Abstract
Purpose
This study aims to explore the loyalty intent of prepaid (contract-free) customers in a market where disloyalty is prevalent and the market has low switching costs.
Design/methodology/approach
A quota, non-probability sampling technique was applied, resulting in the completion of 220 self-administered questionnaires that were used for data analysis. Confirmatory factor analysis and a structural equation model were applied to determine model fit and test the formulated hypotheses for this study.
Findings
The strength of the satisfaction–loyalty relationship is found to be influenced by three specific satisfaction antecedents, strengthened by the mediating role of customer delight and impacted by switching costs.
Practical implications
The findings of this study may guide mobile service providers in their initiatives to secure satisfaction and loyalty in a market context where switching costs are low and the market is described as disloyal.
Originality/value
This study investigates the well-researched relationship between satisfaction and loyalty and the antecedents of customer satisfaction to determine which of these variables should be the focus in a challenging market where consumers are disloyal and switching costs are low.
Keywords
Citation
Mntande, K.A., Stiehler‐Mulder, B. and Roberts-Lombard, M. (2023), "Securing delight and loyalty in a market with low switching costs", European Business Review, Vol. 35 No. 1, pp. 1-22. https://doi.org/10.1108/EBR-03-2022-0043
Publisher
:Emerald Publishing Limited
Copyright © 2022, Kebone Agnes Mntande, Beate Stiehler-Mulder and Mornay Roberts-Lombard.
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Prepaid users (contract-free) account for 87% of the total mobile base in the emerging market of South Africa, with the remainder being postpaid (contract customers) (McKane, 2021). The prepaid market is further characterised by mobile service providers that offer little differentiation, mobile number portability and the absence of termination fees (Groene et al., 2017; Mati and Shambare, 2016, p. 54; Morgan and Govender, 2017, p. 2). These realities contribute to creating a market with low switching costs, where consumers find themselves smoothly switching between service providers and, in some instances, even using multiple service providers at the same time (Sahi et al., 2016, p. 156). Therefore, the question under investigation is:
How can mobile service providers secure a competitive advantage amongst disloyal customers in a market further faced with low switching costs?
This paper argues that the key is to focus on securing satisfaction and loyalty. As the satisfaction–loyalty connection is well known in marketing literature, this study commences by identifying various antecedents of satisfaction and then empirically tests these, as well as the customer satisfaction–loyalty link in this very challenging market context.
Loyalty has been widely supported in marketing literature as a critical element in securing a competitive advantage in a business-to-consumer (B2C) environment (Islam et al., 2021; Yilmaz et al., 2018). In terms of its attitudinal and behavioural nature, loyalty secures a viable benefit for differentiation (Cossío-Silva et al., 2016). Improved knowledge on how to secure customer loyalty remains an important area of exploration in business and marketing literature (Tariq and Mat, 2018). Loyalty can be described as a strong intention to repurchase or support a favoured service or product continuously in the future (Izogo, 2015). Furthermore, the loyalty notion is well positioned in relationship marketing (RM) literature, because it is validated as the decisive outcome of RM (Ngoma and Ntale, 2019). Nevertheless, numerous scholars argue that the satisfaction–loyalty relationship has become fragile and that satisfaction alone does not secure customer loyalty (Ojiaku et al., 2017).
Scholars (Özkan et al., 2020; Setiawan and Sayuti, 2017) have validated that the satisfaction–loyalty relationship can be reinforced when the service provider brands are perceived by consumers to be trustworthy, deliver on service quality promises, offer value for money and deliver a professional and engaging service. Furthermore, customer delight can function as a mediator and reinforce the satisfaction–loyalty relationship. Researchers like Parasuraman et al. (2021) state that customer delight is built on joy and happiness, and flows from satisfaction. This implies that the needs and expectations of customers are met above the required amount (Barnes et al., 2021). In addition, switching costs are critical to securing loyal customers (Quoquab et al., 2016). Moreover, because no tying contracts are part of the mobile prepaid market in South Africa and consumers can change between service provider brands easily, overall levels of loyalty are lowered (Calvo-Porral et al., 2017). As a result, customers’ satisfaction levels and intent to remain with a mobile service provider are largely moderated by switching costs (Garga and Bambale, 2016).
RM research has largely focused on the direct relationships between satisfaction, its antecedents and loyalty. However, to the authors’ knowledge, no previous research study has focused on the combination of antecedents of satisfaction (as inferred in this study) and the relationship between satisfaction and loyalty in the challenging prepaid mobile market in South Africa. Furthermore, there is limited research on the mediating role of customer delight on the satisfaction–loyalty relationship and the moderating role of switching costs in strengthening the trust–satisfaction and the satisfaction–loyalty relationships. Investigating these relationships becomes important in understanding that loyalty influences a consumer to repurchase a specific product or service in the future. This turned out to be a significant aspect to be cognisant of, considering higher levels of competition in the prepaid mobile market (Ahrholdt et al., 2019).
To explore this research gap, this study focuses on an RM and social exchange theory (SET) approach to explore the influence of selected stimuli (trust, service quality, value, corporate image, customer expectations and customer care service) on satisfaction and the influence of the latter on loyalty in a chosen service environment of an emergent market. Additionally, the mediating role of customer delight and the moderating role of switching costs on the satisfaction–loyalty relationship are studied. This study is applied to the South African mobile prepaid market. The competitive nature of this market is high and is characterised by minimal switching barriers for customers, where customers’ loyalty is vital to ensure future market share growth for mobile service providers (TechFinancials.co.za, 2020). Against this background, it has become imperative for mobile service providers in South Africa to understand the factors that influence prepaid mobile customers’ satisfaction, and whether customer delight strengthens their loyalty intent towards the major prepaid mobile brand names in the country, as well as to understand the impact of switching costs.
