Understanding mediators and moderators of the effect of customer satisfaction on loyalty

Abstract Customer satisfaction, loyalty and corporate image play a critical role in improving loyalty within the banking sector. The current study examines the mediators and moderators of the effect of customer satisfaction on loyalty. Data were collected from bank customers (n = 308) using a structured questionnaire through a cross-sectional survey in Chinhoyi, Zimbabwe. Data were analysed using structural equation modelling and moderated regression analyses. Customer satisfaction has a direct positive effect on customer loyalty. Service quality and corporate image were each found to partially mediate the effect of customer satisfaction on customer loyalty. Gender, age, education and income were found not to moderate the effect of customer satisfaction on loyalty. Thus, this study extends the extant services marketing literature by examining the mediators and moderators of the customer satisfaction-customer loyalty relationship within the banking sector. As a result, banks are encouraged to consider customer satisfaction, service quality and image altogether when trying to influence customer loyalty.

ABOUT THE AUTHOR Lovemore Chikazhe holds a PhD in Marketing from Chinhoyi University of Technology. He is currently a lecturer at the same university in the Department of Retail Management. His research area of interest is services marketing. Charles Makanyeza is a senior academic, researcher and consultant who commands respect among his peers. Among many educational qualifications, he holds a PhD in Marketing from the University of KwaZulu-Natal, South Africa. He is an Associate Professor of Marketing and Strategy at the Namibia Business School, University of Namibia. His research areas of interest include marketing and strategy. Blessing Ropafadzo Chigunhah is a practising agricultural entrepreneur, and an avid researcher in agricultural economics and financial services. Currently, she is pursuing a PhD in Agricultural Finance with the Chinhoyi University of Technology.

PUBLIC INTEREST STATEMENT
Customer satisfaction and loyalty play a critical role in the success of banks. The current study examines the mediators and moderators of the effect of customer satisfaction on loyalty. This study examines the mediating effects of service quality and image on the customer satisfaction-loyalty relationship within Zimbabwe's banking sector. Furthermore, the study tests the moderating effect of consumers' demographic characteristics (gender, age, education and income) on the customer satisfaction-loyalty relationship. The study demonstrates that satisfied customers are loyal to the organisation. Moreover, organisations that deliver superior service quality and improve corporate image also strengthen the relationship between customer satisfaction and loyalty. Demographic factors like gender, age, education and income do not influence the effect of customer satisfaction on loyalty within the banking sector. Banks are therefore encouraged to address issues to do with customer satisfaction, service quality as well as corporate image so as to improve customer loyalty.

Introduction
Worldwide markets have become service-oriented with the service industry playing a critical role in all economies. However, competition has become intense within the global service industry such that successful firms are depending more on a sound understanding of the behaviour of their customers (Hosseini & Saravi-Moghadam, 2017). The banking sector is among the most affected service sectors (Sardana & Bajpai, 2020). The increase in market players within the banking sector has resulted in a complex, highly competitive and dynamic business environment (Kumar & Gulati, 2009). However, services and products offered within the banking sector exhibit slight differences which makes it easy for customers to switch service providers. The banking sector is also faced with stiff competition as more players with similar products and services continue to invade the market. As such, banks are under pressure to find ways on how to turn ordinary customers to loyal customers. Moreover, banks are compelled to understand the factors that influence customer loyalty.
Customer loyalty plays a critical role in the success of banks (Ashraf et al., 2018). Through loyal customers, banks are assured of sustainable competitive advantage (Hosseini & Saravi-Moghadam, 2017). Additionally, bank performance largely depends on loyal customers (Liat et al., 2014;Ngo & Nguyen, 2016). Customer-centric banks attract, retain and build intimate longterm relationships with customers (Renganathan et al., 2012). Customer retention is important for banks because it is more expensive to acquire new customers than retain existing ones (Cronin & Taylor, 1992). Understanding factors that influence customer loyalty is a major stride in creating loyal customers. Such factors include service quality, customer satisfaction and image (Ashraf et al., 2018;Darmawan, 2018;Ngo & Nguyen, 2016).
Banks that fail to improve the quality of service are in danger of losing business to competitors (Ndubisi et al., 2007). This makes it imperative for banks to prioritise programmes that improve service quality, which in turn results in customer loyalty. Moreover, customers consider the firm's image when they are faced with a choice (Groonros, 2010). Corporate image is key to a firm since it is the overall impression by public observances about a firm which customers relate to physical and behavioural attributes of the firm (Hong & Marimuthu, 2014). Demographic factors also play an active role in influencing consumer behaviour (Pitchayadejanant & Nakpathom, 2016). They influence perceptions of customers differently especially within the service industry (Akbar, 2013).
There is a plethora of studies that have been conducted within the banking sector focusing on customer loyalty, customer satisfaction, service quality and corporate image (Abd-El- Salam et al., 2013;Ashraf et al., 2018;Darmawan, 2018;Ngo & Nguyen, 2016;Nguyen & Leblanc, 2001). However, it is worth mentioning that there are relatively sparse studies that have examined the mediators of the effect of customer satisfaction on customer loyalty. Moreover, research is inconclusive as regards the moderating effects of demographic variables on the relationship between customer satisfaction and loyalty. Thus, this study extends the extant services marketing literature by examining the mediators and moderators of the customer satisfaction-customer loyalty relationship within the banking sector. Therefore, the specific objectives of the study were to test service quality as a mediator of the customer satisfaction-customer loyalty relationship; to test bank image as a mediator of the customer satisfaction-customer loyalty relationship; and to test the moderating effect of gender, age, education and income on the effect of customer satisfaction on customer loyalty.
The rest of the paper includes a literature review which includes the theoretical framework covering the concepts of customer satisfaction, loyalty, service quality and corporate image. Thereafter, the paper presents the development of research hypotheses, research model, research methodology, analysis and results, discussion and implications, and conclusion.

