheri (2017), media planning by design and selection involves the following important decisions that marketers must apply:  Frequency of message: in order to be effective, how often does an insurance company need to talk to their audience (Fill & Turnbull, 2016).  Reach: as soon as the audience has been identified, the overlay is the main objective of the media, which will create the opportunity to respond (Bell & Taheri, 2017; Kumar, 2012).  The media channels identified for selection: the aim of a distribution channel for insurance companies is to allow insurers to access and purchase products in the most efficient way (Bell & Taheri, 2017; Sanders, 2017). Taking all these steps into account, the marketing planning is recognized as a necessary process, as it improves the ability of companies to cope with a complex market environment while helping companies to generate better results (Percy, 2016). The evolution of technology and the consumer behaviour leads to the needs to improve the marketing communication (Warran, 2016). In order to understand the IMC, it is essential to recognize the importance of 62 the IMC for insurance companies and the following section therefore provides a better understanding. 2.5 The importance of integrated marketing communication in the insurance While playing an important role in communicating the message, integrated marketing communication greatly contributes to the affordability of consumers at lower cost (Linton & Shoenberger, 2019; Percy, 2016). The IMC, which is a strategic tool for companies, has a positive impact on the effectiveness of communication, creativity and brings consistency in communication (Naeem et al., 2013). Bell and Taheri (2017) proposes a new dynamic IMC model, which would enable insurance companies, to focus their marketing communications on the consumer, thus making the message more effective while minimizing consumer’s risks. Finding the perfect IMC requires many different levels of integration. While IMC guides potential consumers through the various stages of their purchasing process, IMC protects the consumer against imminent attacks against competition while retaining the consumer for life (Joshua Lyons Marketing, 2019). To better explain how IMC work for insurance companies, Figure 2.17 makes use of Figure 2.16 to presents the different steps to be used. 63 Figure 2.17: A conceptual model of IMC process for Car Insurance Source: Adapted from Bell and Taheri (2017). There are different steps involved in developing an IMC plan (Bell & Taheri, 2017; Naeem et al., 2013). The first step involves identification and understanding of the target audience and their purchase decision. Mawson (2016) stipulated that there is a long way to perfect the online experience that misleads many car owners over common misunderstanding and unusual terms. However, online reviews and service quality create unique image to support brand position. The second step, lies on generating attractive messages using online promotion mix, tools and platforms. McCabe (2014) suggested that getting appropriate and engaging messages to the target audience can contribute to the profitability and success of insurance companies. This means that IMC offers more possibilities for companies to broadcast certain messages to convince the public to choose their brands and services through various marketing and media communications containing all the message (Yeboah & Atakora, 2013). The final step involves choosing the media mix and promotion mix tools that suit the target audience. Thus, by considering the needs and expectations of car owners for the insurance policy and choosing the right combination of marketing channels, insurers helps consumer in their purchasing decision 64 (Blake, 2018; Mawson, 2016). A number of studies, such as that of McCabe (2014); Naeem et al. (2013) and Kattiyapornpong and Yu (2019), have shown the value of an integrated approach to communications. While digital advances give advertisers the ability to manage their interaction with consumers at a more individual level, it also presents greater risks for those who get it wrong (Bell & Taheri, 2017). 2.6 Summary This chapter has revealed numerous definitions of marketing as consumer-centric trend, which has become increasingly evident in multiple aspects of marketing, ranging from service development to marketing communication. The marketing communication was briefly discussed and the marketing communication mix components were enumerated and explained in regard to how these apply to short-term insurance. The most important task faced by a marketer is to identify and select an optimum promotion mix to help achieve business objectives. This chapter also outlined the details of marketing communication mix and made an attempt to explain the processes of communication. In order to achieve their goals and objectives, insurance industries need to assess their marketing environments, business opportunities and anticipated threats in the future. The ensuing section elaborated on the marketing mix components and how these apply to social media promotion mix. Furthermore, the chapter discussed the integrated service marketing communications and its importance by proposing an IMC process for short-term insurance. The next chapter presents a more in-depth discussion of short-term insurance companies in South Africa and consumer behaviour when it comes to the purchasing of car insurance via social media. The emphasis is on the technology of acceptance model associated with the technology of perceived behaviour on social media promotion mix and the purchase decision. 65 CHAPTER TREE SOCIAL MEDIA AND CONSUMER BEHAVIOUR 3.1 Introduction The present chapter focuses on consumer behaviour with a special emphasis on how their purchase decision is influenced by a possible use of social media. In the past decade, there has been an increase of user-centric web technologies such as blogging, social networking and media sharing platforms. The social media revolution has led to new ways of searching and obtaining information, allowing users to connect and interact in digital spaces increasingly controlled by strangers, which in turn influence opinions in the offline space (Powers et al., 2012). The use of social media by consumers is anxiously monitored by marketing experts, but little is known about how it influences consumers’ decision-making (Voramontri & Klieb, 2019). Manyika et al. (2011) are of the opinion that marketing via social media would be another perspective of interfacing with people, however, it is unexploited. A reported number of studies were conducted on the factors that can facilitate the integration of technology in firms and the impact of social media on online consumer (Akar et al., 2015; Hajli, 2014; Lim et al., 2016; Manyika et al., 2011) without considering the effects of social media promotion on consumer purchase decisions. Fig 3.1, provides an outline of social media and consumer’s behaviour in the context of short- term insurance. This chapter commences with a discussion of the different types of social media used by short-term insurance and their influence on consumer purchase decision. Furthermore, it provides an overview of consumer behaviour and explores the importance of consumer behaviour in terms of short-term insurance and the various internal and external factors that could have an influence on consumers’ behaviour and decision-making. This chapter concludes with a discussion of the different factors that influence the purchase intention related to the current study. 66 Figure 3.1: Chapter Outline INTERNET PENETRATION IN SOUTH AFRICA AN OVERVIEW OF SOCIAL MEDIA SHORT -TERM INSURANCE IN SOUTH AFRICA EVOLUTION OF TECHNOLOGY IN INSURANCE COMPANY CONSUMER BEHAVIOUR CONCEPTUAL FRAMEWORK FACTORS INFLUENCING ONLINE PURCHASE INTENTION 3.2 Internet penetration in South Africa In this section, various sources regarding the internet penetration in South Africa are discussed. With more people using the internet, online shopping is becoming more relevant (Hvass & Munar, 2012), while there is a huge unmet demand for purchasing insurance online (Lsesu Actuarial Society, 2017; Matouscheck, 2017; Pignotti, 2019). The development of the internet began in the early 1960s, with the creation of the ARPA (Advanced Research Projects Agency) which consists of building a strategic communication network between American universities and research laboratories using the ARPA Network marking the beginning of the internet with a unique key feature known as “Innovation” (Bourgeois & Bourgeois, 2014; Cohen-Almagor, 2011; Leiner, Cerf, Clark, Kahn, Kleinrock, Lynch, Postel, Roberts & Wolff, 2012). The internet is made up of protocols that can be described as “a vast interconnection of computer networks that spans the globe” (Coe & Yeung, 2015). According to Bourgeois and Bourgeois (2014), internet is simply a system that sends and receives data. During the 1990s, 67 CHAPTER TREE: SOCIAL MEDIA AND CONSUMER BEHAVIOUR INSURANCE COMPANY the internet became a global phenomenon and in 1993, South Africa launched its first Internet Service (Freedom House, 2011; Goldstuck & Hunter, 2010; Internet Society, 2010). Cullen (2011) describes the internet penetration as the relationship between the number of internet users in each country and its demographic data. The digital technologies and internet have greatly been accessible to young and old in many Africa countries much quicker than developed countries (World Development Report, 2016). A report from Internet World Stats (2020), in Figure 3.2 presents the internet penetration in the world. Figure 3.2: World Internet Penetration Rates: geographic Regions Mid-Year 2020 North America Europe Latin… Oceania/Australia Middle East World, Avg. Asia Africa 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Source: Internet World Stats (2020) Figure 3.2 shows the internet penetration in the world and their penetration rates. The first two on the list are North America with 89.4% and Europe 87.7%, Africa comes in with 39.6%, which is below the average (58.8%). According to Clement (2019), the number of internet users in Africa was estimated to 339.28 million, 455.84 million and 525 million respectively in 2016, 2018 and 2019 (Internet World Stats, 2020). This is in support of Opiyo (2016) who mentioned in his article entitled: Why internet use is low in Africa; one of the main reasons is due to potential consumers who do not always find the internet meaningful because of the poor quality of communication systems and the very high basic costs of internet access. The number of internet users in South Africa in January 2020 were estimated at 36.54 million users, with an increase of 3.1% between 2019 and 2020 (Kemp, 2020). According to De Lanerolle (2012), 68 the majority of internet users in South Africa are young Africans with low income. Five categories of internet users can be identified: café connected which represent 15% of the internet users in South Africa, Mobi’s (20%) described as new internet users, wired (23%) which have more experience with the internet, in the fourth position we have the connected at home (37%) and finally the super connected (5%) are more accustomed to newer technologies. South Africans spend an average of 8 hours and 32 minutes on the internet per day via any device (Kemp, 2019). According to Forbes (2018) and Shaw (2018), people around the globe (53%) are using social media in real time, with 42% spending nearly a quarter of their daily time on social media. This therefore serves as an informed guideline for companies whose services and or products are online to the advantage of the increased number of their consumer on social media platform. The percentage of internet users who made at least one purchase online via any device in the previous months as from January 2019 are presented in Figure 3.3. 69 Figure 3.3: E-Commerce use amongst internet users 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Source: Shaw (2018); Statista (2018) and We are social (2018) Figure 3.3 shows that, worldwide, 75% of internet users purchase a product or service online using any device. While 86% of internet users in Indonesia purchase online, 82% purchases in China are followed by Germany (81%), UK (81%) and Thailand (80%). Below the average (75%), Russia comes with 56%, followed by Colombia (56%) and South Africa with 55% as South Africans like to touch and feel prior the purchasing decision (Bayati, 2017; Rodney & Wakeham, 2016). The next section looks at the social media in a context of short-term insurance. 3.3 Overview of social media The World Wide Web or simply the ‘Web’, founded by Berners Lee in 1989 is a way to access information through the internet. The Web 1.0 refers to the first stage in the World Wide Web, which was totally in favour of organisation-generated content (Zugal et al., 2017). The creation of social networking sites like Facebook, Instagram, Twitter and YouTube led to the popularity of the term ‘social media’. The term ‘social media’ widely used nowadays appeared for the first time in 2004, after LinkedIn created its social networking application (Deleure, Kaplan & Haenlein, 2012). The concept of “Web 2.0” began with a conference brainstorming session between O’Reilly and MediaLive International (O’Reilly, 2009). Launched by O’Reilly in 70 2005, Web 2.0 is a platform where content and applications are frequently changing and users in participatory and collaborative ways share information (Lucenko & Nørgaard, 2012). Based on the Web 2.0 philosophy, social media is a user-friendly web platform with the ability to create and exchange content in a multiple context (Constantinides, 2014; Kaplan & Haenlein, 2010; Tuten & Solomon, 2015). The gap between Web 2.0 and Web 1.0 in terms of technology has moved business focus to consumers, from entities to communities, from publication to participation and from invitation to intrusion (Bothma & Gopaul, 2015). Table 3.1 briefly shows the evolution of the World Wide Web. Table 3.1: The evolution of the World Wide Web Years Descriptions 1970 – Web 1.0 (Multi-User Was created to provide a real time virtual world Dimension) for playing games and online chatting. 1997 – Web 2.0 (Social Media) Was established to allow individual users to create profiles of themselves. 2000+ – Social Media Platforms Was created to share information on different platforms. The internet has grown into an active network where people can successively connect with one another on various platforms (Rooderkerk & Pauwels, 2016; Ryke, 2019). The National Association of Insurance Commissioners (2012) asserts that the emergence of social media is considerably accelerating the advancement of information and communication technologies. Social media penetration in South Africa stood at 37% in January 2020, providing consumers with faster access to information and has increased the online buying process (We are social & Hootsuite, 2019). However, there are still many debates and discussions about a universal definition of social media as social media alters and blends into the evolution of new media. Regardless of what the standardized definition might be, several studies and articles have set out the common fundamental purpose of social media as presented in Table 3.2. 71 Table 3.2: Social Media described Descriptions Source Social media is described as the ‘websites and Botham and Gopaul (2015) applications that enable users to create and share content or to participate in social networking’. Social media is not just an activity; it is an asset of Delerue et al. (2012) treasured time and resources. Contents, or join online communities. Social media is described as a “consumer-generated Putter (2017) media that covers a wide variety of new online sources of information, created and used by consumers with the intention of sharing information with others regarding any topic of interest. Social media is a group of internet-based applications The national association of that allow users to participate in online exchanges, insurance commissioners create. (2012) Social media is the means of online communication Tuten and Solomon (2015) between interconnected and interdependent networks reinforced by technological skills and flexibility. Table 3.2 highlights diverse description of the ‘Social media’, yet the meaning and functions are adequately related. The description made by Putter (2017) will account for this study, because social media is presented as “consumer-generated media” which means the user- generated content is the essence of social media; furthermore, social media is presented as “social networking sites” which allows individuals to create their profile within a bounded system where they can create and share content. The advent of social media has changed the way companies interact with their consumers by making it effective and convenient. The qualities that make the presence on social media successful are identified by Fuchs (2017), Kietzmmann et al. (2011), Tuten and Solomon (2017) as presented in Table 3.3. 72 Table 3.3: Social media characteristics Social media characteristics Descriptions Identity The primary characteristic of a successful social media presence is the ability of the machine to make judgments based on what people do and say. Various functional information about consumers are openly posted on social media platform such as name, location gender and profession. Conversation This is considered to be the means of interaction between consumers depending on what drives them, their online presence and the content of the information. Social presence Is the accessibility of both the organisation and consumers on the social media platform which reflect the ability to build and engage in meaningful relationships? Groups Often regarded as community, referred as/ refers to people with similar or common goals which allows users to create, post and comment. Relationship Describes the degree of association among consumers and organisation which determine the nature and the contents they share. Reputation Attached to trust, online reputation for company determines how consumers perceive the business when tracking, monitoring and choosing information. Sharing Is the final characteristic of social media it entails the kind of information companies are willing to share for consumers to recommend and spread the information. Source: Fuchs (2017); Kietzmmann et al. (2011); Tuten and Solomon (2017) 73 Putro and Haryanto (2015) advised companies to use social media and plan to set up training programmes which will reduce computer anxiety among employees who interact with online users. Social media provides insurance companies with a platform to educate their policyholders about the services they offer, while building brand awareness (Catlin & Lorenz, 2017). Ten websites were identified as the best in South Africa: google.co.za, google.com, youtube.com, facebook.com, Wikipedia.org, news24.com, fnb.co.za, twitter.com, yahoo.com and takealot.com (Carr & Maier, 2013; We Are Social, 2018). The next section provides a brief review of the insurance market in South Africa and the short-term insurance in particular. 3.4 Short-term insurance in South Africa Due to the lack of local insurance market in South Africa, the British rule facilitated the entry of British citizens and business which stimulated the establishment of the Cape Colony in early 1800s (Borschield & Haueter, 2012; Lobo-Guerrero, 2015). The first South African insurance company was founded in Cape Colony by the Zuid-Afrikaansche Branch en Levensversekering Maatschappij in December 1835 (Borschield & Haueter, 2012; Verhoef, 2012). After the mineral discoveries in the late 1860s, many British companies extended their businesses to Johannesburg while more than twenty insurance companies registered in the Cape Colony around 1861 (Borschield & Hauerter, 2012). For the purposes of this study, the term, short- term insurance will dismiss any health insurance that may be perceived as a short-term service in South Africa. Still and Stokes (2016) explained insurance as “the fair transfer of risk from an uncertain but measurable loss, from one entity to another, in exchange for money”. Rudden (2019) described the insurance penetration as the ratio between the value of premiums in a particular year for a particular country. The largest short-term insurance company in 1927 was the British insurer and in 1974, South Africa had a single short-term insurance policy covering all their assets under one umbrella (Hagedorn-Hansen, 2018; Moodley, 2019). Short term insurers include those insurers who provide consumers with immediate coverage against low probability losses, damages or household contents, vehicles, properties as well as personal insurance (Mahlangu, 2018). According to Milpark Education (2016), short-term insurance insures against the unforeseen event with the financial compensation of the loss that has occurred (KPMG, 2019; Milpark Education, 2016; Still & Stoke, 2016). The motor accident insurance was introduced in the early 1930s in response to the dramatic rise in automobile ownership (Borscheid & Haueter, 2012; Moodley, 2019). South Africa is by far the largest African insurance market, 74 generating US$ 44bn of total premiums (African Insurance Organisation, 2018). The insurance penetration across Africa remains very low, and Figure 3.4 indicates the highest penetration of the Sub-Saharan Africa. Figure 3.4: Insurance penetration across Sub-Saharan Africa in 2017 Source: Rudden (2019) In South Africa, the insurance penetration rate was 14% in 2014 and has significantly increased to 17% in 2017, which is the highest rate according to Figure 3.3 (Rudden, 2019). The insurance penetration rate for Namibia, Lesotho, Mauritius and Zimbabwe are ranked between four and seven percent. Compared to the rest of the Sub-Saharan countries, South Africa has the highest level of insurance penetration with a relatively more mature market (PWC, 2018). In 2014, car insurance was unanimously considered extremely competitive. Short-term insurance companies paid far more claims than they collected in 2013, suffering large-scale losses due to extreme weather events and random weakness (Barry, 2014; PWC, 2014). With a low level of insured vehicles in South Africa, the short-term insurance earned ZAR102 billion in billed premiums in 2018 (KPMG, 2019). Figure 3.5 displays the main players, as well as the amount of money based on the premiums accumulated for the year 2018. 75 Figure 3.5: South African short-term insurance market in 2018 (annualised premiums, in ZAR billions) 30 25 20 15 10 5 0 Source: Klynveld Peat Marwick Goerdeler (2019) and Rudden (2019) The top five short-term insurers remained relatively stable, with Santam at the top with (R24 billion) of market share, followed by Hollard (R10 billion), Old Mutual (R9 billion) and respectfully R7 billion for Guardrisk, Outsurance and Telesure. The South African Insurance Association (SAIA) is the representative body of the short-term insurance industry in South Africa. The global short-term insurance market, including South Africa, remains in a phase of below-average profitability. According to Figure 3.4, there has been no change in the top three positions since 2017 while Centriq (R3 billion), Escap (R3 billion) have declined whereas Bryte (R4 billion) and Absa (R3 billion) have remained stagnant (KPMG, 2019). In 2014 the number of brokers and intermediaries for short-term insurers was projected to 14 698, while the same year, the number of short-term insurers was estimated at 12 million, expecting to reach 16.2 million in 2017 (PWC, 2014). In order to pay reduced premiums, 55% of South African policyholders had changed insurer in the preceding three to five years, as mentioned by Accenture (2016). As illustrated in Table 3.4, the South Africa Short-Term insurance has strength and weaknesses according to PWC (2014). 76 Table 3.4: Strength and weakness of SA Short-Term insurance Strengths Weaknesses The ability to grow new talent. Slow adaptation to change and ageing workforce in the intermediary market. The ability of consumers and the industry to Underinvestment in technology. adapt to new and innovative methods of distribution. Entrepreneurial culture encourages product Miss-selling, probably driven by and enterprise development. commission incentives. Diversified multi-channel distribution models. Loss of market share to non-traditional insurers. Source: Compiled from Accenture, 2016 and PWC, 2014 3.5 Digital technology in short-term insurance companies No industry is exempted from innovation, with the advances in technology, companies are enabled to complete extra responsibilities in less time with less effort and more productivity, the insurance industry is not exempted (Kristy, 2017; Van Eeden, 2017). The short-term insurance industry in South Africa has been one of the slowest industries (Accenture, 2016; Moodley, 2019; PWC,2016a) to realise the importance of going digital and may not be aware of R115 billion value of gross written premiums they can stand to gain by 2020 (Accenture, 2016; Mahapa, 2016). Being static for a long time, Nicoletti (2016) advised insurance companies to go digital. Innovation is generally seen as a positive development enabling insurance companies to remain relevant in a competitive market while providing convenience and efficiency to consumers (Kylliäinen, 2019). Looking at insurance companies, technology has enabled the insurance industry to become more efficient and accurate in administrating claims and calculating premiums via online platforms with less time (Bellryck, 2018; Goyal, 2018). As insurance companies continue to question the adoption of digital, the emergence of new competitors highlights the disruptive potential of innovation, which plays an important role in product design, product distribution and the provision of services in the insurance sector (Deloitte, 2017; McKinsey & Company, 2017). 77 A report from the short-term insurance shows that South African consumers are very concerned about the claims procedure while the sector is also being pressured by allegations of fraud (Bizcommunity, 2020; Mahlangu, 2018). Research done by Accenture (2016), with the title: ‘Be digital’, stipulated that consumers expect their insurers to respond promptly and efficiently to their immediate desires and offer loyalty programs while interacting with them on social media. Technology is an important asset to social media and is now being used in the introduction of various forms of social interaction (Berthon et al., 2012). Social media is becoming an integral part of life in contemporary society and has changed the creation, sharing, and consumption of information (Westbrook et al., 2012). Most insurance companies are taking advantage of innovation to tarnish corporate culture and create new opportunities (Daugherty, Carrel-Billiard & Biltz, 2016; Goffe & Jones, 2013). At the forefront of the rise of social media is the World Wide Web (WWW) and the internet. The web in its simplest form is composed of interlinked hypertext documents that can be accessed through web browsers (Khan-Am & Rangsom, 2014), such as Internet Explorer and Chrome. The accelerating rate of technology adoption resulted in the internet being used as a tool for communication, a browser, entertainment, and as a purchasing channel (Rooderkerk & Pauwels, 2016; Tsao & Yang, 2017). 3.5.1 The importance of social media for short-term insurance The development of technology has facilitated the creation of social media, where consumers are now able to publish their personal views and share their experiences in a collaborative way. The key developments and drivers of growth in the local market currently focuses on the African continent’s demand for digitalisation and insurance. The African continents is still one of the least explored in the world with enormous growth potential ( PWC, 2014; Van der Ross, 2015). Companies try not to miss out on a single opportunity by communicating with their market through social media. By using digital technology to better identify consumer needs and preference, insurers often need to customised their offers in order to serve the different demands of the South African consumers (KPMG, 2019; Mahlangu, 2018). A scientific research study on digital platforms conducted by Roesler (2015) has shown that in today’s digital world market research, by taking into consideration the marketing strategy and by building a good relationship with consumer, organisations are more likely to be effective. Understanding media consumption is the key to an effective and efficient relationship with consumers as social media is now challenging traditional media (Chikandiwa, 2013). By trying 78 to understand the adoption of social media over traditional media, Woodall and Colby (2011) proposed four main components of social media and these are:  Satisfying an instinct,  The excitement of sharing,  The search of advice and  Sharing with others who have similar interest. These four components are important because consumers prefer social media to traditional media and insurance companies must use social media effectively to be able to obtain the benefits that social media can offer. Insurance companies have long leveraged social platforms for marketing and brand building, but now they are also finding that social mediums furnish a bounty of data that can be used to improve the underwriting and claims process (Faurie, 2019; Keneally, 2012). Social networking sites being treasures of personal information help insurance companies to investigate accident claims to prevent fraud (Faurie, 2019). By posting the wrong thing at the wrong time, could mean the repudiation of an insurance claim. There have been instances of people attempting to commit insurance fraud but were thwarted due to their social media posts, as per Shelford (2018). Social media users connect with others by following their update, responding and commenting on them (Rhys, 2013). Those from generations preceding Generation Y were slower to adopt social media, making decision-makers sceptical about its usefulness in a commercial context (Flamand et al., 2013). A study on ‘the growing importance of social media for insurance professionals’ by Highland Capital Brokerage (2015) indicated that through a study of 36 companies, it was proved that social media isn’t “taboo” anymore, as insurance companies make use of it. As time goes on, there’s mounting evidence that people are integrating social media into their daily lives and looking to it for help in making educated purchasing decisions. A study titled ‘Social Media Insurance Monitor’, conducted by consultancy firm ITDS among 20 major global insurers from 11 different countries, shows that top insurance companies are all on social media such as Facebook, Twitter, LinkedIn and YouTube (Bassig, 2019). 3.5.2 A different form of social media used for short-term insurance Similar to traditional media, social media includes several channels, and within each channel there are specific vehicles. The beauty of the various social media sites is that companies, according to Highland Capital Brokerage (2015), can use it for numerous purposes and it is 79 important to note that social media is not limited to the known platforms such as Facebook, Twitter, YouTube and blogs. Naujoks et al. (2018) assume that, in most countries, more than half of all insurance consumers are digitally active, meaning they go online to research products/service or conduct important interactions with providers. Bedgood (2016) reported that insurance consumers buy more on digital channels and turn to social media for recommendations, and use different platforms throughout the buying journey. There are numerous categories of social media which require users to create an account by submitting their email address and create a password (Storm, 2020). Social media websites come in a wide variety of ‘flavours’, Dao (2015) and Kaplan and Haenlein (2010) identified six categories of social media platform: Collaborative projects, virtual communities, content communities, virtual games world, blogs and micro blog, social networking sites. These categories include: For the purpose of this study, any online platform that allows users to take part and share content in different contexts is considered as social media. 1) Collaborative projects Collaborative projects are described by Delerue et al. (2012) as distinctive platforms that allow users to spread content, enable users to post without boundaries and modify content in order to suit a purpose. Collaborative projects namely: Wiki-Wiki Web, social bookmarking sites, collaborative tagging, online forums and review sites are regarded as the most powerful platforms of social media, according to Dao (2015). As an example, social bookmarking sites such as Pinterest, StumbleUpon, Flipboard and others allow users to save, tag and share a variety of latest content and media across the internet (Charlesworth, 2014; Kakkar, 2018). By sharing content, insurance providers create a welcoming presence for their company and run different types of social media marketing campaigns that will help generate website traffic and consumer engagement (Waite & Pérez-Vega, 2018). 2) Virtual communities The virtual world implies that our property is in the form of expressions, pictures, audio, sound, videos but not a real life. Du Plessis (2017) described virtual community as a group of persons, who may or may not meet one another but can exchange ideas and opinion through the mediation of social media. On the other hand, Grantham and Habel (2012) refer to virtual communities as a way to interact in real time without geographic boundaries and communication between people and information technology (IT). When online users come 80 together in a community to discuss new ideas or address problems concerning a policy, unexpected solutions are often the result (Kaplan & Haenlein, 2014). People who are only looking for insurance information on the internet are less at risk than those who provide information about themselves to other internet users, but there are many advantages when joining the online insurance community (Thurairaj et al., 2015). By building an online community, insurance provider benefit in many ways such as consumer retention and engagement, trust and consumer service improvement, which are the most effective ways to grow a business (Charlesworth, 2014; Rapcsák, 2019). 3) Content community Du Plessis (2017) acknowledged that content communities provide a platform for brands to create contents that have humanlike qualities and links to respective target markets, for example young consumers. An effective content marketing strategy that allows the brand to position itself in the appropriate social networks, provides insurers with a platform to create and promote content that is attractive to the target audience (Graeme, 2017; Kaplan & Haenlein, 2011). In the wake of its advances in terms of brand loyalty, improvement of contemporary marketing strategy and creation of long-term relationships without compensation, the content community offers a tremendous business opportunity to insurance providers (Cawsey & Rowley, 2016; Du Plessis, 2017; Rosenthal & Brito, 2017). Road safety has always been a concern for the insurance sector and the use of social media in the insurance industry represents an advanced solution for reaching people on social fora (Graeme, 2017). In March 2016, the Western Cape Department of Transport and Public Work launched a road safety campaign on Twitter called “First Kiss” the content marketing had a positive response from people (Central, 2017). 4) Virtual game worlds Numerous brands have recently recognised the relevance of the virtual worlds, which establishes a brand presence in the virtual world (Bleize & Antheunis, 2019). Kaplan and Haenlein (2014) and OECD (2017) recognise three kinds of ways in which insurance providers can successfully increase their sales volume in virtual worlds. This involves the creation of online flagship point of sale, Secondly, place Ads in virtual malls (example, virtual billboards) and lastly, sponsor events beneficial to the brand in the virtual world (examples, videos, movies and music concerts). Scholars agreed that integrating virtual world into marketing strategies of 81 organisation is found to be one of the fundamental factors that influence purchase intentions (Bleize & Antheunis, 2019; Dao, 2015). 5) Blogs and microblogs Regarded as individual web pages, bloggers create contents posts as well as upload contents from the fora . A blog is an online journal regularly updated with publications, where an individual or organisation publishes information on topics of interest (Rapcsák, 2019). Micro blogs are used among young consumers and advertisers as a form of interaction platforms to express their views and spread information (Ebner, 2018; King, 2014). Blogs and Microblogs are the prevailing source of pre-purchase information among online users frequently updated; nevertheless, it is not necessary for both the blogger and the reader to be online at the same time (Ebner, 2018; King, 2014; Tse & Zhang, 2013). 6) Social networking sites Although social networking seems like a new trend, its origins can be traced back to centuries of development (Drew, 2019). Social networking sites are often used interchangeably with social media, enabling the creation of social relationships among individual without boundary and no time limit using a web-based platform (Akhtar et al., 2016). Alongside, social media is an environment that hosts social networking sites, and has a big influence on young consumers on how they collect information about brands and their actual purchasing processes (Mohabier, 2017). Social network usage is one of the most popular online activities estimated in 2019 at 2.95 billion people which is projected to increase to almost 3.1 billion and 3.43 billion respectfully in 2021 and 2023 worldwide (Clement, 2019; Statista, 2019). Figure 3.6 as presented below give us an estimation of the number of social network users in South Africa. Figure 3.6: Number of social network users in South Africa from 2017 to 2023 (in millions) 82 30 25 20 15 10 5 0 2017 2018 2019 2020 2021 2022 2023 Source: Clement, 2019 Figure 3.6 shows that from 2017 to 2023, the number of network users is expected to grow from 18.5 million social network users to 24.3 million users in 2023. South Africa has overcome the age barrier and leads as one of the African countries with the most social networking users with more mobile users than actual computer users (Berger, Sinha & Pawelczyk, 2012; World Wide Worx, 2012). An opportunity is given to insurance industry through social networking sites, to create their respective brand presence on the platform in order to connect or get access to their respective target consumers scattered round the globe (Abdulmajid, 2019; Stokes, 2013). Social networking usage has gained rapid momentum locally, and the most-used social networking sites according to NapoleonCat (2020) are presented in Figure 3.7. 83 Figure 3.7: The most-used social networks site 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Source: NapoleonCat, 2020 Whatsapp (89%), YouTube (87%), Facebook (83%), Facebook Messenger (61%), Instagram (61%) and Twitter (44%) are considered as the most significant social network sites among young consumers in South Africa (Abdulmajid, 2019; NapoleonCat, 2020; Statcounter, 2020; Statista, 2019). Meanwhile, among young consumers, Facebook is regarded as the most popular and most explored social network site in the world (Mbanaso et al., 2015; Paquette, 2013; Putter, 2017; Shen & Bissell, 2013). The use of social networking sites (SNSs) like Facebook, and WhatsApp has increased globally and is playing an essential role in the lives of Generation Y (García-domingo et al., 2017; Hashim & Kutbi 2015; Krasnova, et al., 2017). Considering Figure 3.7, the volume of users on social media allows organisations to improve communication and productivity by disseminating information between different groups. Thus, users of social media platforms have the ability to exercise great influence on the decision making and the behaviour of other consumers without having direct contact with them. The next section looks at online consumers in South Africa in general and in particular the insurance consumer and their purchasing decisions. 84 3.6 Consumer behaviour Marketing experts use consumer behaviour as a concept to gain in-depth knowledge of their shopping behaviour. This section aims to understand the behaviour of car owners when it comes to purchasing insurance policies via social media platforms. Figure 3.8: Consumer behaviour outline OVERVIEW OF CONSUMER BEHAVIOUR ONLINE CONSUMER IN SOUTH AFRICA ONLINE CONSUMER ENGAGEMENT AND DECISION MAKING As presented in Figure 3.8, an overview of consumer behaviour is discussed. 3.6.1 Overview of consumer behaviour In the past, the study of consumer behaviour has mainly focused on why people buy; more recently, the focus has moved to include looking at consumption behaviour – in other words, how and why people consume (Sethna & Blythe, 2016). Consumers today want experiences and young consumers constitute the biggest chunk of the market and therefore attract companies to them (Dalziel, 2016). Since the term “consumer” will be used in this chapter, it is important to first define it. Kumar (2015) defined consumer as “someone who uses, consumes and/or enjoys the benefit of a product/service”. This does not mean that all behaviours can be classified as a consumer behaviour. Table 3.5 presents the definition of consumer behaviour. 85 CONSUMER BEHAVIOUR Table 3.5: The nature of Consumer Behaviour / What consumer behaviour is Nature of consumer behaviour Source Consumer behaviour is the decision making Cant and Van Heerden (2013) process that consumer goes through in selecting, evaluating, buying, using and disposing of products and services. Consumer behaviour is key to the underpinning Horner and Swarbrooke (2016) of all marketing activity which is carried out to develop, promote and sell service/products. “Consumer behaviour is the study of how Kotler and Keller (2016) individuals, groups, and organisation select, buy, use, and dispose of goods, services, ideas, experiences to satisfy their needs and wants”. Consumer behaviour is defined as the mental and Ling (2012) physical acts of individuals, households or other decision making units concerned with ultimate consumption involving the acquisition, own production, use and, in some cases, the dispossession of products and services. Businesses have a lot to gain by studying consumer behaviour. According to Kotler and Keller (2016), consumers do not necessarily shop the same way, and their spending habits have a big impact on the success of a business. Rick, Cryder and Loewenstein (2008) in their study on tightwads and spendthrifts concluded that there are three main categories of buyers: Tightwads: which represent 24% of the population spend less than the average and react less favourably to advertisements. Considered as the most difficult audience to please, the attitude of a tightwad towards expenditure depends upon how much he or she thinks it should cost (McCormick, 2016; Patel, 2017b). 86 Spendthrifts: According to Smith (2014), spendthrifts represent 15% of the population. Spendthrifts are marketers’ dream consumers which are driven by emotion and blinded by the desire to purchase with no remorse (Rick, Cryder & Loewenstein, 2008). Average buyers: considered as the balance between the tightwad and spendthrift, 61% of the population are average buyers (Hannam, 2015; McCormick, 2016). Average buyers think about purchases but spend what they think is appropriate while having a rough idea of their budget (Patel, 2017b; Smith, 2014). As it is essential for a company to understand these different types of buyers, human purchase habits are depicted as a process of “spending until it hurts” (Hannam, 2015). Insurance providers can improve their sales performance by understanding who their consumers are, including their motivations and how they’re using technology to buy car insurance. To understand what prompts people to purchase car insurance, four types of buyer were identified according to the Facebook and ComScore (2017) and Sassian (2018) report. In her study she identified four major buyer-types:  Millennials: They are actively seeking out others’ opinions before buying auto insurance. They are more likely to be motivated by price.  Loyalists: They place a high emphasis on consumer service. Their triggers include contract renewals followed by a new car purchase.  Switchers: They are receptive to advertising and they are likely to research multiple channels such as friends and family, insurance company websites, social media to ensure that they are getting the best deal.  Heavy mobile users: They turn to their mobile platforms to conduct their auto insurance research. Their triggers include a recent car purchase and the desire for lower pricing. There are different types of buyers but most people whittle them down to just three (Hannam, 2015; McCormick, 2016; Patel, 2017b; Rick, Cryder & Loewenstein, 2008; Smith, 2014), while a study on the consumer journey for car insurance identified four types of buyers (Facebook & ComScore, 2017; Sassian, 2018). Consumers are increasingly aware on the impact they have on others and on the planet through the consumption decisions they make. Car insurance buyers are more considerate than average buyers as they carefully consider value proposition, benefits and features. 87 Compared to offline consumers, online consumers have been found to be more willing to innovate and take risks (Dobre & Milovan-Ciuta, 2015). The following section focuses on the online consumer in South Africa. 3.6.2 Online consumers in South Africa With the rise of the internet today, it is possible for consumers to search about anything no matter where they are, place orders with more choice while controlling their media consumption than ever before (Bright & Daugherty, 2012; Stokes, 2013). The vast growth opportunities on social media and the increase number of users provide consumers with easier and faster access to information according to Lee and Barnes (2016). As internet penetration increases by 3.1%, a new large audience of consumers is emerging which will affect the global economy and the retail industry (Kemp, 2020; Ornico, 2018; SAIA, 2017). Although the number of internet users is increasing, the online purchase growth does not necessarily reflect this as South Africa is a little bit behind when it comes to online shopping (Davis, 2019; Ryke, 2019). Traditionally people used to buy insurance through brokers, who assisted in getting the most appropriate coverage at the best price; but nowadays, many people prefer to take out insurance directly on the internet. South African consumers do not entirely reject the concept of purchasing products online, but are hesitant to participate due to the risk they perceived (White, 2016). Delbridge (2019), advises consumers to purchase insurance online as it is easier to understand when compared with the traditional route of an insurance agent. Table 3.6 briefly elaborates on the advantage and disadvantage for consumer to purchase car insurance online. Table 3.6: Advantages and Disadvantages to purchasing insurance online Advantages Description Save by skipping the middle man Many different factors go into insurance ratings so purchasing your insurance online skips the middleman which is the insurance agent. Ask insurance question online The internet is becoming a great resource for insurance information. Instant access to insurance Clients are able to print insurance documents documents online. 