“Modeling the factors that explain customer loyalty in retail banking”

Literature suggests that achieving adequate customer loyalty is a significant determinant of growth and profitability. However, in South Africa, there is no evidence of a validated customer-loyalty-in-retail-banking scale. Thus, this study aimed to contribute to the literature by validating customer loyalty in retail banking as a six-factor structure comprising customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction, which practitioners can use as a marketing guide to better understand customer loyalty. Data was collected from one sample only once, and the sample size was selected (N = 400). Descriptive and confirmatory factor analyses were undertaken to achieve the study’s objective. Confirmatory factor analysis results validated customer loyalty in retail banking as a six-factor structure that includes customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction. The results show no serious multicollinearity between the latent factors and that acceptable internal-consistency reliability was returned for each factor. Moreover, the measurement model returned acceptable composite reliability together with construct, convergent and discriminant validity. Moreover, IFI, TLI, CFI, SRMR and RMSEA model fit index values suggest a good fitting model. Thus, the re-sults concluded that this six-factor model is a reliable and valid instrument of customer loyalty in retail banking and is the first validated customer loyalty scale within the retail-banking context of South Africa. Retail banks are encouraged to use this instrument as a marketing guide in their quest to provide excellent banking services to their market segments, as well as build solid bank-customer relationships.


INTRODUCTION
Given its importance to business, customer loyalty has received substantial volumes of empirical research over the past decades.The loyalty of a customer is defined as a customer's predisposition to support a given business or chain of businesses over a certain period (Knox & Denison, 2000).Customer loyalty can also be described as "customer's commitment to a given service, product or brand".This description can be expanded as "a deeply held commitment to rebuy or re-patronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same-brand-set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior" (Oliver, 1999).
A loyal customer base is central to the profitability and growth of a business.This is because such customers are great sources of cash flow and spread positive word-of-mouth marketing communication (Young, 2005).Harris and Goode (2004) concur and add that customers that are loyal to a business are willing to purchase more goods and services, spend more on the business, and are an easier customer base to reach.In addition, loyal customers serve as passionate promoters for businesses.Repeat purchases, great passion, spreading positive word-of-mouth and favorable attitude toward a brand are benefits attributed to having loyal customer base (Iacobucci, 2016).With particular reference to retail banking, loyal customers are seen to use and test more products and services of the bank, stay in the bank-customer relationship for longer, and refer such products and services to family and friends (Du Toit et al., 2012).
Literature, based on various service settings, has documented the importance of certain factors such as service quality, customer satisfaction, customer commitment, trust and switching cost in building and maintaining a loyal customer base.Evidence from literature, as elucidated below, suggests that businesses, specifically retail banks that effectively manage these factors are able to reap the fruits of customer loyalty.