Customer satisfaction
Customer satisfaction refers to the need contentment, evaluation of ultimate and actual result, desire and assessment of purchase experiences (Groonros, 2010). It focuses on measurement that determines how happy clients are with a firm's products and competences (Bassan & Kathuria, 2016;Gupta, 2016;Khare, 2011;Zeithaml & Bitner, 2013). The study understands customer satisfaction as a measurement used to evaluate how much a client is contented with a bank's product or service, administration and experience.
Customer satisfaction is critical to a business since it can be used to identify potential market opportunities (Bashir et al., 2012;Jawaad et al., 2019). Modern businesses should be customeroriented since customer satisfaction is the starting point of excellence and standard performance (Bassan & Kathuria, 2016;Sendawula et al., 2018). Satisfied customers are the purpose of business because businesses rely on them, rather than customers being dependent on businesses. Satisfied customers are a benefit to the firm in that they do not easily switch suppliers (Harzaviona & Syah, 2020;Nikou & Khiabani, 2020). Satisfied customers share their experiences with others whereas dissatisfied customers share with much more customers about their unhappy experience resulting in the loss of business (Felix, 2017;Taliah, 2007). Moreover, dissatisfied customers may decide not to complain but rather abandon the firm and switch to competitors (Hasfar et al., 2020;Islam et al., 2020). Therefore, service providers should ensure that their customers are satisfied.

Customer loyalty
Customer loyalty refers to the willingness of customers to keep a relationship with a company and to continue using its services and products (Lovelock & Wright, 2002;Zaini et al., 2020). It encompasses, but is not limited to, repeat business transactions by consumers. Moreover, customer loyalty is key in services management (Caruana, 2002). Customer loyalty is regarded as a multi-dimensional construct (Dahiyat et al., 2011). It can be measured using behavioural, attitudinal and composite measures (Cifci & Erdogan, 2016). Attitudinal loyalty is the point at which a customer decides to be faithful as a result of a positive brand inclination. Behavioural loyalty is the point at which a consumer keeps on purchasing a specific product, service or brand (Khajeheian & Ebrahimi, 2020). Behavioural loyalty benefits organisations through increased sales that result from repeat purchases. Composite loyalty combines attitudinal and behavioural measures of loyalty (Iordanova, 2017;Liu et al., 2020). Composite loyalty is valuable because it allows businesses to generate more sales through a strong base of trusted customers (Rasoolimanesh et al., 2019).
The relationship between the firm and loyal customers is built over a long period of time. It is built through a consistent record of encounters with customers (Liat et al., 2014). Also, loyal customers are part of business assets which are difficult to replace (Ndubisi et al., 2007). Moreover, loyal customers are beneficial to an organisation since they add value through repeat purchases. Service costs are also lowered if a firm can maintain loyal customers. Customer loyalty determines business success since repeat transactions result in increased revenue and profits (Iordanova, 2017). Cifci and Erdogan (2016) further expound that the importance of customer loyalty in any business is that it facilitates sales increase. Tarus and Rabach (2013) affirm that getting new customers may be expensive as compared to retaining existing ones since loyal customers do not easily switch suppliers. Acquiring customers can also be an expensive exercise but keeping them loyal may lead to amortisation of acquisition costs (Ngo & Nguyen, 2016). It has also been ascertained that businesses with loyal customers tend to enjoy competitive advantage (Makanyeza, 2015).
Customer loyalty is influenced by several factors that include customer satisfaction, corporate image and service quality (Orozco & Cavazos Arroyo, 2017). Customers' commitment to the organisation is a result of emotional attachment and resistance to switching behaviour (Liat et al., 2014).