88 Purchase insurance anytime Online insurance has the convenience of being available at all hours of the day. Disadvantages Description Insurance knowledge required Without an agent, clients will have to research answer to their insurance questions. Lack of help filing a claim With an online car insurance company, you will have to file a claim on your own. Claims are not difficult to file but in a time of stress, it is nice to have someone to do the work for you. Computer knowledge needed It takes quite a bit of effort to fill in all the information required for a car insurance quote online. Source: Delbridge (2019) and PMD (2020) According to Fin24 (2017), the digital commerce sector in South Africa has a huge growth opportunity and consumers are now embracing the internet for a better deal. Online spending in SA has more than tripled over the past five years, from R5.7bn in 2013 to an estimated R18.1bn in 2018 (Muller, 2018; Yupei, 2019). Almost 80% of South Africans agree that they are more concerned about the security of their personal information when shopping online than when shopping in a store, and 47% say that the security of their personal information is an obstacle to online shopping (Thompson, 2018). Insurers have long struggled to attract and retain consumers and Figure 3.9 briefly shows the complaints and satisfaction in each of the best insurance companies in South Africa. 89 Figure 3.9: Insurers’ satisfaction and complaints over insurance provider 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Consumer Satisfaction Consumers complaints Source: Du Plessis (2019) Virseker insurance took first position in the overall consumer satisfaction with a score of 80.7% followed by Santam (79.2%). South African consumers have very high expectations of their short term Insurance providers, and Figure 3.5 elaborates on the type of complaint addressed by consumers. In terms of complaints, consumers complained the most about the cost of insurance policy (18%), claims handling (14%) and the terms of cover (11%). Furthermore, Du Plessis (2019) mentioned that the industry loyalty score in 2018 dropped from 68.1% to 64.9% in 2019, which means adopting an approach on how to engage consumers and their-decision making. 3.6.3 Online consumer engagement and decision making It is important to note that consumer engagement can occur offline as well as online. Online consumer engagement is one of the most desirable outcomes from social media marketing activity (Emarketer, 2015). The concept of consumer engagement is relatively new in the marketing literature, and the efforts to define the concept and understand its antecedents and consequences are increasing through satisfaction, loyalty and trust (Brodie, llic, Juric & Hollebeek, 2013; Waite & Pérez-Vega, 2018). Moreover, an accepted explanation regarding online consumer engagement by Dessart et al. (2016) refers to interactive as the experiences 90 between consumers, the brand and other consumers that occur online. It has been accepted that consumer engagement results in behavioural outcomes, which means that consumer engagement is multi-dimensional and includes cognitive and emotional components (Brodie et al., 2013; Hollebeek et al., 2014; Vivek et al., 2012; Waite and Pérez-Vega, 2018). However, prior to such behaviours, there are cognitive and affective states as indicated in Table 3.7. Table 3.7: Multiples-dimensions of consumer engagement Dimension Description Example Cognitive How consumers retain A consumer thinking he made the right information about a product choice by purchasing insurance for his car or service. from an insurance provider as it was good value for money. Emotional The series of reactions A consumer feeling relieved that he bought experienced by consumers insurance when his car was involve in an following their interaction accident during a night out. with the brand. Behavioural The actions consumers take The consumer writes a review of his in relation to the brand. experience with the insurance brand on Google and recommends it to others. Source: Brodie et al (2013); Hollebeek et al. (2014); Vivek et al. (2012) and Waite and Pérez- Vega (2018) When it comes to the cognitive dimension, the social media promotion mix may not necessarily have to be positive but the emotional dimension of engagement which it gives to the consumer, the sense of belonging to a group which can result in a purchase decision (Brodie et al., 2013; Dessart et al., 2016). In addition, the behavioural dimension of engagement according to Waite and Pérez-Vega (2018) is the visible outcome of online consumer engagement expressed as interaction. A natural behavioural outcome sought by marketers from engaged consumers in social media is purchase (Zhang et al., 2017). When studying online consumer behaviour, a distinction is often made between consumer engagement and purchasing decisions (Hourigan & Bougoure, 2012; Swiegers, 2018). PwC’s (2016b) stipulated that online shopping in South Africa is in its infancy, as consumers are prepared to visit and brows an online store but do not have confidence in the website to complete a purchase. Thus, Kotler and Armstrong (2014) stated that the buyer’s decision process is a much more in-depth and complex process than just purchasing an item. Despite 91 the gap between browsing and purchasing online, an effort is needed for the growth of online shopping which is so far attributed to a younger generation of consumer more comfortable with the internet (Richa, 2012; Swiegers, 2018; White, 2016). In order to make this study more applicable to the online social media promotion mix, the table below illustrates the traditional consumer decision process with a focus on the campaign strategy that can be applied to influence consumer decision. Table 3.8: Influencing consumer decision making Stage Campaign tactic Need recognition Use social ads with low social distance and high source numbers. Search Promote reviews that are high in temporal immediacy. Evaluation Feedback on the number of sources who are booking and the temporal immediacy of the present offer. Purchase Ask consumer to post online that they have just purchased the product so that they can influence friends. Post-purchase Request review; indicate how many others post reviews. Invite to join the online brand community. Source: Kotler and Amstrong (2014); Lamb et al. (2015) and Waite and Pérez-Vega (2018) To better understand consumer behaviour with regards to car insurance based on Table 3.8, a step by step description of the consumer purchase decision is discussed below. 3.6.3.1 Needs recognition By seeking to create a need and entice consumers to seek and purchase an insurance policy, marketers should build their campaigns by exposing consumers to a mix of online promotions on social media, more effective than website advertising banners (Li et al., 2012). The work of marketers at the stage of identifying needs is to position their services as a solution to a problem or need the consumer can meet. In Waite and Pérez-Vega (2018) point of view, a negative review has a weaker effect if it was published nine years ago versus nine minute ago. Generating awareness for car insurance is fundamental to increase car insurance sales 92 3.6.3.2 Search and evaluation People are usually motivated to search for insurance policies and two reasons come to mind: the purchase of a new insurance plan or the renewal of a current insurance subscription (Ghunaim, 2019). Therefore, it is up to insurance companies to reduce the burden and discomfort by ensuring that their services are easy to find by potential clients wherever they are. The website is considered an essential communication strategy allowing consumers to obtain more information on the services offered (Nasir, 2015). After gathering a satisfying amount of information, the consumer will develop a set of criteria to evaluate and compare the alternatives. According to KPMG (2017), online reviews are the most common way to evaluate the information collected. Voicing consumer experience can significantly influence future purchasing decisions. In conclusion, during the information search and evaluation process, website content, review and consumer experience impact on the attitude and behaviours of consumers before the purchasing decision (Chu et al., 2019). 3.6.3.3 Purchase Based on the information evaluated and the decision whether to purchase or not, the consumer is motivated by a set of expectations regarding the service offers. The purchase decision is influenced by the risk expectation and risk sensitivity, which determine the financial value of insurance (Kotler & Keller, 2012; Meral, 2019) whereby the purchase can be modified, postponed or avoided. Purchasing insurance products is like dieting; costs arise immediately, but benefits are achieved later. Purchasing car insurance online offers the following benefits according to Biddle (2018) and Delbridge (2019): Convenience: purchasing a car insurance policy online enables you to do so from the convenience of your home at times suitable to you. Time saving: online insurance purchase saves you from the hassle of waiting in queues and thus helps you save some time. Paperless Process: purchase of insurance policy online is generally a paperless process, which again adds to your convenience. Safety of payment: payment can be done securely using a debit/credit card or via net banking. 93 Comparison: when purchasing a car insurance policy, the consumer can get a quote through car insurance comparison sites such as hippo.co.za and get-insured.co.za. Instant process: purchasing insurance policy online is an instant process whereby the policy document is issued instantly and sent to your registered email id. Immediacy during the purchasing stage would help insurance providers to display information on their websites regarding how many purchases have been made, or a time limit in which the price will be valid in order to exert influence on online users and lead them to act (Chu et al., 2019; Waite & Pérez-Vega, 2018). 3.6.3.4 Post-purchase A marketer’s work does not end when the service is bought by the consumer (Kotler et al., 2015). Therefore, during the post-purchase stage, the consumer may experience a degree of cognitive dissonance which is one of the biggest challenges that marketers face because they must reassure consumers regarding their purchase (Hoffman & Bateson, 2017; Jordaan & Samuels, 2015; Palmer, 2011). In the insurance industry, there are instances where post- purchase refers to the post experience which is to the post-consumption stage of the decision making process. The desired outcome at this stage is all about consumer satisfaction, which is determined when the consumer evaluates the performance of the service. Companies have always tried to peek inside the minds of consumers to discover what makes them buy certain products or services and not others. Purchasing car insurance online has multiple options on how to go about it and the present study makes use of the Technology of Acceptance Model (TAM) and the Technology of Perceived Behaviour (TPB) which in the next section, explain the influence of social media promotion mix on consumer’s purchasing decision. Considering the theoretical background provided in Chapter one, a conceptual framework is presented below based on previous scholars who investigated the numerous factors that influence consumers’ behaviour to purchase online. 3.7 Conceptual framework Antonenko (2015) describes a conceptual framework as a “visual, either graphically or in narrative form, the main things to be studied, the key factors or variables and the presumed relationships among them”. Several scholars have investigated numerous factors that can affect 94 the purchasing behaviour of online consumers (Hattangadi, 2014; Lim et al., 2016; Mao et al., 2014; Wang, 2017; Ye & Zhang, 2014). The conceptual framework that underpins this study shows that a diverse range of factors indicates that consumers struggle online, which in return affects their purchasing decisions. Based on meta-analysis and literature review from several researchers, the conceptual framework developed for this study is presented in Figure 3.10. Figure 3.10: Conceptual framework The growth of social media has not changed the purchasing decision process of consumers, however, it has completely changed the purchasing pattern. Several important theories illustrate how the purchasing intention is influenced by social media (Bleize & Antheunis, 2019). First, the Technology of Acceptance Model (Davis, 1986) focuses on factors that influence behavioural intentions. Although TAM has its origins in information systems, the theory is also used in the field of marketing communications to explain consumer behaviour. TAM differs from TPB in that it identifies different factors as influencers of a behavioural intention. TAM focuses on two factors: perceived usefulness which refers to the users’ beliefs that the use of technology influences their decisions as to whether to purchase insurance policy on social 95 media and perceived ease of use, describes as the users’ beliefs about whether the benefits of purchasing virtual products outweigh the efforts made to do so. Secondly, the Theory of planned behaviour (Ajzen, 1985) is an influential theory in the field of marketing communication and consumer behaviour that links the beliefs that individuals have, to their behaviour. Consumers’ behaviour is determined by three factors (attitude toward the behaviour, subjective norms and perceived behavioural control) and according to the TPB, a predefined positive or negative attitude that consumers have toward online purchase influences their purchasing intentions (Yin et al., 2019). Furthermore, the perception of how easy it is to acquire an insurance policy on social media also influences the intention to purchase. In the next section, the literature relating to the conceptual model of study traces the foundation of the research. 3.7.1 Perceived behavioural control Perceived behavioural control (PBC) refers to the comfort level of an individual to perform any particular behaviour (Ajzen, 1991). In other words, it is an individual perception about the level of ability in performing a particular behaviour. PBC is also presented as “people’s perception of the ease or difficulty of performing the behaviour of interest, and may consist of variables about the presence or absence of skills, ability, controllability and availability (Ajzen, 1991 & Bashir et al., 2019). Based on previous studies, PBC could be used when investigating online consumers’ behaviour, and the results revealed that people’s behaviour is strongly influenced by their confidence and self-belief in their ability to perform certain behaviour (Greyling, 2017; Manjunath & Nagabhushanam, 2017; Moták et al., 2017; Safeena et al., 2013; Sarkis Jr, 2017). The behavioural control obtained can serve as a substitute according to Greyling (2017) for real behavioural control where it can be used to improve behavioural predictions. Behavioural control allows the consumer to change the service situation by asking the firm to customize its typical offerings (Wirtz & lovelock, 2018). 3.7.2 Perceived usefulness Usefulness is perceived as one of the main reasons why people are receptive to new technology and according to Davis (1986), it is ‘the degree to which a person believes that using a particular 96 system would enhance his or her job performance. Users’ acceptance of computing facilities is one of the main constructs of the technology acceptance model (Davis, 1986). Consumers generate and share useful information on social media based on their personal experiences. Akar and Dalgic (2018) stated that perceived usefulness represents the degree to which an innovation is perceived not to be difficult to understand or operate, while Akhtar, Tahir and Asghar (2016) described perceived usefulness (PU) as the degree to which an individual believes that the use of a particular technology will improve its job performance. Many researchers have developed the TAM model in diverse areas (Awa et al., 2015; Bashir et al., 2019; Karimy et al., 2015; Kim et al., 2012; Lim et al., 2016). In the present study, perceived usefulness (PU) has been selected instead of perceived ease of use as previous studies have been consistent in arguing that PU has a positive direct effect on technology acceptance (Hakkak et al., 2013; Yin et al., 2019). Mir and Ur Rehman (2013), discovered that perceived usefulness has a positive effect on the attitudes of consumers toward the user-generated product content on YouTube, while Zarrad and Debabi (2015) found that there is a negative relationship between perceived usefulness and online purchase intention. Useful websites might lead to increase trust and enhance consumers’ intention to purchase online (Tripathi, 2014). In the case of social media promotion mix, PU is outlined as the degree to which social media platforms provide benefits to individual in their search for information (Miranda et al., 2014). This statement was supported by Bonn, Kim, Kang and Cho (2016) and Mouakket (2015) whereby their findings suggested that the intended use of social networks in purchasing decisions is influenced by its perceived usefulness. 3.7.3 Attitude Insurance providers want to understand how consumers perceived their services and what motivates them to have a positive attitude in regard to their brand. The extent to which consumers will buy a brand and recommend it to others is determined by their perception in the immediate situation (Mwakatumbula et al., 2016; Tripathi, 2014). Perceived as “a learned predisposition to respond in a consistently, favourable or unfavourable manner with respect to a given object”. Fishbein and Ajzen (1975) categorized attitude into two distinctive constructs: attitude toward the object and attitude toward the behaviour. In the context of online shopping, the media platform for an online retailer is the main contact point by which the online retailer and consumers interface in the online purchasing process (Le Roux & Maree, 2016; Lim & Ting, 2012). Former scholars insisted on understanding the users’ expectations and what they 97 think about the social media platforms they use (Bashir et al., 2019; Lim et al., 2016; Tripathi, 2014). The current study tries to understand the attitudes of consumers toward purchasing car insurance online and their behavioural attitudes toward the online promotion mix. In the work of Lim and Ting (2012), their results showed that consumers’ intention to shop online is determined by their attitude towards online shopping, and PU has no influence on the attitudes of consumers towards the use of social media (Lee & Paris, 2013). Notably, the less significant is the attitude towards online decision making, the lower the consumers’ intention to engage in online purchasing will be (Miranda et al., 2014). Consumers are directly involved in social media that favours relationships and community. Consumers are more likely to agree and depend on the information they have received on social media (Chu, 2011). Consumer’s attitudes concerning the website or platform at large are an indicator of their attitudes towards its content. Kiran and Vasantha (2016) in their study perceived social media platforms as a significant medium that influences consumer decision making. The attitude of a consumer in relation to a product/services, that he has read on social media sites or blogs has been found to have a strong positive effect on the consumer purchasing intention (Karimi, 2013). If attitudes and behaviour are highly correlated, then the behaviour of a consumer can be determined by his/her attitude (Putro & Haryanto, 2015). 3.7.4 Social influence The study also makes use of one of the constructs, social influence, which is part of TAM and TPB. Hakkak et al. (2013) described social media influence as “the processes whereby people directly or indirectly influence the thoughts, feelings and actions of others”. Social influence in the context of this research is illustrated as the perceived external pressure that people feel after knowing the factors that influenced their decision to use it, and the degree to which one perceives the importance that others believe in (Kumar, 2015). Feedbacks and comments about a product or service on social media by friends and family influence future purchase. Understanding online decision-making processes can lift our understanding of online consumers to a point, which can only be possible by recognizing the whole process that consumers are engaged in (Lee & Paris, 2013; Nistor, 2011). Individuals have a tendency to adjust their thought, according to the group they are in. In contrast with the past, social influence has broadened due to the use of social media (Akar et al., 2015; Kwahk & Ge, 2012). People tend to adjust their beliefs according to the group they are in. Chung et al. (2013) and Miranda et al. (2014) have identified two forms of social influence, namely external and 98 interpersonal. External influence includes the mass media which adopters may take into account when making their decisions, while interpersonal influence refers to word-of-mouth influence by reference groups such as peers and friends. Chen (2014) emphasized that the online word-of-mouth influence the purchasing decision meaningfully. However, Nistor (2011) pointed out that social influence affect the use of social media and suggested that organisations should consider computer training programmes for their staff. 3.7.5 Purchase intention Online purchase decisions are shaped through the interactions of consumers with the online environment. In order to better understand the purchase decision, Kotler et al. (2015) advised companies to dig deep into the buying decision process. Perceived as a general efficiency measure used to anticipate a behavioural response, purchase intention is described as a strategy for the consumer to purchase a particular service within a specified period of time (Cunningham, 2015). Determining the intentions of consumers to purchase is crucial as these intentions can be used to predict their behaviour (Putro & Haryanto, 2015). Purchasing attitude is a consistent positive or negative reaction towards certain things through learning, which includes favourable or unfavourable evaluation, emotional feeling, and behavioural tendency (Akar & Dalgic, 2018; Pande & Soodan, 2015). Depending on the price and type of cover, insurance consumer classify insurance services by weighting and summation to arrive at a policy that offer a maximum utility (Aglionby, 2016; PWC, 2018). A survey conducted by Accenture (2016) shows that consumers are comfortable browsing and communicating via digital channels such as social media but their purchasing decisions are low. The increasing use of social media has brought about a major change in the approach to educate consumers and establish the link between the intention to purchase and the final decision to purchase insurance policy online (Pütter, 2017; Shelford, 2018). Since an online purchasing decision is commonly perceived as riskier than traditional purchase, previous purchasing experience reduces uncertainty for consumers and increase their intentions to purchase online (Goyal et al., 2013; Swiegers, 2018). Several empirical studies have shown that intention can be a reliable predictor of behaviour (Bashir et al., 2019). Nyagucha (2017) in her study on the impact of social media regarding the decision-making process, found that social media has an impact on the pre-purchase stage and that during the purchase stage, social media is more reliable if one has uncertainties. Not all car owners are comfortable with purchasing insurance policies online. 99 Thus, this study would help service providers to determine the factors that influence car owners to purchase insurance policies online. The current study lays out a conceptual framework to explain the influence of social media promotion mix and the behaviour of consumer when purchasing car insurance online. Dependent variables for this study were selected based on the results from previous studies on the technology of acceptance model (TAM) and the technique of perceived behaviour (TPB) to frame the basis of the research. As part of the conceptual framework, the next section discusses the factors that potentially influence the intention to purchase car insurance online. 3.8 Factors influencing online purchase intentions As part of the conceptual framework, independent variables were identified as factors that influence the intention to purchase car insurance online. Factors are selected from prior studies which it deemed applicable to the current study. Previous research has continuously reported that the Technology of Acceptance Model was very useful in predicting and explaining technology use in various situations (Dillon and Morris, 1996). However, Davis (1989) argued that research should explore other variables that could affect perceived usefulness (PU) and perceived ease of use (PEoU). Dishaw and Strong (1999) noted that one of TAM’s weaknesses is the lack of explicit inclusion of external variables. In fact, many scholars have proposed various extended TAMs and TPBs (Kakkak, Vahdati & Biranvand, 2013; Lee & Paris, 2013; Ye & Zhang, 2014). For a specific insurance policy, there are many factors contributing to consumers’ purchase decisions. Among those are trust, promotion mix, perceived security, perceived tangibility, service quality and social media platforms as presented in Table 3.9. 100 Table 3.9: Independent variables Independent variables Trust X X X X Website characteristics X X Promotion mix X X Perceived security X X X Perceived tangibility X Service quality X X 3.8.1 Trust Found to be a mitigating relationship for purchase intention, trust is known as an important factor in the buyer-seller relationship and online purchasing intention (Tripathi, 2014; Wright, 2015; Ye & Zhang, 2014). Trust can be characterized as one’s willingness to rely upon another (Hansen et al., 2018), or as the belief in dependability and honesty (Kumar & Dange, 2012). Prior studies found that there is a positive association between trust and purchasing intention (Amaro & Duarte, 2015; Tripathi, 2014) and individuals’ trust is considered as one of the most important psychological factors influencing online behaviours (Putra, 2018). According to Karimi (2013), a consumer attitude toward social media can be influenced based on trust which is related to a particular website or environment factors while interacting with the retailers' website. A happy consumer is an impactful advocate for a business, and technology has made every consumer’s voice extremely powerful (Fullerton, 2017). Consumers tend to trust the information they find on social media and according to Erskine (2017), 74% of consumers say that positive reviews make them trust a local business more. A report from Podium (2017) shows how consumers trust each other and influence buying decisions and brand awareness through online reviews with 60% of consumers looking at online reviews at least weekly, and 93% saying online reviews influence their purchasing decisions. Further, the study suggests consumers do trust and engage with online reviews regularly and these reviews remain very 101 Parasuraman, Berry and Zeithaml (2002) Kumar, (2012) Taprial and Kanwar, (2012) Tripathi, (2014) Ye and Zhang, (2014) Amaro &Duarte, (2015) Putra, (2018) Present study influential when it comes to making purchasing decisions (Fullerton, 2017; Podium, 2017). However, when it comes to inconvenience encounter on the internet such as credit card fraud or not receiving the right products, consumers are more concerned, which influence their decision making and hesitation in making those decisions (Amaro & Duarte, 2015; Tripathi, 2014). It is important to understand how users perceive trust when participating in online activities, and the literature shows that the online environment has increased the complexity of the trust relationship. 3.8.2 Promotion mix Promotion mix consists of a variety of incentive tools used to stimulate consumers and accelerate the purchasing decision (Kotler et al., 2015). A promotion mix is used to communicate the benefits of using a particular product or service while influencing the buying behaviour of their consumers (Fill & Turnbull, 2016). Kumar (2015) suggested that the earlier the company tries to influence the consumer through advertisements and promotions, the higher the opportunity they have to influence the decision-making process. In 2017, KPMG conducted an international study on consumer behaviours and preferences related to online shopping, promotions were identified by 25% of respondents as the factors most likely to influence consumers’ decisions regarding the product or the brand to be purchased online. An article published by Sassian (2018), shows that 49% of respondents recalled seeing car insurance advertisements and that the advertisements had helped them discover new insurance brands. In the same article, 44% agreed that coming across advertisements motivated them to consider an insurance provider that they hadn’t previously considered. As the internet has made the world a “global village”, promotion on social media can strategically position a business to reach audience anywhere and everywhere in the world (Ekwueme & Okoro, 2018; Tripathi, 2014). In their study on the influence of social media advertising among students, Bhakuni and Aronkar (2012) discovered that there is a strong positive relationship between purchase intention and social media advertising. Cant (2010) suggested that the sales promotion could establish a positive attitude among consumers, due to the awareness consumers might have when deciding not to pay for a product or service. Armstrong and Kotler (2013) identified sales promotion as the fifth component of the promotional mix and involve the use of short-term incentives to encourage consumers to purchase and stimulate sales force's efforts. Ye and Zhang (2014) in their study on sales promotion and purchasing intention, discovered that sales promotion indirectly affects purchase attitude and intention. The present study will outline the 102 influence of social media promotion mix and how it affects the purchase decision in short-term insurance in Mahikeng. 3.8.3 Perceived security Consumers engaging in any type of online activity are exposed to various security issues. According to Guo et al. (2012) security is the ability of the website to protect consumer’s personal data from any unauthorized disclosure of information during electronic transactions. As security is a perception rather than a reality for average users, some researchers addressed the influence of perceived security on post-adoption behaviours (Meskaran, Ismail & Shanmugam, 2013; Nepomuceno, Laroche & Richard, 2014). Talking of the technical aspect of online security, perceived security is described as the subjective probability with which consumers believe that their personal information will not be viewed, stored and manipulated by inappropriate people (Wright, 2015). As one of the concerns of consumers, online security is a considerable issue for transferring important information like credit card details and personal information (Meskaran et al., 2013). A report by Experian’s Global Identity and Fraud Report confirmed that 74% of consumers see security as the most important element of their online experience (Staff Report, 2019). It has been shown that security issues regarding both personal and financial information are one of the top concerns of internet users (Wright, 2015). Since purchasing insurance on social media implies online payment, consumers direct their attention on how they are protected from risks related to security and research information about the service provider as a means of protection (Meskaran et al., 2013). Looking at social media marketing, assurance is one of the most serious issues affecting the success or the failure of online stores as security tends to prevent consumers from purchasing insurance online (Vasić et al., 2019). Therefore, all the above reveals the importance of security in online store as one of the key factors that consumers take into consideration when deciding to purchase a service online. 3.8.4 Perceived tangibility In marketing, the word tangible refers to things that are physical, items that can be touched and seen (Lee, Lee & Dewald, 2016; Shetty, 2015). In the olden days of marketing, being able to measure how many people viewed a commercial on television or billboard were considered tangible marketing results. Tangible aspects of a service include the exterior and interior design of the business place and the internet attempts to increase the tangibility by providing 103 consumers with high quality information, such as product descriptions, specifications and photographs (Nepomuceno et al., 2014). Tangible products sold online are often perceived as intangible, since consumers have no direct contact with the products purchased despite the psychological risk perceived by consumers (Meskaran et al., 2013; Nepomuceno et al., 2014). Today, when measuring tangible results for social media, marketers might stick to data and numbers (Loras, 2015). A recent report from Mangles (2017) reported that 52% of respondents confirmed that social media had a positive influence on their income and sales. Hsieh and Tsao (2014) described tangible assets as important factors in managing the service encounter and reducing perceived risk. Consumers must constantly make decisions regarding the type of services to purchase and where to purchase. Due to the anonymous nature of car insurance, insurers generally seek out as much information as possible to minimize the perceived risk (Yu & Chen, 2018). Karimi (2013) perceived risk as the uncertainty that consumers face when they cannot foresee the consequences of their purchase decision. Consumer perception of risk varies, depending on the person, the service, the situation and the culture. Shetty (2015) stipulated that tangible marketing is the use of promotional items to contribute to brand recognition and consumer loyalty. 3.8.5 Service quality Consumers often judge the quality of a product or service on the basis of various information panels that they associate with the product. Service quality is described as the consumer’s assessment of the overall excellence and superiority at the service (Lee et al., 2016). Since there is no face-to-face contact between a consumer and employee, service quality has become an essential dimension of online shopping (Kim et al., 2012). It is more difficult for consumer to evaluate the quality of services than the quality of products. A recent study revealed that online insurance service has demonstrated a positive relationship between increased consumer satisfaction and future purchase intentions (Nambiar et al., 2018). The actual quality of services can vary from day to day, from service employee to service employee, and from consumer to consumer, so the marketers try to standardise their services in order to provide consistency of quality (Govender, 2014; Lee et al., 2016). The negative effect of poor service quality is cited as a reason why many consumers prefer to search for products online, but make purchase in traditional shopping environment (Hsieh & Tsao, 2014). Furthermore, it is argued that, service quality is established when a car owner compares his or her expectations about different service providers and the way he or she perceives company 104 performance regarding the service (King Price Insurance, 2019; PMD, 2019). Many consumers prefer to buy from the store, where they can contact support staff directly and review a product before purchasing (Nepomuceno et al., 2014). By providing and sending information either via formal or informal platforms, online vendors increase the expectations of their consumers and add value to their services (Dost et al., 2015). Hence, it is the motive why providing the service quality plays an important part in increasing the consumer satisfaction. 3.8.6 Social media platform In South Africa, there is currently no clear legislation governing the use of the media (Faurie, 2019; PWC, 2016b). With the growing influence of digital platforms in the insurance industry, social PWC media is starting to play an important part in many cases. Over the past ten years, various social media platforms (Facebook, YouTube…) on the internet have changed, opening the door to interaction that goes beyond traditional chat and the sale of insurance policies on social media (Rinehart-Smit et al., 2018; Tayengwa, 2017). Africa has seen some innovation in distribution with the emergence of Social media platforms (Moodley, 2019). However, collaborating with a digital platform can be a way for the insurance industry to go beyond traditional insurance models. In fact, reviews, word of mouth, online communities and forums produced through social media platform, helps consumers in their purchase decisions (Hajli, 2014); recommendations are another tool commonly used by prospective consumers (Valos et al., 2016). Accenture (2016) mentioned that digital technology creates platform for suppliers to respond to changes and consumer circumstances by consistently adding new features to their websites. Tripathi (2014) described that social media platforms enhance the value of the website by introducing interesting features for easy-to-use websites such as games, video/photo sharing, design contents, chatting, quick loading capabilities without the need for high-end communication that keeps the user happy. Lorenzo-Romero, Alarcon-del-Amo and Constantinides (2011) in their study recommended that stimulating features should be introduced in the website in a way that users can easily share video/pictures, like games, chat and innovate contents in order to attract more users. The Credibility of a social medium is a concept, which is described by the judgment of the reader (Yüksel, 2016), and studies show that relatively more than being a source or platform, it depends on the receiver's perceptions. In conclusion, when using social media platforms, whether through a third-party store or a media company, marketers should constantly monitor the use of their products and improve their platforms by offering a comfortable, interesting and easy language with functional design 105 as smooth as possible (Ngumba & Kagiri, 2018). Considering the context of an insurance company, this study uses the TAM and TPB model to explain the users’ acceptance of social media platforms. By conceptualizing a model based on the original TAM and TPB, the present study has identified additional constructs from previous studies related to marketing communication, media consumption and consumer behaviour with the special aim of studying the attitudes of car owners alongside with online promotion mix. 3.9 Summary In this chapter, the researcher critically examined and discussed literature on social media and consumer behaviour, which forms the theoretical background of this study. The evolution of the internet in South Africa has emerged and social media penetration has increased by providing insurance companies a platform to educate their policyholders. The review further elaborates on short-term insurance in South Africa and the evolution of technology in insurance companies. It was identified that South African insurance companies are the slowest industries to go digital. For the purpose of this study, any online platform that allows users to take part and share content in different contexts was considered as social media. As the internet is a fast- changing environment and consumer behaviour changes accordingly, it is imperative to understand the behaviour of car owners when it comes to purchasing insurance policies via social media platforms. Consumers do not necessarily shop the same way, thus, three main categories of buyers were identified and car insurance buyers were more considerate as average buyers as they carefully consider value proposition, benefits and features. Considering the theoretical background provided in Chapter one, the researcher made use of the Technology of Acceptance Model (TAM) and the Technology of Perceived Behaviour (TPB) based on meta- analysis and literature review from several researchers which provided a range of factors that influence the intention to purchase car insurance online. 106 CHAPTER FOUR RESEARCH METHODOLOGY 4.1 Introduction A company needs to undertake research for acquiring information and to have a comprehensive understanding of the needs of all its stakeholders, particularly consumers. However, the reliability of such research is heavily dependent on the use of the current research methodology. Research methodology is the study of different procedures of solving a research problem in a scientific manner (Wild & Diggines, 2013). Correspondingly, Malhotra (2015) explained research as the acquisition of new knowledge by investigating and answering questions a researcher might have regarding the internal and external environments. It is therefore important that a researcher does not only know the research methods used but completely understands the underlying methodology. This chapter provides an in-depth exploration of the research methodology followed for the purposes of this study and to achieve the stated objectives as indicated in Chapter 1. This study commences with an analysis of the research philosophy used and this is followed by a discussion of the research approach that underpins this study. Furthermore there is an exposition of the research design and the study area. Following this is a discussion is provided of the sampling method, the data collection procedure, the data analysis, the statistical techniques and ethical consideration. The chapter terminates with highlighting the ethical considerations applicable to this study. The layout of this chapter is depicted in Figure 4.1. 107 Figure 4.1: Chapter Outline RESEARCH PHILOSOPHY RESEARCH APPROACH RESEARCH DESIGN STUDY AREA AND SAMPLING DESIGN DATA COLLECTION PROCEDURE DATA ANALYSIS AND STATISTICAL TECHNIQUE ETHICAL CONSIDERATIONS 4.2 Research philosophy According to Creswell (2014), a research philosophy is a belief about the way in which data should be collected, analysed and used. Kumar (2019) and Creswell and Creswell (2017) assert that research philosophy provides the basis for inter and trans-disciplinary design of research sustainability. A research philosophy is a conviction of the way and essence of collecting, investigating and evaluating knowledge about a phenomenon (McDaniel & Gates, 2014). The conviction is perceived as a preliminary statement of belief, but it is based on the philosophizing person’s knowledge. Therefore, it is important to know what research philosophy approaches enable a researcher to choose the best approach and the reason for choosing the study assumption in order to conduct and evaluate proper scientific research (Hair et al., 2013; Leedy & Ormrod, 2014). There are many research philosophies, which have been defined as positivist, interpretative, realism and pragmatism, according to Creswell and Creswell (2017). 108 RESEARCH METHODOLOGY 4.2.1 Realism research philosophy Realism research philosophy focuses on the human mind’s notion of sovereignty of reality. This philosophy is based on the concept of a logical approach to a case with proof. Realism can be broken down into two groups named direct realism and critical realism. Direct realism, also known as naive realism, is defined as "what you see is what you get" (Mkansi & Acheampong, 2012). To put it in another way, direct realism depicts the world through personal senses. On the other side, critical realism argues that humans do experience the sensations and images of the real world. According to critical realism, sensations and images of the real world can be deceptive and they usually do not portray the real world. Realistic research philosophy is based on the assumptions that are necessary for the perception of subjective nature of the human (Novikov & Vovikov, 2013). However, the representations and images of the actual world can be misleading, according to critical realism, such that the essential world is not widely represented. 4.2.2 Interpretivist research philosophy Interpretivism, sometimes referred to as interpretivist, entails the analysis of aspects of the research and therefore requires human interest in a sample. Accordingly, “interpretive researchers assume that access to reality (given or socially constructed) is only through social constructions such as language, consciousness, shared meanings, and instruments” (Holden & Lynch, 2004). The interpretivist approach is based on naturalist approaches of data collection, such as interviews and observation. The emergence of interpretative theory within social science was based on the critique of positivism. Therefore, quantitative analysis emphasizes qualitative assessment. Researchers need to see variations between individuals as a social agent, according to an interpretative approach. 4.2.3 Pragmatism research philosophy Pragmatics acknowledges that they approach the universe and science in several different ways. According to pragmatism scientific theory, interpretation is the most critical determinant of scientific methodology (Morgan, 2014). Pragmatics may combine positivistic and interpretative positions in the sense of a specific study, depending on the nature of the research issue. Pragmatism research philosophy, in contrast to positivism and interpretivism research philosophy can incorporate more than one research approach and research strategies into the 109 same analysis. Experiments of pragmatism research theory may also incorporate different approaches, such as methods of qualitative, quantitative, and action research (Rosiek, 2013). The researcher is less restricted carrying out research. 