LITERATURE REVIEW
A full understanding and identification of service quality determinants and its influence on the loyalty of a customer is a key concern for businesses that wish to excel in today's competitive business landscape (Wong & Sohal, 2003).This is crucial as businesses aim to identify, evaluate, control and enhance service quality from the customers' perspective (Johnston, 1995).Measurement and management of service quality are an intricate process because of the distinctive characteristics of services, namely inseparability of production and consumption, intangibility, and heterogeneity of service provision.Parasuraman et al. (1985) posit that comparing customers' past experiences with a service and their perceptions of the service encounter after the actual experience are important determinants of perceived service quality.Service quality is a powerful differentiation tool in which business can distinguish themselves from competitors (Berry et al., 1988).Providing excellent service is crucial to service businesses such as retail banking due to its influence on customer satisfaction.Success and survival within the banking sector are ensured by providing superior quality of service (Clemes, 2007).There is a plethora of empirical evidence, which shows that service quality is an important predictor of customer satisfaction and customer loyalty (Cronin & Taylor, 1992, 1994;Han & Baek, 2004;Hoffman & Bateson, 2006).
The satisfaction of customers can be described as a feeling that customers experience when a product meets or exceeds their expectations and can be explained in terms the disconfirmation paradigm (Torres et al., 2001;Lamb et al., 2011).That is, it explains the extent to which the actual performance is consistent with customers' expectations (Levy, 2014).
The concept of satisfaction can be viewed from a cumulative and transaction-specific perspective or approach.Satisfaction from a cumulative perspective is explained as the overall customer satisfaction that is received with regards to the quality of service and business satisfaction (Yang & Peterson, 2004), while the transaction-specific approach refers to satisfaction as the emotional reaction customers display towards a specific transaction experienced with the business (Oliver, 1997).In this case, satisfaction is viewed "as a post-evaluative judgement concerning a customer's purposeful decision and choice" (Kotler, 2002).
Customer satisfaction is regarded as an important attribute in customer-and-business relationship building (Ndubisi, 2009), and plays a critical role in maintaining a customer-oriented marketing approach in today's business environment, which is applied by many successful businesses around the world (Ngo & Pavelková, 2017), including retail banks.To excel in today's fiercely competitive business environment and build a committed customer base, retail banks are advised to model their business imperative to such an extent that customer satisfaction is guaranteed (Van Deventer & Redda, 2018).Literature suggests that repeat purchases of goods and services are preceded by customer satisfaction (Clemes, 2007).Similarly, Kotler (2002) opines that customer satisfaction is a fundamental driver of repeat purchase behavior and positive word-of-mouth marketing to friends and family.Ngo and Pavelková (2017) add that customer satisfaction is also associated with increased market value, higher margins of profit, and improved investment returns.Numerous empirical results suggest that customer loyalty is predicted by customer satisfaction and is ultimately a successful attribute of maintaining profitable business-to-cus-tomer (B2C) relationships (Patterson & Spreng, 1997;Hoffman & Bateson, 2006).Furthermore, Hoffman and Bateson (2006) suggest that the level of customer satisfaction does determine post-purchase intention customers, and such customers are less likely to switch service providers.
Customer commitment has been recognized as a vital business imperative, and many researchers have investigated the construct and its significance in relationship management.Within the customer relationship context, Moorman et al. (1993) refer to commitment as "an enduring desire to maintain a valued relationship".In services marketing, such as retail banking, building a mutual commitment is an essential business imperative (Berry & Parasuraman, 1991).Morgan and Hunt (1994) concur and add that in such a setting, the bank and the customer should collaborate to boost the investment by building trustworthy and honest relationships.Customer commitment is not the same as customer loyalty; however, they are closely-related concepts (Morgan & Hunt, 1994).As such, commitment is said to be a strong predictor of customer loyalty (Bettencourt, 1997).
It is often argued that the concept of trust is trans-disciplinary in nature and that the concept originates from the political science, economics, psychology and sociology disciplines (Mayer et al., 2000).Trust is "one party's belief that its needs will be fulfilled in the future by actions undertaken by other party" (Anderson & Weitz, 1989).Building a strong business-to-customer (B2C) relationship based on solid trust is an ideal all businesses wish to achieve.Similarly, Redda and Van Deventer (2020) underscore the importance of upholding robust and mutually beneficial relationship customers in the retail-banking sector.Over the recent years, and especially after the 2007-2008 financial crises, bank customers have lost confidence and trust in their banks (Debab & Yateem, 2012), and, as a result, banks are seen to improve their image through a number of marketing activities (Sheth & Sisodia, 2006).Empirical findings in research suggest that customer trust is an important predecessor of customer loyalty (Jarvinen, 2014;Paulssen et al., 2014).Customers who display trusting behaviors to their bank are likely to become loyal customers of the bank.Loonam and O'Loughlin (2008) indicate that the banking sector around the world has faced a num-ber of factors that have negatively affected its performance.These challenges have been attributed to advancements in information and communication technology (ICT), which has inevitably led to increased costs and brand-switching behavior on the customers' side (Haenlein et al., 2007).The deregulation of the industry across the world also opened doors to new players in the industry, which increased competition, and, as result, bank-switching behavior gained momentum.
Research into customer switching behavior and switching costs has gained substantial attention over the recent past (Ngo & Pavelková, 2017; Sahin & Kitapci, 2013).Switching costs can be described as costs that are incurred to both the customer and business when a customer switches or changes a supplier.For example, "when customers switch between banks, they incur costs relating to collecting information about another bank to switch from their current banks" (Jones et al., 2002).In this case, switching cost is viewed as a once-off cost suffered by the customer when switching from one bank to another bank (Kiser, 2002).From the perspective of a banking customer, switching cost can include costs such as the time, financial resources and effort spend to open a new bank account, register with the new bank for online banking or transfer of funds from one bank account to another bank account (Clemes et al., 2010).A thorough understanding and appreciation of the concept of switching costs is vital.This is because Aydin et al. (2006) argue that switching cost mediates the relationship between satisfaction and loyalty.Similarly, Van Deventer and Redda (2018) established the influence of switching cost on customer commitment, and determined the mediating role of switching cost on service quality, bank image and customer satisfaction with regard to customer commitment.In today's competitive business setting, businesses such as banks have regarded switching cost as a key factor in their planning (Barroso & Picon, 2012).
Given the influence of service quality, customer satisfaction, customer commitment, trust and switching cost on customer loyalty, it is important that retail banks consider these factors when evaluating their customer loyalty.To this end, a validated customer-loyalty-in-retail-banking scale is necessary.After a wide-scale online search of some of the largest databases of academic research, no evidence of a validated South African customer-loyalty-in-retail-banking scale could be detected.
To fill this literature gap, the objective of this study was to validate customer loyalty in retail banking as a six-factor structure comprising customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction.To validate the customer-loyalty-in-retail-banking scale, a sample of Generation Y retail banking customers was selected.The study specifically included Generation Y banking customers for a number of reasons.The market size of Generation Y (millennials), who were born between 1986 and 2005 ( (Markert, 2004), is substantial (36% of the population, N = estimated 21 million people) within the South African context (Statistics South Africa, 2020).In addition, they are found to be a lucrative and demanding consumer segment with future earning potential and an appetite for consumption (Twenge & Campbell, 2008).This implies that any business that wishes to excel should aim to keep this market segment in its business by providing excellent service in order to earn their loyalty.Literature suggests that once such loyalty is established, businesses are able to implement effective marketing plans and foster long-term relationships (Gurău, 2012;Lazarevic, 2012).
For these reasons, it is important to have a validated customer-loyalty-in-retail-banking scale.As such, the study will address the following research question: • Is customer loyalty among Generation Y retail banking customers a six-factor structure that consists of customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction?