Theoretical framework
Theories grounding the study
The study is grounded in two theories, RM theory and SET, in terms of the constructs being investigated and their perceived relationships. RM’s foundation is to appeal, grow and sustain relations in the long term by stimulating customer satisfaction (Nyadzayo and Khajehzadeh, 2016). Therefore, satisfaction is argued to be crucial to building long-term relationships with customers (Mostert et al., 2016). RM is built on an inclusive approach towards establishing and managing relationships with customers, which are perceived as beneficial and satisfying (Okonkwo and Ugwuonah, 2019). Consequently, an RM approach strengthens the development of relationships that are long-term-focused, built on trust and deliver on the value expectations of customers (Abeza et al., 2020). Such relationship developments should be based on continuous engagement between the parties, which will strengthen satisfaction and ultimately loyalty (Aldaihani and Ali, 2019).
SET departs from the perspective that the exchange between partners is voluntary with the intent to benefit from it (Barbalet, 2018). The theory holds that the continuation of a relationship between parties depends on the provision and receipt of value through an exchange process (Masterson et al., 2000). Consequently, future relationships being built between parties are founded on the assessment of mutual value received through transactional engagement (Barbalet, 2018). This engagement delivers mutually beneficial outcomes for all role players involved and is built on reciprocal worthwhile dealings (Freudenreich et al., 2020). As a result, if the social exchange of value is characterised by economic benefits, the enhancement of social value or increased engagement between parties, the faithfulness of the parties to the relationship is strengthened, thereby strengthening future loyalty (Rather and Hollebeek, 2019).
Theoretical model development
Interrelationships between constructs (direct effects)
Research conducted in the mobile industry has validated the significance of trust as a precursor to satisfaction in B2C relationships (Aslam et al., 2018; Marinkovic and Kalinic, 2017). Mobile customers choose to interact with a mobile service provider that is trustworthy. The reason for this being that trust lowers doubt in terms of services anticipated and positively influences customers’ willingness to repurchase from the supplier (Bedi, 2015). Therefore, when service providers deliver on customers’ expectations, they instil trust in the customers, which positively influences their overall level of satisfaction (Kim et al., 2017). Hence, it is hypothesised that:
Perceived trust has a positive significant influence on customer satisfaction in the mobile prepaid market.
The role of service quality as an influential precursor to customer satisfaction in the mobile industry is well established in academic literature (Diaz, 2017; Ismail and Yunan, 2016; Quoquab et al., 2016). Lai and Nguyen (2017) argued that service quality is perceived as an important precursor to customer satisfaction in the mobile industry because of the intangible, inseparable and similar nature of services provided in this sector. Petzer et al. (2014) concurred stating that service engagement perceptions in the mobile cellular industry of South Africa influence future levels of customer contentment. Hence, when a mobile service supplier satisfies and illustrates an understanding of customers’ service needs, it can secure increased levels of customer satisfaction in the future (Shava, 2021). As a result, it is hypothesised that:
Perceived service quality has a positive significant influence on customer satisfaction in the mobile prepaid market.
In the mobile industry, customers’ perceived value is considered significant to strengthen overall customer satisfaction with a service provider (Morgan and Govender, 2017). If the mobile service provider is able to provide its customers with value for money, high levels of service delivery and affordable prices, there will be a greater possibility of satisfying the needs of customers (Anwar et al., 2021). Roberts-Lombard and Petzer (2018) validated the importance of perceived value in strengthening overall customer satisfaction in a mobile cellular service environment in South Africa. In their study conducted in Thailand, Pumim et al. (2017) found that the perceived value of customers in a mobile service environment is based on a cost-benefit analysis. If the benefits outweigh the cost, the value perception of customers is higher, stimulating their overall satisfaction levels in the future (Aslam et al., 2018). Consequently, it is hypothesised that:
Perceived value has a positive significant influence on customer satisfaction in the mobile prepaid market.
In services marketing, corporate image is widely argued to be a precursor to satisfaction (Kaur and Soch, 2018). Research on the telecommunications industry has validated that customers’ perceptions of a mobile service provider brand could influence their satisfaction expectations (Carlson et al., 2019; Jere and Mukupa, 2018). A service provider’s image of being reliable, trusting and delivering upon the service needs of customers enhance customer satisfaction levels in the long term (Kaur and Soch, 2018; Nguyen et al., 2020). Thus, it is hypothesised that:
Perceived corporate image has a positive significant influence on customer satisfaction in the mobile prepaid market.
Extensive mobile market studies have argued that by delivering customers’ service needs and wants, increased levels of satisfaction can be achieved (Diaz, 2017; Ismail and Yunan, 2016). Accordingly, it becomes increasingly important for service providers to meet or exceed customer expectations, thereby securing continued customer satisfaction in the future (Hallencreutz and Parmler, 2021). Wang (2015) stated that, in the mobile industry, understanding the service expectations of customers and delivering these on a continuous basis will positively influence the satisfaction experience of mobile service customers (Patra et al., 2021). Therefore, it is hypothesised that:
Perceived customer expectations have a positive significant influence on customer satisfaction in the mobile prepaid market.