Corporate image
Corporate image is understood as the general impression on public observances about a business which is linked to physical and behavioural attributes (Hatch et al., 2003). Likewise, Richard and Zhang (2012) delineate the corporate image as perceptions of a firm reflected in the customer's memory. Furthermore, Hong and Marimuthu (2014) posit that corporate image results from accumulated information about the firm, leading to an attitude or impression towards the same firm. Thus, the corporate image may be viewed as the aggregate measure that is built through credible actions. Additionally, Hatch et al. (2003) emphasise that corporate image is all about the general impression made on the mind of the customer about an organisation. Corporate image is regarded as a mirror of the business' history that communicates information to target customers concerning the quality of its services and products in comparison with those of its competitors (de Leaniz & del Bosque Rodríguez, 2016). Corporate image is developed in the customers' mind through experience and communication (Richard & Zhang, 2012). Liat et al. (2014) further assert that corporate image helps to grow the company's sales and its market share and to create and uphold a loyal relationship with consumers. Corporate image is very key to any business operation because of its strength in the customers' perception when hearing the name of the organisation (Hatch et al., 2003). Richard and Zhang (2012) considered the corporate image as a vital factor for assessing the firm's operation. The corporate image requires a lot of time and massive resources to build, but on the other hand, it can help the company not only by introducing new brands but also in picking up the sales of existing brands (Groonros, 2010). For services organisations to gain a competitive advantage in the marketplace, they ought to create a positive corporate image in the minds of consumers through the use of related marketing strategies (Richard & Zhang, 2012).

Service quality
Service quality represents a gap existing between customer expectations and actual service performance (Liu et al., 2020;Parasuraman et al., 1988). Similarly, Lovelock and Wright (2002) construed service quality as to how well the level of the delivered service matches customer's expectations. Groonros (2010) agrees with Lovelock and Wright (2002) in that service quality results from a comparison between customer expectations and perception of the way the service has been performed. Cronin and Taylor (1992) added that service quality differs only in the phrasing but involves determining whether or not service delivery is meeting or exceeding customer expectations.
Service quality acts as a strong source of competitive advantage within the service industry Woratschek et al., 2020). That is, competitive advantage results from continuous improvement on quality and reliability of the organisation's products (Bahadur et al., 2018;M. S. Iqbal et al., 2018). Continuous improvement of service quality yields more customer satisfaction and loyalty (Chongsanguan et al., 2016;Junior & de Aquino Guimarães, 2012). Therefore, if customers are satisfied with the firm's level of service quality, chances for repeat purchases increase. Service quality plays a differentiating role among similar services. Superior service quality sets apart the firm from its competitors (El Essawi & El Aziz, 2012;Garepasha et al., 2020).
Various approaches have been used to measure service quality in the services environment (e.g., SERVQUAL, SERVPERF and BANKSERV). According to Parasuraman et al. (1988), service quality is operationalized using five dimensions, namely tangibles, reliability, responsiveness, assurance and empathy. As such, they developed the SERVQUAL model to measure service quality based on these five dimensions. Responsiveness is described as the willingness by staff to assist customers and to provide prompt service continuously. Assurance refers to the ability of an organisation's employees to instigate confidence and trust within customers. Tangibles are physical things of an organisation that include staff appearance, equipment and other customers. Empathy is the extent of individualized care given by the firm to its customers. Reliability is described as the ability to perform services accurately and independently. In the SERVQUAL approach, service quality was measured by comparing customer expectations with perceptions. (Berry, 2005;Zeithaml & Bitner, 2003). Cronin and Taylor (1992) developed SERVPERF model for measuring service quality. The SERVPERF is similar to SERVQUAL in that both models are based on the five dimensions of service quality. However, the two approaches differ in that the SERVPERF model measures service quality using customer perceptions only. Avkiran (1994) developed the BANKSERV model for service quality assessment for use in the banking sector based on the four dimensions, namely staff conduct, credibility, communication and access to teller services. Just like the SERVQUAL model, the BANKSERV tool measures service quality based on the difference between customer expectations and perceptions. This study uses the SERVPERF approach because of its simplicity and growing popularity. The SERVPERF tool is less cumbersome as compared to the other two approaches because it only uses customer perceptions. More so, the five service quality dimensions in the SERVPERF model are so broad that they encompass the BANKSERV dimensions.