4.2.4 Positivism research philosophy It must be understood that it is difficult to explain clearly or succinctly the theory of positivism science. This is due to the fact that in the sense of positivism studies, there are broad variations (Saunders, Lewis & Thornhill, 2012). Nevertheless, positivism essentially is based on the belief that knowledge is the only way to discover the truth. Positivists believe, according to Levin (1991), that the truth is stable, measurable, and rational. An investigator’s position in studies of positivism is limited to objective data collection and analysis. Positive results leading to statistical analysis are focused on observations which can be quantified and used by the researcher to make scientific assumptions. Although there is an on-going debate on what research philosophy brings to an investigation, there is no agreement as to how research philosophies are inherently opposed. Benbasat, Goldstein and Mead (1987) recognized that no research philosophy is necessarily better than any other and that a mixture of research philosophy has been proposed by many researchers to improve research efficiency. The choice of a specific research philosophy is impacted by practical implications. There are important philosophical differences between studies that focus on facts and numbers and qualitative studies. The choice between positivist and interpretivist research philosophies or between quantitative and qualitative research methods has traditionally represented a major point of debate. However, the latest developments in the practice of conducting studies have increased the popularity of pragmatist and realist philosophies as well. The focus of this this study is on understanding the influence of the social media promotion mix on car insurance purchasing of residents in Mahikeng through the collection of data from respondents using questionnaires and analysing it using the Statistical Package for Social Science (SPSS). Positivism is essentially based on the belief that knowledge is the only way to discover the truth. Positivists believe, according to Levin (1991), the truth is stable, measurable and rational. Hence, this study is grounded in the positivist research philosophy. Therefore, this philosophy will tend to reduce personal biases and prejudice of the researcher and respondents 110 as it offers the use of more than one research method and technique in order to ensure that the subject is studied from more than one angle (Panhwar et al., 2017; Vosloo, 2014). 4.3 Research approach In social research, the research philosophy and methods contribute to the research approach. There are three research approaches, viz: the qualitative method, the quantitative method, and also mixed methods research (Creswell, 2014). 4.3.1 Qualitative research approach The goal of qualitative research is to systematically explain and analyse issues or phenomena from the perspective of the person or population being studied, and to generate new concepts and theories (Viswambharan & Priya, 2016). It is concise, non-numeric, logically applied and it uses terms. It aims at providing a clear understanding of human behaviour, feelings and experience (Tong, Flemming, Mclnnes, Oliver & Craig, 2012). It is used to explore the perspectives, feelings and experiences of people, and what lies at the core of their lives. Qualitative studies do not require statistical analysis and empirical estimates, as the deep understanding of the individual is the objective of the qualitative tradition (Walia, 2015). The qualitative research approach facilitates the development of an in-depth understanding of the condition under investigation. It also enables the interaction with car insurance owners through interviews, thereby gaining extensive information regarding the socio-economic characteristic of respondents and their relationship with social media. The information obtained is exploratory and cannot be graphed. It investigates the why and the how of decision making (Mohajan, 2018). 4.3.2 Quantitative research approach The concept of quantitative analysis is a systematic investigation of phenomena by gathering quantifiable data and carrying out statistical, mathematical or computational techniques (Panhwar et al., 2017). The object of quantitative research is to develop and employ naturally occurring mathematical models, theories, and hypotheses. This style of work is based on positivist methodology and adheres to the standards of strict sampling (Phophalia, 2010). Quantitative analysis enables the testing of hypotheses by observing the relationship between variables, evaluating it using quantitative instruments, and analyzing data using statistical 111 methods. The methods of quantitative data collection are far more systematic than the methods of collecting qualitative data. Quantitative approaches for gathering data include various types of surveys, such as online surveys, paper surveys, smartphone surveys, face-to-face interviews, and telephone interviews. Quantitative research involves the extraction of large quantities of data using structured techniques that provide more descriptive samples, concentrating on statistical information than individual perceptions (McCusker & Gunaydin, 2014). With the advent of the coronavirus pandemic, the quantitative approaches were suitable as it opens door for online surveys and makes it easy for data collection. 4.3.3 Mixed research approach A mixed research approach, according to Creswell (2014), is described in its simplest form as the process of gathering, evaluating and combining both quantitative and qualitative data in the research process with a single analysis in order to obtain a thorough understanding of the phenomenon being studied. Qualitative data appear to be open-ended without predetermined answers whereas quantitative data typically contain closed-ended answers, such as those contained in questionnaires or psychological instruments. The belief that both methods have prejudices and shortcomings in each type of data persists in the mixed methods approach. Some of the benefits of using quantitative data relative to qualitative data include broad comparability of answers, speed of data collection and the power of numbers (Taheri et al., 2015). 4.3.4 Research approach used in this study Since no research strategy is inherently superior to any other, the choice of research strategy was guided by the research hypotheses and objectives to determine the extent of existing knowledge. Quantitative research takes the form of a positivist approach focusing more on testing and providing theories by proposing research question, hypothesis and collecting data for analysis (Creswell, 2014; McCusker & Gunaydin, 2014). Quantitative research is quite applicable when a research objective involves a managerial action standard. Moreover, quantitative research is quite applicable for this study since the research objective involves a decision-making action standard such as ‘online promotion to influence car owner to purchase insurance policy online’. The present study encompasses both quantitative measurement in the form of numeric rating scales and quantitative analysis in the form of functional statistical 112 measures. Hence, the choice of quantitative approach was justified as it allowed the researcher to determine statistically significant differences between various constructs. In conclusion, the quantitative data are analysed using the Chi-square and logistic regression to gather information on the association between social media usage, the social media promotion mix, consumer behaviour and online purchase decision. 4.4 Research design Research design is generally divided into three types of analysis, specifically exploratory, descriptive, and causal analysis (Cant, 2013). The selection task of the study design consists of a set of actions that lead to the overall analysis. Research design offers, through the planned and organized selection, the overall framework to adopt for an investigation, analysis and interpretation of data (Babin & Zikmund, 2016; Wild & Diggines, 2013). Therefore, research design specifies which research questions must be answered, how and when the data will be collected, and how the data will be analysed. The aim of the study is to determine how the social media promotion mix influences individuals in the process of car insurance purchase decision-making. To answer this question, the research design in this study followed a descriptive quantitative design. In a descriptive quantitative design, structured questionnaires are used to gather the opinion of respondents thereby enabling a researcher to obtain a comprehensive knowledge on the phenomenon under study. Hence, this study followed a descriptive research design to define the characteristics of respondents based on the primary and secondary objectives. Objective 2 aims to provide a demographic profile of car owners in Mahikeng. 4.5 Study area Mahikeng local municipality is the smallest of the five municipalities but the most densely populated area with 78 people per square kilometre in the Ngaka Modiri Molema District Municipality (NMMDM) among others Ditsobotla local municipality, Ramotshere Moiloa local municipality, Tswaing local municipality and Ratlou local municipality (Mahikeng Local municipality, 2020b). 113 Figure 4.2: Study area Source: Mahikeng Local Municipality (2020b) Mahikeng local municipality (see Figure 4.2) is the seat of the North West provincial legislature and the majority of the National State Departments regional offices. Mahikeng, which was renamed from Mafikeng in 2010, is the capital of the North West province in South Africa with first language Setswana at 78%. The Mahikeng local municipality is 3,698 km2 where most of the land in the municipality is farming areas (55%) and then traditional areas (44%). Less than 2% of the Mahikeng area is urban area. It lies close to the province’s border with Botswana, about 240 km. Its workshops make it an important stop on the Zimbabwe railway from Cape Town, and a spur line links the city with Johannesburg. Surrounded by a prosperous cattle nation, Mahikeng is a commercial centre which supports the dairy industry. Being part of the Mahikeng Local Municipality which is divided into 28 wards consisting of 102 villages and suburbs, Mahikeng is a significant regional employer administered along with Mmabatho and other villages. The largest population group in Mahikeng local municipality is black African with 95%. The last recorded population in 2011 was 291 527, and in 2016 was 314394 with 24.4% representing a population under 15 years, 71.3% representing a population between 15 years and 64 years and only 4.3% representing a population over 65 years (Municipalities of South Africa, 2020). 114 4.6 Sampling design Sampling is the process of selecting subsets of a population that need to be included in a research study (Bradley, 2013). On the other hand, Creswell (2014) described a sampling design as the process or technique used to select a sub-group from a population to take part in an analysis. It would be preferable to include the whole population in some form of study, but in most instances it is not feasible to include any subject because the population is virtually finite. This study adapted the five steps of Babin and Zikmund (2016) to determine the sample for the study, which is shown in Figure 4.3. Figure 4.3: Steps to select a sample Target Sampling Sample Sample Select the population frame method size sample Sources: Adapted from Babin and Zikmund (2016) 4.6.1 The target population and sampling The first problem in the development of a sampling plan is to identify people from whom information is required to achieve the study goals. The population of a research sample involves a larger community of participants or respondents from whom a researcher aims to obtain the study results through a survey or interview (Creswell, 2014). McDaniel and Gates (2014) specified the population of interest as a geographic area, demographic characteristics, brand awareness measures, or other factors. Furthermore, Wilson (2014) defined population of interest as the total group of people a researcher wishes to examine, study or obtain information from. This study intends to assess the influence of the social media promotion mix on cars insurance purchasing in Mahikeng Local Municipality, therefore the target population in this study is car owners in Mahikeng Local municipality. 115 4.6.2 Selecting the sampling frame The second step in the process is to identify the sampling frame. McDaniel and Gates (2014) describe a sampling frame as a list of population elements from which to pick the units to be sampled. Thus, a sampling frame is a list of the interested population from which the researcher selects the individuals to be included in a study (Wilson, 2014). Therefore, the survey frame is the primary source of measurement units in the population where both the sample and sample units exist (Burns et al., 2017). Because this study aims to investigate the impact of social media promotion mix on car insurance purchasing decision in Mahikeng Local Municipality, the sampling frame is all car owners in the Mahikeng Local Municipality. However, the latest statistical data for the Mahikeng population in 2016 (314394) were presented as follows: less than 15 years (24.4%), between 15 to 64 years (71.3%), and greater than 65 years (4.3%). To be able to drive on a public road in South Africa, a person should be 18 years or older to hold a Professional Driving Permit (PDP) for a passenger vehicle (Govender, 2014). Hence, the total licensed vehicle population in Mahikeng municipality is estimated at 46 463 (ENATIS, 2019), which is the sample frame of this study representing 14.77 % of total population in Mahikeng Local Municipality. 4.6.3 Select sampling method The third step in developing a sampling plan is the selection of a sampling method, which depends on the objectives of a study and the nature of the problem under investigation. Sampling methods can be grouped under two headings, probability and non-probability sampling, as depicted in Figure 4.4. 116 Figure 4.4: Sample methods Sampling methods Probability sampling Non-Probability sampling Random sampling Convenience sampling Stratified sampling Purposive sampling Cluster sampling Quota sampling Sources: Adapted from Burns et al. (2017) and Hair et al. (2013) The following delineation provides a synopsis of the different sampling methods in order to understand which one is best for selecting the sample size for this study. 4.6.3.1 Probability sampling methods Probability samples are selected in such a way that each element of the population has a known, non-zero probability of selection (Creswell, 2014). Probability samples include samples where an objective selection procedure is used, resulting in a known probability for being chosen by every member of the population of interest (Wilson, 2014). There are various methods of probability sampling and these are briefly explained below.  Random sampling: According to McDaniel and Gates (2013), this is the best-known and most widely used probability sampling method. In addition, they stated that every potential member of the population has an equal chance of being chosen for the survey in a simple, random sample.  Stratified random sampling: Wilson (2014) describes a stratified random sample as a probability sampling procedure in which the sample selected is required to include possible respondents from each of the main population segments. Stratified sampling refers to a 117 technique where the population is divided into subgroups (strata) and then picked at random from the strata (Patten & Newhart, 2017).  Cluster sampling: this is a procedure in which clusters of population units are selected at random and then all or some of the units in the chosen clusters are studied (Bernt & Petzer, 2012). Researchers should keep in mind the costs and degree of use as well as the advantages and disadvantages of each method when choosing an appropriate probability sampling method (McDaniel & Gates, 2013). 4.6.3.2 Non-probability sampling Non-probability methods rely on human judgement. Malhotra (2010) describes a non- probability sample as a sample that fails to fulfil a probability sample criterion. Lacobucci and Churchill (2010) describe the non-probability sample as a system in which population participants do not have an equal opportunity to be selected. There are several non-random methods and these are:  Convenience sampling: Convenience sampling is a method where researchers target the most available members of the interested population (Wilson, 2014). A convenience survey uses respondents who are available quickly or conveniently, with the advantage of cost and time savings (Berndt & Petzer, 2012).  Purposive sampling: The researcher subjectively and purposefully selects the sample components which is convenient when large sampling is not required (Malhotra, 2010). Judgmental sampling therefore means that a researcher or field worker makes a decision as to who may best assist in the analysis (Berndt & Petzer, 2012).  Quota sampling: The researcher classifies the population by pertinent properties, determines the desired proportion to sample from each class and fixes quotas for each interviewer (Zikmund & Babin, 2010). Berndt and Petzer (2012) describe it as a method of stratified sampling in which the selection of sample members within each stratum is made, but the selection is non-random rather than those elements being selected randomly. This sampling method ensures the representation of certain groups in the sample. It is clear from the above discussion that in non-probability sampling, not all members of the population have a chance to participate in a study, unlike probability sampling, where each member of the population has a chance to be selected. Since the researcher wants to understand the impact of social promotion mix on car insurance purchasing decision, the selection criteria 118 among the population will be “are you a car owner?” and those who respond with a “No” are excluded from the sample so that there are chances that the results obtained will be highly accurate with a minimum margin error. Whether potential participants/ car owner are insured or not, respondents were selected on the basis of their availability. Hence, a purposive, also called judgmental sampling method, which is a non-probability sampling method, has been selected to ensure that insurance and non-insurance subscribers were identified and included in this study, as recommended by Hair et al. (2013). Now that the sampling method is known, the selection of the sample size is dealt with in the next section. 4.6.4 Determine sample size After the sampling methods have been chosen, the next step as illustrated in Figure 4.4, is to define the suitable sample size. McDaniel and Gates (2015) explain the sample size as the number of elements or individuals to be included in the final sample. In quantitative research, the main ways of deciding on sample size are by calculation, budget and number of sub-groups to be analysed (Wilson, 2014). However, McCarthy, Whittaker, Boyle and Eyal (2017) point out that the higher the sample size, the smaller the sampling error will be, although it increases the cost and time of gaining responses. In any social science research, estimating an appropriate sample size becomes important and is the method by which we determine the optimal number of participants required to be able to obtain ethically and scientifically valid results. Generally, the sample size for any study depends on many factors namely: acceptable level of significance, power of the study, expected effect size, underlying event rate in the population and the standard deviation in the population (Berndt & Petzer, 2012). Sampling, in a nutshell, is taking a sample from a population for analysis. This study makes use of a non-probability sampling design. The first step consisted of identifying the study area which is the Mahikeng Local Municipality in this instance and a given number of car owners were selected among the total licensed vehicle population in Mahikeng municipality estimated to 46 463 (ENATIS, 2019), in order to ensure that the sample is as representative as possible of the entire research population. From the list of 31 wards consisting of 102 villages and suburbs in Mahikeng Local municipality, the two main places which are Mahikeng and Mmabatho were purposely selected based on the demographic and economic characteristics. In 2016, the population was 314394 indicating an increase population by 7.27% (Mahikeng Local Municipality, 2020). This means that in 2016, the population of Mmabatho increased to about 41081 and the Mahikeng population increased by approximately 16216, which means a total of 57297 people for 119 Mahikeng and Mmabatho which represents the hotspot of a high level of employment in Mahikeng Local Municipality where the main economic sectors are agriculture, manufacturing, trade, tourism and government services (Mahikeng Local Municipality, 2020b). As stated earlier, among the total population of 314394, the number of car licences owned by people in Mahikeng local municipality is 46463. Using mathematical calculations, the number of car licences owned by Mahikeng and Mmabatho’s population which is 57297 people is 8467 licenced vehicles. In this study, based on the 8467 licenced vehicles using ROASOFT with a margin error of 5%, confidence level needed of 90% and the response distribution rate of 50%, the sample size calculated was 263 respondents. Furthermore, in order to maximise chances to select cars owners in the sample, the researcher targeted workers because they have high chance to be older than 18 years to possess a driver’s licence and own a car (ENATIS, 2019). Hence, four entities with more than 20 employees were selected in each place of Mmabatho and Mahikeng to maximise the sample size. However, in Mmabatho, the premieris office, Mahikeng Local Municipality, SABC (South African Broadcasting Corporation) and ESCOM (Electricity Supply Commission) were contacted through their communication departments and permission was granted only by the premier’s office and the Mahikeng Local Municipality where the link was sent to the communication office and shared with employees through their intranet. In Mahikeng, the four entities contacted were the Department of social development, the Labour department, Police station and Department of Health and permission was granted only by the Department of social department and Labour department through their cellule of communication where the links were sent to be shared among employees through their intranet expecting a sample size of 263 car owners in the Mahikeng Local Municipality. 120 Figure 4.5: Sample categories In conclusion, the summary of the sample plan for this study is presented in Table 4.1. Table 4.1: Sample plan for the study Sample plan Target population Males and females, older than the age of 18 who own a car. Sample frame Total licensed vehicle population in Mahikeng municipality is estimated to be 46 463 Total licensed vehicle population in Mahikeng and Mmabatho is estimated to 8467 Sampling method Non-probability sampling which includes purposive sampling. Method of sample size ROASOFT calculation Expected sample size 263 121 4.7 Data collection procedure This step entails the specification of the operational procedure for selecting the sample elements (Burns et al., 2017). For the current study, this step determines how to contact the prospective respondents (Hair et al., 2013). This section deals with the data collection procedure which started with information types and their sources, followed by the research instruments, and finally the data-collection method was discussed. 4.7.1 Identify information types and sources Berndt and Petzer (2012) identified two types of information/sources namely, primary and secondary information. Internal secondary data include data from inside the company which has already been collected. In contrast to this are primary data which are precisely gathered to address a particular problem a company identified (Feinberg et al., 2013; Neelankavil, 2015). To achieve the objectives of this study, both secondary and primary data were used. Figure 4.6 provides a summary of the different types of data and the sources. Figure 4.6: Information source Information source Secondary data Primary data Internal data Quantitative data Qualitative data External data Observations Experiments Surveys Printed questionnaires Online questionnaires Source: Adapted from Burns et al. (2017); Creswell and Creswell (2017) and Wild and Diggines (2013). As presented in Figure 4.6, secondary data are internal and external data (Burns et al., 2017; Creswell, 2014; Wild & Diggines, 2013). Internal data include data from inside the company 122 which has already been collected and Creswell (2014) identified four areas where a company can collect information such as from sales, finances, marketing and human resources. Meanwhile, external secondary data are acquired from outside the company and Malhotra (2015) advises companies to look at consumer feedback, surveys and competitors. Secondary research is likely to validate the findings of previous authors on the basis of Rhys (2013) and support this study, as well as the research gap identified in literature. Secondary data led to the development of the literature review and the formulation of the conceptual framework of this study based on acceptance technologies and planned behaviour (Chin, 2016; Greyling, 2017; Manjunath & Nagabhushanam, 2017; Safeena et al., 2013). Through the secondary data, the research question was generated, and further comprehensive knowledge about the social media promotion mix and car insurance in South Africa was gained. Secondary data used for this study were collected from various academic journals and articles including previous studies, relevant books and the internet to create an argument for this research study, as well as, to clarify the variables of the study. Since secondary data are not adequate on its own, primary data were needed to explore the research question and to test the conceptual framework. Figure 4.6 further indicates that primary data can be classified into two categories; namely, quantitative and qualitative data. Quantitative data imply data collected through a set of structured questions with fixed response options, administered to a large number of respondents, while qualitative data refer to data collected through methods of observation or recorded during one-to-one interviews (Burns et al., 2017; Malhotra, 2015; Silver et al., 2012). The South African insurance industry has been one of the slower industries to realise the importance of going digital and sufficient research is necessary for marketers to be able to make knowledgeable and lucrative decisions (Mahlangu, 2018; Moodley, 2019; Tayengwa, 2017). To address the research question a quantitative approach was chosen, and the research model was tested using primary data collected from the population sample through questionnaire as research instruments. 4.7.2 Research instruments Research instruments are tools or equipment used by researchers for data-collection purposes (Burns et al., 2017). This section presents the questionnaire response format, followed by the measurement scales, the questionnaire layout is presented, and finally the pilot study is discussed for validity and reliability of the instruments used. 123 4.7.2.1 Questionnaire response format Malhotra (2015), in his book entitled Essentials of marketing research: a hands on orientation, identified three response formats and these are: open-ended, close-ended, and scaled-responses that can be used in a study.  Open-ended questions: McDaniel and Gates (2014) explain that open-ended question responses give participants an opportunity to answer a question in their own words. Instead of being restricted to choose from a given set of options, McDaniel and Gates (2014) clarify that open-ended questions are used to gain more elaborate answers from respondents. Generally, open-ended responses seeking factual information are expensive and time- consuming (Malhotra, 2015). This type of questions are used in this study in order to obtain a more detailed response from respondents.  Close-ended questions: According to Feinberg et al. (2013), this is a technique where a limited number of options are given to respondents and Ortinau et al. (2013) identify two types of closed questions, namely, multiple-choice questions and dichotomous questions as presented below. o Multiple-choice questions require a participant to select one or several answers from predetermined options (Feinberg et al., 2013). Questions related to ethnicity are examples of a multiple-choice question. o Dichotomous questions require a participant to select one or two alternatives, for example ‘yes’ or ‘no’ (Wild & Diggines, 2013). Although dichotomous questions are simple and quickly answered, there is a risk that the content of interest has some meaning that can be measured accurately by using dichotomous questions.  Scaled-response questions: Kumar (2019) listed two scale questions as comparative and non-comparative scales that provide a participant with a range within which measured objects are located. In agreement with Kumar (2019), Feinberg et al. (2013) suggest that a comparative scale requires a straightforward comparison of a stimulus aimed at showing a respondent's attitude towards an object centred on a particular object, although a non-comparative scale enables the subject to show a specific object's mood or feeling or actions without any relation to another object (Hair et al., 2013). The Likert scale is a popular type of multi-element scale in which respondents indicate 124 to what extent they agree or disagree with each statement (Burns et al., 2017). Developed by Rensis Likert in 1932, Likert’s initial scale consisted of five options, modified by various researchers to a 7-point scale (Edmondson et al., 2012). 4.7.2.2 Measurement scales Measurement scales refer to the mechanism for assigning and categorizing variables (Brown et al., 2013). In addition, the authors describe four types of scales used to calculate attributes; namely, the nominal, ordinal, interval, and ratio scales. Every measurement scale has some properties which in effect determine the significance of using such statistical analyses.  Nominal scales: A nominal scale is a measurement scale that is used to allocate incidents or objects into different categories. This type of scale does not require the use of class ranked numeric values or divisions, but merely unique identifiers to mark each category (Brown et al., 2013; Hair et al., 2013). Nominal scales are also considered the most basic method of measurement and are used in many disciplines to classify and analyse data.(Burns et al. 2017; Marshall & Rossman, 2011) and therefore, assigned numbers serve only as labels as conferred by Edmondson et al. (2012). Demographic questions such as gender are examples of nominal scales to which is attributed a value of 1, for example, to Females and a value 2 to Males, or vice versa when computerizing data.  Ordinal scale: The ordinal scale is the 2nd measurement standard, which records the data ranking and ordering without explicitly deciding the degree of difference between them. The second of the four measurement scales is the ordinary measurement standard (Brown et al., 2013; Creswell & Creswell, 2017). Ordinary data is quantitative data that has orders that exist spontaneously and the discrepancy between them is unknown. They can be named, grouped and ranked as well (Edmondson et al., 2012; Hair et al., 2013). As mentioned by Burns et al. (2017), it is important to note that an ordinary scale means that classes must be ordered in such a way that each case in one class is considered to be greater than (or less than) each case in another class.  Interval scales: As the third level of measurement, interval scales are explained by Babin and Zikmund (2016) and Wild and Diggines (2013) as a quantitative measurement scale where the difference between two variables is significant. The interval scale is quantitative in that it can quantify the difference between values (Burns et al., 2017), although in an interval scale, in the absence of the absolute 0 and that it works on the principle of an 125 arbitrary 0, the division of the variables is not possible. Thus, although the interval scale allows the analysis of a large number of data, it does not allow the calculation of ratios.  Ratio scales: Ratio scales are similar to interval scales and is the highest level scale since it allows establishing the absolute difference between each scale point (Hair et al., 2013). However, ratio scales also have an absolute zero where a negative length is not possible. Table 4.2 helps clarifying the fundamental differences between the four scales of measurement. The table shows that only the ratio scale meets the criteria for all four properties of scales of measurement. Table 4.2: Measurement scale Indications Indicates direction Indicates Absolute zero difference of difference amount of difference Nominal X Ordinal X X Internal X X X Ratio X X X X For this study, open-ended type questions were used, as well as closed-end questions that provide specific guidance and are therefore considered as an effective way for obtaining data. Regarding the scale question types, this study included non-comparative scales and specifically multi-item rating scales using a 5-point unlabelled continuous Likert scale. 4.7.2.3 Questionnaire design and layout The literature review was analysed and through this process, the constructs of the study that were used for the development of the questions used in the questionnaire represented. As Babin and Zikmund (2016) explain, the design of a questionnaire is a decision which asks for a better understanding of achieving the objectives. Therefore, they ensure that the questionnaire is applicable to a study and that the questions designed and/or adopted from defined scales are accurate and reliable. Initially, the questionnaire was divided into three (03) sections. All demographic questions in section A were measured using nominal scales. With respect to the interval scale used, the questions in section B and C dealing with the constructs investigated in 126 this study, made use of 5-point unlabelled continuous Liker scales, as suggested by Burns et al. (2017). The questionnaire starts with the introduction which informs respondents on what the study is all about. The identities of the participants are not available as no identifiable information such as names, contact phone number or address was required and the questionnaire was in print form and also sent via e-mail and text messages to participants. The introduction (consent letter) includes the aim of the study, information regarding confidentiality and anonymity of the respondents, and also information about the availability and dissemination of the results. Section A contains more insight into the demographic information of car owners in Mahikeng. The focus of this section of the questionnaire is to obtain information on the following demographic descriptors of the respondents: gender, age group, and monthly income. Furthermore, to achieve the first objective, respondents were asked to indicate whether their cars were insured and which media had triggered their intention to purchase insurance. The second section of the questionnaire (section B) explored respondents’ social media usage. The items in section B develops questions on one construct social media usage using nine (09) statements intended to indicate the extent to which respondents agree with each of the statements using a 5-point unlabelled continuous Likert scale, to investigate the general internet usage of the respondents. The third section of the questionnaire (section C) consists of ten (10) constructs divided into fifty-seven statements related to the social media promotion mix and consumer behaviour. It included exploring the respondents’ level of agreement with the statements (05) related to perceived usefulness, behavioural control (7 statements), social influence (5 statements), attitude (5 statements), perceived security (5 statements), service quality (6 statements), perceived trust (6 statements), perceived tangibility (6 statements), the social media promotion mix (8 statements) and purchasing intention (4 statements). The scale items have been adopted and adapted from previous reliable studies and are aligned to the context of this study. Every statement in this section of the questionnaire is provided in Table 4.3 which indicates the response format and scale type for each statement. 127 Table 4.3: Summary of the scales used in the questionnaire Items Response Scale Objecti Source format type ves Section A Demographic information Please indicate your Gender Dichotomous Please indicate your age group. Multiple-choice Monthly income Multi-choice Is your vehicle insured? Dichotomous Which statement is the most applicable Multi-choice Which media triggered your intention to Multiple-choice purchase insurance policy. Section B Social media usage 1 construct with 9 statements Multiple-choice Nominal Self-generated Multi-item Interval Bashir et al. Likert scale (2019) Tripathi (2014) Mayfield (2008) Section C Social media promotion mix and consumer behaviour Social media promotion mix (1 construct Multi-item Interval Parasuraman with 8 statements) Likert scale et al. (2005) Consumer behaviour (8 constructs with 29 Kim & statements) Lennon (2013) Online purchase decision 1 construct with 4 statements Likert scale Interval Self-generated Once the questionnaire was ready, the next step was the distribution of the questionnaire for collecting the data required for the pilot study. 128 Nominal Primary Secondary Secondary Secondary Self-generated 4.7.2.4 Pilot study Once the questionnaire had been developed, the questionnaire was pre-tested through a pilot before the actual data were collected to test the relevance and accuracy of the questions included in the questionnaire. Babin and Zikmund (2016) describe a pilot study as a small- scale preliminary study to assess the feasibility, duration, adverse effects and to improve the design of the instrument before conducting a large-scale research project. In order for the research instrument to be effective and efficient, it is expected for these instruments to meet two most fundamental criteria, namely reliability and validity (Bolarinwa, 2015). Validity is described as an instrument's ability to measure what it should measure (Brynard & Hanekom, 2006). The measurement of an instrument faithfully reflects the notion it is intended to measure. There are five validity requirements that can be used to assess the validity of a design or an instrument, according to Brynard and Hanekom (2006), namely content validity, criterion-related validity, construct validity, face validity and external validity. However, Reliability applies to accuracy and correctness of measures taken (Brynard & Hanekom, 2006). If, at a later point, the same instrument is used under the same conditions, it must be able to generate the same data. The methods, named test-retest methods, the split-half method was developed to ensure consistency in terms of reliability (Notsi, 2012). Pilot studies are done to refine the measures and reduce the risk that a large-scale study might include flaws that will influence the data collected (Burns et al., 2017). The pilot study comprised several components which are intended to determine the feasibility of the study, recruitment of subjects, testing the measurement instrument, data entry and analysis (Hassan, Schattner & Mazza, 2006). 1) To determine the feasibility of the study protocol A pilot study was conducted on selected friends who are car owners in Mahikeng during the month of February 2020. In the first pilot, the provisional study protocol based on car’s owners and voluntary was strictly adhered to, that is a small-scale version of the complete survey was tested, from respondents to data analysis. The researcher agreed to enrol 25 car owners, male and female, aged from 18 years and over by sharing the link of the online questionnaire through their different social media. Among the 25 questionnaires sent, only 20 questionnaires were received and grouped into car’s owners insured and car’s owners uninsured in order to balance the two groups for analysis. 129 2) Recruitment of subjects The researcher invited subjects to participate in the study, with adequate time given for the respondents to consider whether they wished to participate by sending to the researcher their email to demonstrate their consent. Then they were handed the questionnaire by email and two weeks was the deadline to receive the response. By the deadline, 20 questionnaires had been received which were used for the pilot study. 3) Testing the measurement instrument Pilot studies are normally less structured than the large-scale study and the sample population of the pilot test was a sample of 20 respondents. The measurement instrument (questionnaire) required self-completion by respondents. An important factor was to ensure that the questionnaire items accurately addressed the research questions. The pilot also tested whether the questionnaire was comprehensible and appropriate, and that the questions were well- defined, clearly understood and presented in a consistent manner. The questionnaire was divided into three sections the related to section a which is demographic information, section B was social media usage and the last section C was social media promotion mix, consumer behaviour and purchasing intention. The questionnaire was produced in English and was piloted 3 times using the 20 respondents each time. The issues that were observed among respondents in the pilot of the questionnaire included:  Ability to comprehend the instructions in the covering page of the questionnaire  Understanding of questionnaire items, the items used, the sequence of questions and the flows of statements  The format, including the font and layout  Length of the questionnaire (meaning time taken to complete the questionnaire)  And other comments by the respondents At the end, all comments were taken into consideration and errors amended and re-piloted until no further changes were considered necessary. As specified before, the pilot process took 2 weeks. The first time the questionnaire was sent, it took one week to receive all 20 responses. As respondents attempted to respond to all questions, there were some items that they missed because the questions were spaced too close to each other, causing some of the participants to miss a line. In addition, there was considerable discrepancy in the answers to some of the items, either because they were too vague or due to a language barrier, resulting in respondents not 130 understanding the questions properly. This was observed with the items asking about social media usage and social media promotion mix. To analyse the reliability of variables for this study, Cronbach’s alpha is one of the popular approaches. Cronbach’s alpha was used to examine the internal reliability of the total 11 constructs used to measure the influence of social media on car insurance purchasing decision-making. Only 1 construct was used to measure the social media usage which had 9 statements, while 10 constructs were used to measure the social media promotion mix, consumer behaviour and purchasing intention with questions varying between 1 to 8 statements. The Cronbach’s alpha varies from 0 to 1 and a value of 0.6 or less indicates unsatisfactory internal consistency reliability (Gray, 2013). Table 4.4: Reliability Statistics Cronbach's Alpha N of Items .951 11 Source: Author own calculation using SPSS The Cronbach’s alpha obtained is 0.951 and this means that 95.1% of the variability in the compensated scoring by combining those 11 items are internally consistent reliable variance. This is in line with Shabalala (2016) who indicates that a Cronbach alpha of 0.72 and higher is quite acceptable in social science research. 131 Table 4.5: Selection of the best items to include in the study Constructs Number of Scale Mean if Scale Corrected Cronbach's statements Item Deleted Variance if Item-Total Alpha if Item Item Correlation Deleted Deleted SMP (social 9 33.1556 53.189 .880 .942 media usage) PU (perceived 5 32.7019 52.493 .771 .948 usefulness) PBC (perceived 7 32.6944 54.385 .912 .941 behavioural control) SI (Social 5 32.6648 54.787 .857 .943 influence) A (Attitude) 5 32.9241 54.011 .792 .946 PS (perceived 5 32.8870 55.605 .701 .950 security) SQ (Service 6 32.4611 57.802 .848 .945 quality) PT (Perceived 6 33.1278 56.080 .761 .947 trust) PTA (Perceived 6 32.6000 57.721 .913 .943 tangibility) SMPM (social 8 32.4056 58.569 .788 .947 media promotion mix) PI (purchasing 6 33.1000 62.872 .505 .954 intention) Source: Author’s own calculations using SPSS Results from Table 4.5 revealed that the highest Cronbach’s Alpha is .954 meaning when item PI is deleted, it exceeds the original estimate reliability of .951. This means that item PI should be deleted in the final questionnaire; therefore this study is based on 10 constructs without purchasing intention (PI). After these corrections, the questionnaires were re-sent for the 132 second time to the same respondents and after 3 days, all 20 questionnaires were received. This time for some items, the boxes were placed too close together which made it difficult for the researcher to identify which one the respondents had ticked. Reformatting was done to overcome this problem and a section D was created to capture the car insurance purchasing decisions which were now dichotomous items, meaning they have two possible responses (yes or no). There were also a few typographical errors and some of the coding for the items was wrong. Finally, when the questionnaire was resent for the third time to the same respondents, responses were received after 3 days and this time all constructs and other corrections were widely used to validate and reduce the number of statements. From this pilot study respondents encountered no difficulty understanding the items in English. 