Marketing literature has extensively argued that customer service support positively influences customer satisfaction (Diaz, 2017; Lai and Nguyen, 2017; Pumim et al., 2017). In their study on the Korean smartphone market, Kim et al. (2016) established that customers experiencing a positive and participative service experience tend to feel more satisfactory towards the supplier. Akroush and Mahadin (2019) concurred, stating that fast, efficient and professional service delivery is a vital part of the service experience to secure consumer contentment. Subsequently, it is hypothesised that:
Perceived customer care service has a positive significant influence on customer satisfaction in the mobile prepaid market.
Customer loyalty can be reinforced through the provision of a high-quality service experience that positively influences customers’ service quality expectations (Aburayya et al., 2020). Therefore, mobile service providers must become increasingly focused on the delivery of customer satisfaction outcomes that will strengthen customer loyalty in the long term (Mulyono and Pasaribu, 2021). This view was shared by Petzer et al. (2014), who asserted that loyalty is guided by the overall level of fulfilment that a customer has with a mobile cellular service provider. Customers will remain in the relationship if it is beneficial to them in terms of financial rewards, the resolution of problems that they might experience, the receipt of positive service experiences and an engaging relational approach that is built on trust, respect and transparency (Cheng et al., 2019). As such, customer satisfaction levels can be enhanced and their overall loyalty intention to the service provider strengthened (Lai and Nguyen, 2017). Roberts-Lombard and Petzer (2018) were in agreement and stated that in a mobile cellular industry environment in South Africa, satisfaction positively influences customers’ future loyalty intentions. Consequently, it is hypothesised that:
Customer satisfaction has a positive significant influence on customer loyalty in the mobile prepaid market.
The mediating effect of customer delight on the relationship between customer satisfaction and customer loyalty
Considering H3, it is argued that customer delight may be a mediator between satisfaction and loyalty. The importance of delight in nurturing the loyalty of customers has been extensively explored in marketing literature (Ahrholdt et al., 2019; Berman, 2005; Kageyama and Barreda, 2018). Furthermore, these studies have argued that customers who are experiencing delight in the service delivery process and who are not simply satisfied with the service delivery received are more willing to purchase from the supplier and become loyal (Ahrholdt et al., 2019). According to Loureiro et al. (2014), customer delight is more than simply satisfying customers, because it encompasses emotive elements in the satisfaction–disconfirmation evaluation process of service delivery. As a result, customers who remember a positive service experience that stimulates positive emotions reflect an increased intent to repurchase from a supplier. Consequently, although satisfaction does influence repurchase intention in the future, it is delight (as an emotive element) that stimulates future loyalty intention (Wang et al., 2017). Therefore, it is hypothesised that:
Customer delight mediates the relationship between customer satisfaction and customer loyalty in the mobile prepaid market.
The moderating role of switching costs on the relationship between customer satisfaction and customer loyalty
Scholars (Harazneh et al., 2020; Rahi and Ghani, 2016; Willys, 2018) have contended that switching costs moderate customers’ intent to switch in a service-related environment. Kim et al. (2016) concurred, stating that different kinds of switching costs (e.g. numerous alternatives and minimal search effort) can strengthen customers’ willingness to switch, despite them being content with their mobile service provider. However, Mittal (2016) purported that customers can become more satisfied and ultimately loyal to a supplier when they believe that it is too costly to switch to a competitor, and vice versa. D.T. Nguyen et al. (2020) agreed, asserting that higher switching costs can strengthen customer loyalty to a provider. As this market faces low switching costs, understanding the implications of switching costs of the satisfaction–loyalty relationship is key. Hence, it is hypothesised that:
Switching costs moderate the relationship between customer satisfaction and customer loyalty in the mobile prepaid market.
Figure 1 reflects the hypothesised model recommended.
Research methodology
Ethical clearance
Ethical clearance for the study was provided by the University of Johannesburg in South Africa. The ethical clearance number for the study is 2020SCiiS49.
Sampling
The study’s population encompassed mobile prepaid customers located in the Gauteng province of South Africa who are customers of the three largest network operators in the country, namely, Vodacom, MTN and Cell C. South Africa’s mobile cellular industry is considered one of the industries in the country’s telecommunications services environment that reflects the most rapid growth (Frost and Sullivan, 2017, p. 11; van Niekerk, 2022). The sector comprises numerous service providers, four mobile network operators (Vodacom, MTN, Cell C and Telkom) and multiple mobile network virtual operators (Business Monitor International TechKnowledge, 2021, p. 9). Vodacom and MTN are considered the two market leaders, with 38.2% and 31.9% of market share, respectively, whereas Cell C is a less prominent competitor with a market share of 12.6% (McKane, 2021).
Prepaid (contract-free) services currently dominate the mobile market, with prepaid subscribers being responsible for approximately 87% of the total mobile market share in South Africa, comprising almost 97.1 million mobile subscribers. The remaining 13% of market share consists of contract customers (McKane, 2021). Gauteng was chosen for this study because it is the most prosperous region in South Africa, with a high mobile penetration presence (Mzekandaba, 2016). Gauteng is the most diverse province in South Africa in terms of ethnicity, constitutes the largest concentration of prepaid mobile customers in the country and produces the largest gross domestic product to the South African economy (Statista, 2022; Stats SA, 2022). Therefore, Gauteng is perceived as the economic hub of South Africa and a landscape characterised by a multitude of ethnic groups using mobile cellular service in the country (Alexander, 2018; Statista, 2022; Stats SA, 2022). A sample size of 400 respondents was targeted, while 220 responses were received and used for data analysis. The sample size for this study was deemed acceptable as it aligned with sample sizes that have been used previously in similar studies (Anjum et al., 2016; Kaur and Soch, 2018; Quoquab et al., 2016). Table 1 informs on the quotas (50–50 split based on gender) and the number of questionnaires that were fielded.