METHOD
The research design applied in this study was descriptive and single cross-sectional.Generation Y retail banking customers between 18 and 24 years of age, studying at South African public higher education institutions (HEIs), were the study's specified population of interest.The 26-registered public HEIs in South Africa were included in the frame of sampling.Subsequently, a judgment sample of two Gauteng-based HEI campuses was cho-sen.Fieldworkers used the mall-intercept survey method to collect data from a non-probability convenience sample of 400 participants.Participation in the study was voluntary, and all ethical processes such as obtaining ethical clearance and approval for questionnaire distribution at the respective campuses were duly followed.
A self-administered survey instrument was designed to collect data.As part of the questionnaire, the information letter delineated the study's objective and promised that the participants' information would be protected.Section A of the questionnaire was developed to gather data concerning the participants' demographics and determined the participants' ownership of a bank account.Section B of the questionnaire included validated scales from previously published studies.
Customer loyalty, service quality, customer commitment, trust and switching cost were measured using scales validated by Lewis and Soureli (2006), whereas customer satisfaction was measured using a scale validated by Veloutsou et al. (2004).Three items were measured in each factor using a six-point Likert-type scale, in which one denoted strongly disagree and six strongly agree.
Two IBM Statistical Packages were used to analyze the data, namely SPSS and AMOS, Version 27 for Windows.Descriptive, reliability and validity, correlation statistics, together with the diagnostics for collinearity and confirmatory factor analysis using the maximum likelihood approach, formed part of the data analysis.