1) Questionnaire to be used The finalised questionnaire designed for this study is provided in Annexure A and consists of four sections: The introduction which informs respondents on what the study is all about. The identity of the participants is anonymous since no identifying information, such as names, contact telephone numbers or addresses, was required and the questionnaire was sent to the participants via e-mail. The first section obtains more insight into the demographic information of car owners in Mahikeng. The focus of this section (section A) of the questionnaire is to obtain information on the following demographic descriptors of the respondents: gender, age group, and monthly income. The second section of the questionnaire (section B) explored respondents’ social media usage. The constructs in section B were developed to investigate the general internet usage of the respondents based on seven statements. The third section of the questionnaire (section C) is included to explore the respondents’ level of agreement with the statements related to perceived usefulness, behavioural control, social influence, attitude, perceived security, service quality, perceived trust, perceived tangibility and the social media promotion mix. This section consists of thirty-five statements divided into nine constructs related to the social media promotion mix and consumer behaviour. The scale statements have been adopted and adapted from previous reliable studies and are aligned to the context of this study. The fourth section of the questionnaire (section D) consists of one dichotomous statement, related to the intention to purchase an insurance policy online. 133 2) Data entry and analysis From the 20 questionnaires validated, a basic descriptive statistical analysis was done. Out of the 20 respondents, 13 were females and 7 were males. In addition 15 respondents had their cars insured while 5 had their cars uninsured. All other results on the social media usage and social media promotion mix were satisfactory and the preliminary conclusion revealed the social media promotion mix was positively affecting respondent to purchase their car insurance online. With the pilot study found satisfied, the next step was to collect data from a large number of cars owners in Mahikeng local municipality for data collection for global and deeper analysis. 4.7.3 Data-collection method Data-collection refers to the actual collecting of information for a study, which can either be person-administered, computer-administered or self-administered (Burns et al., 2017). The following section will start with a discussion of the secondary data collection followed by primary data collection. Research precedence professes that secondary data be collected first and reviewed prior to collecting primary data (McDaniel & Gates, 2014; Neelankavil, 2015). 4.7.3.1 Methods of collecting secondary data For the purposes of this study, external secondary data were gathered from multiple academic sources such as marketing research journals, social media posts, business reviews, online purchasing decision research, and customer behaviour journals. Such secondary sources of data were used to provide a comprehensive literature review and also for conceptualizing a model which summarise the relationships between the constructs, as recommended by Ortinau et al. (2013). 4.7.3.2 Methods of collecting primary data Quantitative research methods focus on quantifying the research problem and the data obtained from quantitative methods lend themselves to the use of statistical techniques (Berndt & Petzer, 2012). As indicated in Figure 4.6, primary data can be collected using observation, experimental designs and survey data. 134 1) Observational data McDaniel and Gates (2014) stated that this is the systematic practice of documenting behavioural patterns without asking or engaging with the individuals concerned. Babin and Zikmund (2016) describe observations as a group of people being observed during observational research, and that their behaviour is registered for further study. The main advantage of observation research, as mentioned by Berndt and Petzer (2012) and Feinberg et al. (2013) is that researchers can see what people really do rather than having to depend on what they say they did, thereby avoiding many biasing factors. 2) Experimental data This is observed through experimentation in which one variable is introduced in the experiment and where the effect on an alternative variable is observed. In other words, experimental data are used to examine whether an independent variable shift induces a predicted change in a dependent variable (Wild & Diggines, 2013). The experimental method aims at creating an independent impact on different variables, while one or more independent variables are manipulated, to analyse the effects of the dependent variable (Babin & Zikmund, 2016; Burns et al., 2017). Experimental data compared to observational data studies are very expensive and time-consuming and therefore are not used very often (Silver et al., 2012). 3) Survey data This relies on the use of a questionnaire which is a set of questions designed to generate the data necessary to accomplish the objectives of a research study (Creswell, 2014). Survey research is a method in which information can be collected from participants through various techniques (Malhotra, 2015).The aim of this study was to investigate the influence of the social media promotion mix on the car insurance purchasing of residents in Mahikeng. Hence, data were collected using online questionnaire via Google Forms. Wolber (2012) describes Google Forms as a user-friendly method for developing online surveys to collect answers in an online table. Surveys have various advantages and drawbacks, such as questions which do not reliably assess the attitudes of respondents and the complexity of collecting in-depth data (Hair et al., 2013). 135 A questionnaire is a tool designed specifically to collect evidence that will be analysed to back the conclusions and recommendations of this study (Babbie, 2010). In this study, questionnaires were sent through email addresses of the contacted persons in each department or entities where permission was granted (see Figure 4.7). The link of the online questionnaire was also sent through Facebook (see Figure 4), WhatsApp and other social media. Figure 4.7: Letter of approval from the department of economic development environment conservation and tourism 136 Figure 4.8: Online message posted Therefore, a strong advantage for opting for a survey was that it was faster and cheaper compared to experiments and observational studies (Hair et al., 2013). The researcher expected 263 questionnaires within two months (March and April 2020) from the respective respondents for data analysis. The confinement due to preventive measures against the spread of the 2019 Coronavirus disease (COVID-19) affected the educational system in particular and the country in general. Due to covid-19, the researcher had to switch from face to face to virtual survey administration and data collection. The Covid-19 made it difficult to reach participants, thus some were less engaged due to the stress and uncertainty resulting from the pandemic. 4.8 Data analysis and statistical technique McDaniel and Gates (2014) indicated that there is a data preparation process to be followed once the questionnaires are received from the fieldwork. Hence, once data had been collected, the data went through a process of checking the questionnaires, then data were edited and coded. After coding the variables, the data needed to be captured into Excel, then the data needed to be cleaned and ready to be analysed using statistical techniques in order to give meaning to the raw data collected. 137 4.8.1 Checking of the questionnaire The initial step in questionnaire checking involves reviewing all questionnaires for completeness or completion quality. There are several reasons why questionnaires are deemed unacceptable:  If there are too many omissions in a questionnaire. The number of response frequency can vary due to non-responses as all questions were not mandatory due to ethics as anyone has the right not to respond. Some questionnaires were not fully answered, which does not make the entire questionnaire unusable. In some cases, data were not gathered from people who should have been interviewed.  If the questionnaire is returned after the cut-off date. In some cases where questionnaires were returned after the due date but received before the analysis was done, or when the targeted response rates were not achieved, then such questionnaires could still be considered for inclusion in the analysis. However, if the response target was reached or questionnaires arrived after the analysis was done, then such questionnaires could be ignored.  If the questionnaire was completed by a non-eligible person. In the event of a questionnaire being completed by a non-eligible person and it was known to or detectible by an experienced researcher/fieldworker, such questionnaires could not be considered for analysis.  If the respondent did not understand or follow the instructions. In the event of a respondent not understanding or following instructions, such questionnaires should also not be considered for analysis. After receiving the response, the only questionnaires taken into consideration were respondents who indicated that they were car owners as specified by the sampling method. Hence, from the sample size of 263 responses, the response rate of around 60% for most research should be the goal and certainly is the expectation (Burns et al, 2017). Thus, the minimum response expected was 157 cars owners in Mahikeng Local Municipality. To reach the sample size expected for this study, the researcher had to deploy the survey through various online channels, follow up on each participant via email, WhatsApp, Facebook and phone call. Some participants complained about internet access and others chose to ignore 138 or delete the survey. From the 263 responses expected, the number of questionnaire received on the 30th April 2020 which was the deadline for collection were 240 responses representing roughly 91% of the response rate. The remaining 23 responses were not taken into account as they came after the due date and the data had already been sent for analysis. The selected number of participants was categorized into insurance subscribers and non-subscribers to obtain a balanced point of view on the influence of the social media promotion mix on the car owners when considering short term insurance. From the 240 collected, 20 questionnaires were disqualified for not meeting the criteria of being car owners. Therefore, the responses selected were 220 respondents. According to Survey police (2015), “to achieve statistically valid results, we recommend that a statistically significant sample of n=400 completed surveys be obtained for online market research surveys. This will provide statistical validity at the 95% confidence level with +/- 5% confidence interval. For clients on a tighter budget, we sometimes recommend a sample of n=200 complete online surveys which provides statistical validity at the 95% confidence level with +/- 7 % confidence interval. In any event, a reliable sample source is very important, as is an unbiased random sample methodology. The equally sized sample groups enabled determining the influence of the social media promotion mix on each strata. 4.8.2 Data editing and screening Editing is the review of the responses and consists of screening the questionnaires to identify illegible and incomplete responses (Malhotra & Malhotra, 2012). Responses must especially be legible when dealing with a large number of unstructured questions to be able to do proper coding if required. Creswell and Creswell (2017) indicate that unsatisfactory responses can be dealt with by returning to the field in order to get better data, assign missing values, and discard unsatisfactory respondents. Bradley (2013) advices various actions with any identified problem such as:  Deduce the answer by inspecting other answers from the same respondent.  Do nothing and leave the data dirty.  Reject the entire data record for the given respondent.  Return to the respondent and ask the question again. For the purposes of this study, all questionnaires were checked to make sure the number of questionnaires from insured car owners was balanced with those of uninsured car owners. In 139 addition, from the 220 responses selected, nineteen (19) were disqualified because of missing values which were not assigned and unsatisfactory responses were rejected during the editing of the questionnaires obtained for this study. The online questionnaires were also subjected to be verified by screening the responses and the satisfied remaining 201 responses were coded. 4.8.3 Coding Creswell and Creswell (2017) describe coding as a representation for a specific response to a specific question along with the data record and column position where the code is. Coding of data is essentially the process that turns responses into a format that can be analysed (Kumar, 2019). Where the answers to a question are represented as points on a scale from 1 to 5, these numbers were directly entered unto a grid. The answers took a different form, which were translated into a numerical scale. Spreadsheets were used as a format to convert responses into data codes for analysis purposes. Coding is required to identify individual responses as indicated in Table 4.6. Table 4.6: Example of data coded in Excel spreadsheet Age Monthly Is your SMP1 PU1 PBC1 SM A1 income vehicle (Rand) insured 2 1 2 1 1 1 2 2 2 4 1 10 2 2 3 3 2 4 1 19 3 3 3 3 2 1 1 18 4 4 3 3 2 4 2 1 5 5 5 5 2 4 1 20 5 5 3 3 2 2 2 1 3 3 5 1 2 2 2 17 1 3 2 5 3 4 1 17 5 4 5 4 For the purpose of this study, the online questionnaire on Google Forms was pre-coded for the closed-ended questions, while responses to the open-ended questionnaire were coded after downloading the dataset. In addition, data were converted into an Excel spreadsheet, eliminating coding errors. The 201 sets of data obtained from respondents were captured into 140 an electronic dataset (see Annexure B) which is a matrix arrangement of numbers in rows and columns, similar to that of a Microsoft Excel spreadsheet (Babin & Zikmund, 2016; Burns et al., 2017). 4.8.4 Data entry Data entry involves transferring the coded data from the questionnaires into computer-readable format (Feinberg et al., 2013). The data entry method depends on the method used for collecting the data and the availability of equipment (Malhotra & Malhotra, 2012). In the case of the online questionnaire used for this study, the open ended data codes were entered manually into excel sheet after being codified. 4.8.5 Data Cleaning The cleaning of data occurs once the data have been entered into a spreadsheet, which consists of removing errors and inconsistencies from data in order to enhance the quality of data (Edmonds & Kennedy, 2016). Responses can be logically inconsistent in various ways. Malhotra (2015) lists some of the best practices for data cleaning:  Sort data by different attributes.  Keep track of every date cleaning operation.  Analyse the summary statistics for each column.  Break large datasets into smaller sets of data. After the data had been cleaned, statistical techniques were used for analysing the data using SPSS (Version 24). 4.8.6 Statistical technique for data analysis After data had been cleaned, edited, coded and captured, various statistical procedures can be used for analysis and structural equation modelling (Hair et al., 2013). Data analysis refers to the process where the dataset is described by calculating some statistics which characterise the various aspects of the dataset (Burns et al., 2017). Data analysis implies the interpretation of data in order to draw outcomes that mirror the ideas, interests and theories that instigated the research (Babbie, 2013; Kumar, 2019). Because this study used mixed methods, hence there are different techniques for each research method. For a qualitative method, descriptive analysis called univariate analysis was used while there are a number of methods that can be 141 used to analyse quantitative data, ranging from bivariate analysis to more complex multivariate analysis (such as regression analysis, correlation, linear regression, Anova, Chi-square, cluster analysis and structural equation modelling) (Babbie, 2013; Cant, 2011; Kesharwani et al., 2018; Kumar, 2019). Univariate data analysis involves the analysis of only one variable at a time, while bivariate and multivariate data analysis investigates the relationship between two or more variables. For the purposes of this study, the following statistical techniques were utilised for the purpose of this study as specified in Table 4.7. Table 4.7: Secondary objectives and data analysis Objectives Statistical technique To describe the socio-economic characteristic of car Descriptive analysis owners in Mahikeng. (Univariate) To investigate the relationship between the demographic, Chi-Square (Bivariate). socio-economic and socio-media usage and purchase decision-making amongst car owners in Mahikeng. To determine the relationship between social media usage, Chi-Square (Bivariate). social media promotion mix, consumer behaviour and online purchasing decisions in Mahikeng. To investigate the impact of online promotion mix on the Logistic regression purchase decision making amongst car owners in (Multivariate) Mahikeng. 4.8.6.1 Descriptive statistical analysis (Univariate) Descriptive statistics, according to Hair et al. (2013), comprises procedures that are used to explain or summarize the imperative features of a group of measurements. Descriptive insights were based on car owners in Mahikeng and their usage profile of social media. Descriptive statistics are used on a sample of participants to summarise and describe the data acquired (Hair et al., 2013). Similarly, Feinberg et al. (2013) assert that descriptive statistics are used when the results of every question in the survey is to outlined, whereby the demographic description of the sample is included. Information on the gender, age and income enable making inferences about the sample. Whether their car is insured or not, and the reason and the media that triggered their intention to take out car insurance. Questions were included about consumers’ 142 online experience and the time spent online, and this information was used to create a more comprehensive understanding of the car owners in Mahikeng and their technology usage tendencies. The description of the raw data collected from the demographic and usage description questions provided more reliable and enlightening results and conclusions. The different types of descriptive techniques used in this study are presented and discussed in Table 4.8. Table 4.8: Different types of descriptive techniques Descriptive Definition technique Mean This is the most common measure of central tendency and refers to the average value of a group of numbers (Kumar, 2019; Babin & Zikmund, 2016). The mean score is calculated by dividing the sum of the responses by the number of respondents who have answered the question (Aaker et al., 2013). Percentage The percentage is the number of respondents who have answered the question in a specific way, multiply by 100 (Aaker et al., 2013). Standard This is calculated by subtracting the mean score from the square of each deviation number and them summating it followed by dividing that sum by the total number of responses minus one then taking the square root of the result (Hair et al., 2013). 4.8.6.2 Chi Square (Bivariate) For an instrument (the questionnaire of this study) to be trustworthy it is to be assumed that the data collected are both reliable and valid. 1) Reliability test Whenever humans are part of measurement procedure, there is the concern of whether the results are reliable or consistent. A test would be considered accurate if the instrument used measured the same way with the same subjects each time it was used under the same conditions (Babin & Zikmund, 2016). Reliability refers to the degree to which results are stable and consistent with the instrument used to conduct the study (Burns et al., 2017). The theory underlying the discussion of estimating an instrument’s reliability is sometimes called classical 143 measurement theory, developed by Charles Spearman in 1904. If a measurement device is absolutely accurate, it would have a perfect positive correlation with the scores of reality. If an incident or occurrence is weighed twice, and the true scores did not change, then both times the same result would be obtained. Reliability is evaluated using the Alpha value (α) of the Cronbach which is an internal consistency measure. The lowest acceptable Cronbach’s Alpha (α) value is 0.6, according to Dasgupta et al. (2017). This study used this benchmark to determine the reliability of the items in each of the constructs of the questionnaire. If α is greater than 0.6, it is concluded that the constructs were reliable. But if α is less than 0.6, it is concluded that the ability to predict scores from one item would not be possible. In terms of accuracy and precision, reliability is analogous to precision, while validity is analogous to accuracy. 2) Validity test The construct validity of an operationalization is the extent to which it really measures (or manipulates) what it claims to measure. When the dimension being measured is an abstract construct that is inferred from directly observable events, then it is referred to as construct validity. Validity indicates the extent of a relationship between a scale and the measure of independent criterion variable (Dikko, 2016). The main purpose for exploring construct validity is to determine whether inferences made about the results of an assessment are meaningful and serve the purpose of the assessment. The relevance of the evidence of validity includes a measure’s reliability, whether it covers the construct of interest, and whether the scores it produces are correlated with other variables expected to be or not to be correlated with and with variables that are conceptually distinct. Looking at the p-value of a construct, if the p-value is less than 0.05 (5% significance level), the construct is then significantly for this item, meaning that the construct is valid. 3) Chi-square test To determine the relationship amongst specific constructs, the focus of this research is on the Chi-Square, as mentioned by Clow and James (2014) and Gravetter et al. (2016). The Chi- square is intended to test how likely an observed distribution is due to chance (Malhotra, 2015), how well the observed distribution of data fits with the distribution that is expected if the variables are independent. Kumar (2019) stipulated that the Chi-square is commonly used for 144 testing relationships between categorical variables in the same population. In order to measure the association between the constructs used in the questionnaire of this study, reliability and validity tests were used to test the consistency of a measure and the extent to which the scores from a measure represent the variables of the constructs in the questionnaire. Chi-square was tested using the Pearson’s Chi-square. Looking at the p-value, if the p-value is less than 0.05 (5% level of significance), then it is concluded that there is a significant association between two variables. 4.8.6.3 Logistic regression analysis (Multivariate) Logistic regression is a statistical method similar to linear regression since logistical regression finds an equation that predicts an outcome for a binary variable, Y from one or more response variables, which can be nominal, ordinal, interval or a ratio-level (Tolles & Meurer, 2016). However, unlike linear regression, the response variables can be categorical or continuous as the model does not strictly require continuous data. The name logistical regression is used when the dependent variable has only two values, such as 0 and 1, or Yes and No. According to Michalaki, Quddus, Pitfield and Huetson (2015), logistic regression competes with discriminant analysis as a method for analysing categorical response variables. Many statisticians feel that logistical regression is more versatile and better suited for modelling most situations than is discriminant analysis. This is because logistical regression does not assume that the independent variables are normally distributed, as discriminant analysis does. The greatest advantage is that continuous explanatory variables can be used and it is easier to handle more than two explanatory variables simultaneously. Although apparently trivial, this last characteristic is essential when interest is expressed in the impact of various explanatory variables on the response variable, which is car insurance purchasing decision-making in this study (DiGangi & Hefner, 2013). A logistical regression is used to obtain a ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. Because chance is a ratio, what will be actually modelled is the logarithm of the chance given by: 𝜋 log ( ) = 𝛽0 + 𝛽1𝑥1 + 𝛽2𝑥2 +⋯ .+𝛽𝑚𝑥 1 − 𝜋 𝑚 Where 𝜋 indicates the probability of an event and 𝛽𝑖 the regression coefficients are associated with the reference group and the 𝑥𝑖 represents the explanatory variables. At this point, an 145 important concept must be highlighted. The reference group represented by 𝛽0, is constituted by those individuals presenting the reference level of each and every variable 𝑥1…𝑚. To predict if the social media promotion mix influence of purchasing decision-making for car insurance, logistic regression uses the log odds ratio rather than probabilities and an iterative maximum likelihood method rather than a least squares to fit the final model (Sperandei, 2014). Logistic regression analysis can also be carried out in SPSS using the NOMREG procedure and a forward stepwise selection procedure is recommended. The results from all these techniques were used to answer the research questions and understand the influence of social media promotion mix on car insurance purchasing of residents in Mahikeng after taking into consideration the ethical aspect of research. 4.9 Ethical considerations According to Flick (2006), in certain countries, codes of ethics have been established and ethical committees have been set up to enforce and monitor the code on a broader scale as an ethical feature of science. The key explanation for this is to safeguard the rights of respondents and avoid the misuse of data from causing scandals. An integral aspect of the study process is informed consent, and the IRB (institutional review board) checks the consent form. In certain situations, such as with surveys, if participants complete the survey, consent can be inferred. Nonetheless, data are exchanged with the participants about the conduct of the research, also as part of the survey instructions. The IRB is responsible for the transparency of all research and for the protection of human subjects and their privacy. Therefore, it is important to obtain ethical approval from the relevant research ethics board before starting a research project. By signing the North West University Code of conduct for researchers and obtaining a Certificate in Research Ethics, a researchers has the right to pursue this research project. Authors are expected to report on the ethical aspects of their analysis in any research. Many readers decide whether a review board approved the study and whether there was participant consent. These two critical topics should be known by readers, but they should also be mindful of other ethical concerns when reading a research paper (Connelly, 2014). In the planning of this study, ethical clearance was sought and granted by the Ethics Committee of the Faculty of Economic and Management Science of the North-West University (ethics certificate number NWU-01407-19-A4 included as Annexure C). Some of the principles which were safeguarded entailed beneficence, respect for human dignity, and anonymity. 146 4.10 Summary This chapter addressed the research methodology and its application in this study. The marketing research process was used as framework for the discussion and implementation of the research method employed in this study. In order to answer the research questions, the positivism research philosophy was adopted and mixed research approach was used as researcher aims to understand through qualitative approach and measure through quantitative approach, the impact of social media promotion mix on car insurance online purchasing decisions. Furthermore, descriptive and causal research designs were used to guide the researcher to reach his goals. The next step of this chapter was the description of the study area to understand his demographic and socio-economic dynamic where the study must be conducted. The next step discussed the sampling design starting with the study population, selecting the sampling frame, selecting the sampling method and finally determining the sample size. Furthermore, the step of data collection procedure was discussed from identifying information type and sources to the data collection method to conduct this study. In addition, the data analysis procedures were presented and statistical techniques such as descriptive analysis, Chi-square and logistic regression used to analyse data collected under strict ethical consideration. 147 CHAPTER FIVE RESULTS AND DISCUSSIONS 5.1 Introduction The research method guiding this study was outlined at length in the previous chapter. This chapter presents and discusses the results which are supplemented by the explanation on how this contributed towards achieving the objectives as outlined in Chapter One. It is necessary to note that when formulating the results section, the results of a study do not prove anything. Only the research question underpinning the research can be verified or denied by the research results. The act of articulating the outcomes, however, allows you to consider the issue from inside, split it into bits, and interpret the research problem from multiple perspectives. In this chapter, to present results more effectively, using non-textual elements, such as figures and tables, is appropriate (Bhatia & Mitra, 2012). You must clearly differentiate information that would usually be included in the study from any raw data or any information that may be included as an appendix in determining what data to describe in your results section. Raw data should not normally be used in the main text of the study. In this chapter, the presentation of the results obtained starts with the univariate test results, which is the descriptive analysis of the demographic characteristics of car owners. This is followed by an elaboration on the bivariate tests results conducted to establish whether there is a relationship between the demographic characteristics of car owners, their social media platform usage, the promotion mix, consumer behaviour, and the purchasing of car insurance by using the Chi-square test. In addition, the chapter presents the multivariate tests using logistic regression to investigate the impact of promotion mix on the car insurance purchasing of residents in Mahikeng. As the chapter concludes with the summary, the layout of this chapter is graphically depicted in Figure 5.1 148 Figure 5.1: Layout of the chapter UNIVARIATE TEST DESCRIPTIVE ANALYSIS BIVARIATE TEST RELIABILITY TEST, VALIDITY TEST CHI-SQUARE MULTIVARIATE TEST LOGISTIC REGRESSION 5.2 Univariate test statistics The simplest form of data analysis is Univariate Analysis. "Uni" means "one," so your data have only one variable, in other words. Univariate analysis does not deal with triggers or relationships (as opposed to regression) and it is primarily intended to describe; take information, summarize the information and find data patterns. Univariate statistics are used to describe the frequencies of demographic characteristics (gender, age and monthly income) used in this study to gather information from car owners residing in Mahikeng. In addition, this section describes car insurance status and practices of respondents. Furthermore, this section describes the frequencies of car owners related to social media usage, social media sites and average time spent online. This section ends firstly, with the description of the demographic characteristics of car owners in relation to the purchase of insurance, secondly the frequencies 149 CHAPTER FIVE: DATA ANALYSIS AND INTERPRETATION of insured and uninsured cars in relation to the purchase decision, and lastly a description of the frequencies of media triggering the intention to purchase insurance in relation to purchasing decision. Additionally, the time spent on social media by the respondents in relation to their decision to purchase car insurance is described. 5.2.1 Demographic characteristics of car owners related to car insurance in Mahikeng This section provides an understanding of the demographic characteristics of car owners in Mahikeng such as gender, age and monthly income. In addition, the demographic and economic characteristics of respondents in relation to their car’s insurance status are discussed. 5.2.1.1 Demographic characteristics of car owners The study of a population based on factors such as age, ethnicity, sex, family status, education level, income and occupation is perceived as demographics characteristics. Demographic data refer to socio-economic statistics expressed statistically, which include employment, education, wages, marriage rates, birth and death rates and other variables. For several reasons, including policy formulation and economic market analysis, states, businesses, and non- government organisations use demographics data to learn more about the characteristics of a population (Ghafoor, 2012). For the purposes of this study, demographic characteristics of respondents discussed are gender, age and income. 150 Table 5.1: Demographic characteristics of car owners Variable Category Frequency Percentage Gender Male 98 49 Female 103 51 Total 201 100.0 Age Up to 20 Years 11 5.5 21 to 40 Years 116 57.7 41 to 60 Years 61 30.3 Above 60 Years 13 6.5 Total 201 100.0 Monthly Income Below R5 000 18 9.0 R5 001 to R10 000 58 28.9 R10 001 to R15 000 75 37.3 Above R15 000 50 24.9 Total 201 100.0 The gender distribution of the respondents in this study is shown in Table 5.1. Results show that the majority of respondents were female (51%), while males represented only 49% of the respondents. However, the number of respondents per gender group is sufficiently equal enough for comparative purposes, as supported by Lama (2020) who found that among the South African, population which is currently 58.93 million, 51% are female while 49% are male. It is interesting to note that the majority of the respondents (5.5+57.7=63.2%) are below the age of 40 years with 57.7% aged between 21 and 40 years and this is in line with the national ENATIS statistics indicating that most car owners in South Africa are under the age of 40 years. This could also be explained as in South Africa, people between the ages of 21 to 40 are most exposed to work and able to buy a car. However, those below 20 years are likely to be unemployed. According to Writer (2019), it is important to remember that the salary information for PayScale is calculated by years of experience, and not directly by age. It may, however, be concluded that since most workers leave university at age 21, experience and age are closely related. However, it cannot be concluded that the results of this study are representative of the number of car owners as this result indicates the distribution of the age group participation. In addition, Table 5.1 further indicates that the majority of the participants (37.3+24.9=62.2%), who are all car owners, earn at least R10 001.00 per month and this is in 151 contrary to the figures of the entire South Africa presented by Credit Suisse Wealth Report cited by Writer (2019 b), indicating that about 50% of the South Africa population earned less than R10 000.00 a month. This is explained by the lack of opportunity in South Africa which acts as a significant barrier to success. The financial constraints preventing the population from saving money and paying off their debt constitute therefore a huge barrier to achieve the aspiration like owning a car. However, the result obtained in the Mahikeng local municipality can be explained by the fact that most of the working class are located in Mahikeng and Mmabatho. 5.2.1.2 Car insurance status and practices of respondents Insurance is a vital service as it can be very expensive to have your car damaged or stolen and not be able to repair it without help. It is a great inconvenience not to repair or replace a damaged or stolen car; which is where car insurance providers come in as they can cover the cost that is priced for the owner of the car. Respondents can start the registration process on social media, and later on receive a coupon via email with the amount to be paid. However, in South Africa, car owners are not legally required to take out car insurance unless the car was purchased with a loan from a bank or other financial institution. Hence, this section aims to know who among respondents had their cars insured or not. And among respondents who did not have their car insured, it was important to understand the reason behind the reluctance. In addition, for those having their car insured, it was necessary to understand the media through which their intention to purchase insurance policy was triggered. The results obtained after the data was statistically analysed yielded the results as indicated in the Table 5.2. 152 Table 5.2: Car insurance status and practices of respondents Variables Category Frequency Percentage Is your vehicle Yes 109 54.2 insured? No 92 45.8 Total 201 100.0 Reason why I would High number of complaints 59 29.4 not take up insurance Lack of trust 53 26.4 Complexity of information 38 18.9 It is expensive 37 18.4 Not interested 14 6.9 Total 201 100.0 Media that triggers my Traditional media (TV, intention to purchase radio, newspaper, flyers 102 50.7 insurance policy etc.) Social media (Facebook, 99 49.3 Twitter etc.) Total 201 100.0 The results in Table 5.2 reflect that 54,2% of the respondents in Mahikeng Local Municipality do have car insurance, while 45.8% of respondents do not have their cars insured. However, it cannot be concluded that the results of this study are representative of the entire South Africa as recent statistics show that about 65 to 70 % of the approximately 12 million vehicles on South Africa roads are uninsured (Middle East Insurance Review, 2020). Among the reason not to purchase insurance policies online, results from Table 5.2 showed that a majority of respondents (29,4 + 26.4 + 18.9 + 18.4 = 93.1) are not willing to purchase insurance because of the high number of complaints, lack of trust, complexity of information and also car insurance is perceived as too expensive while 6.9% of car owners are not interested in purchasing car insurance. This means that the main reason making car owners reluctant to purchase car insurance in Mahikeng Local municipality depends in the majority of cases on insurance companies. This result is in line with those of SA people contributing (2020), as they mentioned that the reason why people do not insure their cars is the absence of knowledge. The aim of the insurance policy is not only to serve a social role or contribute to a more civilized, 153 informed and healthy society, but also to protect the car. The consequences of an eventual accident are not known to people. It is widely believed that misfortunes should not happen to themselves and that saving money means not getting insurance. Although paying for insurance leads to more expenses, being uninsured can be even more expensive. The responsibility for driving then falls on the driver’s own financial resources. Consequently, it is normally too late before they realize their mistake. In addition, results from Table 5.2 show that concerning the media that trigger the intention to purchase insurance policy, the majority of the respondents (50.7%) were triggered by traditional media such as TV, radio and newspaper in order to purchase insurance policies, while about 49.3% of respondents were triggered by social media. According to Clement (2020), 56.3 percent of the South African population are internet users. This share is projected to grow to 62.3 percent in 2025. However, the result of this study is in line with Figures on internet access in Mahikeng shown by a community survey (2016), indicating that 50% of the population have means of internet access in Mahikeng Local municipality with only 6% of internet access by cell phone, 6 % by other mobile services, and only 2% at place of work. 5.2.1.3 Demographic characteristics of respondents in relation to car insurance status In South Africa, there are two major car insurance forms, namely own assurance and third party insurance., The Third-party auto insurance, is the most basic insurance that can be obtained, to pay for the loss of a car for anyone you might have injured (SA People Contributor, 2020), as it covers and accounts for the harm of another person and not their own car. Compared to comprehensive insurance, this entails damage to the car itself and damage to the other individual. It would be your liability to compensate for the loss if you are not covered and you lose a car by colliding with it and it happens to be your fault. The damage could cost you thousands of rand. Even if the car destroyed in an accident is covered, the insurer of that person can do whatever it takes to make you pay for it or the insurance to pay for the loss. Hence, results obtained after data had been statistically analysed yielded the results indicated in Table 5.3. Table 5.3: Demographic characteristics of respondents in relation to car insurance status 154 Is your vehicle insured? Category Yes No Gender Male 55.1% 44.9% Female 53.4% 46.6% Age Up to 20 years 36.4% 63.6% 21 to 40 years 57.8% 42.2% 41 to 60 years 49.2% 50.8% Above 60 years 61.5% 38.5% Monthly Below R5 000 27.8% 72.2% Income(Rand) R5 001 to R10 000 51.7% 48.3% R10 001 to R15 56% 44% 000 Above R15 000 64% 36% Table 5.3 presents the crosstab between gender and car insurance status. The result shows that the majority of respondents (55.1%) who have their car insured are male while 53.4% who are female have their car insured. This result is in line with those of Rajgopaul (2017), who revealed that insurance for South African women has become important now that more women are graduating and more women are making strides in their workplace. This research shows that women are better drivers because they are less likely to commit traffic violations like reckless driving, driving whilst under the influence of alcohol and speeding. Furthermore, Table 5.3 presents the crosstab between age group and car insurance status and results show that most respondents with insured car (61.5%) are aged above 60 years, following by 57.8% which are aged between 21 and 40 years. These results are in line with Fitzpatrick (2020) who found that age is one of the primary factors that push car owners to subscribe to car insurance in South Africa. Thus, once young drivers gain more experience and hit 25, their car insurance costs drop about 30%. Costs continue to generally decline with each birthday. Once drivers reach 50, they'll see their best rates. Around age 60, however, car insurance costs begin to increase and compare to what drivers see in their 40s. Table 5.3 presents the crosstab between income group and car insurance status and result show that most of the respondents (64% and 56%) with insured cars earned above R10 000 monthly as income. This is in line with Bolderdijk, Knockaert, Steg and Verhoef (2011) who revealed 155 that one reason why respondents do not insure their cars is affordability as many South Africans cannot afford adequate vehicle insurance, even third-party only cover. Indeed, it is not only car insurance that South Africans struggle with other types such as personal life are far from many consumers’ minds. 5.2.2 Social media access and usage among cars owners in Mahikeng Social media is a computer-based technology that, through creating virtual networks and communities, enables the exchange of ideas, thoughts and knowledge. Social media, by nature, is internet-based and provides users with rapid electronic content communication. Personal details, records, images, and photographs are included in the material. Users connect via device, tablet or smartphone via web-based software or web application with social media, sometimes using it for messaging (Dollarhide, 2020). This section refers to the social media access and usage, which consist of the preferred social media, frequency of visiting social media and the influence of social media in their purchase decision. 5.2.2.1 Social media usage Social media began as a way for friends and family to communicate, but was later embraced by companies who wanted to take advantage of a common new medium of communication in order to reach consumers. The power of social media is the ability to communicate and exchange data simultaneously with everyone on Earth, or with several people. Social media is an indispensable instrument for corporations. In order to find and connect with consumers, businesses use the network to drive revenue through advertisement and marketing, measure market trends, and provide customer service or assistance. In South Africa, 40% of the population are active social media users. That is 22.89 million people out of an estimated population of over 57 million. However, there are many social media websites used around the world with the most popular as of January 2019 named Facebook (2.27 billion users), YouTube (1.9 billion users), WhatsApp (1.5 billion users), Twitter (1.08 billion users) and Instagram (1 billion users) (Dollarhide, 2020). Therefore, in this study, respondents were requested to indicate the media they use the most often from the list of social media mentioned as indicated in Table 5.4. 156 Results from Table 5.4 show that Facebook, WhatsApp and YouTube were the three (03) most used social media among respondents (32.9+25.9+21.4=80.2%), while Twitter, Instagram and others (Google, Skype, Snapchat, TikTok, Linkedln, etc.) represented only 19.8%. Table 5.4: Social media usage1 Social Media Sites Frequency Percentage (%) Rank Facebook 66 32.9 Rank1 WhatsApp 52 25.9 Rank2 YouTube 43 21.4 Rank3 Twitter 23 11.4 Rank4 Other (Google, Skype, Snapchat, 13 6.4 Rank5 TikTok, etc) Instagram 4 2.0 Rank6 Total 201 100% This results are in line with those of Lama (2020), which indicates that the figures for the most used social media websites in South Africa as of January 2020, are WhatsApp (about 89% users), YouTube (about 87% users), Facebook (83% users), Instagram (about 61% users) and Twitter (about 44% users). 5.2.2.2 Frequency of logging into social media sites According to the Pew Research Centre (2019), the role of social media in helping companies is substantial. Social media enables consumer communication, allowing social connections to be melded on e-commerce sites. Its ability to gather data allows one to concentrate on marketing efforts and market analysis. It helps to advertise goods and services, as it allows potential buyers to distribute targeted, timely, and exclusive deals and coupons. Social networking can also help create relationships with consumers through loyalty programmes. Hence, the respondents were requested to indicate their frequency of logging into social media sites. 