The study applied a non-probability sampling method through the use of quota sampling. To ensure the selected population was well represented, quotas based on network subscription and gender were applied to the study. The respondents were mobile cellular prepaid customers of the three dominant role players in the South African mobile cellular market, namely, Vodacom, MTN and Cell C. These mobile cellular service providers have a combined market share of 82.7% of the prepaid mobile cellular market in the country. In addition, the study wanted to secure a 50–50 split in terms of gender to secure a balanced representation of the male/female distribution in the sample population.
Data collection
Data were collected over a six-week period via a self-administered survey. Fieldworkers were trained to distribute the hard copy survey to qualifying respondents. Furthermore, fieldworkers were required to purposefully fill quotas based on race, age and gender to ensure the study’s target population was adequately representative of the diverse South African demographic profile. Consequently, the selection of the sample was based on non-probability sampling by meeting predetermined quotas in a purposeful manner.
Measures and items
Items used in the questionnaire were revised from previously published studies to ensure that they evaluate the loyalty intent of prepaid mobile customers in an emerging African market. Screening questions were used to guarantee that the respondents were prepaid customers of the study’s selected mobile brands. Respondents had to adhere to the following requirements to partake in the study: be a South African citizen, have their own cell phone, have a choice in the mobile cellular network service provider they are currently using and be a prepaid customer of one of the major mobile cellular service providers (i.e. Vodacom, MTN and Cell C). Furthermore, the questionnaire comprised four sections. The first part encompassed questions to obtain personal information from respondents. Part two included items relating to the constructs measuring the direct relationships in the study, while part three included items measuring the role of the moderating variables. The fourth part referred to items measuring the mediating variable, as applied to the study. A five-point Likert scale was applied to the study, where 5 referred to “Strongly agree” and 1 to “Strongly disagree”. Table 2 reflects the different items used in the questionnaire.
Data analysis strategy
The Statistical Package for Social Scientists version 24 was applied to assess the direct effects of the relationships proposed in the study. The measurement model was assessed by establishing its psychometric properties through confirmatory factor analysis. To assess model fit, the Satorra-Bentler χ2/df ratio (<3) (Muthén and Muthén,1998/2017), root mean square error of approximation (RMSEA) (<0.05), comparative fit indices (CFI) (>0.95) and standardised root mean square residual (<0.08) were considered (Hu and Bentler, 1999).
Regression analysis was done to test the indirect effects of mediation between constructs and to test for moderation. For the mediation results, the Hayes process macro (version 3.5.3) was used. Hence, a mediation analysis was carried out using a bootstrapping estimation with 5,000 resamples and 95% bias-corrected confidence intervals (BCCIs) generated to determine whether a zero is contained between the lower level (LLCIs) and upper level confidence intervals (ULCIs) for both direct and indirect effects. To obtain the moderation results, an interaction term was added between the two variables.
Results
Assessment of normality
The outcome of the normality test results for the collected data was significant (p < 0.05) and indicative of univariate non-normality. Normal distribution was inferred using the central limit theorem because of the large sample size. Assessment of normality was secured through the performance of skewness and kurtosis tests (Kolmogorov–Smirnov and Shapiro–Wilks tests) on the different scale items in the study.
Assessment of the measurement model
Confirmatory factor analysis was performed to assess the new model. The model fit of the measurement model was assessed and it was concluded that the model fits the data adequately, with a normed chi-square (χ2/df) of 3.014, a normed fit index (NFI) of 0.868, a Tucker–Lewis index (TLI) of 0.896, a CFI of 0.907 and an RMSEA of 0.070, as presented in Table 3.
Table 4 provides insight into the factor loadings and average variance explained (AVE) of the items used to measure the study’s constructs. The factor loadings and AVEs for all constructs were greater than 0.50, indicating that the criterion for convergent validity for the research instrument was met. Concerning reliability, the composite reliability and the Cronbach’s alpha values for the constructs exceeded the recommended value of 0.70, thus the scales used are reliable and have internal consistency (Wiid and Diggines, 2015).
Furthermore, it is clear from Table 5 that the constructs illustrate discriminant validity. Constructs met the discriminant validity criterion, with most of the square roots of AVEs surpassing the inter-construct correlations (Fornell and Larcker, 1981). As a result, it can be argued that the model illustrates satisfactory reliability and construct validity. Considering the satisfactory results, the structural model for the study could be assessed.
Assessment of the structural model
Similar to the measurement model, the structural model also secured the measurement of the goodness-of-fit measures. The model fit indices of the structural model disclosed that the model fits the data sufficiently. It was found that the normed chi-square (χ2/df) was 3.078, the NFI was 0.902, the TLI was 0.915, the CFI was 0.931 and the RMSEA was 0.071, as presented in Table 6. Subsequently, the structural paths for the study were inspected.
Table 7 reflects the outcome of the different hypotheses formulated for the study. It is evident that perceived corporate image, perceived customer expectations and perceived customer care service significantly and positively influence customer satisfaction, whereas perceived service quality, perceived trust and perceived value do not. In addition, perceived customer satisfaction significantly and positively influences customer loyalty.
Assessment of indirect effects
Mediation analysis.
Table 8 illustrates the mediation analysis results, demonstrating that a zero is not contained between the LLCIs and ULCIs of the BCCIs for the direct and indirect effects. Therefore, it can be assumed that mediation is apparent, with customer delight partially mediating the relationship between customer satisfaction and customer loyalty (β = 0.340, 95% BCCI [0.230; 0.464]). Consequently, H8 can be supported regarding the mediation effect of customer delight on the relationship between customer satisfaction and customer loyalty.