RESULTS
Data cleaning was performed to remove all those questionnaires that do not meet this study's target population specifications.Consequently, 271 questionnaires remained for further analysis, which equates to a study response rate of nearly 70%.
In accordance with the target population specifications, participants between the ages of 18 and 24 years made up the sample.The sample included slightly more male than female participants and was representative of the 11 official South African language groups, five ethnic groups and nine provinces.Table 1 organizes the statistics on the sample.
For each latent factor, descriptive statistics (mean = X ̄; standard deviation = σ), Cronbach's alphas (α) and coefficients of Pearson's product-moment correlation were calculated.The Cronbach's alpha value is indicative of internal-consistency reliability, whereas the correlation coefficients point towards the relationship between the latent factors and the measurement theory's nomological validity.Moreover, collinearity diagnostics were performed to assess whether there is multicollinearity between the factors.Table 2 reports on the results.
As Table 2 showsn, each latent factor returned a mean value that exceeds 3.5.There is evidence of internal-consistency reliability given that each latent factor returned a Cronbach's alpha value greater than the suggested value of 0.70 (Malhotra, 2010).The correlation analysis showed that a statistically significant positive relationship (p ≤ 0.01) was evident between each pair of latent factors, which suggests the measurement theory's nomological validity (Hair et al., 2010).Given that the strongest correlation coefficient (r = 0.74) was below the recommended level of 0.90, the chances of multicollinearity between the factors are slim (Pallant, 2013).To assess more subtle forms of multicollinearity, the diagnostics for collinearity were performed.The tolerance values (TV) ranged between 0.30 and 0.72, which exceed the suggested level of 0.10, and the average variance inflation factor (VIF) of 2.26 is below the recommended level of 10 (Pallant, 2010).As such, serious multicollinearity concerns could be eliminated.With no serious multicollinearity between the latent factors, together with the nomological validity of the measurement theory established, a measurement model was proposed.
Using the maximum likelihood approach, confirmatory factor analysis was performed for a specified six-factor measurement model, which included customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction.Each latent factor contained three indicators.To identify the model, each of the six latent factors' first loading was set at 1.0.In doing this, 189 distinct sample moments were derived with 68 distinct parameters to be estimated, equating to 121 degrees of freedom (df) based on an over-identified model.In addition, a chi-square value of 307.02 (p = 0.001) was produced.To check for any problematic estimates, the measurement model was assessed in terms of standardized factor loadings greater than 1.0 or lower than -1.0.In addition, negative error variances were checked (Hair et al., 2014).To evaluate composite reliability (CR) and construct validity, the CR, average variance extracted (AVE) and heterotrait-monotrait (HTMT) values were calculated.
In addition, the correlation coefficients for each latent factor and its observed variable were computed.The estimates of the measurement model are reported in Table 3.
Table 3 suggests that the estimates were not problematic and that there was a statistically significant (p ≤ 0.01) relationship between each latent factor and its observed variable.With CR values exceeding 0.70 and AVE values above 0.50, CR and convergent validity are confirmed (Malhotra, 2010;Hair et al., 2014).Concerning discriminant validity, the HTMT values did not exceed 0.85, which point towards discriminant validity (Henseler et al., 2015).There is evidence of construct validity given the combination of convergent and discriminant validity together with the nomological validity confirmed in Table 2 (Malhotra, 2010).
Fit to the model was evaluated using "the incremental fit index (IFI), Tucker-Lewis index (TLI), comparative fit index (CFI), the standardized root mean residual (SRMR), the root mean square of approximation (RMSEA), and the chi-square statistic" (Van Deventer, 2018, p. 191).Acceptable fit to the model is achieved when the chi-square value is non-significant and when the IFI, TLI and CFI values exceed 0.90.In addition, the RMSEA value should be equal of less than 0.08 (Malhotra, 2010), whereas the SRMR value should not exceed 0.1 (Hair et al., 2014).While the model of measurement achieved a significant chi-square value of 307.02 with 121 degrees of freedom (df), all other fit measures indicate good model fit with IFI = 0.95, TLI = 0.93, CFI = 0.95, SRMR = 0.05 and RMSEA = 0.08.
The measurement model specified in this study not only exhibited good model fit, but also acceptable internal-consistency and CR, as well as nomological, convergent, discriminant and construct validity.As such, a structural model may be tested.According to the literature, the structural model will assess whether service quality, customer commitment, trust, switching cost and customer satisfaction have a direct positive influence on customer satisfaction in the context of retail banking.

DISCUSSION
The results of the study reveal that, on a six-point Likert-type scale used, Generation Y customers are loyal and committed to their retail bank and consider the quality of service they receive as sufficient.Furthermore, Generation Y customers have trust in their retail bank, are satisfied with their retail bank and are of the opinion that it would be too much of an effort and a waste of time to switch to another retail bank.Furthermore, the correlation analysis shows that the strongest relationship was found between customer loyalty and customer satisfaction (r = 0.74), closely followed by customer satisfaction and trust (r = 0.73

CONCLUSION
The purpose of this study was to explain the process followed to validate customer loyalty in retail banking as a six-factor structure consisting of customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction.Using a sample of Generation Y retail-banking customers, the confirmatory factor analysis results validated that customer loyalty in retail banking is a six-factor structure that includes customer loyalty, service quality, customer commitment, trust, switching cost and customer satisfaction.The results show that there was no serious multicollinearity between the latent factors and that acceptable internal-consistency reliability was returned for each factor.Furthermore, the correlation analysis confirmed the nomological validity of the theory of measurement.Moreover, the measurement model returned acceptable CR together with construct, convergent and discriminant validity.In addition, the model fit index values of IFI, TLI, CFI, SRMR and RMSEA suggest a good fitting model.Thus, the results of this study concluded that this six-factor model is a reliable and valid measure of customer loyalty in retail banking and is the first validated customer loyalty scale within the retail-banking context of South Africa.
).Moreover, the specified measurement model recorded no problematic estimates and displayed evidence of CR, as well as three forms of validity, namely convergent, discriminant and construct validity.In addition, the measurement model's fit indices were indicative of acceptable model fit, making this an appropriate measurement model to test in structural equation modeling.As such, retail banks are encouraged to use this validated customer-loyalty-in-retail-banking scale to assess whether service quality, customer commitment, trust, switching cost and customer satisfaction have an influence on customer loyalty.This study is not without limitations.For example, a convenience sample was employed to survey participants.As such, when generalizing the results to the whole Generation Y banking population, great care should be taken.Moreover, this study's sample was limited in terms of geographical location.In addition, Generation Y banking customers from only two HEI campuses participated in this study.Therefore, this study could be carried out on a larger scale in the future.Other future research opportunities include a longitudinal study and qualitative studies.