157 Figure 5.2: Frequency of login into social media sites Four different frequencies were identified in order to know the frequency by which respondents in Mahikeng use social media sites. Results from Figure 5.2 specify that the majority of respondents (49.3%) expresses a strong interest to social media sites almost every day, whereas 17.9% of respondents log into sites four to five times a week while 14.4% of respondents log in two to three times a week. In addition, results show that 18.4% respondents present a lack of interest on social media sites as they visit it once a week. These results are in line with those of Per Research Centre (2019), who revealed that, for many users, social media is part of their daily routine. However, roughly three-quarters of Facebook users and around six in ten Instagram users visit these sites at least once a day. 5.2.2.3 Average time spend on social media sites As stated earlier, social media is an inseparable part of our everyday lives. It is always there, from the moment we wake up until we fall asleep with our phone in hand. Hence, this study judged it important to ask respondents how much time they spent on social media. Results obtained after data were statistically analysed yielded the results as indicated in Table 5.5. 158 Table 5.5: Average time spent on social media sites per day Average time spent on social media sites per day Frequency Percentage (%) More than 2 Hours 79 39.3% 2 Hours 44 21.9% 1 Hours 36 17.9% 30 Minutes 42 20.9% Total 201 100 As presented in Table 5.5, the average time spent per day on social media sites has been studied in four different time slots. Results show that the majority of respondents (39.3+21.9 = 61.2%) spend at least two hours on social media on a daily basis. This result is in line with that of Media Update (2019) who revealed that the average time South Africans spend on social media per day is 2 hours 48 minutes, which is above the global average of 2 hours 16 minutes. This implies that South African companies can use social media to market their products as 40% of people in South Africa join social media to stay up to date with current events and news. 5.2.3 Demographic and economic variables in relation to insurance purchasing decisions This section describes the demographic characteristics, economics characteristics, social media access and usage among car owners in Mahikeng in relation to their purchasing decision on car insurance. 5.2.3.1 Gender and insurance purchasing decision In selecting the insurance type of their car in terms of class, design, and needs, women and men have a distinct buying behaviour. Hence, it was necessary to crosstab gender and their purchasing decision on car insurance. Results obtained after data had been statistically analysed yielded the results as indicated in Figure 5.2. 159 Figure 5.3: Gender and purchasing decision Figure 5.3 describes the variable gender in relation to car insurance purchasing decisions and results show that among respondents, most female (60.2%) purchase car insurance online while 57.1% of males are willing to purchase car insurance online. However, results show that, 42.9% of male and 39.8% of female were not willing to purchase car insurance using social media. This result is in line with Wheels24 (2019) who revealed that despite the myths surrounding women and car insurance, some believe that it is definitely untrue that women are worse drivers than men and submit more claims for accident damage. However, in South Africa, women have become far more independent as drivers over the past few decades, and they certainly play a far bigger role in purchasing vehicles and more cautious when driving and are less likely to cause a crash. 5.2.3.2 Age group and purchasing decision It may not seem fair, but age is the biggest factor while deciding on your car insurance rates. Statistics show that certain age groups are more likely to get into accidents, or have moving violations. Thus, the researcher crosstabbed the variables age and purchasing decision to find out which age rate is willing to subscribe to car insurance, results obtained after statistical analysis of the data produced the results as shown in Figure 5.3. 160 Figure 5.4: Age group and purchasing decision Figure 5.4 describes the variable age in relation to car insurance purchasing decisions. Results show that the majority of respondents that purchase car insurance are aged from 18 to 40 years (72.7% and 57.8%) and above the age of 60 years (69.2%). These results are contrary to those of Gusner (2012) who revealed that clients are in the sweet spot for the best car insurance rates from most companies if you're between the ages of 40 and 60. This is explained by the fact that generally, these drivers have settled down, have a family and drive responsibly and are accountable for their finances. In addition, due to inexperience, young drivers are more likely to be involved in accidents. Adolescents are more careless than adults, and they have far higher incidences resulting in death. Furthermore, after 60 years, car insurance premiums begin to rise slowly from that point forward. It does not mean that older drivers are more reckless, but rather their driving is affected by physical changes related to age. 5.2.3.3 Monthly income and purchasing decision Among the reasons people avoid buying car insurance in South Africa, we have the affordability of car insurance. In fact just about 35% of all cars are insured in South Africa. Most South Africans cannot afford to insure their cars. In addition, one of the most important factors to consider when purchasing a new car insurance policy is the surplus cost of insurance. Low insurance rates might also mean a high insurance excess cost and if you do not make an informed decision at the outset of your policy, you could be in for a nasty surprise if you're 161 ever in a car accident (Mokhothu, 2020). To avoid a potential catastrophe on car finance repayment in South Africa, financial specialists recommend that no more than 20% of monthly take home pay should be used towards car expenses (Corke, Martin, 2020).Thus, the researcher crosstabs monthly income group and car insurance purchasing decisions in order to identify which income group among respondents purchased more car insurance. After data had been statistically analysed, results obtained are displayed in Figure 5.4. Figure 5.5: Monthly income and purchasing decision Figure 5.5 describes the variable monthly salary in relation to car insurance purchasing decision. Results show that among respondents, most respondents (68%) who intended to purchase car insurance online were earning above R15 000, whereas most respondents who were not intended to purchase car insurance online (50.7%) were earning a salary between R10 000 to R150 000. These results are in line with Luckhoff (2018) who revealed that as car insurance is compulsory when buying through a loan, the minimum monthly income required to buy a cheap car in South Africa is between R16 000 and R18 265 looking at the three cheapest cars available currently in South Africa to see what a client needs to earn in order to be able to afford them, based at no deposit, no balloon, a 60-month term with a 12% interest rate. 5.2.3.4 Vehicle insured and online purchasing Social media offers insurance firms with an ability to better understand their target audience, which is vital when it comes to producing compelling and quality content (Nicholson, 2020). 162 Social media for insurance companies is both rewarding and challenging. However, social media has become crucial to the insurance business and the rewards insurance agencies are reaping on social media outweigh the challenges. Hence, car insurance companies should take a practical approach to social media to ensure compliance, avoid pitfalls and enjoy the benefits. That is why the researcher is interested in knowing the number of respondents who used online purchasing for their car insurance. Data statistically analysed produced the results as indicated in Figure 5.6. Figure 5.6: Vehicle insured and online purchasing Figure 5.6 describes the variable vehicle insured in relation to car insurance purchasing decision. Results show that most respondents (61.5%) whose cars were insured purchased their insurance online through the influence of social media. This is contrary to the trends of online search in South Africa where the purchase decision has a low percentage when compared with the rest of the world with ± 50%. While it is no wonder that social media has managed to change virtually every aspect of modern life. As more insurance companies utilize social media to introduce and promote their services, the effects that such a strategy will have on the car insurance business in the long run are still unknown as many car insurance companies utilise social media channels to obtain information that customers are not willing to share on social media (The Digital Age, 2018). Thus social media posts might directly increase the visibility of the services. For the consumers, one of the key benefits of using social media is being able to access different kinds of online information with direct user feedback and participation. Such 163 honesty and familiarity provide the investigator with very accurate and relevant information, and many businesses are taking advantage of this fact. In addition, results from Figure 5.6 show that 38.5% of vehicles that were insured did not purchase car insurance through the influence of social media. This can be explained by the lack of trust to share their personal information online. According to Bahney (2018), increasingly websites that provide car insurance quotes or price reviews, often without consumer permission, will snag the comprehensive personal data provided and send it to insurance companies, brokers or industry organisations. 5.2.3.5 Media that triggered the intention to purchase insurance and purchasing decision The previous unpenetrated rural insurance sector in Africa now has access to mobile devices, allowing insurers to communicate with them directly. Where intermediate channels have historically been seen as costly, cheaper access is provided by direct channels. Technology, especially mobile phones and social media, are seen as the key enablers to increase access to new consumers, to analyse behavioural data at reduced costs and to design new, more suitable goods (Muguto, 2018). Thus, it was important to crosstab media that trigger the intention to purchase insurance and purchasing decisions (results obtained after data had been statistically analysed and presented in Figure 5.7). Figure 5.7: Media triggers your intention to purchase insurance and purchasing decision 164 Figure 5.7 describes the variable media triggers your intention to purchase insurance in relation to car insurance purchasing decision. Results show that 59.6% of car owners using social media (Facebook, twitter, etc.) were likely to purchase car insurance online while 57.8% of car owners using traditional media (TV, Radio, etc.) were likely to purchase car insurance online. On the other hand, results show that 42.2% of car owners using traditional media were not likely to purchase car insurance online whereas about 40.4% of car owners using social media were not likely to purchase car insurance online. This result is in line with Auto General (2016), who found that it is important for any company to have an online presence. Consumers expect insurance company to be online as well. They do not only rely on social media to provide information; as the demand for service across these channels has also increased. For a very low cost, insurance company can expect an increase in their business by referrals and several cross- selling opportunities. If car insurance companies are successful in their social media business pursuits, they could protect the loyalty of consumers, increase income, and offer a place in this very competitive industry. 5.2.3.6 Number of times respondents access social media and purchasing decision South Africa’s social media activity is also one of the fastest growing in the world, where the country ranked 17th for its relative growth (seeing a 28% increase in activity year-on-year) and tied for 9th for net growth, having added 5 million new users since January 2018 (Writer, 2019c). The more consumers visit social media, the more they have the chance to view car insurance companies’ post which must be at 1 or 2 per day to be sure to be seen. Thus, the researcher crosstabled the number of times respondents access social media and car insurance purchasing decision in order to know how much time the majority of respondents spent on social media. Results obtained after analysing the data yielded a bar chart as indicated in Figure 5.8. 165 Figure 5.8: Number of times respondent accesses social media and purchasing decision Figure 5.8 describes the variable number of times the respondent accesses social media in relation to car insurance purchasing decisions. Results show that most respondents (62.1%) intended to purchase car insurance online by accessing social media 2 to 3 times a week while 59.6% of car owners that intend to purchase car insurance online access social media almost every day. In addition, 56.8% of car owners who intend to purchase car insurance online access social media once a week, whereas 55.6% of respondents who intend to purchase car insurance online access social media 4 to 5 times a week. Every social media platform has its own peak time when posts get more engagement. According to Williams (2020), consumers who connect more often with brands on social media are likely to purchase and be loyal customers, with about nine out of 10 people saying they buy from companies they follow on social networks. 5.2.3.7 Time spent on social media and purchasing decision South Africans spend more time using social media platforms (2 hours and 48 minutes) than the global average, which is an opportunity for car insurance to increase their visibility and sales. Thus, the researcher tried to discover how much time most respondents purchasing car insurance spent on social media. After data had been statistically analysed, results obtained are presented in Figure 5.9. 166 Figure 5.9: Time spent on social media and purchasing decisions Figure 5.9 describes the variable time spent on social media in relation to car insurance purchasing decisions. Results show that most car owners (66.7%) spending an hour on social media intended to purchase car insurance online. In addition, results show that 60.8% of car owners who spent more than 2 hours per day on social media were willing to purchase car insurance online. Also, results show that 59.1% of respondent spending 2 hours on social media were willing to purchase car insurance online. Also, only 47.6% of respondents spending 30 minutes on social media were willing to purchase car insurance online. The influence of social media is not something that company owners can afford to ignore. Consumers who spend more time on social media during their shopping processes are four times more likely to spend more on purchases than those who do not, the Deloitte report noted (Roesler, 2015). Even deeper it goes. The study reports that by using social media to help shop before or during a trip to the supermarket, shoppers are 29 percent more likely to make a purchase on the same day. The results from the above section dealt with the univariate analysis involving the analysis of a single variable on respondents and their car insurance status in order to describe the demographic and economic characteristics of respondents in relation to their car insurance status, to describe the respondents’ social media usage, and finally the demographic and economic description of respondents in relation to their car insurance purchasing decisions. However, while the previous section focused on univariate, it does not deal with causes or relationships (unlike regression). Thus, the next section presents the results from the bivariate analysis in order to determine the empirical relationship between two variables. 167 5.3 Bivariate test (Chi-square) Bivariate analysis is the simultaneous analysis of two variables (attributes). It explores the concept of a relationship between two variables, whether there is an association and the strength of that association, or whether there are differences between two variables and the significance of those differences (Vergni, Todisco, Di Lena & Mannocchi, 2020; Brunner, Sikorska & Seibert, 2018; Aguiar‐Conraria & Soares, 2014). In bivariate analysis, the Chi-square test is used to test for a statistically significant relationship between nominal and ordinal variables (Sharpe, 2015). In this study, the researcher used Chi-square to determine wheher there is a significant association between variables identified. Hence, this section tests first the association between the demographic, economic and socio-media usage and purchasing decision using Chi-Square. Secondly, this section determines the relationship between social media usage, social media promotion mix, consumer behaviour and online purchasing decisions using reliability, validity tests before conducting the Chi-square as all these variables are determined by many constructs each under 5 Likert-square. 5.3.1 Association between the demographic, economic variables and online purchasing decisions The null hypothesis of the Chi-square test is that no relationship exists on the categorical variables in the population; they are independent. As stated in Chapter four, the null hypothesis is rejected if the p-value is less than 0.05 (5% level of significance), then it is concluded that there is a significant association between two variables. Table 5.6: Association between the demographic, socio-economic and social media usage and online purchasing decision Test Variables Pearson's df p-value Chi-Square Gender * Online Purchasing Decision .193 1 .661 Age * Online Purchasing Decision 1.751 3 .626 Monthly Income (Rands) * Online Purchasing Decision 4.813 3 .186 Is your vehicle insured? * Online Purchasing Decision .749 1 .387 Reason why I would not take up insurance * Online 8.733 4 .068 Purchasing Decision 168 Media that triggers my intention to purchase insurance .064 1 .801 policy * Online Purchasing Decision Which of these social media sites do you use regularly? * 5.368 5 .373 Online Purchasing Decision How often do you access your social media sites? * .373 3 .946 Online Purchasing Decision Results from Table 5.6 show that the Chi-square of gender associated with purchasing online decision was 0.193 with a probability value of 0.661. The Chi-square of age associated with online purchasing decision was 1.751 with a probability value of 0.626. The Chi-square of monthly income associated with online purchasing decision was 4.813 with a probability value of 0.186. The Chi-square of whether the vehicle is insured associated with the online purchasing decision was 0.749 with a probability value of 0.387. The Chi-square of the reason why a respondent would not take up insurance associated with online purchasing decisions was 8.733 with a probability value of 0.068. The Chi-square of media that triggers the intention to purchase an insurance policy associated with online purchasing decision was 0.064 with a probability value of 0.801. In addition, the Chi-square which of the social media sites used regularly associated with online purchasing decision was 5.368 with a probability value of 0.373. The Chi-square on how often respondent access social media sites associated with online purchasing decision was 0.373 with a probability value of 0.946. From the results, all the p-values of the Chi-square test of association for all pairs of variables in the Table 5.6 are insignificant at the 5% level of significance (p-values > 0.05) and this implies that there is no significant association between each of the variables and online purchasing decisions except the variable ‘reason why not to take up insurance’ which is significant at a 10% level of significance as their p-value is less than 10%. This means that the reason why not taking car insurance should be seriously taken as priorities in order to increase car insurance sales. This implies that car insurance companies most improve their services and their marketing strategies in order to reduce the number of complaints, create awareness among customers and simplify the ways to inform, reduce prices and working toward improving confidence among customers. 169 5.3.2 Association between social media usage, social promotion mix, consumer behaviour and online purchasing decisions This is done through the reliability and validity test of all the constructs of social media usage, social promotion mix and consumer behaviour. This is followed by the test of their association with online purchasing decision using Chi-square. 5.3.2.1 Social media usage In order to determine the relationship between social media usage and car insurance online purchasing decisions, the study first discusses the statistical methods such as reliability and validity in order to check agreement among or between constructs. 1) Reliability test for social media usage To assess the extent to which a given construct of the social media usage is reliable, the researcher must have a number of social media usage characterized by more than one construct. If agreement between the constructs is strong, then it is said that the process is accurate, but this is by no means a guarantee that the ratings actually represent the dimension they are meant to reflect, i.e. that they are valid. If, on the other hand, the agreement between the constructs is low, the value of the ratings is severely limited (Drost, 2011). Results from Table 5.7 below show a Cronbach’s of 0.632. The Cronbach’s Alpha can be improved by deleting variables with negative corrected item-total correlation, and this approach was used in this study, where necessary. The Table 5.6 shows that the three constructs remaining in the Social Media Usage in Relation to Insurance scale have a Cronbach’s Alpha which is greater than 0.6, therefore the construct is reliable. Table 5.7: Reliability test of social media usage Reliability Statistics1 Cronbach's Alpha Number of Items .632 3 2) Validity test for social media usage 1SMP_7 was excluded from the scale due to a negative corrected-item total correction 170 Validity is the extent to which the scores from a measure represent the variable they are intended to. It is vital for a test to be valid in order for the results to be accurately applied and interpreted. This study used construct validity to ensure that the method of measurement matches the construct SMP_4, SMP_5, SMP_6 we want to measure as SMP_1, SMP_2 and SMP_3 were not a 5 Likert scale questions. Looking at the p-value of a construct, if the p-value is less than 0.05 (5% significance level), the construct is then significant for this item, meaning that the construct is valid. Table 5.8: Validity test of social media usage Social Media Usage in Relation to Insurance Estimate Std.Err z-value P-Value SMP_4 0.673 0.111 6.061 0.000 SMP_5 0.945 0.130 7.244 0.000 SMP_6 0.654 0.106 6.191 0.000 Table 5.8 above shows the validity test. Results show that all p-values in the table above are less than 0.05, therefore all three constructs in the item Social Media Usage in Relation to Insurance are valid, and none of them should be excluded from the item social media usage. 5.3.2.2 Social media promotion mix and consumer behaviour In order to determine the relationship between social media promotion mix, consumer behaviour and car insurance online purchasing decision, the study discusses first the statistical methods such as reliability and validity in order to check agreement among or between constructs. 1) Reliability test of social media promotion mix and consumer behaviour We need to provide a number of social media usage defined by more than one construct to determine the degree to which a given social media usage construct is accurate. If there is a clear consensus between the constructs, then the method is claimed to be specific, but this is by no means a guarantee that the ratings genuinely represent the dimension they are supposed to portray, i.e. that they are accurate. 171 Table 5.9: Reliability test of social media promotion mix and consumer behaviour Reliability Statistics Cronbach's Alpha Number of Items Perceived usefulness .60 3 Perceived behavioural control .643 5 Social influence .5992 2 Attitude .610 3 Perceived security .60 3 Service quality .60 4 Perceived trust .641 4 Perceived tangibility .675 4 Social media promotion mix .661 6 According to Dasgupta et al (2017), the lowest acceptable Cronbach’s Alpha value is 0.6; therefore this study used this benchmark to determine the reliability of the items in each of the constructs of the questionnaire. The Table 5.9 shows that each construct of the Social Media Promotion Mix and Consumer Behaviour has Cronbach’s Alpha with at least 0.6, therefore, we can conclude that each of these constructs representing the theme perceived usefulness, perceived behavioural control, social media promotion mix, etc. are reliable. 2) Validity test of social media promotion mix and consumer behaviour Validity is the extent to which the scores from a measure represent the variable they are intended to. It is vital for a test to be valid in order for the results to be accurately applied and interpreted. Looking at the p-value of a construct, if the p-value is less than 0.05 (5% significance level), the construct is then significant for this item, meaning that the construct is valid. Results of the validity test of constructs perceived usefulness, perceived behavioural control, social influence, attitude, perceived security, service quality, perceived trust, perceived trust and social media promotion mix is presented in Table 5.10. 172 Table 5.10: Validity test of social media promotion mix and consumer behaviour Perceived usefulness Estimate Std.Err z-value P-Value PU 1 0.676 0.095 7.088 0.000 PU 2 0.700 0.094 7.461 0.000 PU 3 0.729 0.092 7.922 0.000 Perceived behavioural control PBC 1 0.647 0.106 6.121 0.000 PBC 2 0.813 0.095 8.592 0.000 PBC 3 0.620 0.091 6.797 0.000 PBC 4 0.735 0.089 8.260 0.000 PBC 5 0.634 0.103 6.166 0.000 Social influence SI 1 0.614 0.101 6.059 0.000 SI 2 0.709 0.112 6.339 0.000 Attitude A1 0.648 0.097 6.708 0.000 A2 0.782 0.087 8.960 0.000 A3 0.733 0.094 7.831 0.000 Perceived security PS 1 0.641 0.100 6.384 0.000 PS 2 0.742 0.100 7.437 0.000 PS 3 0.784 0.090 8.736 0.000 Service quality SQ 1 0.733 0.092 7.957 0.000 SQ 2 0.691 0.100 6.916 0.000 SQ 3 0.684 0.092 7.397 0.000 SQ 4 0.535 0.084 6.399 0.000 Perceived trust PT 1 0.734 0.089 8.287 0.000 PT 2 0.567 0.093 6.098 0.000 PT 3 0.677 0.089 7.626 0.000 PT 4 0.693 0.086 8.022 0.000 173 Perceived tangibility PTA 1 0.646 0.086 7.542 0.000 PTA 2 0.689 0.084 8.184 0.000 PTA 3 0.673 0.081 8.331 0.000 PTA 4 0.789 0.083 9.465 0.000 Social media promotion mix PMX 1 0.322 0.094 3.411 0.001 PMX 2 0.620 0.091 6.836 0.000 PMX 3 0.738 0.088 8.353 0.000 PMX 4 0.762 0.084 9.069 0.000 PMX 5 0.610 0.089 6.822 0.000 PMX 6 0.659 0.085 7.710 0.000 SI_3 was excluded from the Social Influence construct due to negative corrected item-total correlation. Table 5.10 presents the validity test of social media promotion mix and consumer behaviour constructs. Results show that all p-values in this table representing the constructs of different themes (variables) are less than 0.05, therefore, the study concludes that all the constructs under each items of the Social Media Promotion Mix and Consumer Behaviour significantly belong to their respective items and none of the constructs should be excluded from the items. 5.3.2.3 Relationships between online purchasing decision-making and the constructs (Chi-square) The null hypothesis of the Chi-square test is that no relationship exists on the categorical variables in the population; they are independent. As stated in Chapter four, the null hypothesis is rejected if the p-value is less than 0.05 (5% level of significance), then it is concluded that there is significant association between two variables. Table 5.11 presents result of the relationship between online purchasing decision and variables such as social media usage, promotion mix and consumer behaviour elements. 174 Table 5.11: Relationships between online purchasing decisions and the other variables Testing Variables Pearson df P- Chi- Value Square Social Media Usage in Relation to Insurance * Online Purchasing 8.772 4 .067 Decision Perceived Usefulness * Online Purchasing Decision 1.257 4 .869 Attitude * Online Purchasing Decision 10.484*3 4 .033 Service Quality * Online Purchasing Decision 14.967* 4 .005 Perceived Trust * Online Purchasing Decision 10.660* 4 .031 Perceived Tangibility * Online Purchasing Decision 4.002 4 .406 Social Promotional Mix * Online Purchasing Decision 18.426* 4 .001 Results show that the p-value of the Chi-square test of association between Attitude (3 constructs) and Online Purchasing Decision is less than 0.05 (p-value < 5%), meaning that the variable attitude is significant at 5% level of significance. Therefore, the study concludes that variables’ attitude is significantly associated with online purchasing decisions. The result is in line with those of Warayuanti and Suyanto (2015) who found that attitudes of consumers have an influence on purchasing decision via online shopping. In addition, results show that the p- value of the chi-square test of association between of Service Quality (4 constructs) and Online Purchasing Decision is less than 0.05 (p-value < 5%), meaning that service quality is significant at the 5% level of significance. Therefore, the study concludes that the variable service quality is significantly associated with online purchasing decision. This result is supported by Arslan and Zaman (2015), who studied the impact of service quality on consumer purchase intention and their results revealed that most consumers’ purchasing decisions depend on service quality. Furthermore, results show that the p-value of the Chi-square test of association between perceived Trust (4 constructs) and Online Purchasing Decision is less than 0.05 (P-value < 5%), meaning that the variable perceived trust is significant at the 5% level of significance. Therefore, the study concludes that the variable perceived trust is significantly associated with online purchasing decisions. This result is supported by Kim, Xu and Gupta (2012) who 3 * Significant at 5% 175 revealed that perceived trust exerted a stronger effect than perceived price on purchase intentions for both potential and repeat customers of an online store. Results from Table 5.11 show that the p-value of the Chi-square test of association between social media Promotional Mix (6 constructs) and Online Purchasing Decision is less than 0.05 (p-value < 5%), meaning that this variable is significant at the 5% level of significance. Therefore, the study concludes that attitude, service quality, perceived trust and social media promotion mix are significantly associated with online purchasing decision. This result is supported by Bashar, Ahmad and Wasiq (2012) who revealed that the social media promotion mix helps consumers in their purchase decision-making of mobile service. While bivariate analysis was used in this section to find out if there is a relationship between two different variables, the next section applied multivariate tests to analyse the relationship between three or more variables. 1.4 Multivariate test (Stepwise logistic regression test) Multivariate analysis examines several variables to see if one or more of them are predictive of a certain outcome. The predictive variables are independent variables and the outcome is the dependent variable. The variables can be continuous, meaning that they can have a set of values, or they can be dichotomous, meaning that the answer to a yes or no query is interpreted. Multiple regression analysis is the most common method used in the multiple analysis to find correlations between variables. However, because the outcome of this study is online purchasing decisions, which are dichotomous, this section presents the stepwise logistic regression test in order to investigate the impact of social media promotion mix on online purchasing decision of cars insurance in Mahikeng. This process begins with the omnibus test and the results are presented in Table 5.12. Results from Table 5.12 show that the p-value of the omnibus test is significant at the 5% level of significance indicating that the logistical regression is significant overall. 176 Table 5.12: Omnibus test Omnibus Tests of Model Coefficients Chi-square df P-value Model 27.499 4 .000 Furthermore, results from Table 5.13 revealed that the model explains about 12.8% to 17.2% of the total variation in the likelihood of purchasing insurance online. Since the explainable variation is less than 75%, it is not sufficient and this is only a challenge if the model is to be used for allocating unknown subjects to either purchasing online or not. However, this does not defy the other purpose of logistic regression which is to identify significant variables that impact online car insurance purchasing decisions, especially that the overall model is significant. Table 5.13: Model summary Model Summary Cox & Snell R Square Nagelkerke R Square .128 .172 Table 5.14 presents the results from the Hosmer and Lemeshow test and it revealed that the p- value of the Hosmer and Lemeshow test is greater than 97%, which implies that the model fits the data well (it doesn’t under- or over-fit the data). Table 5.14: Hosmer and Lemeshow test Hosmer and Lemeshow Test Chi-square Df p-value .248 3 .970 Finally, Table 5.15 shows the variables that were retained in the model by the stepwise regression model. These are the variables which are significant in determining the likelihood of purchasing insurance online. The coefficients in the results are the values for the Logistic regression equation for predicting the dependent variable from the independent variable and are in log-odds units. All these variables increase the odds of purchasing insurance online and all the parameter estimates (B) are positive. 177 Table 5.15: Logistic regression Variables in the Equation B S.E. Wald df p-vale Exp(B) Service_Quality_Agree 1.167 .406 8.267 1 .004 3.212 Social_Promo_Mix_Agre 1.153 .474 5.911 1 .015 3.167 e Monthly_Income3_R100 .643 .325 3.923 1 .048 1.902 01_to_R15 000 I_spend_30_minutes_usi .897 .382 5.519 1 .019 2.451 ng_social_media Constant -2.683 .670 16.036 1 .000 .068 Results from Table 5.15 revealed that service quality_ agree (where respondents agree on all constructs of service quality) has an odds ratio of 1.167 with a p-value of 0.004 which is less than 5%, meaning that if service quality increases by one unit, online purchasing decisions of car insurance will likely increase by 1.167. Despite that, the result is in line with Arslan and Zaman (2015), which is also supported by Srivastava and Sharma (2013) who indicated an indirect effect of service quality on switching behaviour via customer satisfaction and repurchase intention. In addition, Kitapci, Akdogan and Dortyol (2014) revealed that through empathy and assurance which are positively related to customer satisfaction, customer satisfaction has a significant effect on word of mouth and repurchasing intention which were found to be highly related. This implies that service quality should be improved by insurance companies in order to satisfy customers and expect a repurchasing intention. The results from Table 5.15 also revealed that the odds ratio of social promotion Mix_Agree (where respondents agree on all constructs of social media promotion mix) was 1.153 with a p-value of 0.015 which is less than 5%, meaning that social media promotion Mix has a positive significant effect on car insurance online purchasing decisions. If more effort is put in 1% on the social media promotion Mix, the online purchase decision of car insurance will likely increase by 1.153. This result is in line with those of Saravanakumar and Sugantha Lakshmi (2012) who revealed that marketers today see social media as a perfect chance to raise market 178 share figures. Marketers are only too pleased to see the social web as a new collection of platforms from which their products or services can be promoted. Social media marketing mix makes it possible for businesses to create a contact channel with their customers, advertise their products, improve customer purchasing decision through sales, and then develop brand equity as enjoyment which are the key determinant of social media networks usage as tool for supporting the purchasing decision (Di Pietro & Pantano, 2012). Furthermore, improved customer loyalty and customer repurchasing decision are obtained in this way. However, since it is a two-way channel, this contact takes effort and care to handle. Disgruntled customers may complain loudly, and easily reach potential customers and thereby harm the reputation of the company. The result in Table 5.15 revealed that the odds ratio of monthly income 3_R1 0001 _to _R15 000 (monthly income ranging between R10 001 to R15 000) was 0.643 and was statistically significant at 5% level as p-value was 0.048 <5%. Thus the monthly income ranging between R10 001 to R15 000 has a significant influence on car insurance online purchasing decisions. This is an indication that there will be an increase by 0.643 in online purchasing decision of car insurance if monthly income increases by one rand keeping the range between R10 001 to R15 000. According to Prime Meridian Direct (PMD) (2019), in South Africa, car owners are not allowed legally to take out car insurance unless the car has been bought with a loan from a bank or other financial institution. Thus, this result is supported by Nkanjeni (2019) who revealed that customers must earn at least between R10 000 and R15 000 in order to purchase a car costing around R99, 900 for a new car in 2019 and not spend more than 20% of their gross monthly income on a car. The results in Table 5.14 show that spending 30 minutes per day using social media has an odds-on ratio of 0.897 and significantly related to car insurance online purchasing decision at 5% as it has a p-value of 0.019 which is less than 5%. Thus, spending 30 minutes per day on social media influences the decision to purchase car insurance online. The odds ratio of the variable spending 30 minutes per day on social media was 0.0897, and this is an indication that for every increase by one minute from the 30 minutes per day on social media, a 0.897 increase is expected on the online purchasing decision of car insurance. This study is in line with those of Harridge-March and Quinton (2009) who revealed that social marketing technologies also permit marketers to customise their messages and have a dialogue with customers. This means 179 the more time customers spend on social media, the more likely they view post or adverts as social media connects company directly to customers. 5.5 Summary This Chapter focused on the use of various means of statistical analysis set up to achieve the empirical objectives of the study which was to investigate the influence of the social media promotion mix on car insurance purchasing decision of resident in Mahikeng local municipality. The first statistical analysis used descriptive analysis and cross-tabulation to describe the demographic characteristic of respondents, describe the social media access and usage among respondents and finally describe the demographic and economic variables in relation to car insurance purchase decision. Results on demographic characteristics of respondents revealed that most respondents were female (51%), aged below 20 years and 40 years who earned at least R10 000. Furthermore results show that most of the respondents (54.2%) have their cars insured. Among those whose cars were insured, the majority (50.7%) were motivated by traditional media. However, among those who did not subscribe for car insurance, the reasons were because of a high number of complaints, lack of trust, affordability and complexity of information. In addition, results from the demographic characteristic of respondents in relation to car insurance status show that the majority of respondents (55.1%) who have their cars insured were male. The majority which car is insured are aged above 60 years and between 21 to 40 years. The majority of respondents with insured cars earned a monthly salary above R10 000. Regarding the description of social media access and usage among respondents, Facebook, WhatsApp and YouTube were the most social media among respondents. The majority of respondents (49.3%) expressed a strong interest in social media by getting online almost every day. In addition the majority of respondents (61.2%) spend at least 2 hours on social media on daily basis. Looking at the demographic and economic variables in relation to purchasing decisions, the results show that the majority of respondents who purchased car insurance online were females (60.2%), aged between 18 and 40 years and above 60 years, and earned above R15 000. In addition, most respondents whose cars were insured purchased online insurance through social media. Most of the respondents (59.6%) using social media were likely to purchase car insurance online. Results also show that most respondents (62.1%) who intended to purchase car insurance online access social media 2 to 3 times a week, the majority of 180 respondents (66.7%) spending an hour on social media intended to purchase car insurance online. The second set of models was set up to use bivariate analysis (chi-square) to test the relationship between two variables. First, the study tests the relationship between the demographic and economic variables and online purchasing decisions. Results revealed that individually, gender, income, been insured or not, reasons that motivate car owners to purchase insurance, the type of social media used, and how often car owners access social media are not significantly related to the purchase decision of car insurance online; except for the variable ‘reason why not to take up insurance’ which correlated to online purchasing decision as it is significant at a 10% level of significance (p-value is less than 10%). Secondly, after checking for the reliability and validity of constructs, a Chi-square test was used to test the significant relationship between construct and online purchasing decisions. Results show that attitude, service quality, perceived trust and social media promotion mix are significantly associated with online purchasing decisions. The last set of statistical analysis named logistic regression was employed to investigate the effect of two or more variables (independent variables) on outcome namely online purchasing decisions which are dichotomous (Yes or no). Results show that service quality, social media promotion mix, monthly income ranging between R10 000 to R15 000, and spending at least 30 minutes per day on social media significantly influenced the purchase decision of car insurance online. In the next Chapter, the study will conclude by giving a summary and conclusions as well as the recommendations arising from it. 181 CHAPTER SIX CONCLUSIONS AND RECOMMENDATIONS 6.1 Introduction The main purpose of this study was to investigate the impact of the social media promotion mix on car insurance purchasing decision-making in Mahikeng. This chapter summarises what has been done in this study and based on the results, policies and recommendations are suggested in order to address the research gaps which were identified. This chapter commences with revisiting the motivation and objective of the study and this is followed by a summary of the marketing and integrated marketing communication mix in South Africa. Thereafter follows a review of social media and consumer behaviour related to car insurance in South Africa. This is followed by a review of the research methodology, the findings of the study, and then the recommendations. 6.2 Motivation and objectives of the study Given the fact that car insurance is not compulsory in South Africa, a large part of the population is lax about insurance, especially amongst the black community. In addition, SAIA (2017) revealed that in South Africa, only 35% of vehicles are insured. Thus, South African insurance companies are facing intense competition such as convincing consumers to subscribe to an insurance policy, and also to retain those who are already their costumers as the rate of cancellation is a concern. Fin24 (2017) indicated that the number of uninsured vehicles on South Africa's roads continues to increase, as it is the case in 2017 where the number of uninsured vehicles rose from ten to twelve million (70%) in 2018. Several authors have drawn a conclusion from these findings by assuming that: cars on the South African roads are uninsured due to the excessive rate of premium policies; car owners think insurance is unnecessary as they never get involved in an accident; and finally, consumers do not trust the providers (Aglionby, 2016; Bowen, 2019; Prime Meridian Direct, 2018). The use of social media would be extremely beneficial to educate consumers, for generating competitive intelligence, and cause the creation of networks through which messages can be aimed at consumers. Hence, it is important for an insurance company to integrate the social media promotion mix in their marketing, as well as interacting with consumers in order to 182 create awareness. Therefore, the aim of this study was to investigate the impact of the social media promotion mix on insurance purchase decisions: as evidenced by car owners in Mahikeng. This study makes a contribution towards the marketing of car insurance by means of a set of recommendations, which ought to be considered by car insurance marketers. The empirical findings and recommendations of this study can serve as evidence for car insurance companies about the importance of the social media promotion mix as a marketing tool and to initiate further research in other sectors related to the social media promotion mix. To ensure that the primary objective of the study is reached, the secondary objectives formulated are: Objective 1: To obtain a demographic description of car owners in Mahikeng. Objective 2: To test the association between socio-economic variables and purchasing decisions Objective 3: To determine the relationship between social media platforms usage, online promotion mix, consumer behaviour and purchase decision-making amongst residents in Mahikeng. Objective 4: To investigate the impact of online promotion mix and the purchasing decisions of residents in Mahikeng. 