Table 9 presents the results for the moderation effects for switching costs (H9). A statistically significant relationship was evident between loyalty and switching costs (the p-value was less than 0.05). The R-squared values reflected a value of 0.636, explaining a 63.6% of the variance in customer satisfaction. Therefore, 63.6% of a possible change in the level of customer satisfaction of prepaid mobile cellular customers was caused by switching costs. Thus, it can be assumed that switching costs moderate the relationship between customer satisfaction and customer loyalty. Subsequently, it can be argued that the inclusion of switching costs as a moderator confirms a significant shift in variance in the relationship between satisfaction and customer loyalty, with the inclusion of the moderation of switching costs in the satisfaction–loyalty relationship. Consequently, H9 is supported.
Discussion
Satisfaction has been researched extensively in marketing literature and is perceived as an important antecedent in strengthening future loyalty intentions (Saengchai and Jermsittiparsert, 2020). However, this paper explored the role of satisfaction in influencing loyalty in a challenging prepaid mobile market and based only on selected customer satisfaction-focused efforts that may be undertaken by mobile service providers to influence future loyalty intentions. The study further explored the mediating influence of customer delight on the connection between customer satisfaction and customer loyalty, and the moderating influence of switching costs on the relationship between customer satisfaction and customer loyalty. The study is contextualised to the South African prepaid mobile industry, where the strengthening of customer satisfaction can enhance future customer loyalty towards a mobile service provider.
In terms of the selected satisfaction-focused efforts, it was established that perceived corporate image, perceived customer expectations and perceived customer care service significantly and positively influence customer satisfaction in a prepaid mobile context. The findings concur with other research indicating that perceived corporate image, perceived customer expectations and perceived customer care service have a significant and positive influence on customers’ loyalty intentions (Asnawi et al., 2020; de Leaniz and del Bosque Rodríguez, 2016). Furthermore, in contrast to the findings of numerous scholars, perceived trust, perceived service quality and perceived value do not influence satisfaction (Lee, 2021; Uzir et al., 2021). Nevertheless, a positive and significant relationship was found between satisfaction and loyalty, as promulgated by Woratschek et al. (2020).
Concerning the role of customer delight as mediator, it was established that delight partially mediates the relationship between satisfaction and loyalty. This finding is supported by scholars like Kim and Park (2019). Moreover, switching costs were found to moderate the relationship between satisfaction and loyalty (Edward et al., 2010; Ngo and Pavelková, 2017).
Theoretical and managerial implications of the study
The contribution made by the study is twofold. It makes theoretical contributions based on the study’s findings and practical contributions. These are discussed in the sections that follow.
Theoretical implications
An improved understanding of the antecedents of customer satisfaction, strengthening the satisfaction–loyalty relationship in a challenging market is required. The study’s results have validated the interrelationships between satisfaction-focused efforts (perceived corporate image, perceived customer expectations and perceived customer care service), satisfaction and loyalty. Knowledge of these direct relationships is crucial, considering its relevance to marketing theory and its contribution in testing these variables in a market context characterised by disloyalty and low switching costs. It becomes evident that the satisfaction of prepaid mobile cellular service customers is guided by various factors. First, should prepaid mobile service customers perceive evidence of customer service care and the exceeding of their expectations, they will illustrate enhanced levels of satisfaction with their mobile service provider. Consequently, if customers’ service expectations are exceeded, this will strengthen their satisfaction levels in the long term (Strenitzerová and Gaňa, 2018). Second, prepaid mobile cellular customers will illustrate feelings of service satisfaction because of fast, efficient and friendly service experiences. Furthermore, polite and engaging service delivery will enhance customer satisfaction towards the mobile cellular service provider, ultimately strengthening customers’ loyalty in the future (refer to Table 7) (Shankar et al., 2020; Srivastava and Bhatnagar, 2013). Existing research in the marketing domain has explored numerous antecedents to satisfaction in a B2C environment (Marinkovic and Kalinic, 2017; Strenitzerová and Gaňa, 2018). However, the results from this study identify the variables that play the largest role in enhancing the satisfaction–loyalty relationship in a very disloyal market.
A perspective on customer delight in fostering the satisfaction–loyalty relationship in a challenging market.
The research findings support the partial mediation role of customer delight on the satisfaction–loyalty relationship. Marketing scholars (Kageyama and Barreda, 2018; Kim and Park, 2019) validate the importance of customer delight in strengthening customers’ future loyalty intentions in multiple settings. These authors further promulgate the application of delight to studies exploring the satisfaction–loyalty relationship. Therefore, it seems that despite satisfaction being critical in driving customers’ future loyalty intentions, customer delight should also be considered an element that can strengthen the delight of customers in a service setting. New studies can add to the results established by this study by testing the mediating role of customer delight in a different service setting within the framework of the satisfaction–loyalty relationship.
A perspective on switching costs in the satisfaction–loyalty relationship in a challenging market.
The results confirm the moderating role of switching costs on the satisfaction–loyalty relationship, suggesting that as much as 63% of a possible change in the level of satisfaction can be attributed to switching costs. This finding is in agreement with Hadi et al. (2019), Harazneh et al. (2020) and Ngo et al. (2019), who stated that switching costs are vital in managing the loyalty of customers in multiple settings, and should be explored more in depth to investigate the satisfaction–loyalty relationship. Consequently, it would seem that for businesses to ensure their customers’ future loyalty, they must focus on strengthening the factors that contribute to satisfaction, because switching costs (which in this market sample was low) pose a challenge to satisfaction levels, and without satisfaction it is difficult to secure loyalty intentions. Moreover, the earlier finding pertaining to the mediating role of customer delight may be considered an additional aspect to focus on to counter the effect of switching costs in this context. New studies could build on these identified variables that strengthen satisfaction and further explore their roles in limiting switching costs – this can also be done in different settings or markets across the globe.
