A service recovery model for the mobile internet service provider industry

Abstract

Due to the nature of services – being intangible, perishable and requiring the human-element – the service delivery process can be relatively complex, thus posing distinct marketing challenges. This process is even further impeded by customers’ subjective assessment of the service experience. As such, irrespective of the service provider’s commitment to deliver satisfying and error-free services, it might not always be able to meet customers’ expectations, inevitably resulting in service failures. Service failures often result in customer dissatisfaction, disloyalty, or defection. These negative behaviours can be minimised by properly handling customer complaints and having service recovery strategies in place. Successful service recovery is, therefore, essential in sustaining customer satisfaction and loyalty. As the South African mobile internet service provider (ISP) industry has been experiencing a significant increase in customer complaints (about service failures) and poor complaint resolution, this study set out to investigate the service recovery actions of these providers. As such, the study developed a service recovery model for the South African mobile ISP industry, with a view into the service recovery attributes that influence customers’ satisfaction with the recovery effort, as well as the behavioural outcomes that could result from customers who are satisfied with the service recovery. The study implemented a quantitative descriptive research design. The target population comprised customers (i.e. contract and prepaid) of the main South African mobile ISPs (i.e. Cell C, MTN, Telkom, or Vodacom), who have complained to their mobile ISP. A total of 484 usable responses were obtained through non-probability convenience sampling. The primary data was collected by means of an online survey made available on social networking sites and an online panel (by Consulta). The empirical data analysis included (a) descriptive statistics, (b) Cronbach’s alpha coefficients to test the reliability of the scales, (c) a confirmatory factor analysis to confirm the validity of the scales and (d) structural equation modelling (SEM) to test the conceptual model and hypothesised relationships. The structural model results indicated an acceptable model fit, with statistically significant structural paths supporting H1, H2, H4, H5, and H6. As such, it is recommended that South African mobile ISPs focus on the implementation of effective service recovery actions, such as compensation, response speed, apology, and explanation, as these attributes were found to have a positive effect on respondents’ satisfaction with service recovery. Mobile ISPs are furthermore advised to ensure that their customers are satisfied with the provided service recovery effort, as this can improve their trust, generate positive eWOM, and encourage repurchases. Several theoretical and managerial contributions were made from the research findings. From a theoretical perspective, this study introduced service recovery attributes (i.e. compensation, response speed, apology, and explanation) as a multi-dimensional construct. The study further contributes to the service recovery literature, by establishing the relationships between the antecedents of satisfaction with service recovery as well as the behavioural outcomes of service recovery. From a managerial perspective, the service recovery model developed in this study provides a comprehensive tool that South African mobile ISPs can implement to manage service failures, restore customer satisfaction, and encourage positive behavioural responses. Ultimately, the research findings serve as a basis for identifying the antecedents and behavioural outcomes of satisfaction with service recovery. It is recommended that future research expand these findings by testing the service recovery model in different service industries in order to determine the relevance and viability of the model.