6.3 Summary of the marketing and integrated marketing communication for insurance companies History points out that without suitable marketing (CIM, 2015) companies cannot understand the needs and preferences of their consumers, which also applies to short-term insurance companies. Marketing plays a vital role in the insurance industry and serves to increase sales while maintaining market share (Sanders, 2017). It is necessary to obtain a comprehensive understanding of the type of marketing strategy used by short-term insurance. To continually evaluate and re-evaluate their business activities, insurance companies should take into consideration the 10Ps of services marketing, identified as: product, promotion, price, place, people, physical evidence, process, packaging, positioning and partnership. The more competitive the market, the more difficult it is to choose the most effective marketing communication mix and approach. Consistency in informing consumers about what is available and beneficial to them is crucial in helping insurance companies to identify the most 183 appropriate communication strategy for their target market (Eiman, 2017). The marketing communication mix, also known as the promotional mix, consists of: advertising, sales promotion, public relations, personal selling and direct marketing. The insurance company has to determine the appropriate blend of these promotional elements into an ideal mix to effectively market the company’s services. Integrated marketing communication (IMC) provides a solid interpretation of all the main components of the marketing communication mix. Not too many years down the line, and the perception of IMC shifted from a narrow view into a more holistic view, which consists of ensuring that all components of the communication mix are linked (Vongkhamheng, 2017). Integrated marketing communication can influence the purchasing behaviour of consumers by transmitting messages via several marketing communication channels and allow an insurance company to reduce its advertising costs and minimise the duplication of advertising designs and photography (Kattiyapornpong & Yu, 2019; Pluta-Olearnik & Organizations, 2018; Vongkhamheng, 2017). While playing an important role in communicating a message, integrated marketing communication greatly contributes to affordability for consumers at a lower cost (Linton & Shoenberger, 2019; Percy, 2016). Bell and Taheri (2017) propose a new dynamic IMC model, as shown in Figure 2.13 in Chapter Two, which would enable insurance companies to focus their marketing communications on the consumer, thus making the message more effective while minimizing consumer risks. The integration of social media into businesses is considered as one of the most important activities in today’s business environment, as the effective use of social media brings about great opportunities for insurance companies. To better explain how IMC works for insurance companies, a conceptual model of the IMC process for car insurance was presented in Chapter two. 6.4 Summary of social media and consumer behaviour over car insurance in South Africa The evolution of the internet in South Africa has emerged and social media penetration has increased by providing insurance companies with a platform to educate their policy-holders. Ten websites were identified as the best in South Africa: Google.co.za, Google.com, YouTube.com, Facebook.com, Wikipedia.org, News24.com, FNB.co.za, Twitter.com, Yahoo.com and Takealot.com (We Are Social, 2018; Carr & Maier, 2013). For the purposes of this study, any online platform that allows users to take part in and share content in different contexts was considered as social media. The review further elaborates on short-term insurance 184 in South Africa and the evolution of technology in insurance companies. It was identified that South African insurance companies are by far the largest African insurance market and have been one of the slowest industries to go digital (Accenture, 2016; Moodley, 2019). For the purposes of this study, the term short-term insurance excluded any forms of health insurance. As the internet is a quick changing environment and consumer behaviour changes accordingly, it is imperative to understand the behaviour of car owners when it comes to purchasing an insurance policy via social media platforms. It was mentioned that South African consumers do not entirely reject the concept of purchasing products online, but are hesitant to participate due to the risks they perceive (White, 2016). Consumers do not necessarily shop the same way thus three main categories of buyers were identified and insurance buyers are considered as average buyers as they carefully consider value propositions, benefits and features. Considering the theoretical background provided in Chapter One, the Technology of Acceptance Model (TAM) and the Technology of Perceived Behaviour (TPB) were utilised for the purpose of this study and based on a concept-analysis and literature review from several researchers whom provided a range of factors that influence the intention to purchase car insurance online. 6.5 Summary of the methodology used in this study This section presents a summary of the methodology and analytical techniques used to achieve the purpose of this study. The methodology is sub-divided into three sections. The first section, called univariate testing, was used to address the first objective which is to describe the demographic and economics characteristics and the social media usage of car owners in Mahikeng, in addition this test described all the characteristics related to car insurance online purchasing decision-making. The second section presents bivariate tests and was used to address the second objective, which is to test the association between the demographic and economic factors and car insurance online purchasing decision-making using the Chi-square. In addition, the Chi-square was conducted to address the third objective, which is to test the association between social media usage, consumer behaviour, the social media promotion mix and car insurance online purchasing. As the constructs of social media usage, consumer behaviour elements and social media promotion mix are based on five point Likert scale, there was a need to conduct the test of reliability and validity before conducting the Chi-square test. 185 The third part of this chapter focuses on methods used to address objective four, which is to investigate the impact of the online promotion mix on car owner purchasing insurance decision- making in Mahikeng by using logistic regression. 6.6 Summary of the findings The summary of the results from the previous chapter is presented in this section. This starts with the findings to answer research objective one, which is to describe the demographic and economic characteristics of car owners in Mahikeng based on the descriptive analysis. This is followed by a summary of the findings to answer the second research objective, which is to test the association between socioeconomic variables and purchasing decision-making using the Chi-square test. In addition, a summary of the findings to answer the third research objective, which is to determine the relationship between social media platforms usage, the online promotion mix, consumer behaviour and purchase decision making amongst car owners in Mahikeng using the reliability test, the validity test and the Chi-square. Lastly, a summary of findings was provided to answer the four research objectives, which is to investigate the impact of the online promotion mix on car owners purchasing insurance in Mahikeng using logistic regression. 6.6.1 Research question one: What are the demographic and socio-economic characteristics of cars owners in Mahikeng? The descriptive statistics revealed that:  Most of the car owners who participated in this study are female (51.0%)  Most of the participants are aged between 21 years to 40 years  Most of the participants earn between R10 001 to R15 000  Most of the cars are insured (54.2%)  A large part of the participants (29.4%) are not taking up insurance because of the high number of complaints.  Many of the participants (50.7%) revealed that traditional media (TV, radio, etc.) triggers their intention to purchase insurance policies.  Many participants (52.2%) used Facebook as social media.  A large portion of the participants (49.3%) used social media almost every day. 186  Only a very small portion of the participants (9.3%) do spend more than 2 hours per day on social media websites. The descriptive statistics of the demographic and socio-economic variables in relation to online purchasing decision revealed that:  Most of the car owners who intended to purchase car insurance online are females (60.2%).  The participants who intended to purchase car insurance online are aged above 60 years (69.2%).  A large portion of participants (68%) who intended to purchase car insurance online are earning above R15 000.  Most of the car owners (61.5%) who intended to purchase car insurance online are those with their cars insured.  A small portion of participants (59.6%) who intended to purchase car insurance online are triggered by social media (Facebook, Twitter, etc.).  Many of the participants (62.1%) who intended to purchase car insurance online accessed social media 2 to 3 times a week.  A large portion of participants (66.7%) who intended to purchase car insurance online spend at least an hour per day on social media. 6.6.2 Research question two: What is the relationship between demographics, economics variables and online purchasing decisions of car insurance in Mahikeng? The results obtained from the Chi-square test show that all the p-values of the Chi-square test association for all pairs of variables, are insignificant at the 5% level of significance (p-values > 0.05). This means that the null hypothesis which stated that there is no relationship between demographic, economic variables and car online purchasing decisions cannot be rejected. Hence the study concludes that there is no significant association between the demographic and economic variables and online purchasing decision-making. 187 6.6.3 Research question three: What is the relationship between social media usage, online promotion mix, consumer behaviour variables and online purchasing decisions of car insurance in Mahikeng? This section aims to answer the research question three which consist of testing the hypothesis such as: the relationship between social media usage, consumer behaviour. Social media promotion mix and online purchasing decision of car insurance. 6.6.3.1 Reliability and validity test result Results from the reliability and validity test were based on social media usage, consumer behaviour and social media promotion mix.  Social media usage The results from the reliability test show that the three items remaining in the Social Media Usage in relation to Insurance scale have a Cronbach’s Alpha which is greater than 0.6, therefore the construct is reliable. In addition, results from the validity test show that all the constructs are valid, and none of them should be excluded from the item social media usage.  Social media promotion mix and consumer behaviour The results from the reliability test show that each of the constructs Social Media Promotion Mix and Consumer Behaviour has a Cronbach’s Alpha which is at least 0.6,. Therefore, it can be concluded that each of these constructs represents the theme such as perceived usefulness, perceived behavioural control, social media promotion mix, etc are reliable. In addition, the validity test shows that all p-values of the constructs of different themes (variables) are less than 0.05, therefore, it is concluded that all the constructs under each item of Social Media Promotion Mix and Consumer Behaviour are valid, and none of the constructs are to be excluded from the items. 6.6.3.2 Chi-square test The results show that the p-values of the Chi-square test of association between social media platform usage and Online Purchasing Decision was 0.067, which is greater than 0.05 (p-value >5%), meaning that the null hypothesis stating that there is no relationship between the online 188 social media platform usage and the purchase decision cannot be rejected . Therefore, the study concludes that the variable social media platform usage is insignificantly associated with online purchasing decisions. The results show that the p-values of the Chi-square test of association between Attitude and Online Purchasing Decision, Service Quality and Online Purchasing Decision, Perceived Trust and Online Purchasing Decision are less than 0.05 (p-value < 5%), meaning that the null hypothesis stating that there is no relationship between the consumer behaviour components (Attitude, service quality and perceived trust) and the purchasing decision is rejected. Therefore, the study concludes that the variable consumer behaviour is significantly associated with online purchasing decisions. The results also show that the p-values of the Chi-square test of association between Social Promotional Mix and Online Purchasing Decision was 0.01 which is less than 0.05 (p-value < 5%), meaning that the null hypothesis which stated that there is no relationship between the online promotion mix and the purchasing decision is rejected. Therefore, the study concludes that the variable social media promotion mix is significantly associated with online purchasing decision. 6.6.4 Research question four: What is the impact of the social media promotion mix on online purchasing decisions of car insurance in Mahikeng? Results from the Logistic regression test show that respondents agreed on service quality which was positive and statistically significant as the p-value was less than 5%, meaning that if respondents are satisfied with service quality, they are likely to purchase car insurance online. In addition, results from the Logistic regression concluded that respondents earning monthly incomes between R10 000 to R15 000 were positive and statistically significant to online purchase decision as the p-value was less than 5%. This implies that respondents earning monthly incomes between R10 000 to R 15 000 are likely to purchase their car insurance online. Furthermore, results from the Logistic regression show that respondents spending at least 30 minutes per day using social media is positive and statistically significant on car insurance online purchasing decision as their p-value was less than 5% significant level. This implies that respondents are likely to purchase car insurance online if they spent at least 30 minutes on social media. 189 Further the result revealed that the variable respondents agreed that the social media promotion mix was positive and significant to influence car insurance online purchasing decision as the p-value was less than 5% significant level. This implies that respondents are likely to purchase car insurance online if they are satisfied with social media promotion mix. Hence, based on these results, the null hypothesis which stated that social media promotion mix does not impact on online purchasing decision of car insurance is rejected and the study conclude that social media promotion mix impact online purchasing decision of car insurance among resident in Mahikeng. 6.7 Policy recommendations and implications This study has provided results that could be used to propose some policy recommendations in South Africa in order to improve car insurance subscriptions through a social media promotion mix. The recommendations are suggested based on the empirical results. As far as South Africa is concerned, results revealed that the number of car insurance subscriptions can be increased through social media online promotion mixes. Therefore the study suggests a number of potential ways to close the gap in the area for which public and private interventions may want to focus on in order to achieve a significant impact on the car insurance industry in South Africa. 6.7.1 Conceptual framework This section briefly discusses the extended framework proposed by this study with six constructs. The six constructs represent the factors that influence car owners’ decisions to purchase insurance policies via social media. The study has managed to reveal the current status of the effect of social media promotion mix on the consumer purchasing decision. It is expected that the framework will help insurance companies to design, implement and deliver an effective social media promotion mix targeting car owners. As presented in Figure 6.1, four constructs were identified as factors affecting the purchasing decision of car insurance online. 190 Figure 6.1: Constructs affecting the purchase decision of car insurance online Promotion mix Service quality Attitude Purchase Trust decision Income Time spent on social media The study proposed an alternate model to be used by car insurance, and the model shows that the social media sphere which has become increasingly important to most companies influence the purchasing decision. The study revealed that among the constructs proposed, only five were identified as being able to influence the purchasing decision and these are: promotion mix, consumer behaviour (trust, service quality and time spent on social media), and income. By focusing on these constructs, insurance companies should be able to convince car owners to purchase their car insurance online. The next section gives recommendations based on the findings. 6.7.2 Policy recommendations emanating from social media promotion mix and online purchasing decision The findings show that the promotion mix on social media does influence car owners’ decision to purchase their insurance policies online. The hypothesis consisted of six statements, which were used to accomplish the research objective. The results revealed that respondents agree on all constructs of the social media promotion mix, which means that car owners in Mahikeng are willing to purchase insurance policies online if more effort were put on the promotion mix. It was revealed from the findings that sales promotion, advertising, publicity, personal selling and live video are the most important promotional strategies that can be used by car insurance providers in order to influence car owners to purchase insurance policy on social media. Correctly implemented, these promotional tools can increase the effectiveness of the communication between insurance company and consumers. Due to the flexibility of the 191 internet, insurance companies can make use of online advertising which will allow brokers and insurance agents to interact and market their service as consumers spend more time online. Furthermore, special attention must be paid to the quality of the promotion mix as one of the significant findings emerging from this study is that consumers agree that promotion mix on social media is unrealistic and exaggerated but still agree that promotion mixes influence their purchasing decisions and are willing to purchase future insurance policies online. This is supported by Bhakuni and Aronkar (2012) who outlined that there is a strong relationship between the purchasing decision and social media advertising. An important implication of this is that the South African advertising regulator must monitor the implementation of advertising on social media in order for insurance companies to close the gap between what is required for an advert and what is done on the ground. In addition, insurance companies should acknowledge that advertising is about quality and should be done according to specific criteria such as having a clear call to action, easy to recall, raise brand awareness and introduce new services. Another implication of the findings is that consumer attitudes toward promotion mix on social media are influenced and insurance companies should create a sense of credibility by avoiding deceptive and misleading content in their online advertising. Furthermore, it was also shown from the findings that by using digital advertising, loyalty programmes, direct marketing, discounts and sponsored events can positively influence the online purchasing decision. This is in line with the result of KPMG (2019) and Sassian (2018), who reported that promotion is identified as the factor most likely to influence online consumers’ decision and that consumers recall seeing advertisements online which helped them to discover new insurance brands. In order for consumers to continue purchasing insurance policies on social media, insurance companies should put more effort into digital advertising, loyalty programmes and sponsored events by constantly evaluating their marketing strategies through surveys, return on investment and consumer engagement. By providing good service quality, insurance companies receive free advertising on other websites by satisfied consumers which in return improves consumer trust and confidentiality. Insurance companies should implement a digital marketing plan which will allow them to have an effective result of their campaigns. Among all recommendations, insurance companies should educate their consumers on the gap between what car owners want and what they truly need for their cars. The insurance companies should also educate their consumers on the available insurance discounts, claim processes while creating experiences for consumers through events and newsletters. By doing 192 so, insurance companies will be able to build trust, reduce complaints and enhance consumer loyalty. 6.7.3 Policy recommendations emanating from consumer behaviour and online purchasing decision The study revealed that consumer behaviour is significantly associated with car insurance online purchasing decisions. Not all car owners are comfortable with purchasing insurance policies online. Moreover, it was mentioned that some components of consumer behaviour such as attitude, service quality and perceived trust influence the online purchasing decision. Therefore, a policy implication arising from the results is that insurance companies should understand how consumers perceive their services and what motivates them to purchase their services by doing a monthly survey and after sales services. By understanding the motive behind consumer purchasing decisions and the factors influencing their decisions, the result shows that perceived quality is a factor that optimizes sales. As it stands, insurance companies must ensure that they offer quality services in order to attract and encourage car owners to purchase insurance policy by being closer to them and making them co-producers. Furthermore, it is argued that, service quality is established when a car owner compares his or her expectations about different service providers and the way he or she perceives company performance regarding the service (King Price Insurance, 2019; PMD, 2019). In view of this, it is recommended that insurance companies should invest in service training and ask for feedback from consumers in order to evaluate the sales force. Insurance companies should also follow up on consumer complaints by providing additional online services through their different platforms to interact with online consumers which will improve consumers’ retention. Online consumers trust insurance companies and are willing to purchase insurance policies online. The implication of the result is that the more trustworthy consumers are about the insurance the better they are able to carry out their information. Moreover, insurance companies should always identify the needs of car owners and make them feel that they can always trust and search for help. Insurance companies should be well establish virtually and physically with a clear name, logo, link and price options, terms and conditions which will allow them to differentiate themselves from the competition. By providing support, solving complaints and awarding rewards to each consumer that recommends insurance services will be an effective way to enhance consumer trust and attract more consumers. 193 6.7.4 Policy recommendations emanating from income and online purchasing decision The result from the crosstab between income group and car insurance status shows that most respondents with insured cars earn above R10 000 monthly as income. Insurance companies should focus on car owners with incomes above R10 000 as drivers with high incomes have fewer accidents. According to Hernández, Jiménez and Martín (2011) higher income causes internet users to perceive lower implicit risks in undertaking online purchases and thereby affects their demand for internet product and services. One of the reason why respondents do not insure their cars is affordability as many South Africans cannot afford adequate vehicle insurance, even third-party cover. Hence, this study suggested that, the government should make third-party car insurance compulsory in South Africa and insurance companies should strive to provide quality service at competitive prices. Insurance companies should not consider credit scores when calculating premiums as this unfairly penalizes lower-income car owners. 6.8 Practical significance of the study The study has made some important contributions to the literature on the relationship between social media promotion mix and consumer behaviours. Firstly, the result from the study conclusively shows that online promotion mix influences the purchasing decision by satisfying and retaining consumers. Secondly, it is indicated in the study that the online behaviour of consumers regarding promotion mix influences their purchasing decisions. By investigating the influence of social media promotion mix in order for car owner to purchase insurance online, the researcher was able to obtain a better understanding between online promotion mix and consumer behaviour. The results revealed that car owners are always on social media and spend more than two hours daily which is the best motivation for insurance companies to spend more of their efforts on the online promotion mix. Furthermore, the consumer attitude, service quality, perceived trust and social media promotion mix are the most important for car owners when it comes to purchasing insurance online. This clearly indicates that online promotion mix influences the purchasing decision, and therefore, insurance companies should invest more efforts on their marketing campaigns and consumer commitment as they are able to understand what motivates their decision. The next section discusses the limitations of the study. 194 6.9 Limitations of the study Limitations could influence the finding of any study, although this study included various age groups, gender, monthly income and the type of insurance coverage, the findings cannot be generalised to include the entire short-term insurance industry in South Africa. Certain aspects of the research process could have caused certain limitations, and some of the limitations are addressed in the following section. Related to the choice of the target group and the study area, some limitations were prevented by screening questions and restricted to short-term insurance in Mahikeng. The screening excluded respondents under 18 years and those who do not own a car. Due to the financial constraints and time the current study made use of a non-probability purposive sampling method, which cannot be generalised to the entire population. Another limitation is that the study focused on one local municipality of Ngaka Modiri Molema district. Concerning insurance services, the study did not focus on all insurance services but instead focused on short-term insurance; however, insurance companies also offer long-term insurance services. Therefore, the results cannot be generalised to all insurance companies. The limitation of the study should not be ignored as it provides opportunities for further research. 6.10 Opportunities for further research Other research opportunities may arise from this research, both from the knowledge gained as well as from the limitations encountered. For further study the following recommendation should be taken into consideration:  With regard to the questionnaire, it should be tested again and applied offline in order to have a better understanding of the influence of social media on the purchasing decision.  Another aspect to consider is to conduct the survey at different times of the year to determine the relevance of influencing factors.  It should be interesting for further research to also focus on long-term insurance.  Further research should explore a mixed method for better understanding of the reasons behind the consumer decision to purchase a product or service on social media.  Future research could use probability methods 195  It is recommended that future research should focus on a specific social network site to obtain a more comprehensive account of the constructs identified in this research.  Due to the large number of respondents who do not subscribe to an insurance policy, additional research should be done in order to further explore the respondents’ states of mind and attitudes in this regards.  It is recommended that the measurement items for all constructs investigated in this study be retested to obtain a better understanding of the effect of the promotion mix on the purchasing decision.  It is recommended that further research should be extended to the whole of South Africa or other countries in the world. 6.11 Conclusion This chapter gives an understanding of the social media promotion mix (advertisement, live video, email link, event and personal selling), as well as of the consumer behaviour factors involved (perceived trust, service quality, security, behavioural control and social influence). The chapter furthermore extends existing literature by examining how these factors influence online purchasing decisions. An overview of the study was presented, followed by recommendations, the practical signification of the study, the limitation of the study and opportunity for further research. In conclusion, the study completes its task by identifying which factors influence online purchase decisions, since each secondary objective was explored and achieved. In order to increase the number of insured cars on South Africa's roads, insurance companies should make use of social media promotion mix which can influence the decision of car owners to subscribe and purchase insurance policies via social media. In conclusion, the study completes its task by identifying promotion mix, service quality, trust and social media platform as factors that can influence car owners to purchase insurance policies online. The technology of acceptance model and the technology of perceived behaviour used in this study may also be adapted in future studies and among different segments. The research aimed to be a comprehensive study on how to encourage car owners to purchase insurance policies using social media. 196 REFERENCES Aaker, D.A. Kumar, V. Leone, R.P. & Day, G.S. 2013. Marketing research. New York, NY: Wiley. Aarnio, H. 2017. International Digital Marketing Strategy as a Growth Opportunity: Case: Finnish startup. AASA (Automobile Association of South Africa). 2018. Don’t take the insurance bait - cheaper is not always better. https://www.aa.co.za/insights/dont-take-the-insurance-bait- cheaper-is-not-always-better Date of access: 22 Nov 2019. Abdulmajid, A.F.A. 2019. Impact and Challenges of Digital Market due to Globalisation. Sumedha Journal of Management, 8(3):207-212. Accenture. 2016. Be digital: A R115,2 billion opportunity for South Africa's short-term insurance industry. https://www.accenture.com/_acnmedia/PDF-25/Accenture-Be-Digital- POV.pdfla=en Date of access: 04 Feb 2020. Accenture. 2017. Technology vision for insurance 2017. https://www.accenture.com/t20170418t020959__w__/ph- en/_acnmedia/accenture/conversion-assets/nonsecureclients/documents/pdf/2/accenture- technologyvision-insurance-2017 Date of access: 10 June 2020. Aglionby, J. 2016. Africa’s insurance market a ‘giant waking up’. Financial Times. https://www.ft.com/content/bc87016a-2430-11e6-9d4d-c11776a5124d Date of access: 22 Feb 2019. Agrawal, N. 2020. How InsurTech-Insurance partnership delivers new product innovations. https://www.mantralabsglobal.com/blog/insurtech-insurance-partnership/ Date of access: 18 May 2020. Aguiar‐Conraria, L. & Soares, M.J. 2014. The continuous wavelet transform: Moving beyond uni‐and bivariate analysis. Journal of Economic Surveys, 28(2), 344-375. 197 AIO (African Insurance Organisation). 2018. Africa Insurance Barometer 2018. Market survey.https://pulse.schanzalms.com/files/media/files/aac2d1e0123a5b5f5df7008326f20a3a/ Africa_Insurance_Barometer_WEB_E.pdf Date of access: 24 Oct 2019. Ajzen, I. 1985. From intentions to actions: A theory of planned behavior. Action control. Springer. 11-39. Ajzen, I. 1991. The theory of planned behavior. Organizational behavior and human decision processes, 50(2):179-211. Akar, E. & Dalgic, T. 2018. Understanding online consumers’ purchase intentions: a contribution from social network theory. Behaviour & Information Technology, 37(5), 473- 487. Akar, E. Yüksel, H F. & Bulut, Z A. 2015. The impact of social influence on the decision- making process of sports consumers on Facebook. İnternet Uygulamaları ve Yönetimi Dergisi, 6(2):5-27. Akhtar, N. Tahir, M. & Asghar, Z. 2016. Impact of Social Media Marketing on Consumer Purchase Intention. International Review of Social Sciences. 4th Issue 10:385-394. Akinlo, T. & Apanisile, O. T. 2014. Relationship between insurance and economic growth in Sub-Saharan Africa: A panel data analysis Modern Economy. Allen, M.W. & Craig, C.A. 2016. Rethinking corporate social responsibility in the age of climate change: a communication perspective. International Journal of Corporate Social Responsibility, 1(1):1-11. Amaro, S. & Duarte, P. 2015. An integrative model of consumers' intentions to purchase travel online. Tourism management, 46:64-79. American Marketing Association, 2014. https://www.marketingstudyguide.com/amas- definition-marketing/ Accessed: 29 January 2019. American Marketing Association. 2017 https://www.ama.org/the-definition-of-marketing- what-is-marketing. 198 Andrews, J.C. & Shimp, T.A. 2017. Advertising, promotion, and other aspects of integrated marketing communications. London: Nelson Education. Andrus, A. 2020. What is digital marketing and how do I get started? https://www.disruptiveadvertising.com/marketing/digital-marketing/ Date of access: 26 May 2020. Andzulis, J.M. Panagopoulos, N.G.& Rapp, A. 2012. A review of social media and implications for the sales process. Journal of Personal Selling & Sales Management, 32(3):305-316. Antonenko, P D. 2015. The instrumental value of conceptual frameworks in educational technology research. Educational Technology Research and Development, 63(1):53-71. Armitage, C.J. & Conner, M. 2001. Efficacy of the theory of planned behaviour: A meta‐ analytic review. British journal of social psychology, 40(4):471-499. Armstrong, G. & Kotler, P. 2013. Marketing: an introduction 11th ed. New Jersey: Pearson Education Limited. Armstrong, G. Adam, S. Denize, S. & Kotler, P. 2014. Principles of marketing. Pearson Australia. Arslan, M. & Zaman, R. 2015. Impact of Brand Image and Service Quality on Consumer Purchase Intentions. A Study of Retail Stores in Pakistan. GRIN Verlag. Athapaththu, J C., Kulathunga, D. & Mawatha, B. 2018. Factors Affecting Online Purchase Intention: Effects of Technology and Social Commerce. International Business Research, 11(10):111-128. Augustyniak, K. 2019. How to Push the Envelope with Direct Mail Marketing in 2019. Growwithfarm, https://www.growwithfarm.com/financial-direct-mail-marketing/ Date of access: 15 Jan 2020. Auto General. 2016. Social media for the insurance broker. Blog. Thursday 8. https://www.autogen.co.za/blog/press-releases/social-media-for-the-insurance-broker/ Date of access: 19 May 2019. 199 Awa, H O. Ojiabo, O U. & Emecheta, B C. 2015. Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs. Journal of Science & Technology Policy Management, 6(1):76-94. Aziz, Y.A & Chok, N.V. 2013. The role of Halal awareness, Halal certification, and marketing components in determining Halal purchase intention among non-Muslims in Malaysia: A structural equation modelling approach. Journal of International Food & Agribusiness Marketing, 25(1):1-23. Babbie, E R. 2013. The basics of social research: Cengage learning. Babbie, E. 2010. The practice of social research. 12thed. Belmont, CA: Wadsworth Babin, B J. & Zikmund, W G. 2016. Exploring marketing research: Mason, OH: Cengage. Babin, B.J. & Zikmund, W.G. 2015. Exploring marketing research. Cengage Learning. Bahney. A. 2018. It’s not just Facebook that’s is collecting your data. CNN Money. April 12. https://money.cnn.com/2018/04/12/pf/auto-insurance-data-collection/index.html Baker, M.J. & Hart, S. 2016. The Marketing Book. 7th edition. Routledge. Baker, M.J. 2014. Marketing Strategy and Management 5ed: Palgrave McMillan. Banderker, A. 2018. First South African insurtech to join plug and play. https://www.fanews.co.za/article/company-news-results/1/sanlam/1055/first-south-african- insurtech-partner-to-join-plug-and-play/24656 Date of access: 18 September 2019. Barendse, R. 2012. The changing landscape of motor insurance in south Africa. https://www.cover.co.za/the-changing-landscape-of-motor-insurance-in-south-africa/ Date of access: 15 Feb 2019. Barnard, S.M. Bothma, C.H. & Cant, M.C. 2017. The identification of criteria for the optimal use of Facebook pages for marketing purposes: a South African perspective. Journal of Business Retail Management Research, 11(2). Barone, A. 2019. Contractors’ All Risks (CAR) Insurance. htts://www.investopedia.com/terms/c/contractors-all-risks-car-insurance.asp Date of access: 16 January 2020. 200 Barry, H. 2014. Short-term insurers take a R1.6bn hammering. Available online at: https://www.moneyweb.co.za/archive/shortterm-insurers-take-a-r16bn-hammering/ Date of access: 09 May 2019. Bashar, A. Ahmad, I. & Wasiq, M. 2012. Effectiveness of social media as a marketing tool: An empirical study. International Journal of Marketing, Financial Services & Management Research, 1(11), 88-99. Bashir, A.M. Bayat, A. Olutuase, S.O. & Abdul Latiff, Z.A.2019. Factors affecting consumers’ intention towards purchasing halal food in South Africa: a structural equation modelling. Journal of food products marketing, 25(1):26-48. Bassig, M. 2019. Social Media Marketing For Insurance: Dos and Don’ts. https://www.reviewtrackers.com/blog/social-media-marketing-insurance/ Date of access: 07 Jan 2020. Bayati, V. 2017. Exploring the impact of embedded social media within the corporate websites of media organisations. Queensland University of Technology. Bazini, E. Elmazi, L. & Sinanaj, S. 2012. Importance of relationship marketing management in the insurance business in Albania. Procedia-Social and Behavioral Sciences, 44, 155-162. Be Wiser Insurance. 2019. Number of uninsured drivers caught on UK roads fell by a third in 2018. Bewiser, https://www.bewiser.co.uk/news/car-insurance/number-uninsured-drivers- caught-uk-roads-fell-third-2018 27 Nov 2019. Bedgood, L. 2016. How to Power Your Insurance Agency with Social Media. https://v12data.com/blog/how-power-your-insurance-agency-social-media/ Date of access: 07 Jan 2020. Bedgood, L. 2017. The digital marketing imperative: Key strategies for insurers to target today’s modern insurance consumer. https://www.v12data.com/blog/digital-marketing- imperative-key-strategies-insurers-target-todays-modern-insurance-consumer/ Date of access: 12 February 2019. Beger, G., Sinha, A. & Pawelczyk, K. 2012. South African mobile generation. Study on South Africa Young People on Mobiles, 1-48. 201 Belch, G E. 2017. Advertising and promotion: An integrated marketing communications perspective: McGraw-Hill. Belch, G. & Belch, M. 2018. Advertising And Promotion: An Integrated Marketing Communications Perspective. 11th ed. New York: McGraw-Hill education. Bell, G. & Taheri, B. 2017. Marketing Communications: An advertising, promotion and branding perspective. Goodfellow Publishers Ltd. Bellryck. 2018. The evolution of short-term insurance. https://www.bellryck.co.za/index.php/evolution-short-term-insurance/ Date of access: 07 May 2019. Benady. D. 2014. How technology is changing marketing. https://www.theguardian.com/media-network/media-network-blog/2014/sep/29/technology- changing-marketing-digital-media> Date of access 20 March 2018. Benbasat, I. Goldstein, D.K. & Mead, M. 1987. The case research strategy in studies of information systems. MIS quarterly, pp.369-386. Berndt, A. & Petzer, D. 2012. Marketing research. New York: Heinemann. Berndt, A. & Tait, M. 2013. Relationship Marketing and Customer relationship management 2nd ed. Cape Town: Juta & Company Ltd. Berners-Lee, T.J. 1989. Information management: A proposal (No. CERN-DD-89-001-OC). Berthon, P.R., Pitt, L.F., Plangger, K. & Shapiro, D. 2012. Marketing meets Web 2.0, social media, and creative consumers: Implications for international marketing strategy. Business horizons, 55(3):261-271. Bhakuni, P. & Aronkar, P. 2012. Effect of social media advertising on purchase intentions of students-An empirical study conducted in Gwalior City. International Journal of Applied Services Marketing Perspectives, 1(1): 73. Bhasin, H. 2017. Societal marketing concept. https://www.marketing91.com/societal- marketing-concept/ Date of access: 24 January 2019. 202 Bhatia, S. and Mitra, P., 2012. Summarizing figures, tables, and algorithms in scientific publications to augment search results. ACM Transactions on Information Systems (TOIS), 30(1):1-24. Biddle, S. 2018. Six benefits of buying car insurance online. https://www.praguepost.com/blog/benefits-buying-car-insurance-online Date of access: 27 June 2020. Bizcommunity. 2020. Businesses will have to fight for survival in 2020. BIzcommunity, https://www.bizcommunity.com/Article/196/19/199622.html Date of access: 14 Feb 2020. Blake, M. 2018. 10 customer experience tips for insurance in 2018. https://www.forbes.com/sites/blakemorgan/2018/04/19/10-customer-experience-tips-for- insurance-in-2018/#4811de2f5e2f Date of access: 27 Feb 2019. Blakeman, R. 2018. Integrated marketing communication: creative strategy from idea to implementation. Rowman & Littlefield. Bleize, D.N.M. & Antheunis, M. L. 2019. Factors influencing purchase intent in virtual worlds: a review of the literature. Journal of Marketing Communications, 25(4):403-420. Bolarinwa, O.A. 2015. Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 22(4):195. Bolderdijk, J.W. Knockaert, J. Steg, E.M. & Verhoef, E.T. 2011. Effects of Pay-As-You- Drive vehicle insurance on young drivers’ speed choice: Results of a Dutch field experiment. Accident Analysis & Prevention, 43(3), 1181-1186. Bonn, M A. Kim, W G. Kang, S. & Cho, M. 2016. Purchasing wine online: The effects of social influence, perceived usefulness, perceived ease of use, and wine involvement. Journal of Hospitality Marketing & Management, 25(7):841-869. Bonner, M. 2018. Adjusters, underwriters and other insurer employees. https://www.thebalancesmb.com/types-of-insurance-company-employees-462563 Date of access: 12 February 2019]. 203 Boom, B.H. & Bitner, M.J. 1981. Marketing strategies and organization structures for service firm. Marketing of Services. Chicago: America Association. Borden, N.H. 1964. “The concept of the Marketing Mix”, Journal of Advertising Research, June, 2-7. Borscheid, P. & Haueter, N.V. 2012. World insurance: the evolution of a global risk network. Oxford University Press. Bosari, J. 2013. What really goes into determining your insurance rates. Forbes. https://www.forbes.com/sites/moneywisewomen/2013/01/08/what-really-goes-into- determining-your-insurance-rates/#1dfe838e3f85 Date of access: 22 Feb 2020. Bothma, M. 2018. A model for commitment and online community citizenship behaviour intention on Facebook (Doctoral Thesis, North-West University). Bothma, N. & Gopaul, M. 2015. E-marketing in the South African context. Cape Town, South Africa: Juta & Company. Botten, N. & McManus, J. 1999. Competitive strategies for service organizations. Purdue University Press. Bourgeois, D. & Bourgeois, D.T. 2014. Networking and Communication. Information Systems for Business and Beyond. Bowden, J. 2014. Gain consumer confidence by respecting privacy with your big data marketing. Available online at: https://www.digital-warriors.com/respect-privacy-big-data- marketing/ Date of access: 01 May 2019. Bowen, A. 2019. Best cheap car insurance companies for 2019. The simple dollar. https://www.thesimpledollar.com/cheap-car-insurance/ Date of access: 21 Feb 2019. Bradley, N. 2013. Marketing research: tools & techniques:, United Kingdom: Oxford University Press. Bright, L. F. & Daugherty, T. 2012. Does customization impact advertising effectiveness? An exploratory study of consumer perceptions of advertising in customized online environments. Journal of Marketing Communications, 18(1):19-37. 204 Brodie, R.J. Ilic, A. Juric, B. & Hollebeek, L. 2013. Consumer engagement in a virtual brand community: An exploratory analysis. Journal of business research, 66(1):105-114. Brown, T J. Suter, T. A. & Churchill, G. A. 2013. Basic marketing research. Cengage Learning. Brown, Z.Z., 2017. Improving communication in the insurance industry, international insurance society. https://www.internationalinsurance.org/sites/default/files/2018- 03/Improving%20Communication%20in%20the%20Insurance%20Industry.pdf Date of access: 15 Nov 2019. Brunner, M.I. Sikorska, A.E. & Seibert, J. 2018. Bivariate analysis of floods in climate impact assessments. Science of The Total Environment, 616, 1392-1403. Brynard, P.A. & Hanekom, S.X. 2006. Introduction to research in management-related fields. Pretoria: Van Schaik. Burns, A.C. Veeck, A. & Bush, R.F. 2017. Marketing research: Essex: Pearson. Buttle, F. & Maklan, S. 2019. Customer relationship management: concepts and technologies. Routledge. Cant, M.C. & Van Heerden.2013. Marketing Management: A South African Perspective. Cant, M.C. (ed.). 2010. Marketing: an introduction. Cape Town: Juta. Cant, M.C. 2011. Marketing management: A South African perspective. Juta & Company Ltd. Cant, M.C. Van Heerden, C.H. 2017. Marketing management: A South African perspective. Cape Town: Juta & Co. Cant, M.C. Wiid, J.A. & Kallier, S.M. 2015. Product strategy: Factors that influence product strategy decisions of SMEs in South Africa. Journal of Applied Business Research (JABR), 31(2), 621-630. Carr, N K. & Maier, S P. 2013. Social media policies: Managing risks in a rapidly developing technological environment. Call for Papers. 