Managerial implications
In terms of the study’s practical significance, it is evident that mobile service providers should reinforce the satisfaction–loyalty relationship by focusing on those identified factors that will enhance customer satisfaction – namely, delighting customers and strengthening corporate image, perceived customer expectations and perceived customer care service. For example, mobile cellular service providers should exceed the expectations of customers by engaging with them, as important stakeholders in the relationship building chain, through multiple platforms (e.g. mobile phone, email or social media platforms like Facebook or Instagram) in terms of enquiries or complaints. Customers want to be acknowledged, heard and feel valued. Consequently, mobile cellular service providers should ensure that their communication with customers is 24/7, making access to the company a 360-degree possibility through the application of the Fourth Industrial Revolution, such as chatbots, to address customer enquires or complaints.
In the case of a service failure, these service providers must ensure that the issue is resolved in a fast and professional manner through continuous engagement with the customer on the resolution applied to fix the matter at hand. Mobile cellular customers want engaging and professional service care through various platforms to secure convenience and ease of use. These channels should secure prompt engagement with the customers on issues of importance or concern (service care can be delivered by professional employees and chatbots). Mobile service providers must guarantee that their employees have an understanding of and empathy for the challenges or enquiries of the customers, addressing these in a polite, quick and solution-driven manner.
For customers to engage with the mobile cellular service provider, customer care services should be accessible to customers through a convenient channel and also in their mother tongue. Through this approach, customers are provided with engagement tools that can stimulate a positive interaction between the service provider and the customers. When practising customer engagement in a mobile cellular service environment, service providers need to understand that customer service is focused more on securing the delivery of the task in a professional manner, while customer care has a more compassionate approach towards service delivery. Their customer care service strategies should embrace this difference in their service design approach.
Service providers should also engage in continuous research with their target markets to better understand their evolving mobile service needs and implement online and offline customer service strategies that will exceed customer expectations, and enhance the perceived customer care service and customer expectation aspects. Corporate image is often associated with the public relations component of an organisation. Hence, managers should bring this aspect to the attention of the relevant departments and strategise on strengthening corporate image. For instance, corporate image can be improved if mobile cellular service providers strengthen their social media presence on platforms like Instagram, Facebook and LinkedIn. Moreover, the cellular website can be built up by enhancing visual imagery, including technology assistants like chatbots to secure 24/7 customer service engagement, and communicating brand success on platforms through customer testimonials, celebrity endorsements and the incorporation of virtual reality interactions to create personalised experiences with the cellular brand. The latter can be accommodated at mobile cellular branches or through online interactive platforms accessible to the customer (being a prepaid customer of the mobile cellular service provider).
Furthermore, mobile service providers need to strategise on methods to secure an enjoyable service experience, which may result in delighting customers, as the findings suggest that this may aid in strengthening the satisfaction–loyalty connection. Such measures could entail the effective resolution of a query or problem, or an uninterrupted network service to ensure that calls are made with ease. Considering this, customer delight in a mobile cellular service environment needs to ensure that customer expectations are exceeded, continuous value is delivered to the customer through service excellence, experiences with the service provider are memorable and service recovery is secured in a professional and solution-driven manner. Consequently, delight in the mobile cellular service industry of an emerging market can be delivered by providing customers with real-time support on a 24/7 basis through live chats and engagement tools, such as chatbots; by training employees to become more customer-centric through empathy and emotional maturity in managing customer enquiries or complaints; by solving customer pain points fast, efficiently and in a friendly and engaging manner; and by sending customers a small gift on their birthday.
More generally, mobile service providers can review all their customer engagement touchpoints (e.g. the front office of a branch, call centres, website or application interaction and chatbots engagement) and strategise around how they may secure good customer care perceptions and exceed customer expectations across these channels. In addition, frontline employees should be trained to ensure that they, as an imperative contact point, provide engaging, joyful, satisfactory and unforgettable customer experiences, as well as good after-sales service support. For example, good after-sales service support could include training on how to use a specific mobile phone brand, providing online support to customers who require such a service, securing a hassle-free return or replacement policy on mobile phones, and swapping SIM cards. The success of customer satisfaction in a service-orientated environment would require employees to be friendly and approachable, and have a sympathetic attitude concerning the customers’ needs, wants and trepidations. Thus, mobile service providers need to ensure that their staff are developed continuously regarding aspects like sympathy, thoughtfulness, emotional intelligence and professional service engagement. In addition, mobile service providers should also consider providing ongoing service support to their customers by means of live chats and chatbot engagements that are not necessarily bound by office hours, thereby ensuring continuous availability for customer service support needs.
Conclusively, mobile cellular service providers should take the responsibility in terms of educating their customer base on how to use technology to engage with the supplier. For instance, free training videos can be provided that customers (e.g. prepaid customers) can view on how to use chatbots to address frequently asked questions. Furthermore, customers can be provided with in-house training sessions by the mobile cellular service provider at a time that is convenient to the customer. The development of training schedules, incorporating sessions throughout the working day, on a Tuesday, Wednesday and Thursday, for a long-term scheduled period of the year, can be considered.