205 Cascio, W.F. & Montealegre, R. 2016. How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3, 349-375. Catlin, T. & Lorenz, J.T. 2017. Digital disruption in insurance: Cutting through the noise. Digit. McKinsey. Catlin, T. Duncan, E. Fanderl, H. & Lorenz, J-T. 2017. The growth engine: Superior customer experience in insurance. Cawsey, T. & Rowley, J. 2016. Social media brand building strategies in B2B companies. Marketing Intelligence & Planning. Central, C. 2017. These road safety campaigns will make you think. Alberton record https://albertonrecord.co.za/101581/these-road-safety-campaigns-will-make-you-think/ Date of access: 12 Feb 2020. Chan, C.S.C. 2012. Marketing death: Culture and the making of a life insurance market in China. OUP USA. Charlesworth, A. 2014. An introduction to social media marketing. Routledge. Chartered institute of Public Relations, 2015. Chartered Institute of Public Relations. https://www.cipr.co.uk/content/policy/careers-advice/what-pr Date of access: 10 April 2019. Chen, L. 2014. The influence of social media on consumer behavior: An empirical study on factors influencing consumer purchase intention in China under the social media context. Aarhus University, pp.1-128. Chen, M-F. & Tung, P-J. 2014. Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International journal of hospitality management, 36:221-230. Cheng, E.W.L. 2019. Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM). Educational Technology Research and Development, 67(1):21-37. Chibvura, F.R. 2017. Promotional tools used by medical insurance companies: an international student perspective (Doctoral Thesis). 206 https://openscholar.dut.ac.za/bitstream/10321/2641/1/CHIBVURA_FR_2017.pdf Date of access: 15 June 2019. Chikandiwa, S.T. 2013. The role of social media in the marketing communication mix: a case study of South African banks (Doctoral Thesis, University of Zululand). Chin, Y-C. 2016. Consumer Acceptance of Online Complaint Forms: An Integration of TPB, TAM and Values Perspective. Business and Economic Research, 6(2):265-279. Cholak, M. 2015. Healthcare Insurers: Three focus areas for differentiation. http://customerthink.com/healthcare-insurers-three-focus-areas-for-differentiation/ Date of access: 11 February 2019. Chong, Nicole. (2017, July 14). Social marketing strategies for insurance brands 2017. https://www.synthesio.com/blog/social-marketing-strategies-insurance-brands/ Date of access: 08 March 2018. Christotoua. 2017. Brand Positioning: “Cheap insurance” vs “Proper insurance”. https://toua.co.za/2017/06/27/brand-positioning-cheap-insurance-vs-proper-insurance/ Date of access: 20 Jan 2020. Chu, S C. Lien, C H. & Cao, Y. 2019. Electronic word-of-mouth (eWOM) on WeChat: examining the influence of sense of belonging, need for self-enhancement, and consumer engagement on Chinese travellers’ eWOM. International Journal of Advertising, 38(1):26-49. Chu, S.C. 2011. Viral advertising in social media: Participation in Facebook groups and responses among college-aged users. Journal of interactive advertising, 12(1):30-43. Chung, N. Han, H. & Koo, C., 2013. Tourists' Attachment Processes and Behavioural Changes in Social Media: Persuasion and Reference Group Influence Perspective. In PACIS (p. 79). Churchill, D.A. & Iacobucci, D. 2010. Market research. Methodological Foundations, 2. CIM (Chartered Institute of Marketing). 2015. Marketing and the 7Ps: A brief summary of marketing and how it work. https://www.cim.co.uk/media/4772/7ps.pdf Date of access: 05 May 2020. 207 Claessens, M. 2018. Types of consumer products and marketing considerations–convenience, shopping, specialty and unsought products. Date of access: 18 Feb 2020 Clement, J. 2019. Number of social network users in South Africa from 2017 to 2023. https://www.statista.com/statistics/972776/number-of-social-network-users-in-south-africa/ Date of access: 12 June 2020. Clement.J. 2020. South Africa online usage penetration 2015-2025. Statista july 14. https://www.statista.com/statistics/484933/internet-user-reach-south-africa/ Date of access: 25 August 2020. Clow, K.E. & James, K.E. 2014. The marketing research process. Essentials of marketing research. Putting research into practice, pp.25-61. Coe, N.M. & Yeung, H.W.C. 2015. Global production networks: Theorizing economic development in an interconnected world. Oxford University Press. Cohen‐Almagor, R. 2011. Fighting hate and bigotry on the Internet. Policy & Internet, 3(3):1- 26. Collomb, J. 2017. How do leading insurance companies use customer knowledge to their advantage. https://www.myfeelback.com/en/blog/how-insurance-companies-use-customer- knowledge-advantage Date of access: 11 May 2020. Compare, 2019. Compare car insurance in South Africa. https://www.comparecarinsurance.co.za/ Date of access: 12 May 2020 Connelly, L.M., 2014. Ethical considerations in research studies. Medsurg Nursing, 23(1):54- 56. Constantinides, E. 2014. Foundations of social media marketing. Procedia-Social and behavioral sciences, 148,40-57. Cooper, D.R. & Schindler, P.S. 2014. Business research methods. Twelfth edition. New York, NY: McGraw-Hill Irwin. 208 Corke. M & Martin.J. 2020. Minimum salary to qualify for car finance: What you need to know. Finder. May 14. https://www.finder.com/za/minimum-salary-to-qualify-for-car- finance. Creswell, J W. & Creswell, J D. 2017. Research design: Qualitative, quantitative, and mixed methods approaches. New York: Sage Publications. Creswell, J.W. 2014. Research design: Qualitative, quantitative, and mixed methods approaches: Thousand Oaks, CA: Sage Publications, Inc. Cristal, J. 2017. A complete guide to partnership marketing: part one. https://econsultancy.com/a-complete-guide-to-partnership-marketing-part-one/ Date of access: 08 March 2019. Cullen, R. 2011. Handbook of research on overcoming digital divides: Constructing an equitable and competitive information society. Online Information Review. Cunningham, N. 2018. Introduction to marketing- a southern African perspective. Pretoria: Van Schaik. Dalziel, R.C. 2016. Factors influencing South African female generation Y students’ purchase behaviour of beauty products (Doctoral Thesis, North-West University (South Africa), Vaal Triangle Campus). Dangaiso. P.T. 2014. The effects of sales promotion strategies on company perfomance: A case of Telone Zimbabwe. Thesis, Midlands State University, Gweru, Zimbabwe. http://ir.msu.ac.zw:8080/xmlui/handle/11408/486 Date of access: 14 April 2020. Dao, D V. 2015. Social media classification scheme in online teaching and learning activities: A consideration for educators. International journal of education and social science, 2(4):85- 94. Dasgupta, P. Bhattacherjee, S. Dasgupta, S. Roy, J.K. Mukherjee, A. & Biswas, R. 2017. Nomophobic behaviors among smartphone using medical and engineering students in two colleges of West Bengal. Indian Journal of Public Health, 61(3):199. Daugherty, P. Carrel-Billiard, M. & Biltz, MJ. 2016. 'Platform Economy: Technology-driven business Model Innovation From the Outside In', Accenture, Technology Vision 2016, p 15. 209 Davis, F. D. 1986. A technology acceptance model for empirically testing new end-user information systems. Cambridge, MA. Davis, L. 2019. What does the current South African ecommerce landscape look like. Available at: https://flickerleap.com/south-african-ecommerce-landscape/ Date of access: 21 June 2020. Davis, S. 2018. Social responsibility & the insurance industry. https://talentegg.ca/incubator/2018/04/02/social-responsibility-insurance-industry/ Date of access on 25 January 2019. De Lanerolle, I. 2012. The New Wave: Who connects to the Internet, how they connect and what they do when they connect. South African Network Society Project. University of Witwatersrand), http://www. networksociety. co. za Date of access: 13 Oct 2019. De Meyer-Heydenrych, C. Human, D. Maduku, D.K. Meintjes, C. & Nel, J. 2017. Principles of marketing. Cape Town: Oxford University Press, South Africa. Deepak, R.K.A. & Jeyakumar, S. 2019. Marketing management. Educreation Publishing. Delbridge, E. 2019. Should you shop for car insurance online? https://www.thebalance.com/pros-and-cons-of-online-car-insurance-527046 Date of access: 03 May 2019. Delerue, H, Kaplan, A M. & Haenlein, M. 2012. Social media: back to the roots and back to the future. Journal of Systems and Information Technology. Deloitte. 2017. Insurance outlook: Tech innovation key to overcome growth challenges. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/financial-services/us-fsi- insurance-industry-outlook-infographic-update-2017.pdf Date of access: 19 June 2019. Dessart, L. Veloutsou, C. & Morgan-Thomas, A. 2016. Capturing consumer engagement: duality, dimensionality and measurement. Journal of Marketing Management, 32(5-6):399- 426. Dewdney, A. & Ride, P. 2014. The digital media handbook, 2nd ed. New York: Routledge. 210 Di Pietro, L. & Pantano, E. 2012. An empirical investigation of social network influence on consumer purchasing decision: The case of Facebook. Journal of Direct, Data and Digital Marketing Practice, 14(1), pp.18-29. DiGangi, E.A. & Hefner, J.T. 2013. Ancestry estimation. In Research methods in human skeletal biology (pp. 117-149). Academic Press. Dikko, M. 2016. Establishing Construct Validity and Reliability: Pilot Testing of a Qualitative Interview for Research in Takaful (Islamic Insurance). Qualitative Report, 21(3). Dillon, A. & Morris, M.G. 1996. User acceptance of new information technology: theories and models. Medford, NJ: Information Today. Dishaw, M.T. & Strong, D.M. 1999. Extending the technology acceptance model with task– technology fit constructs. Information & management, 36(1):9-21. Dobre, C. & Milovan-Ciuta, A.M. 2015. Personality influences on online stores customers behavior. Ecoforum Journal, 4(1), p.9. Dollarhide.M.E. 2020. Social media definition. Investtopedia. September 6. https://www.investopedia.com/terms/s/social-media.asp Date of access: 19 October 2020. Dost, B. Khyzer, M. Illyas, M. & Abdul Rehman, C. 2015. Online shopping trends and its effects on consumer buying behavior: A case study of young generation of Pakistan. NG- Journal of Social Development, 417(3868):1-22. Drew, H. 2019. Complete History of Social Media: Then and Now. https://smallbiztrends.com/2013/05/the-complete-history-of-social-media-infographic.html Date of access: 17 July 2019. Drost, E.A. 2011. Validity and reliability in social science research. Education Research and perspectives, 38(1), 105. Du Plessis, C. 2017. The role of content marketing in social media content communities. South African Journal of Information Management, 19(1):1-7. 211 Du Plessis, J. 2019. Updated: Best & Worst Insurance Companies of 2019 in SA. Money Panda. https://moneypanda.co.za/news/lets-talk-car-insurance-updated-list-of-the-best-worst- insurance-companies-in-sa/ 17 Feb 2019. Duan, M., 2012. Strategic management and marketing strategy in insurance companies: case: China Life Insurance Company Limited in Shifang. Duffett Mr, R.G. & Wakeham Dr, M., 2016. Social media marketing communications effect on attitudes among millennials in South Africa. The African Journal of Information Systems, 8(3):2. Duneva-Stoyanova, E. 2019. Critical Evaluation on the Effectiveness of the Electronic Business Communications in the Area of Real Estate. 2019 International Conference on Creative Business for Smart and Sustainable Growth (CREBUS) organised by: IEEE. p. 1-3. Dunn, Kevin., 2018. Differentiation in a mature market: The key to success for insurance companies. https://www.fja.com/about-us/news-overview/ Date of access: 14 May 2020. Durett, M. 2016. The evolution of the marketing mix (and what inbound has to do with it), https://www.square2marketing.com/blog/inbound-marketing-mix Date of access: 29 January 2019. Ebner, M. 2018. Microblogs. In The SAGE Encyclopedia of the Internet (pp. 640-641). Sage Publications. Edmonds, W.A. & Kennedy, T.D. 2016. An applied guide to research designs: Quantitative, qualitative, and mixed methods: Sage Publications. Edmondson, D.R. Edwards, Y.D. & Boyer, S.L. 2012. Likert scales: A marketing perspective. International journal of business, marketing, and decision sciences, 5(2):73-85. Eiman, S.M. 2017. A visual semiotic analysis of the hidden meanings, myths and ideologies in Old Mutual South Africa's CSR 2.0 corporate advertising (Doctoral Thesis). Ekwueme, A C. & Okoro, N. 2018. Analysis of the use of social media advertising among selected online businesses in Nigeria. European Centre for Research Training and Development UK. http://www.eajournals.org/wp-content/uploads/Analysis-of-the-Use-of- 212 Social-Media-Advertising-among-Selected-Online-Businesses-in-Nigeria.pdf Date of access: 7 Feb 2020. Electronic national administration traffic information system. 2019. Live vehicle population as at 31 January 2019. http://www.enatis.com/index.php/statistics/71-live-vehicle-population- per-registering-authority Date of access: 02 Oct 2019. EMarketer. 2015. Increasing audience engagement key objective in social media marketing. ENATIS (Electronic national administration traffic information system). 2019. Live vehicle population as at 31 January 2019. enatis.com, http://www.enatis.com/index.php/statistics/71- live-vehicle-population-per-registering-authority 20 Oct 2019. Ernest-Jones, S. 2019. Why Smart Insurance Companies are Going Direct to Consumer https://blog.globalwebindex.com/marketing/direct-to-consumer-insurance/ Date of access: 19 March 2020. Erskine, R. 2017. 20 Online Reputation Statistics That Every Business Owner Needs To Know. Forbes. https://www.forbes.com/sites/ryanerskine/2017/09/19/20-online-reputation- statistics-that-every-business-owner-needs-to-know/#1a78ec1fcc5c Date of access: 31 Oct 2019. Facebook. & ComScore. 2017. The US consumer auto insurance journey. https://www.facebook.com/business/m/usautoinsurance Date of access: 19 June 2020. Fan Bi. 2017. Before, during and after: How to Improve Customer Service Every Step of the Way. https://www.salesforce.com/ca/blog/2017/02/improve-customer-service.html. Date of access: 18 May 2020. Faurie, J. 2019. Imagine underwriting a claim using social media. Fanews. https://www.fanews.co.za/article/legal-affairs/10/general/1120/imagine-underwriting-a- claim-using-social-media/27188 Date of access: 04 Feb 2020. Feinberg, F M. Taylor, J R. & Kinnear, T C. 2013. Modern Marketing Research: Concepts. Methods, and Cases, 2nd edition, Cengage Learning. Fill, C. & Turnbull, S L. 2016. Marketing communications: brands, experiences and participation. New York: Pearson. 213 Fin24. 2017. Impact of SA's lack of growth on the insurance industry. Fin24. https://www.fin24.com/Money/Insurance/impact-of-sas-lack-of-growth-on-insurance- industry-20170502 20 March 2018. Finne, A. & Grönroos, C. 2017. Communication-in-use: customer-integrated marketing communication. European Journal of Marketing, 51(3), 445-463. Fishbein, M. & Ajzen, I. 1975. Belief, attitude, and behavior: An introduction to theory and research. Reading, Mass: Addison Wesley. Fitzpatrick. M. 2020. How age affects car insurance costs. ValuePenguin. September 11. https://www.valuepenguin.com/how-age-affects-auto-insurance-costs Date of access: 13 July 2020. Flamand, T. Matino, P. & Marizien, J. 2013. Insurance and social media. https://www2.deloitte.com/content/dam/Deloitte/lu/Documents/financial-services/lu- insurance-social-media-23102013.pdf Date of access: 15 April 2019. Forbes. 2018. 4 Tips To Help Your Business Flourish on Social Media. https://www.forbes.com/sites/forbescommunicationscouncil/2018/05/11/how-social-media- can-move-your-business-forward/?nowelcome=1#656357354cf2 Date of access: 26 June 2018. Forsey, C. 2018. What is public relations? The definition of PR in 100 words or less. https://blog.hubspot.com/marketing/public-relations-definition Date of access: 08 April 2019. Fourie, L. 2014. Public relations : theory and practice. Cape Town: Juta. Freedom House. 2011. South Africa. www.freedomhouse.org/sites/default/.../South%20Africa_FOTN2011.pdf Date of access: 05 June 2020. Fuchs, C. 2017. Social media: A critical introduction. New York: Sage. Fullerton, L. 2017. Online reviews impact purchasing decisions for over 93% of consumers, report suggests. The drum, https://www.thedrum.com/news/2017/03/27/online-reviews- impact-purchasing-decisions-over-93-consumers-report-suggests Date of access: 31 Oct 2019. 214 Garcia, I. 2011. Social media-integration: theory-model. Social Media Today. https://www.socialmediatoday.com/content/social-media-integration-theory-model Date of access: 18 April 2020. García-Domingo, M. Aranda, M. & Fuentes, V.M. 2017. ‘Facebook use in university students: Exposure and reinforcement search’, Procedia – Social and Behavioral Sciences 237, 249–254. https://doi.org/10.1016/j.sbspro.2017.02.071 Date of access: 21 May 2020. Gavriletea, M. 2013. Communication in Insurance. Journal of International Finance and Economics, 13(2). Gehrig, F. 2018. The art of personal selling in the digital age. https://www.propertycasualty360.com/2018/05/30/the-art-of-personal-selling-in-the-digital- age/?slreturn=20190323041801 Date of access: 23 April 2019. Gerber, D. 2016. A few common misconceptions when buying a car. Fin24, https://www.fin24.com/Money/Vehicle-Finance/a-few-common-misconceptions-when- buying-a-car-20160329 Date of access: 7 Feb 2019. Ghafoor, M.M. 2012. Role of demographic characteristics on job satisfaction. Far East Research Centre, 6(1), 30-45. Ghunaim, F. 2019. Digital insurance: the customer journey. https://www.vardot.com/en- us/ideas/blog/digital-insurance-customer-journey Date of access: 25 June 2020. Girdlestone, M. 2018. Building Customer Loyalty in the Insurance Industry. https://www.merkleinc.com/blog/building-customer-loyalty-insurance-industry Date of access: 7 Jan 2020. Goffee, R. & Jones, G. 2013. Creating the best workplace on earth. Harvard Business Review, 91(5):98-106. Goldstuck, A. & Hunter, K. 2010. SA Internet growth accelerates. http://www.worldwideworx.com/sa-internet-growth-accelerates/ Date of access: 05 June 2020. 215 Govender, K.K. 2014. Public transport service quality in South Africa: A case study of bus and mini bus services in Johannesburg. African Journal of Business Management, 8(10):317- 326. Goyal, A, Maity, M, Thamizhvanan, A. & Xavier, MJ. 2013. Determinants of customers' online purchase intention: an empirical study in India. Journal of Indian Business Research. Goyal, R. 2018. How technology has evolved in the insurance industry. https://www.deccanchronicle.com/technology/in-other-news/240918/how-technology-has- evolved-in-the-insurance-industry.html Date of access: 07 May 2019. Graeme, A. 2017. How Insurance Brands are Reaching Millennials with Content and Social Marketing. https://blog.digimind.com/en/insight-driven-marketing/how-insurance-brands-are- reaching-millennials-with-content-and-social-marketing Date of access: 12 Feb 2020. Grantham, J. & Habel, C. 2012. An investigation of factors driving virtual communities. In Proceedings of the Thirteenth Australasian User Interface. Australian Computer Society, Inc, Conference-Volume 126 (pp. 91-92). Gravetter, F.J. Wallnau, L.B. Forzano, L.A.B. & Witnauer, J.E. 2020. Essentials of statistics for the behavioral sciences. Cengage Learning. Gray, D E. 2013. Doing research in the real world: Sage. Grewal, D. Roggeveen, A.L. Compeau, L.D. & Levy, M. 2012. Retail value-based pricing strategies: New times, new technologies, new consumers. Journal of Retailing, 88(1), 1-6. Greyling, E. 2017. The applicability of the Theory of Planned Behaviour to choosing a career as a rural physician in South Africa. University of Pretoria. Guettler, A. 2019. Examples of Brand-Positioning Strategy. https://smallbusiness.chron.com/examples-brandpositioning-strategy-25213.html 20 Jan 2020. Guo, X. Ling, K. C. & Liu, M. 2012. Evaluating factors influencing consumer satisfaction towards online shopping in China. Asian Social Science, 8(13):40. 216 Gusner.P. 2012. The cheapest age for car insurance. Carinsurance.com. July 25. https://www.nasdaq.com/articles/the-cheapest-age-for-car-insurance-2012-07-25 Hagedorn-Hansen, Y. 2018. Transformation of the South African Short-term Insurance Industry: The Case of Santam, 1918-2011 (Doctoral Thesis, University of Johannesburg). Hair, J.F. Celsi, M. Ortinau, D.J. & Bush, R.P. 2013. Essentials of marketing research. New York, NY: McGraw-Hill/Irwin. Hajli, M.N. 2014. A study of the impact of social media on consumers. International Journal of Market Resarch56 (53): 387-404. Hakkak, M, Vahdati, H. & Biranvand, V 2013. An extended technology acceptance model for detecting influencing factors: An empirical investigation. Management Science Letters, 3(11):2795-2804. Hannam, A. 2015. How to use psychology to optimise spending in 3 main types of buyers. https://www.linkedin.com/pulse/how-use-psychology-optimise-spending-3-main-types- buyers-alice-hannam Date of access: 20 June 2020. Hansen, J M. Saridakis, G. & Benson, V. 2018. Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80:197-206. Harker, M. Brennan, R. Kotler, P. & Armstrong, G. 2015. Marketing: An Introduction. Harridge-March, S. & Quinton, S. 2009. Virtual snakes and ladders: social networks and the relationship marketing loyalty ladder. The marketing review, 9(2), pp.171-181. Harris-Ferrante, K. 2012. Top 10 Technologies with the Greatest Impact for the Property and Casualty Insurance Industry. Gartner. Harvey, Steve. 2017. What is the marketing mix, and how does it fit with your brand strategy? https://fabrikbrands.com/what-is-the-marketing-mix/. Date of access: 15 May 2020. Hasan, Ali. 2014. Marketing and Selected Cases, first print, Publisher: CAPS, Yogyakarta. 217 Hashim, K. & Kutbi, I. 2015. ‘Perceptions of social media impact on students’ social behavior: A comparison between arts and science students’. International Journal of Education and Social Science, 2(4):122–131. Hassan, Z. A., Schattner, P., & Mazza, D. (2006). Doing a Pilot Study: Why is it Essential?. Malaysian family physician: the official journal of the Academy of Family Physicians of Malaysia, 1(2-3):70–73. Hattangadi, P. 2014. Is buying insurance online better than buying from an agent. Quora. https://www.quora.com/Is-buying-insurance-online-better-than-buying-from-an-agent Date of access: 17 Nov 2019. Hernández, B., Jiménez, J., & Martín, M.J. 2011. Age, gender and income: do they really moderate online shopping behaviour?. Online information review. Heyhoe, S. 2018. Blog “No one wants to work in the insurance industry!’’. https://www.questback.com/blog/seven-ways-insurance-companies-can-attract-and-develop- diverse-talent/ Date of access: 11 February 2019. Highland Capital Brokerage. 2015. The growing importance of social media for insurance professionals. https://blog.highlandbrokerage.com/social-media-the-growing-importance-of- social-media-for-financial-and-insurance-advisors/ Date of access: 15 April 2019. Hill, S. 2015. How much do online advertisers really know about you? We asked an expert. https://www.digitaltrends.com/computing/how-do-advertisers-track-you-online-we-found- out/ Date of access: 15 Jan 2020. Hippo. 2017. AA Releases Statistics on Car Insurance in South Africa. https://www.hippo.co.za/news/aa-releases-statistics-on-car-insurance-in-south-africa/ Dare of access: 22 Nov 2019. Hoffman, K.D. & Bateson, J.E.G. 2017. Services marketing: concepts, strategies and cases. 5th ed. Boston: Cengage. Holden, M.T. & Lynch, P. 2004. Choosing the appropriate methodology: Understanding research philosophy. The marketing review, 4(4):397-409. Horner, S. & Swarbrooke, J., 2016. Consumer behaviour in tourism. Routledge. 218 Hose, C. 2018. “Examples of societal marketing.” Small business-chrocom. http://smallbusiness.chron.com/examples-societal-marketing-22709.html Date of access:25 January 2019. Hourigan, S R. & Bougoure, U S. 2012. Towards a better understanding of fashion clothing involvement. Australasian Marketing Journal (AMJ), 20(2):127-135. Hsieh, M T. & Tsao, W C. 2014. Reducing perceived online shopping risk to enhance loyalty: a website quality perspective. Journal of Risk Research, 17(2):241-261. Hsuan, T L. & Yazdanifard, R. 2014. The Review of the Most Effective of Online Advertisement Techniques to Affect Online Customer buying Decision. Global Journal of Management and Business Research. Hurn, B.J. 2014. Body language a minefield for international business people. Industrial and commercial training, 46(4):188-193. https://doi.org/10.1108/ICT-01-2014-0004 Hutchison, A. 2017. A customary insurance law?. SA Mercantile Law Journal, 29(1), 17-42. Hvass, K.A. & Munar, A.M. 2012. The takeoff of social media in tourism. Journal of vacation marketing, 18(2):93-103. Insight Survey, 2019. How is technology revolutionizing SA’s short-term insurance industry. https://m.bizcommunity.com/Article/196/19/197463.html Accessed date: 23 April 2020. International Labour Organisation(ILO). 2019. The South African Labour Guide. https://www.labourguide.co.za/most-recent/1810-labour-minister-puts-child-labour-under- spotlight Date of access: 17 February 2020. Internet Society. 2010. African internet history: Highlights. https://www.internetsociety.org/wp-content/uploads/2017/09/history_internet_africa.pdf. Date of access: 05 June 2020. Internet World Stats. 2020. Internet World Stats Usage and Population Statistic. https://www.internetworldstats.com/stats.htm Date of access: 12 Feb 2020. 219 Ismail, N. 2017. Meeting customer demands: the insurance market needs to adapt to digital. https://www.information-age.com/meeting-customer-demands-insurance-market-needs- adapt-digital-123468124/. Date of access: 06 May 2020. Jandaghi, G. Mokhles, A. & Kharazi, H. 2011. Market-orientation and its impact on the performance of Asia Insurance Company in Kerman province. Journal of Economics and Behavioral Studies, 3(1):1-7. Jobber, D. & Ellis-Chadwick, F. 2016. Principles and practice of marketing. 8th McGraw- Hill Higher Education. Jordaan, Y. & Samuel, J. 2015. Grasping service marketing, 3rd ed. Pretoria: Yolanda Jordaan & Melani Prinsloo. Joshua Lyons Marketing. 2019. The Importance of Having Integrated Marketing Communications. Joshua Lyons Marketing. https://www.jjlyonsmarketing.com/the- importance-of-having-integrated-marketing-communications/ Date of access: 20 Feb 2020. Kagan, J. 2018. Black Box Insurance. Investopedia, https://www.investopedia.com/terms/b/black-box-insurance.asp Date of access: 22 Feb 2019 Kakkar, G. 2018. What are the different types of social media? Digital vidya. https://www.digitalvidya.com/blog/types-of-social-media/ Date of access: 12 Feb 2020. Kanibir, H. Saydan, R. & Nart, S. 2014. Determining the antecedents of marketing competencies of SMEs for international market performance. Procedia-Social and Behavioral Sciences, 150, 12-23. Kaplan, A & Haenlein, M. 2014. Collaborative projects (social media application): About Wikipedia, the free encyclopedia. Business horizons, 57(5):617-626. Kaplan, A.M. & Haenlein, M. 2010. Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(51):59-68. Kareh, A. 2018. Evolution of the four Ps: Revisiting the marketing mix. https://www. Forbes. com/sites/forbesagencycouncil Date of access: 22 April 2019. 220 Karimi, B.J. 2014. Impact of Relationship Marketing Practices on Customer Retention in the Insurance Industry in Kenya. MBA Dissertation. University of Nairobi. Karimi, S. 2013. A purchase decision-making process model of online consumers and its influential factoral cross sector analysis. Doctora Thesis Manchester, UK: The University of Manchester. Karimy, M., Zareban, I., Araban, M. & Montazeri, A. 2015. An extended theory of planned behaviour (TPB) used to predict smoking behaviour among a sample of Iranian medical students. International journal of high risk behaviours addiction, 4(3). Kattiyapornpong, U. & Yu, X. 2019. Determinants of the effectiveness of integrated marketing communications (IMC): Insights from volunteer tourism organizations. Journal of Tourism Quarterly, 1(1):14-30. Keegan, W.J.2014. Global marketing management, 8th ed. Harlow, UK: Pearson. Keelson, S.A. 2012. The Evolution of the Marketing Concepts: Theoretically Different Roads Leading to Practically Same Destination!. In Global Conference on Business & Finance Proceedings (7(1);173-183). Institute for Business & Finance Research. Kemp, S. 2019. Digital 2019: Global Internet Use Accelerates. We are social, https://wearesocial.com/blog/2019/01/digital-2019-global-internet-use-accelerates Date of access: 13 Feb 2020. Kemp, S. 2020. Digital 2020: South Africa. https://datareportal.com/reports/digital-2020- south-africa Date of access: 19 April 2020. Keneally, B. 2012. Social media has immediate impact on insurance industry: Experts. https://www.businessinsurance.com/article/00010101/NEWS06/120609918/Social-media- has-immediate-impact-on-insurance-industry-Experts Date of accessed: 15 April 2019. Kenton, W. 2019. Direct Marketing. https://www.investopedia.com/terms/d/direct- marketing.asp Date of access: 11 Feb 2019. Kesharwani, S. Sakar, M P. & Kumari, S. 2018. Marketing Research: An Applied Orientation. Global Journal of Enterprise Information System, 10(2):86-93. 221 Khan-Am, W & Rangsom, K. 2014. Factor affecting selecting web or Facebook channel for online purchasing. International Journal of Applied Computer Technology and Information Systems, 3(2):1-6. Khatib, F. 2016. The impact of social media characteristics on purchase decision empirical study of Saudi customers in Aseer Region. International Journal of Business and Social Science:7(4), 41-50. Khoshku, R. & Farahani, T. 2018. The Role of Market-Orientation on the Financial Statements of Insurance Companies:(Case Study: Representations of Tehran Asia Insurance). International Journal of Innovation in the Digital Economy (IJIDE), 9(1),51-60. Khristy, H. 2017. How technology impacts the insurance sector. http://www.xprimm.com/How-technology-impacts-the-insurance-sector-articol-117,163-9 Kietzmann, J.H. Hermkens, K. McCarthy, I.P. & Silvestre, B.S. 2011. Social Media? Get serious! Understanding the functional building blocks of Social Media. Business Horizons.54, pp.241-251.818.htm Date of access: 07 May 2019. Kim, C. Galliers, R D. Shin, N. Ryoo, J-H. & Kim, J. 2012. Factors influencing Internet shopping value and customer repurchase intention. Electronic Commerce Research and Applications, 11(4):374-387. Kim, H.W. Xu, Y. & Gupta, S. 2012. Which is more important in Internet shopping, perceived price or trust?. Electronic Commerce Research and Applications, 11(3), 241-252. King Price Insurance. 2019. Car insurance: The only car insurance in the world that decreases monthly. https://www.kingprice.co.za/insurance-products/car-insurance/ Date of access: 20 February 2020. King, M. 2014. Corporate blogging and microblogging: An analysis of dialogue, interactivity and engagement in organisation-public communication through social media (Doctoral Thesis). Kiran, P. & Vasantha, S. 2016. Transformation of consumer attitude through social media towards the purchase intention of cars. Indian Journal of Science and Technology, 9 (21). http://www.indjst.org/index.php/indjst/article/viewFile/92608/70193 Date of access: 24 May 2018. 222 Kitapci, O. Akdogan, C. & Dortyol, İ.T. 2014. The impact of service quality dimensions on patient satisfaction, repurchase intentions and word-of-mouth communication in the public healthcare industry. Procedia-Social and Behavioral Sciences, 148, 161-169. Klepek, M. & Starzyczná, H. 2018. Marketing communication model for social networks. Journal of Business Economics and Management, 19(3):500-520. Knoesen, M. 2019. AIE draws some big industry names. https://www.fanews.co.za/article/people-and-companies/12/events/1212/aie-draws-some-big- industry-names/26632 Date of access: 29 April 2019. Koekemoer, L. 2014. Marketing communication: An integrated approach. Juta. Kokemuller, N. 2017. Insurance product definition. Bizfluent. https://bizfluent.com/facts- 6905261-insurance-product-definition.html Date of access: 30 Jan 2019. Kopp, C. M. 2019. Product differentiation. https://www.investopedia.com/terms/p/product_differentiation.asp Date of access: 11 February 2019. Kotler, P. & Armstrong, G. 2014. Principles of marketing: 15th global ed. Harlow: Pearson. Kotler, P. & Keller, K. 2012. A framework for Marketing management, 12th ed. Harlow, UK: Pearson Education Limited. Kotler, P. & Keller, K. L. 2016. Marketing management. 15th ed. New York: Pearson Education Limited. Kotler, P. Burton, S. Deans, K. Brown, L. & Armstrong, G. 2015. Marketing. Pearson Higher Education AU. Kotler, P. Keller, K.L. Ancarani, F. & Costabile, M. 2014. Marketing management 14/e. Pearson. KPMG (Klynveld Peat Marwick Goerdeler). 2017. The truth about online consumers. 2017 Global online consumer report. Available online at: 223 https://assets.kpmg/content/dam/kpmg/xx/pdf/2017/01/the-truth-about-online-consumers.pdf Date of access: 03 May 2019. KPMG (Klynveld Peat Marwick Goerdeler). 2019. The South African insurance industry survey 2019. Johannesburg. https://home.kpmg/content/dam/kpmg/za/pdf/south-african- insurance-survey-2019.pdf Date of access: 04 Feb 2019. Krasnova, H. Veltri, N.F. Eling, N. & Buxmann, P., 2017. Why men and women continue to use social networking sites: The role of gender differences. The Journal of Strategic Information Systems, 26(4):261-284. Kruger, P. 2017. Trends in Motor Insurance. Moonstone, https://www.moonstone.co.za/trends-in-motor-insurance/ 27 Nov 2019. Kumar, A. 2012. Managing marketing mix and communications in a digital era: the role of traditional and new media in a multichannel environment. State University of New York at Buffalo. Kumar, D. 2015. Consumer Behaviour: Includes Online Buying Trends. Oxford University Press. Kumar, R. 2019. Research methodology: A step-by-step guide for beginners: Sage Publications Limited. Kumar, V. & Dange, U. 2012. A study of factors affecting online buying behavior: A conceptual model. Ujwala, A Study of Factors Affecting Online Buying Behavior: A Conceptual Model (August 25, 2012). Kwahk, K.Y& Kim, B. 2017. Effects of social media on consumers’ purchase decisions: evidence from Taobao. Service Business, 11(4):803-829. Kwahk, K.Y. & Ge, X. 2012. The effects of social media on e-commerce: A perspective of social impact theory. In 2012 45th Hawaii international conference on system sciences (pp. 1814-1823). IEEE. Kylliäinen, J. 2019. The importance of innovation-What does it mean for businesses and our society. https://www.viima.com/blog/importance-of-innovation Date of access: 13 December 2019. 224 Lake, l. 2017. Learn about selling orientation. https://www.thebalancesmb.com/what-is- selling-orientation-2295562 Date of access: 24 Feb 209. Lama.2020. Social media statistics and usage in South Africa. Talkwalker 23 july. https://www.talkwalker.com/blog/social-media-stats-south-africa Date of access: 18 August 2020. Lamb, C.W. Hair, J F. & McDaniel, C. 2014. MKTG: Marketing: Cengage Learning. Lamb, C.W. Hair, J.F. & McDaniel, C. 2011. Essentials of marketing: Cengage Learning. ISBN 9780538478342, 672. Lamb, CW. 2012. Marketing. Cengage Learning. Landini, S. 2012. Motor insurance. http://www.aida.org.uk/workpart_motorins.asp Date of access: 13 May 2020. Las Vegas Color Graphics. 2014. Best practices and helpful tips for direct mail for insurance companies. https://www.lasvegascolor.com/tips-direct-mail-for-insurance-companies/ Date of access: 01 May 2019. Lauren, L. 2019. What Is Positioning in a Marketing Plan? https://smallbusiness.chron.com/positioning-marketing-plan-22983.html Date of access:20 Jan 2020. Lazzari, Z. 2018. Examples of sales-oriented business. https://yourbusiness.azcentral.com/examples-salesoriented-business-11277.html Date of access: 24 January 2019. Le Roux, I. & Maree, T. 2016. Motivation, engagement, attitudes and buying intent of female Facebook users. Acta Commercii, 16(1):1-11. Lee, GJ. & Barnes, T. 2016. Factors driving online apparel shopping in South Africa. The Retail Marketing Review, 12(1):33-53. Lee, L. Lee, M J. & Dewald, B. 2016. Measuring the customers’ perception of tangible service quality in the restaurant industry: an emphasis on the upscale dining segment. Journal of Foodservice Business Research, 19(1):21-38. 225 Lee, W. & Paris, C.M. 2013. Knowledge sharing and social technology acceptance model: Promoting local events and festivals through Facebook. Tourism Analysis, 18(14),457-469. Leedy, P.D. & Ormrod, J.E. 2014. Qualitative research. Practical research: Planning and design. Pearson Education. Leefeldt, Ed. 2017. The dangerous rise in uninsured drivers. https://www.cbsnews.com/news/the-dangerous-rise-in-uninsured-drivers/ Date of access: 10 June 2020. Leiner, B.M. Cerf, V.G. Clark, D.D. Kahn, R.E. Kleinrock, L. Lynch, D.C. Postel, J. Roberts, L.G. & Wolff, S. 2012. Internet Society. A brief history of the Internet URL: http://www. internetsociety. org/internet/what-internet/history-internet/brief-history-internet [WebSite Cache ID 6HxW7CLoL]. Levin, M. 1991. The reification-realism-positivism controversy in macromarketing: A philosopher’s view. https://doi.org/10.1177/027614679101100106 Date of access: 17 August 2019. Li, Y M. Lee, Y L. & Lien, N J. 2012. Online social advertising via influential endorsers. International Journal of Electronic Commerce, 16(3):119-154. Likert, R. 1932. A technique for the measurement of attitudes. Archives of psychology. Lim, C-C. & Goh, Y-N. 2019. Investigating the purchase intention toward healthy drinks among Urban consumers in Malaysia. Journal of Foodservice Business Research, 22(3):286- 302. Lim, W.M. & Ting, D.H. 2012. E-shopping: an Analysis of the Technology Acceptance Model. Modern Applied Science, 6(4):49. Lim, Y.J. Osman, A. Salahuddin, S.N. Romle, A.R. & Abdullah, S. 2016. Factors influencing online shopping behavior: the mediating role of purchase intention. Procedia economics finance, 35:401-410. Ling, P. 2012. Introduction to Consumer Behaviour. In action, p.1. http://lib.oup.com.au/he/samples/ling_CBA_sample.pdf Date of access: 03 May 2019. 226 Linton, I. & Shoenberger, E. 2019. The Importance of Integrated Marketing Communications. Small Business-Chron. https://smallbusiness.chron.com/importance- integrated-marketing-communications-73248.html Date of access: 20 Feb 2020. Lobo-Guerrero, L. 2015. World insurance: the evolution of a global risk network. Londre, L.S. 2017. Several Concepts, Terms and Useful Definitions Help Explain and Aid in the Understanding of Marketing and Related Activities, including Marketing Concepts, Marketing Objectives, Strategies and Tactics, Marketing Mix (4P’s), and the Nine P’s (9P’s) of Marketing. International Journal. Londre Marketing Consultant, 6-9. Loras, S. 2015. How to deliver tangible results on social media. Clickz, https://www.clickz.com/how-to-deliver-tangible-results-on-social-media/89803/ Date of access: 19 May 2019. Lorenzo-Romero, C. Alarcón-del-Amo, M.D.C. & Constantinides, E. 2014. Determinants of use of social media tools in retailing sector. Journal of theoretical and applied electronic commerce research, 9(1):44-55. Lovelock, C. & Patterson, P. 2015. Services marketing. Pearson Australia. Lsesu Actuarial Society, 2017. SME insurance market set for digital transformation. https://www.lsesuactsoc.com/single-post/2017/12/08/SME-insurance-market-set-for-digital- transformation Date of access: 05 June 2020. Lucenko, K. & Nørgaard, M.K. 2012. Integrated marketing communications and social media. Unpublished Bachelor thesis. Aarhus School of Business and Social Science. http://pure. au. dk/portal-asb- student/files/45282492/Integrated_Marketing_Communications_and_Social_Media. pdf Date of access: 20 Jan 2019. Luckhoff.C.2018. How much do you need to ear in order to afford a new car? AutoTrader. 27 February. https://www.autotrader.co.za/cars/news-and-advice/automotive-news/how-much- do-you-need-to-earn-in-order-to-afford-a-new-car/3520 Date of access: 15 April 2020. Lukka, V .& James, P.T. 2014. Attitudes toward Facebook advertising. Journal of management and Marketing Research, 14,1. 227 Lunderberg, A. 2019. The different types of digital marketing (and how to use them). https://99designs.com/blog/marketing-advertising/types-digital-marketing/ Date of access 26 May 2020. Madubanya, P.P.M. 2015. The influence of customer relationship management on customer loyalty at a South African life insurance company (Doctoral Thesis, Cape Peninsula University of Technology). Mafikeng Local Municipality .2020b. Mafikeng local municipality integrated development plan 2020-2021. http://www.mahikeng.gov.za/wp-content/uploads/MLM-IDP2020-21.pdf Mafikeng Local Municipality. 2020a. Overview of Mafikeng Local Municipality. http://www.mahikeng.gov.za/overview/ Date of access: 6 October 2020. Mafikeng Local Municipality. 2020b. Overview of Mafikeng Local Municipality. http://www.mahikeng.gov.za/overview/ Date of access: 17 July 2020. Mahapa, J. 2016. South African Short-Term Sector Slow To Embrace Digital – Accenture Study Shows. Accenture, https://www.accenture.com/za-en/company-news-release-short- term-insurance Date of access: 19 May 2019. Maharaj, Y. 2016. Will SA’s short-term insurance industry prosper? https://www.insightsurvey.co.za/blog/will-sas-short-term-insurance-industry-prosper Date of access: 14 February 2019. Mahlangu, T. 2018. The digitalisation of the insurance industry. Cover, https://www.cover.co.za/the-digitisation-of-the-insurance-industry/ Date of access: 07 May 2019. Malembo, Amir. 2015. The Role of Advertisement Media in the Consumer Buying Behaviour: The Case of Fast Jet Tanzania. The Open University Of Tanzania. Malhotra, N K. 2015. Essentials of marketing research: A hands-on orientation. Pearson Essex. Malhotra, N.K. & Malhotra, N.K. 2012. Basic marketing research: Integration of social media. Boston: Pearson. 228 Mangles, C. 2017. How businesses use social media: 2017 report. https://www.smartinsights.com/social-media-marketing/social-media-strategy/businesses- use-social-media-2017-report/ Date of access: 9 May 2020. Manjunath, K.S.K. & Nagabhushanam, M. 2017. Application of Technology Acceptance Model in Consumer Behaviour Towards Internet Purchases. American Association for Science and Technology, 3(3):12-19. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C. & Byers, A.H. 2011. Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute. Mao, Y. Zhu, J.X.& Sang, Y. 2014. Consumer purchase intention research based on social media marketing. International Journal of Business and Social Science, 5(10):1. Maoyan, Z. Sangyang. 2014. Consumer purchase intention research based on social media marketing. International Journal of Business and Social Science, 5(10):92-97. Mapheto, L M. Oni, O A. & Matiza, T. 2014. The Utilisation of Integrated Marketing Communication Strategies by Small Retailers in Mankweng, South Africa. Mediterranean Journal of Social Sciences, 5(15):111. Marcinkiewicz, C. 2011. Nowoczesna koncepcja komunikacji marketingowej jako dialog przedsiębiorstwa z otoczeniem. Prace Naukowe Akademii im. Jana Długosza w Częstochowie. Pragmata tes Oikonomias, (5):103-116. Markgraf, B. 2018. Eight P’s in marketing tourism. https://smallbusiness.chron.com/eight-ps- marketing-tourism-42140.html Date of access: 05 March 2019. Marshall, C. & Rossman, G.B. 2011. Designing qualitative research 5th Edition. California: Sage Publications. Masuku, I. 2018. Car insurance premiums: it’s mostly about you. https://www.sowetanlive.co.za/business/money/2018-06-21-car-insurance-premiums-its- mostly-about-you/ Date of access: 30 January 2019. 229 Matouschek, G. 2017. Global digital small business insurance survey: this time it’s personal. https://www.strategyand.pwc.com/gx/en/insights/2017/digital-sme-insurance-survey.html Date of access: 05 June 2020. Mawson, S. 2016. The Motor Insurance Purchase Decision Journey Revealed. SessionCam https://sessioncam.com/motor-insurance-purchase-decision-journey-revealed/ Date of access: 26 June 2018. Mbanaso, U.M. Dandaura, E.S. Ezeh, G.N. & Iwuchukwu, U.C. 2015. November. The use of social networking service among Nigerian youths between ages 16 and 25 years. In 2015 International Conference on Cyberspace (CYBER-Abuja) (14-21).IEEE. McCabe, S. 2014. The Routledge handbook of tourism marketing. Routledge. McCarthy, C.J. Whittaker, T.A. Boyle, L.H. & Eyal, M. 2017. Quantitative approaches to group research: Suggestions for best practices. The Journal for Specialists in Group Work, 42(1): 3-16. McCarthy, E.J. 1960. Basic marketing: a managerial approach. Homewood, IL: Richard D. Irwin. Inc. 1979 McCarthy Basic Marketing: A Managerial Approach. 1979. McCormick, M. 2016. The 3 types of buyers – And how to deal with them. https://blog.blackcurve.com/the-3-types-of-buyers-and-how-to-deal-with-them Date of access: 20 June 2020. McCusker, K. & Gunaydin, S. 2014. Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 1-6. McCusker, K. & Gunaydin, S. 2015. Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 30(7), 537-542. McDaniel, C. & Gates, R. 2014. Marketing Research. 10th Ed. Washington, DC: Wiley Global Education. McDaniel, C.D. Lamb, C.W. &Hair, J.F. 2013. Introduction to marketing. South-Western Cengage Learning. 230 McKinsey. & Company. 2013. Global Media Report 2013. http://www.mckinsey.com/client_service/media_and_entertainment Date of access: 10 Feb 2019. McKinsey. & Company. 2017. Digital disruption in insurance: cutting through the noise. https://www.mckinsey.com/~/media/mckinsey/industries/financial%20services/our%20insigh ts/time%20for%20insurance%20companies%20to%20face%20digital%20reality/digital- disruption-in-insurance.ashx Date of access: 08 March 2019. Md Husin, M. & Ab Rahman, A. 2016. Do Muslims intend to participate in Islamic insurance? Analysis from theory of planned behaviour. Journal of Islamic Accounting Business Research, 7(1):42-58. Media Update.2019. Infographic: 2019 South African social media stats. AmaSocial. 14 August. https://www.mediaupdate.co.za/social/146925/infographic-2019-south-african- social-media-stats Date of access: 21 March 2020. Meral, H. 2019. The behavioural science on buying insurance. https://www.insurancethoughtleadership.com/the-behavioral-science-on-buying/. Date of access: 27 June 2020. Meskaran, F. Ismail, Z. & Shanmugam, B. 2013. Online purchase intention: Effects of trust and security perception. Australian journal of basic and applied sciences, 7(6):307-315. Metz, J. 2020. Tips for first-time car insurance buyers. https://www.forbes.com/advisor/car- insurance/tips-first-time-car-insurance-buyers/ Date of access: 2 September 2020. Meurer, W.J. & Tolles, J. 2017. Logistic regression diagnostics: understanding how well a model predicts outcomes. Jama, 317(10):1068-1069. Michalaki, P. Quddus, M.A. Pitfield, D. & Huetson, A. 2015. Exploring the factors affecting motorway accident severity in England using the generalised ordered logistic regression model. Journal of safety research, 55:89-97. Middle East insurance review. 2020. South Africa: Around 8 million vehicles are uninsured. https://www.meinsurancereview.com/News/View-NewsLetter- Article?id=60936&Type=Africa# Date of access: 16 May 2020. 