Origin of the study, research limitations and areas for future research
This study originates from the master’s degree dissertation of KA Mntande published at the University of Johannesburg under the title “Deconstructing the Building of Customer Loyalty in the Mobile Prepaid Market”. The co-authors on this article were the supervisors of the dissertation. The study is limited because only selected antecedents (i.e. perceived trust, perceived service quality, perceived value, perceived corporate image, perceived customer expectations and perceived customer care service) to satisfaction were explored in an industry-specific service environment and context. Yet, the paper provides attentive understanding into the selected antecedents of satisfaction in this mobile service environment. In addition, the study applied a quota, non-probability sampling technique that affects the ability to generalise the findings. Finally, because of the marginal model fit secured in the paper, the results and managerial implications should be interpreted against this background. Future research studies could include employee skills and service experience as antecedents to satisfaction. Furthermore, exploring customer engagement as a mediator in terms of the relationship between satisfaction and loyalty in a different service setting can be secured. A comparison can also be done between diverse markets, diverse sectors or between an emerging and an established market to explore the influence of the mediator or moderators on the satisfaction–loyalty relationship. Lastly, the contrary findings to existing literature pertaining to the antecedents of perceived trust, perceived service quality and perceived value should be explored in similar disloyal markets with low switching costs to determine whether similar findings may be achieved. Additional areas of further research identified may be reviewed in the theoretical contribution section of this paper.
Figures
Quotas and number of questionnaires fielded
| Mobile cellular service provider | Market share (%) | Percentage of total questionnaires fielded (%) | No. of fielded questionnaires | Target gender distribution on fielded questionnaires |
|---|---|---|---|---|
| Vodacom | 38.2 | 43.6 | 96 | 48 females; 48 males |
| MTN | 31.9 | 38.9 | 86 | 43 females; 43 males |
| Cell C | 12.6 | 17.5 | 38 | 19 females; 19 males |
| Total | 82.7 | 100 | 220 | 220 |
Measurement of constructs
| Key construct | Item count | Source |
|---|---|---|
| Perceived trust | 3 | Van Vuuren et al. (2012) |
| Perceived service quality | 5 | Nyadzayo and Khajehzadeh (2016) |
| Perceived value | 5 | Calvo-Porral and Lévy-Mangin (2015); Nyadzayo and Khajehzadeh (2016) |
| Perceived corporate image | 3 | Giovanis (2016) |
| Perceived customer expectations | 3 | Dutta et al. (2017) |
| Perceived customer care service | 5 | Shen and Tang (2018) |
| Customer loyalty | 4 | Chuah et al. (2017), Nyadzayo and Khajehzadeh (2016) |
| Customer satisfaction | 5 | Chuah et al. (2017) |
| Switching costs | 5 | Quoquab et al. (2016), Kaur and Soch (2018); Giovanis (2016) |
| Customer delight | 5 | Berman (2005) |
Measurement model – goodness-of-fit assessment
| Category of model of goodness-of-fit | Selected indices | Acceptable fit | Model fit outcomes |
|---|---|---|---|
| Absolute fit index | Chi-square (χ2)/CMIN | A value of χ2 < 3.0 indicates good fit (Awang, 2015; Hair et al., 2019, p. 636) | 3.014 |
| df | 473 | ||
| p-value | 0.000 | ||
| RMSEA | RMSEA < 0.06 good (Cangur and Ercan, 2015, p. 157) | 0.070 | |
| CFI | Value of ≥0.90 indicates good fit (Hair et al., 2019, p. 640) | 0.907 | |
| Incremental fit index | NFI | Value of >0.80 (Forza and Filippini, 1998, p. 14) or ≥0.90 indicates good fit (Hair et al., 2019, p. 640; Hooper et al., 2008, p. 55) | 0.868 |
| NNFI (TLI) | Value of ≥0.90 indicates good fit (Cangur and Ercan, 2015, p. 158) | 0.896 |
Convergent validity and reliability scores
| Construct and items | Factor loadings | Cronbach’s alpha value | CR value | AVE | |
|---|---|---|---|---|---|
| Perceived trust (PT) | PT1 | 0.756 | 0.798 | 0.813 | 0.592 |
| PT2 | 0.773 | ||||
| PT3 | 0.779 | ||||
| Perceived service quality (PSQ) | PSQ1 | 0.867 | 0.828 | 0.923 | 0.707 |
| PSQ2 | 0.842 | ||||
| PSQ3 | 0.753 | ||||
| PSQ4 | 0.845 | ||||
| PSQ5 | 0.890 | ||||
| Perceived value (PV) | PV1 | 0.762 | 0.832 | 0.833 | 0.501 |
| PV2 | 0.686 | ||||
| PV3 | 0.719 | ||||
| PV4 | 0.725 | ||||
| PV5 | 0.640 | ||||
| Perceived customer expectations (PCE) | PCE1 | 0.888 | 0.876 | 0.864 | 0.681 |
| PCE2 | 0.773 | ||||
| PCE3 | 0.810 | ||||
| Perceived corporate image (PCI) | PCI1 | 0.849 | 0.844 | 0.880 | 0.710 |
| PC12 | 0.883 | ||||