231 Milpark Education (Pty) Ltd. 2016. Personal lines STPL101 15a. (Learner Guide). Mir, I.A. & Ur REHMAN, K. 2013. Factors affecting consumer attitudes and intentions toward user-generated product content on YouTube. Management & Marketing, 8(4). Miranda, F.J. Rubio, S. Chamorro, A. & Loureiro, S.M. 2014. Using social networks sites in the purchasing decision process. International Journal of E-Business Research (IJEBR), 10(3):18-35. Miryala, R.K. & Reddy, M.V.R. 2015. Trends, Challenges and Innovations in Management, Vol. ///. Hyderabad, India: Zenon Academic. Mitchell, B. 2020. What are network protocols? Network protocols explained. https://www.lifewire.com/definition-of-protocol-network-817949 Date of access: 17 March 2020. Mkansi, M. & Acheampong, E.A. 2012. Research philosophy debates and classifications: students’ dilemma. Electronic Journal of Business Research Methods, 10(2):132-140. Mohabier, R. 2017. The application of a social networking learning tool in a primary school within South Africa. University of Pretoria. Mohajan, H.K. 2018. Qualitative research methodology in social sciences and related subjects. Journal of Economic Development, Environment and People, 7(1): 23-48. Mokebe, M. 2018. The influence of social media on consumer purchasing decisions for motor insurances products in South Africa. http://wiredspace.wits.ac.za/handle/10539/27882 Date of access: 15 Nov 2019. Mokhothu. M. 2020. Car insurance: The top five reasons why people do not like to pay to insure their ride. The South African. April 19. https://www.thesouthafrican.com/news/finance/car-insurance-the-top-five-reasons-why- people-dont-like-to-pay-to-insure-their-ride/ Moodley, A J. 2019. Digital Transformation in South Africa's Short-Term Insurance Sector: Traditional Insurers' Responses to the Internet of Things (IoT) and Insurtech. The African Journal of Information and Communication, 24:1-16. 232 Moonda, L. 2017. Short-term insurance made easy. https://www.fanews.co.za/article/compliance-regulatory/2/saia-south-african-insurance- association/1081/short-term-insurance-made-easy/21747 Date of access: 14 February 2019. Moonstone. 2018. Short-term Insurance -Latest trends. https://www.moonstone.co.za/short- term-insurance-what-are-the-latest-trends/ Date of access: 28 Oct 2019. Morgan, D.L. 2014. Pragmatism as a paradigm for social research. Qualitative inquiry, 20(8):1045-1053. Moták, L, Neuville, E. Chambres, P. Marmoiton, F. Monéger, F. Coutarel, Fabien. & Izaute, M. 2017. Antecedent variables of intentions to use an autonomous shuttle: Moving beyond TAM and TPB? Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology, 67(5):269-278. Mouakket, S. 2015. Factors influencing continuance intention to use social network sites: The Facebook case. Computers in Human Behavior, 53:102-110. Muguto, V. 2018. Africa’s insurance industry poised for growth. MoneyMarketing, 2018(Oct 2018), 1-1. Muller, J. 2018. SA consumers swarm online but still lag way behind international trends. https://www.businesslive.co.za/bd/companies/retail-and-consumer/2018-11-25-sa- consumers-swarm-online-as-tech-enabled-shopping-makes-strides/ Date of access: 03 May 2019. Municipalities of South Africa. 2012. Map. https://municipalities.co.za/map/142/ngaka- modiri-molema-district-municipality. Date of access: 21 Nov 2019. Municipality of South Africa. 2020. Mahikeng Local Municipality, Demographic information. https://municipalities.co.za/demographic/1203/mahikeng-local-municipality. Date of access: 6 October 2020 Mwakatumbula, H. Moshi, G.C. & Mitomo, H. 2016. Determinants of Consumers’ Knowledge on their Rights in Telecommunication Markets: Case of Tanzania. Int. J. Manag. Public Sect. Inf. Commun. Technol, 7:9-21. 233 Naeem, B. Bilal, M. & Naz, U. 2013. Integrated marketing communication: a review paper. Interdisciplinary journal of contemporary research in business, 5(5):124-133. NAIC (National Association of Insurance Commissioners). 2012. The Use of Social Media in Insurance (2012). South Africa. https://www.naic.org/store/free/USM-OP.pdf Date of access: 12 Feb 209. Nambiar, B. K, Ramanathan, H. N, Rana, S. & Prashar, S. 2018. Perceived service quality and customer satisfaction: A missing link in Indian banking sector. Vision, 23(1):44-55. Napoleonat. 2020. Social media users in South Africa. https://napoleoncat.com/stats/social- media-users-in-south_africa/2020/02 Date of access: 18 July 2020. Nasır, S. 2015. Customer relationship management strategies in the digital era: Business Science Reference. Naujoks, H. Brettel, T. Signh, H. Darnell, D. & Schwedel, A. 2017. Customer behaviour and loyalty in insurance: global; edition 2017. https://www.bain.com/insights/customer-behavior- loyalty-in-insurance-global-2017/ Date of access: 30 January 2019. Naujoks, H. Darnell, D. Schwedel, A. Singh H. & Brettel, T. 2018. Customers Know What They Want. Are Insurers Listening. https://www.bain.com/insights/customers-know-what- they-want-are-insurers-listening/ Date of access: 6 May 2020. Neelankavil, P. J. 2015. International business research. Library of Congress publication. Nepomuceno, M.V. Laroche, M. & Richard, M.O. 2014. How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns. Journal of Retailing and Consumer Services, 21(4):619-629. Netland, T H. & Powell, D J. 2016. The Routledge companion to lean management. Routledge. Ngumba, A. W. & Kagiri, A. 2018. Role of consumer behaviour on the adoption of online shopping in Nairobi city county–a case of Naivas supermarket. European Journal of Business and Strategic Management, 3(2):81-97. 234 Nicholson. L. 2020. Social Media in the Insurance Industry. Blog February 03. https://www.hitsearchlimited.com/news/social-media-in-the-insurance-industry Nicoletti, B. 2016. Innovation in Insurance. Digital Insurance. Springer Nistor, C. 2011. A conceptual model for the use of social media in companies. Available at SSRN 1898670. Nkanjeni. U. 2019. These are the cars you can afford in 2019, based on your monthly salary. Times Live. 04 July. https://www.timeslive.co.za/news/south-africa/2019-07-04-these-are- the-cars-you-can-afford-in-2019-based-on-your-monthly-salary/ Norman, K. 2020. How to estimate car insurance before buying a car. https://www.nerdwallet.com/blog/insurance/estimate-car-insurance/ Date of access:28 September 2020. Notsi, P.Y. 2012. Financial reporting as a tool for promoting accountability. Cape Town: Juta. Novikov, A.M. &Novikov, D.A. 2013. “Research Methodology: From Philosophy of Science to Research Design” CRC Press Novikov, A.M. &Novikov, D.A. 2013. “Research Methodology: From Philosophy of Science to Research Design” CRC Press Nyagucha, M.A. 2017. Impact of Social Media on Consumer's Decision Making Process among the Youth in Nairobi (Doctoral dissertation, United States International University- Africa). O’Leary, Z. 2010. The essential guide to doing your research project. Odunlami, I.B. & Akinruwa, T.E. 2014. Effect of Promotion on Product Awareness. International Journal of Education and Research, 2(9), 451-472. OECD (Organisation for Economic Co-operation and Development). 2017. Technology and innovation in the insurance sector. https://www.oecd.org/pensions/Technology-and- innovation-in-the-insurance-sector.pdf Date of access: 10 June 2019. 235 Ogbonna, B.U. & Ogwo, O.E. 2013. Market orientation and corporate performance of insurance firms in Nigeria. international Journal of Marketing studies, 5(3), 104. O'Leary, Z. 2017. The essential guide to doing your research project. Sage. Olivier, G. 2018. An analysis of e-tailing opportunities in the South African sports business industry. North-West University. Opiyo, E. 2016. Why internet use is low in Africa. SciDev. https://www.scidev.net/global/icts/news/internet-africa-local-content.html Date of access: 13 Feb 2020. O'Reilly, T. 2009. What is web 2.0. "O'Reilly Media, Inc." Organ, T. 2014. How life insurers can differentiate themselves in the marketplace. https://www.thinkadvisor.com/2014/01/07/how-life-insurers-can-differentiate-themselves- in/?slreturn=20190111044507 Date of access: 11 February 2019. Ornico. 2018. SA's Indispensable Social Media Landscape. http://website.ornico.co.za/wp- content/uploads/2017/10/SML2018_Executive-Summary.pdf Date of access: 15 April 2020. Ortinau, D J. Hair, J .F. Bush, R P. & Celsi, M. W. 2013. Essentials of Marketing Research: McGraw-Hill. OUTsurance. 2011. The R400 and R800 quote promotions. https://www.outsurance.co.za/car-insurance/r400promo/ Date of access: 20 February 2020. Oxford Business Group. 2016. South African insurance sector undergoes a period of transformation. https://oxfordbusinessgroup.com/overview/opportunity-and-challenge-sector- midst-far-reaching-transformations Date of access: 21March 2018. Pahwa, A. 2018. What is public relations? PR functions, types, & examples. https://blog.hubspot.com/marketing/public-relations-definition Date of access: 08 April 2019. Palmer, A. 2011. Principles of services marketing. 6th ed. Maidenhead: McGraw-Hill. Pan, J Y & Truong, D. 2018. Passengers’ intentions to use low-cost carriers: An extended theory of planned behavior model. Journal of Air Transport Management, 69:38-48. 236 Pande, A. C. & Soodan, V. 2015. Role of consumer attitudes, beliefs and subjective norms as predictors of purchase behaviour: a study on personal care purchases. The Business & Management Review, 5(4):284. Panhwar, A.H. Ansari, S. & S. A.A. 2017.Post-positivism: An effective paradigm for social and education research. https://www.researchgate.net/publication/317605754_Post- positivism_An_Effective_Paradigm_for_Social_and_Educational_Research Date of access: 20 February 2018. Paquette, H. 2013. Social Media as a Marketing Tool: A Literature Review (Major Papers by Master of Science Students. Paper 2). Parasuraman, A. Berry, L & Zeithaml, V. 2002. Refinement and reassessment of the SERVQUAL scale. Journal of retailing, 67(4):114-139. Parrick, Mikaela. 2018. Why Don’t Millennials Want to Work in Insurance? https://brownandjoseph.com/blog/why-dont-millennials-want-work-insurance/. Date of access: 15 May 2020. Patel, N. 2017a. How to appeal to the three main types of buyers. https://www.crazyegg.com/blog/3-types-of-buyers/ Date of access: 20 June 2020. Patel, S. 2017b. The Importance of Building Culture in Your Organization. https://www.inc.com/sujan-patel/importance-of-building-culture-in-your-organization.html Date of access:15 May 2020. Patten, M L & Newhart, M. 2017. Understanding research methods: An overview of the essentials: Routledge. Pearson, O. 2017. What is direct marketing in the insurance sector? https://pocketsense.com/direct-marketing-insurance-sector-5796285.html Date of access: 30 April 2019. Pearson, R & Yoneyama, T. 2015. Corporate forms and organizational choice in international insurance. Oxford University Press. Percy, L. 2014. Strategic integrated marketing communications. New York: Routledge. 237 Percy, L. 2016. Strategic advertising management: Oxford University Press. Pew Research Center.2019. Social media fact sheet. Internet & Technology. June 12. https://www.pewresearch.org/internet/fact-sheet/social-media/ Date of access:16 October 2020 Pfukwa, A. 2015. The motor insurance industry in South Africa: a survival analysis (Doctoral Thesis). Phophalia, A. K. 2010. Modern research methodology: New trends and techniques. Paradise Publishers. Pignotti, Michelle. 2019. How can B2B companies tackle the SME sweet spot? https://www.linkedin.com/pulse/how-can-b2b-companies-tackle-sme-sweet-spot-michele- pignotti Date of access: 05 June 2020. Pinho, J.C.M.R. & Soares, A.M. 2011. Examining the technology acceptance model in the adoption of social networks. Journal of Research in Interactive Marketing, 116-129. Plaksij, Z. 2019. Sales process. A roadmap to better sales performance. https://www.superoffice.com/blog/sales-process/ Date of access: 23 April 2019. Pluta-Olearnik, M. 2018. Integrated marketing communication—concepts, practice, new challenges. Marketing of Scientific Research Organizations, 28(2):121-138. PMD (Prime Meridian Direct). 2018. Why Don’t All South African Car Owners Have Car Insurance? https://prime.co.za/news/south-african-car-owners-car-insurance/ Date of access: 01 Aug 2019. PMD (Prime Meridian Direct). 2019. Compulsory Third Party Car Insurance in South Africa – Any Progress in 2019?, https://prime.co.za/news/compulsory-third-party-car-insurance-in- south-africa-any-progress-in-2019/ Date of access: 22 Nov 2019. PMD (Prime Meridian Direct). 2020. What are the Potential Benefits of Comprehensive Car Insurance in 2020?. https://prime.co.za/news/what-are-the-potential-benefits-of- comprehensive-car-insurance-in-2020/ Date of access: 22 May 2020. 238 Podium. 2017. Consumers Get "Buy" With a Little Help From Their Friends. http://learn.podium.com/rs/841-BRM-380/images/2017-SOOR-Infographic.jpg Date of access: 31 October 2019. Population city. 2020. Mafikeng Population. http://population.city/south-africa/mafikeng/ Date of access: 9 October 2020. Powers, T. Advincula, D. Austin, M.S. Graiko, S. & Snyder, J. 2012. Digital and social media in the purchase decision process: A special report from the Advertising Research Foundation. Journal of advertising research, 52(4):479-489. Prachi, M., 2019. Service marketing. https://theinvestorsbook.com/service-marketing.html Date of access: 11 May 2020. Prasetyo, D.B. & Nuzula, F.A. 2015. Integrated marketing communications (IMC) strategy of Banyuwangi Regency’s Government in effort to introduce the potential of local tourism. The SIJ Transactions on Industrial, Financial & Business Management (IFBM), 3(6), 99-102. Pride, W.M. & Ferrell, O.C. 2013. Foundations of marketing, 5th ed. Mason, OH: Cengage Learning. PRSA, (Public Relations Society of America). 2012. Public relations defined: a modern definition for the new era of public relations. http://prdefinition.prsa.org/ Date of access: 08 April 2019. Putra, A. 2018. Factors influencing the adoption of M-commerce in Indonesia: a study of TAM and TPB integration model (Doctoral Thesis). Putro, H.B. & Haryanto, B. 2015. Factors affecting purchase intention of online shopping in Zalora Indonesia. Journal of Economics, Management and Trade.1-12. Pütter, M. 2017. The Impact of Social Media on Consumer Buying Intention. Journal of International Business Research and Marketing, 3(1):7-13. PWC (Price Waterhouse Coopers). 2014. Africa insurance trends. https://www.pwc.co.za/en/assets/pdf/south-african-insurance-2014.pdf Date of access: 22 Feb 2019. 239 PwC (Price Waterhouse Coopers)a. 2016. Insurance through challenging times: Insurance industry. https://www.pwc.co.za/en/assets/pdf/insurance-industry-analysis-2016pdf.pdf Date of access: 04 Feb 2020. PWC (Price WaterhouseCoopers)b. 2016. Prospects in the Retail and Consumer goods Sector in ten Sub-Saharan countries. https://www.pwc.co.za/en/assets/pdf/retail-in-africa.pdf Date of access: 20 April 2020. PWC (PricewaterhouseCoopers). 2018. African insurance industry poised for growth. https://www.pwc.co.za/en/assets/pdf/south-african-insurance-2018.pdf Date of access: 31 Oct 2019. Quain, S. 2018. Difference between product orientation and production orientation. https://smallbusiness.chron.com/difference-between-product-orientation-production- orientation-16004.html Date of access: 24 January 2019. Qualman, E. 2011. How social media transforms the way we live and do business. Ipswich, MA: Business Book Summaries. Raidió Teilifís Éireann. 2016. One in 14 private vehicles on Irish roads now uninsured. https://www.rte.ie/news/2016/1219/839842-uninsured-drivers-motor-insurance/ Date of access: 27 Nov 2019. Rajgopaul. D. 2017. Why women pay less for insurance, yes you are better drivers. https://www.iol.co.za/business-report/economy/why-women-pay-less-for-insurance-yes-you- are-better-drivers-10705483 Date of access: 25 March 2019. Rapcsák, D. 2019. The Benefits of Building an Online Community. vcc.live blog (https://vcc.live/blog/benefits-online-community/ Date of access: 12 Feb 2020. Rhys, C. 2013. Top technologies with the greatest impact of the South African insurance industry in 2013 and beyond. FAnews. https://www.fanews.co.za/article/technology/41/general/1204/top-technologies-with-the- greatest-impact-for-the-south-african-insurance-industry-in-2013-and-beyond/13036 Date of access: 20 May 2019. 240 Richa, D. 2012. Impact of demographic factors of consumers on online shopping behaviour: A study of consumers in India. International journal of engineering and management sciences, 3(1):43-52. Richards, L. 2018. The importance of product positioning to the marketing plan. https://smallbusiness.chron.com/importance-product-positioning-marketing-plan-24275.html Date of access: 14 February 2019. Richardson, N. & Gosnay, R.M. 2010. A quick start guide to social media marketing: high impact low-cost marketing that works. Kogan Page Publishers. Rick, S I, Cryder, C E. & Loewenstein, G. 2008. Tightwads and spendthrifts. Journal of consumer research, 34(6):767-782. Rinehart-Smit, K, Johnson, C. & Chamberlain, D. 2018. The potential of digital platforms as distributors and enablers of insurance in Africa. Cenfri. https://cenfri.org/articles/the- potential-of-digital-platforms-as-distributors-and-enablers-of-insurance-in-africa/ Date of access: 04 Fe 2020. Rodney, G. & Wakeham Dr, M. 2016. Social media marketing communications effect on attitudes among millennials in South Africa. The African Journal of Information Systems, 8(3):2. Roesler, P. 2015. How social media influences consumer buying decisions. Bizjournals, https://www.bizjournals.com/bizjournals/how-to/marketing/2015/05/how-social-media- influences-consumer-buying.html Date of access: 14 Jan 2019. Rogala, A. 2015. Towards a new paradigm of integrated marketing communication? (In. DIEM: Dubrovnik International Economic Meeting organised by: Sveučilište u Dubrovniku. 698-709). Rooderkerk, R P. & Pauwels, K H. 2016. No comment?! The drivers of reactions to online posts in professional groups. Journal of Interactive Marketing, 35:1-15. Rosenthal, B. & Brito, E.P. 2017. How virtual brand community traces may increase fan engagement in brand pages. Business Horizons, 60(3):375-384. 241 Rosiek, J.L. 2013. Pragmatism and post-qualitative futures. International Journal of Qualitative Studies in Education, 26(6):692-705. Rouse, M. 2013. Positioning. https://whatis.techtarget.com/definition/positioning Date of access: 14 February, 2019. Rudden, J. 2019. Rate of insurance penetration in Sub-Saharan Africa in 2017, by country. Statista, https://www.statista.com/statistics/727403/insurance-penetration-in-sub-saharan- africa-by-country/ Date of access: 07 Mars 2020. Ryan, D. 2017. Understanding Digital Marketing: Marketing Strategies for Engaging the Digital Generation. 4thed. Kogan Page Ltd. New York. Ryke, L. 2019. Consumer buying behaviour in online fashion retail: a study of South African millennial males (Doctoral Thesis, Stellenbosch: Stellenbosch University). SA people contributor. 2020. Third-party car insurances: 70% of cars in South Africa are not insured. April 1. https://www.sapeople.com/2020/04/01/third-party-car-insurances-70-of- cars-in-south-africa-are-not-insured/ Date of access: 15 July 2020. Safeena, R. Date, H. Hundewale, N. & Kammani, A. 2013. Combination of TAM and TPB in internet banking adoption. International Journal of Computer Theory and Engineering, 5(1):146. SAIA (South African Insurance Association). 2013. The SAIA code of conduct. https://www.hollard.co.za/binaries/content/assets/hollardcoza/pages/about-us/legal- requirements/south-africa/saia-code-of-conduct-2013.pdf Date of access: 23 September 2019. SAIA (South African Insurance Association). 2017. Annual review: partnering for a secure and inclusive future. file:///C:/Users/NWUUser/Downloads/annual-review-2017-p.pdf Date of access: 31 Aug 2018. Sakara, A. & Alhassan, F. 2014. An assessment of sales promotion as effective tool for customer retention in telecommunications industry of ghana. International Journal of Economics Commerce and Management, 2(10). 242 Sam, E.J. 2019. Why Smart Insurance Companies are Going Direct to Consumer. Globalwebindex. https://blog.globalwebindex.com/marketing/direct-to-consumer-insurance/ Date of access: 15 Jan 2020. Sanders, D. 2017. Insurance distribution channels. https://www.cii.co.uk/learning- index/articles/insurance-distribution-channels/46267 Date of access: 13 March 2019. Santam. 2016. Integrated report. https://www.santam.co.za/media/2682253/santam-ir- 2016.pdf Date of access: 02 May 2020. Santam.2018. Integrated report. https://www.santam.co.za/media/2684712/santam_ir_- 2018.pdf Date of access: 14 May 2020. Saraswathy, M. 2016. Insurance firms launch consumer awareness drive. https://www.business-standard.com/article/finance/insurance-firms-launch-consumer- awareness-drive-116010500785_1.html Date of access: 16 March 2019. Saravanakumar, M. & SuganthaLakshmi, T. 2012. Social media marketing. Life Science Journal, 9(4), 4444-4451. Sarkis Jr, A.M. 2017. A comparative study of theoretical behaviour change models predicting empirical evidence for residential energy conservation behaviours. Journal of Cleaner Production, 141:526-537. Sarmah, H.K. Hazarika, B.B. & Choudhury, G. 2013. An investigation on effect of bias on determination of sample size on the basis of data related to the students of schools of Guwahati. International Journal of Applied Mathematics & Statistical Sciences (IJAMSS), 2(1):33-48. Sarno, A. 2012. PR tips for insurance companies. https://everything-pr.com/public-relations- insurance-company/ Date of access: 08 March 2019. Sassian, M. 2018. What motivates people to shop for auto insurance? A study conducted by Facebook and ComScore. http://www.iii.org/insuranceindustryblog/what-motivates-people- to-shop-for-auto-insurance-a-study-conducted-by-facebook-and-comscore/ Date of access: 03 May 2019. 243 Saunders, M N.K. 2011. Research methods for business students, 5/e: Pearson Education India. Saunders, M. Lewis, P. & Thornhill, A. 2012. Research methods for business students (6. utg.). Harlow: Pearson. Saunders, M.N. & Lewis, P. 2012. Doing research in business & management: An essential guide to planning your project. Pearson. Sentosa, I. & Mat, N.K.N. 2012. Examining a theory of planned behavior (TPB) and technology acceptance model (TAM) in internet purchasing using structural equation modelling. Researchers’ World, 3(2 Part 2):62. Seric, M. Saura, I.G. & Mikulic, J. 2016. Exploring integrated marketing communications, brand awareness, and brand image in hospitality marketing: a cross-cultural approach. Sethna, Z. & Blythe, J. 2016. Consumer behaviour. Sage. Shabalala, N.C. 2016. The Impact of mobile offices as a mode of service delivery by the Department of Home Affairs in Ngaka Modiri Molema District Municipality (North West Province) (Doctoral Thesis, North-West University (South Africa)). Shameem, B. & Gupta, S. 2012. Marketing strategies in life insurance service. International Journal of Marketing, Financial Services & Management Research, 1(11):132-141. Sharpe, D. 2015. Chi-Square Test is Statistically Significant: Now What?. Practical Assessment, Research, and Evaluation, 20(1), 8. Shaw, A. 2018. How Social Media Can Move Your Business Forward Forbes. https://www.forbes.com/sites/forbescommunicationscouncil/2018/05/11/how-social-media- can-move-your-business-forward/#6db6d4a34cf2 Date of access: 12 Feb 2020. Shelford, D. 2018. Ways social media is changing the insurance industry. https://crewdo.com.au/social-media-impact/ Date of access: 15 April 2019. Shen, B. & Bissell, K. 2013. Social media, social me: A content analysis of beauty companies’ use of Facebook, in marketing and branding. Journal of Promotion Management, 19, 629–651. DOI: 10.1080/10496491.2013.829160. 244 Sheppard, B.H., Hartwick, Jon & Warshaw, P. R 1988. The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of consumer research, 15(3):325-343. Sherman. 2019. Digital Marketing vs Traditional Marketing: Which Produces Better ROI? Lyfe Marketing (Vol. 2019.). US. https://www.lyfemarketing.com/blog/digital-marketing-vs- traditional-marketing/ Date of access: 11 February 2020. Shetty, S. 2015. What comes to mind when you hear "Tangible Advertising?". Zhenyu Technology Pvt. Ltd https://specialties.bayt.com/en/specialties/q/150546/what-comes-to- mind-when-you-hear-quot-tangible-advertising-quot/ Date of access:15 July 2019. Shi, H. Wang, S. & Zhao, D. 2017. Exploring urban resident’s vehicular PM2. 5 reduction behavior intention: An application of the extended theory of planned behavior. Journal of cleaner production, 147:603-613. Shimp, T.A. & Andrews, J.C. 2013. Integrated marketing communications. Integrated Marketing Communications. Silver, L. Stevens, R E. Wrenn, B. & Loudon, D L. 2012. The essentials of marketing research. Routledge. Simplilearn. 2020. Traditional Marketing vs. Digital Marketing: Which One Is Better. Available at https://www.simplilearn.com/traditional-marketing-vs-digital-marketing-article Date of access 26 May 2020. Simpson, A. G. 2018. Insurtech partnership: what insurers want and get. https://www.insurancejournal.com/magazines/mag-features/2018/10/15/503988.htm Date of access: 18 May 2020. Slack, N. & Brandon-Jones, A. 2018. Operations and process management: principles and practice for strategic impact. Pearson UK. Smith, J. 2014. The 3types of buyers, and how to optimize for each one. https://www.neurosciencemarketing.com/blog/articles/3-types-buyers.htm Date of access: 20 June 2020. 245 Sperandei, S. 2014. Understanding logistic regression analysis. Biochemia medica, 24(1):12- 18. Srilal, P. S. 2016. The importance of marketing mix to the travel, tourism and hospitality management and analyse the pricing strategies and policies. https://www.slideshare.net/PaulSolaman/the-importance-of-marketing-mix-to-the-travel- tourism-and-hospitality-management-and-analyse-the-pricing-strategies-and-policies Date of access: 05 March 2019.[PowerPoint presentation]. Srivastava, K. & Sharma, N.K. 2013. Service quality, corporate brand image, and switching behavior: The mediating role of customer satisfaction and repurchase intention. Services Marketing Quarterly, 34(4), 274-291. Staff Report. 2019. 70% consumers would share more data if there was a perceived benefit. BusinessReport. https://www.iol.co.za/business-report/technology/70-consumers-would- share-more-data-if-there-was-a-perceived-benefit-19127835 Date of access: 03 Feb 2020. Standberry, S. 2019. Digital Marketing vs Traditional Marketing: Which Produces Better ROI? Lyfe Marketing (Vol. 2019.). US. Stat SA (Statistics South Africa). 2016a. Community survey 2016 provincial profile: North West. Statssa, http://cs2016.statssa.gov.za/wp-content/uploads/2018/07/NorthWest.pdf Date of access: 13 July 2019. Stat SA (Statistics South Africa). 2016b. South African Community Survey 2016. Indicators derived from the full population Community Survey. Date of access: 22 June 2019. Statcounter. 2020. Social Media Stats South Africa (Jan 2019 – Jan 2020). https://gs.statcounter.com/social-media-stats/all/south-africa Date of access: 12 Feb 2020. Statista. 2019. Number of social network users worldwide from 2010 to 2021 (in billions). https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/ Date of access: 12 Feb 2020. 246 Ster, V. D. W. (1993). Marketing en Detailhandel (Marketing and Retailing). The Netherlands: Groningen, Wolters-Noordhoff, 328. Still, L. & Stokes, G. 2016. Short Term Insurance in South Africa 2016/17. https://aon.co.za/Assets/docs/publications/Short_Term_Insurance_in_South_Africa_2016- 17_Condensed_Version.pdf Date of access: 02 May 2020. Stokes, R. 2013. eMarketing: The essential guide to marketing in a digital world: Independent. Storm, M. 2020. 5 types of social media and examples of each. https://www.webfx.com/blog/social-media/types-of-social-media/ Date of access: 07 September 2020. Survey Police .2015. How to determine the sample size for an online survey. March 7, https://www.surveypolice.com/blog/how-to-determine-the-sample-size-for-an-online-survey/ Date of access: 3 October 2020. Swiegers, L. 2018. Perceived risk barriers to online shopping: experiences of technologically enabled generation y consumers (Doctoral Thesis, Stellenbosch: Stellenbosch University). Taber, K.S. 2018. The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res Sci Educ 48, 1273–1296 (2018). https://doi.org/10.1007/s11165-016-9602-2 Date of access: 07 April 2019. Taheri, M. Qarache, H.A. Qarache, A.A. Yoosefi, M. 2015. The effects of zinc-oxide nanoparticles on growth parameters of corn (SC704). DOI: 10.17975/sfj-2015-011 Date of access: 18 April 2018. Taprial, V. & Kanwar, P., 2012. Understanding social media. Bookboon. Tay, L. & Diener, E. 2011. Needs and subjective well-being around the world. Journal of Personality and Social Psychology. http://academic.udayton.edu/jackbauer/Readings%20595/Tay%20Diener%2011%20needs%2 0WB%20world%20copy.pdf Date of access: 28 January 2019. 247 Tayengwa, S. 2017. Digital transformation - the new-age insurer. Johannesburg: TransUnion Africa. https://www.cover.co.za/wp-content/uploads/2017/09/Digitisation-In-Insurance- Presentation-SamuelT-1.pdf Date of access: 4 Feb 2019. Tekletsion, A. 2019. The effect of marketing mix on consumer buying behaviour of small and medium enterprises (SMEs) in Addis Ababa. (The case of lideta, kolfe-keraniyo and arada sub cities). (Master dissertation). The Digital Age. 2018. The social media fury and the insurance market: Data as an asset and hazard. The digital age at the University of the New South Wales. August 24. https://blogs.unsw.edu.au/thedigitalage/blog/2018/08/the-social-media-fury-and-the- insurance-market-data-as-an-asset-and-hazard/ Date of access: 10 April 2020. Theaker, A. 2012. The public relations handbook, 4th ed. New York: Routledge. Thompson, R. 2018. Opinion: five consumer spending trends to watch out for in 2018. https://www.iol.co.za/business-report/opinion/opinion-five-consumer-spending-trends-to- watch-out-for-in-2018-13148720 Date of access: 03 May 2019. Thurairaj, S. Hoon, E.P. Roy, S.S. & Fong, P.W. 2015. Reflections of Students' Language Usage in Social Networking Sites: Making or Marring Academic English. Electronic Journal of e-Learning, 13(4):302-316. Tlapana, T.P. 2017. Customer service as a strategic tool amongst independent retail food chains in KwaZulu-Natal (Doctoral Thesis). Tolles, J. & Meurer, W J. 2016. Logistic regression: relating patient characteristics to outcomes. Jama, 316(5):533-534. Tong, A. Flemming, K. McInnes, Oliver, E. S. & Craig, J. 2012. Enhancing transparency in reporting the synthesis of qualitative research: Entreq. BMC Medical Research Methodology, 12:181. Tripathi, S. 2014. Factors influencing the technology acceptance of social media in India: a literature Review and research agenda for future. Journal of Advances in Computer Science and Information Technology (ACSIT), 1(2):43-47. 248 Tsao, W. & Yang, F. 2017. Factors that influence the intention to use mobile shopping platforms, which feature virtual shelves and QR codes – Based on TAM. International Review of Management and Business Research, 6(2):758-776. Tse, T.S. & Zhang, E.Y. 2013. Analysis of blogs and microblogs: A case study of Chinese bloggers sharing their Hong Kong travel experiences. Asia Pacific Journal of Tourism Research, 18(4):314-329. Tuten, L.T. & Solomon, R.M. 2015. Social Media Marketing. 2nd edition. Tuten, T.L. & Solomon, M.R. 2017. Social media marketing. Sage. Unmetric. 2017. 6 social media trends in the South African insurance industry. https://unmetric.com/resources/6-social-media-trends-in-the-south-african-insurance-industry Date of access: 21 September 2020. Valos, M.J. Habibi, F.H. Casidy, R. Driesener, C.B. & Maplestone, V.L. 2016. Exploring the integration of social media within integrated marketing communication frameworks. Marketing Intelligence & Planning. Van der Ross, R. 2015. Identifying the benefits of social media within large financial institutions in South Africa. University of the Western Cape. Van Eeden, J. 2017. Technology is disrupting Africa’s insurance industry. https://mg.co.za/article/2017-02-24-00-technology-is-disrupting-africas-insurance-industry Date of access: 07 May 2019. Van Heerden, C.H. & Drotsky, A. 2014. Personal selling. Cape Town: Juta. Vasić, N, Kilibarda, M. & Kaurin, T. 2019. The influence of online shopping determinants on customer satisfaction in the Serbian market. Journal of theoretical and applied electronic commerce research, 14(2):0-0. Vergni, L. Todisco, F. Di Lena, B. & Mannocchi, F. 2020. Bivariate analysis of drought duration and severity for irrigation planning. Agricultural Water Management, 229, 105926. Verhoef, G. 2012. South Africa: Leading African Insurance. (In. World insurance: the evolution of a global risk network organised by: Oxford University Press. p. 325-348). 249 Vinerean, S., Cetina, I., Dumitrescu, L. & Tichindelean, M., 2013. The effects of social media marketing on online consumer behaviour. International Journal of Business and Management, 8 (14):66. Viswambharan, A.P. & Priya, K.R. 2016. Documentary analysis as a qualitative methodology to explore disaster mental health: insights from analysing a documentary on communal riots. Qualitative research, 16(1):43-59. Vivek, S D. Beatty, S E. & Morgan, R M. 2012. Customer engagement: Exploring customer relationships beyond purchase. Journal of marketing theory and practice, 20(2):122-146. Vongkhamheng, L. 2017. Integrated marketing communication strategies for SME firms in the tourism sector in Laos (Master's Dissertation). Voramontri, D. & Klieb, L. 2019. Impact of social media on consumer behaviour. International Journal of Information and Decision Sciences, 11(3):209-233. Vosloo, J.J. 2014. Chapter 6: Data analysis and interpretation. Data Analysis and Interpretation, 449(53), 316-324. Waite, K & Pérez-Vega, R. 2018. Essentials of Digital Marketing. Walia, R. 2015. A Saga of Qualitative Research. Social Criminol, 5(2):124. Wang, S. Fan, J. Zhao, D. Yang, S. & Fu, Y.J.T. 2016. Predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behaviour model. 43(1):123-143. Wang, Y. 2017. Online Purchase Intention Based on TAM and IAM: A literature review. International Journal of e-Education, e-Business, e-Management and e-Learning, http://www.ijeeee.org/vol8/445-BM0010.pdf Date of access: 26 Feb 2019. Warayuanti, W. & Suyanto, A.M.A. 2015. The influence of lifestyles and consumers attitudes on product purchasing decision via online shopping in Indonesia. European journal of business and management, 7(8), 74-80. We are social. & Hootsuite’. 2019. Digital in 2019. https://wearesocial.com/uk/digital-2019 Date of access: 07 June 2020. 250 We are social. 2018. Global digital report. https://digitalreport.wearesocial.com/ Date of access: 16 Nov 2019. Westbrook, R. Karlgaard, T. White, C. & Knapic, Jo. 2012. A holistic approach to evaluating social media’s successful implementation into emergency management operations: Applied research in an action research study. International Journal of Information Systems for Crisis Response and Management (IJISCRAM), 4(3):1-13. Wheels24. 2018. Five things to consider when choosing car insurance. https://www.wheels24.co.za/News/Guides_and_Lists/5-things-to-consider-when-choosing- car-insurance-20180124 Date of access: 14 February 2019. White, A. 2016. Online sales vs. in-store sales. http://www.bizcommunity.com/Article/196/754/143990.html Date of access: 19 Mars 2020. Wild, J & Diggines, C. 2013. Marketing research. 2nd Cape Town: Juta & Company Ltd. Williams, J. 2016. Social media marketing strategies for rapid growth. Routledge. Williams. R. 2020. 90% of people buy from brands they follow on social media, study says. Mobile marketer. May 5. https://www.mobilemarketer.com/news/90-of-people-buy-from- brands-they-follow-on-social-media-study-says/577342/ Wilson, J. 2014. Essentials of business research: A guide to doing your research project: Sage. Wirtz, J. & Lovelock, C. 2018. Service Marketing Communications. WS Professional. Wolber, A. 2012. Use Google Forms to create a survey. techrepublic. com. Dosegljivo: http://www. techrepublic. com/blog/google-in-the-enterprise/use-google-forms-to-create-a- survey Date of access: 19 June 2019. Woodall, G. & Colby, C. 2011. The results are in: social media techniques vs. focus groups for qualitative research. MRA’s Alert, pp.23-27. World Development Report. 2016. Digital Dividends. https://www.worldbank.org/en/publication/wdr2016 Date of access: 15 November 2019. 251 World Wide Worx. 2012. Social media breaks barriers in SA. http://www.worldwideworx.com/socialmedia2012/ Date of access: 13 June 2020. Wright, A I. 2015. Security risk and social presence in E-commerce. Writer. S. 2019c. South Africans spend over 8 hours a day online – and a third of that time is spent on social media. BusinessTech. 1 February. https://businesstech.co.za/news/internet/296716/south-africans-spend-over-8-hours-a-day- online-and-a-third-of-that-time-is-spent-on-social-media/ Date of access: 17 February 2020. Writer.S. 2019b. How much money South Africans consider’s enough’ to earn each month. BusinessTech. 22 July. https://businesstech.co.za/news/wealth/330557/how-much-money- south-africans-consider-enough-to-earn-each-month/ Date of access: 09 February 2020. Yang, H. Lee, H. & Zo, H. 2017. User acceptance of smart home services: an extension of the theory of planned behavior. Industrial Management & Data Systems, 117(1):68-89. Ye, L,R. & Zhang, H-H. 2014. Sales promotion and purchasing intention: Applying the technology acceptance model in consumer-to-consumer marketplaces. International Journal of Business, Humanities Technology, 4(3):1-5. Yeboah, A. & Atakora, A. 2013. Integrated marketing communication: How can it influence customer satisfaction. European Journal of Business and Management, 5(2):41-57. Yin, X. Wang, H. Xia, Q. & Gu, Q. 2019. How Social Interaction Affects Purchase Intention in Social Commerce: A Cultural Perspective. Sustainability, 11(8):2423. Youngman, W. 2014. How people buy car insurance: Part 2: The role of the brand. https://blog.gfk.com/2014/08/how-people-buy-car-insurance-part-2-the-role-of-the-brand/ Date of access: 22 Feb 2019. Yu, T.W. & Chen, T.J. 2018. Online travel insurance purchase intention: a transaction cost perspective. Journal of Travel & Tourism Marketing, 35(9):1175-1186. Yu, Y. Yi, W. Feng, Y. & Liu, J. 2018. Understanding the Intention to Use Commercial Bike-sharing Systems: An Integration of TAM and TPB. In. Proceedings of the 51st Hawaii International Conference on System Sciences organised by.???? 252 Yüksel, H.F. 2016. Factors affecting purchase intention in YouTube videos. The Journal of Knowledge Economy & Knowledge Management, 11(2):33-47. Yupei, H. 2019. China-Africa Joint Endeavor on the Digital Silk Road: Opportunities, Challenges and Approaches. China Int'l Stud., 78:13. Zarrad, H. & Debabi, M. 2015. Analyzing the effect of electronic word of mouth on tourists’ attitude toward destination and travel intention. International research journal of social sciences, 4(4):53-60. ZenithOptimedia. 2015. Internet use to drive 1.4% increase in media consumption in 2015. https://www.zenithmedia.com/internet-use-drive-1-4-increase-media-consumption-2015/ Date of access: 17 September 2018. Zhang, Y. Trusov, M. Stephen, A T. & Jamal, Z. 2017. Online shopping and social media: friends or foes? Journal of Marketing, 81(6):24-41. Zugal, S. Pinggera, J. Neurauter, M. Maran, T. & Weber, B. 2017. Cheetah experimental platform web 1.0: cleaning pupillary data. arXiv preprint arXiv:1703.09468. 253 ANNEXURE A: Questionnaire Request to participate in a research survey Dear participants, My name is Ndeudjeu Joseline Nadia; I am conducting an academic research study for the completion of my Master in Marketing Management at the North West University, Mafikeng Campus with the title “Influence of the social media promotion mix on car insurance purchasing in Mahikeng” Please note the following: Your name will not appear on the questionnaire and the answers that you provide will be strictly confidential. Kindly assist by completing this questionnaire. It will take between 10 and 15 minutes of your precious time to complete. I am highly grateful for your valuable response. The results of the study will be used for academic purposes only and may be published in an academic journal. Please complete the following by indicating an X in the appropriate block. Sincerely, Nadia Joseline Ndeudjeu SECTION A: DEMOGRAPHICAL INFORMATION The purpose of the demographical descriptors used is to do a comparative analysis in order to establish if there are any concurrences and/or contradictions concerning the customer experiences and expectations as per the demographic descriptors included in this study. The demographic descriptors are also used for further statistical analysis purposes and will not be used for profiling purposes. Are you a car’s owner? If yes, please carry on with the questionnaire. 1. Gender Male Female 2. Up to 20 Age 21 - 40 41 - 60 Above 60 3. Monthly income (Rand) Below 5 000 5 001 – 10 000 10 001 – 15 000 Above 15 000 4. Is your vehicle insured Yes No 5. Which statement is the most applicable for you not to take out insurance? Complexity of information High number of complaints It is expensive Lack of trust Not interested Other (please specify) 6. Which media triggers your intention to purchase insurance policy? Traditional media (TV, radio, newspaper, flyers etc.) Social media (Facebook, twitter etc.) SECTION B: SOCIAL MEDIA USAGE 1. Which of these social media sites do you use most? Facebook YouTube Twitter WhatsApp TipAdvisor Instagram WeChat Others (please specify) 1 2. How often do you access your 3. How much time do you social media sites? spend each time you access these social media sites? Almost every day 30 minutes 4 to 5 times a week 1 hour 2 to 3 times a week 2 hours Once a week More than 2 hours 4. Please rank every statement by ticking (X) the appropriate block. Where 1= strongly disagree (-) 5= strongly agree (+) Social media provides a platform for insurance companies to educate consumers about their services. Using social media platform helps me make decisions better before I purchase a service. Using social media platforms increases my interest in buying insurance policy. Searching information on social media platforms is time consuming. SECTION C: SOCIAL MEDIA PROMOTION MIX AND CONSUMER BEHAVIOUR Please rank each statement (X) in the appropriate block/box. Where 1= strongly disagree (-) 5= strongly agree (+) Perceived usefulness The insurance website provide relevant price and service comparisons. The website is well designed in order not to waste my time. Brand image, colour and symbols create a superior brand messages. Perceived behavioural control I visit several insurance website before purchasing decision. The number of followers on a company website influences my decision. I am confident that searching information through insurance website positively influences my decision. My decision to purchase a service on social media is influenced when a service goes viral 2 Strongly agree Agree Strongly agreed Neutral Agree Neutral Disagree Disagree Strongly Strongly disagreed disagree A bad review on social media site will negatively influence my purchase decision. Social influence Company that apply social responsibility on social media influence my purchase decision. Company that engage with other trusted brands and influencers affect my purchase decision. Before purchasing a service on social media, I seek for my friends’ opinions. Attitude I believe it is a good idea to purchase insurance policy online. Using social media to search information trigger my intention to purchase. Purchasing insurance online is appealing. Perceived security I feel secure when sharing my information on social media. The insurance website looks secure for carrying out transaction. The insurance website has valid links. Service quality A quick respond from the sales force influence my purchase decision positively. I will purchase insurance policy online if the service provider offers the best deal. My decision to purchase a service on social media is influenced when a service goes viral. Online shopping procedure is worry-free and effortless. Perceived trust Information provided by insurance companies is reliable. Online promotion mix is trustworthy than traditional media. Purchasing a service on social media is trustworthy. I consider the message on social media trustworthy. Perceived tangibility The insurance website looks attractive. The company website design and appearance influence my decision. The slogan and visuals of the chosen ad on social media influence my purchasing decision The insurance website uses appropriate colour Social media promotion mix Promotion mix on social media is unrealistic and exaggerated. Advertisement displayed on social media positively influences my purchase decision. 3 Live video promotion influences my purchasing decision. I will purchase insurance policy online if the service provider remind me about new offers using email link to the offers. The attitude of the sales forces during the personal selling influence my purchase decision. Event sponsored by insurance company positively influence my purchase decision. SECTION D: THE ONLINE PURCHASE DECISION 6. Please answer each statement (X) in the appropriate block/box. Is there a possibility that in future, your purchase of insurance policy will be highly influence by online promotion mix? 4 Yes No ANNEXE B: Ethical clearance Private Bag X6001, Potchefstroom South Africa 2520 Tel: 018 299-1111/2222 Web: http://www.nwu.ac.za Economic and Management Sciences Research Ethics Committee (EMS-REC) Tel: 018 299-1427 Email: Bennie.Linde@nwu.ac.za 25 October 2019 Prof M Potgieter Per e-mail Dear Prof Potgieter EMS-REC FEEDBACK: 25102019 Student: Ndeudjeu, JN (26195658)(NWU-01407-19-A4) Applicant: Prof M Potgieter – MCom in Marketing Management Your ethics application on, The influence of the social media promotion mix on car insurance purchases in Mahikeng, that served on the EMS-REC meeting of 25 October 2019, refers. Outcome: Approved as a minimal risk study. A number NWU-01407-19-A4 is given for three years of ethics clearance. Kind regards, Prof Bennie Linde Chairperson: Economic and Management Sciences Research Ethics Committee (EMS-REC) Potchefstroom Campus ANNEXE C: Editing confirmation letter Declaration This is to declare that I, Annette L Combrink, accredited language editor and translator of the South African Translators’ Institute, have language- edited the dissertation by J.N. Ndeudjeu orcid.org 0000 0002 2694 7492 with the title Influence of the social media promotion mix on the car insurance purchasing of residents in Mahikeng Prof Annette L Combrink Accredited translator and language editor South African Translators’ Institute Membership No. 1000356 Date: 6 December 2020