| PCI3 | 0.793 | ||||
| Perceived customer care service (PCCS) | PCCS1 | 0.758 | 0.809 | 0.869 | 0.570 |
| PCCS2 | 0.789 | ||||
| PCCS3 | 0.787 | ||||
| PCCS4 | 0.738 | ||||
| PCCS5 | 0.699 | ||||
| Customer satisfaction (CS) | CS1 | 0.841 | 0.884 | 0.802 | 0.503 |
| CS2 | 0.745 | ||||
| CS3 | 0.788 | ||||
| CS4 | 0.793 | ||||
| Customer loyalty (CL) | CL1 | 0.730 | 0.901 | 0.835 | 0.503 |
| CL2 | 0.719 | ||||
| CL3 | 0.694 | ||||
| CL4 | 0.714 | ||||
| CL5 | 0.748 | ||||
| Switching costs (SC) | SC1 | 0.778 | 0.745 | 0.817 | 0.528 |
| SC2 | 0.694 | ||||
| SC3 | 0.737 | ||||
| SC4 | 0.694 | ||||
| Customer delight (CD) | CD1 | 0.774 | 0.922 | 0.904 | 0.574 |
Discriminant (divergent) validity scores (SQRT values in bold)
| Research construct | PV | PCS | PCL | PT | PSQ | PCE | PCI | PCCS | CD | SC |
|---|---|---|---|---|---|---|---|---|---|---|
| PV | 0.708 | |||||||||
| PCS | 0.705 | 0.703 | ||||||||
| PCL | 0.614 | 0.782 | 0.703 | |||||||
| PT | 0.644 | 0.688 | 0.687 | 0.769 | ||||||
| PSQ | 0.707 | 0.752 | 0.717 | 0.779 | 0.840 | |||||
| PCE | 0.686 | 0.829 | 0.765 | 0.692 | 0.742 | 0.825 | ||||
| PCI | 0.643 | 0.723 | 0.761 | 0.690 | 0.755 | 0.786 | 0.843 | |||
| C | 0.640 | 0.702 | 0.785 | 0.659 | 0.677 | 0.687 | 0.737 | |||
| PCCS | 0.612 | 0.774 | 0.736 | 0.632 | 0.716 | 0.723 | 0.736 | 0.755 | ||
| SC | 0.680 | 0.744 | 0.743 | 0.634 | 0.690 | 0.704 | 0.679 | 0.717 | 0.727 | |
| CD | 0.429 | 0.433 | 0.523 | 0.415 | 0.430 | 0.434 | 0.399 | 0.430 | 0.558 | 0.758 |
PV = perceived value; PCS = perceived customer satisfaction; PCL = perceived customer loyalty; PT = perceived trust; PSQ = perceived service quality; PCE = perceived customer expectations; PCI = perceived customer image; PCCS = perceived customer care service; SC = switching costs; CD = customer delight
Structural model: goodness-of-fit assessment
| Category of model of goodness-of-fit | Selected indices | Acceptable fit | Model fit outcomes |
|---|---|---|---|
| Absolute fit index | Chi-square (χ2)/CMIN | A value of χ2 < 3.0 indicates good fit (Awang, 2015, p. 57) | 3.078 |
| df | 244 | ||
| p-value | 0.000 | ||
| RMSEA | RMSEA < 0.06 good (Cangur and Ercan, 2015, p. 157) | 0.071 | |
| Incremental fit index | CFI | Value of ≥0.90 indicates good fit (Cangur and Ercan, 2015, p. 159) | 0.931 |
| NFI | Value of > 0.80 (Forza and Filippini, 1998, p. 14) or ≥0.90 indicates good fit (Hair et al., 2019, p. 640; Hooper et al., 2008, p. 55) | 0.902 | |
| NNFI (TLI) | Value of ≥0.90 indicates good fit (Hair et al., 2019, p. 640) | 0.915 |
Structural model estimates for the proposed model
| Structural path | Hypothesis | Path coefficients(β) | T-statistics(t) | p-value | Rejected/supported |
|---|---|---|---|---|---|
| PT → CS | H1 | 0.043 | 0.546 | 0.585 | Rejected |
| PSQ → CS | H2 | 0.126 | 1.222 | 0.222 | Rejected |
| PV → CS | H3 | −0.107 | −0.743 | 0.457 | Rejected |
| PCI → CS | H4 | 0.569 | 3.449 | 0.000 | Accepted |
| PCE → CS | H5 | −0.316 | −2.220 | 0.006 | Accepted |
| PCCS → CS | H6 | 0.525 | 3.203 | 0.001 | Accepted |
| PCS → CL | H7 | 0.996 | 16.279 | 0.000 | Accepted |
PT = perceived trust; CS = customer satisfaction; PSQ = perceived service quality; PV = perceived value; PCI = perceived corporate image; PCE = perceived customer expectations; PCCS = perceived customer care service; PCS = perceived customer satisfaction; CL = customer loyalty
Regression analysis summary of the mediation of customer delight on the relationship between customer satisfaction and customer loyalty
| Construct X → M → Y |
Direct effect (β) [LLCI; ULCI] |
Indirect effect (β) [LLCI; ULCI] |
Probability value (p) | Hypothesis result (p < 0.05) |
|---|---|---|---|---|
| Satisfaction → delight → loyalty | 0.654 [0.547; 0.760] | 0.340 [0.230; 0.464] | 0.000 | Partial mediation supported |
X = exogenous variable; M = mediating variable; Y = endogenous variable
Regression analysis summary of the moderation of switching costs on the relationship between customer satisfaction and customer loyalty
| Dependent variable | Independent variables | p-value | Beta value (β) | R-squared value | Adjusted R-squared value |
|---|---|---|---|---|---|
| Satisfaction | Switching costs | 0.000 | 0.436 | 0.636 | 0.633 |
| Loyalty |
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Acknowledgements
Research funding: This work was financially supported by the Department of Marketing Management at the University of Johannesburg in South Africa.
Disclaimer: Any opinion, finding and conclusion or recommendation expressed in this material is that of the authors and the Department of Marketing Management at the University of Johannesburg in South Africa does not accept any liability in this regard.