Demographic factors
Demographics refers to characteristics of consumers comprising gender, age, education, income, marital status, literacy, among others (Bhatt & Bhatt, 2016). Chauhan et al. (2016) stressed the importance of demographics in marketing research. Demography influences customers' decision making (Kamboj & Singh, 2018;Olasina, 2015). Similarly, the buying decision-making process within the banking sector is highly dependent on such factors as gender, age, income and education of the respondents (Chawla & Joshi, 2017). Shaikh and Karjaluoto (2015) confirm that social-cultural factors such as demographic factors impact on customer satisfaction and loyalty in the banking environment. Likewise, both psychographic and demographic variables (e.g., age, gender, personal income, and education) affect consumers' decisions within the banking sector (Olasina, 2015;Shaikh & Karjaluoto, 2015). Additionally, Lee et al. (2015) observe that demographic factors like employment status, income level, gender, age, marital status, and area of residence influence the behaviour of bank customers.

Development of research hypotheses and research model
The relationship between customer satisfaction and customer loyalty is crucial within the banking sector (El-Adly, 2019; Rahayu et al., 2020;Raza et al., 2020). Furthermore, successful banks are dependent on a strong base of satisfied and loyal customers . The general agreement in the literature confirms a positive relationship between customer satisfaction and customer loyalty (Abd-El- Salam et al., 2013;Asongu et al., 2020;Chiguvi & Guruwo, 2017;Kamboj & Singh, 2018;Thakur, 2014). A study by Akbar and Parvez (2009) to establish the impact of service quality, trust, and customer satisfaction on customer loyalty found that customer satisfaction influences customer loyalty. In another study by Thakur (2014) to establish the relationship between customer satisfaction and loyalty, it was found that customer satisfaction has a positive effect on customer loyalty. Similarly, El-Adly (2019) investigated the association between customer perceived value, customer satisfaction, and customer loyalty and found that customer satisfaction was positively correlated to customer loyalty. Thus, it is hypothesised that:

H 1: Customer satisfaction has a direct positive effect on customer loyalty
Service quality plays an important role in influencing customer satisfaction (Chawla & Joshi, 2017;Gong & Yi, 2018;Iskhakova et al., 2020;Liat et al., 2017;Teka & Sharma, 2017). B.L. Cheng and Rashid (2013) conducted a study to test the influence of customer satisfaction on service quality. The study found that customer satisfaction positively influences service quality. In a related study by Rashid (2013) to examine the effect of customer satisfaction and service quality on loyalty, it was established that both customer satisfaction and service quality influence customer loyalty. Likewise, Dimyati (2018) carried out a similar study to establish the effect of customer satisfaction on loyalty. It was concluded that customer satisfaction has a positive impact on customer loyalty. Similarly, Izogo (2017) studied the effect of service quality on customer loyalty. Results of the study show that service quality is a strong predictor of customer loyalty. A study by Gong and Yin (2018) confirms a positive relationship between service quality and customer loyalty. This discussion shows that customer satisfaction and service quality each positively influences customer loyalty. Hence, it is logical to expect service quality to act as a mediator for the customer satisfaction-customer loyalty relationship. Likewise, it is posited that: H 2 : Service quality mediates the effect of customer satisfaction on customer loyalty Corporate image is a key variable within the banking sector (Dimyati, 2018;Gong & Yin, 2018). Moreover, bank customers consider the bank image seriously when they are faced with a choice to make (Izogo, 2017). Several studies confirm that corporate image positively influences customer loyalty (de Leaniz & del Bosque Rodríguez, 2016;Liat et al., 2017;Setiawan & Sayuti, 2017). In their study, de Leaniz and del Bosque Rodríguez (2016) sought to establish the drivers of customer loyalty. The results confirm that corporate image positively influences customer loyalty. Liat et al. (2017) studied the relationship between customer satisfaction and corporate image. They found that corporate image influences customer loyalty. Similarly, Setiawan and Sayuti (2017) studied the effect of service quality, customer trust and corporate image on customer satisfaction and loyalty. They concluded that corporate image is a good predictor of customer loyalty. This extant empirical literature tells us that both customer satisfaction and corporate image have a positive effect on customer loyalty. As such, it is plausible to assume that corporate image can mediate the customer satisfaction-customer loyalty relationship. Therefore, it is postulated that:

H 3: Corporate image mediates the effect of customer satisfaction on customer loyalty
Customer satisfaction has a significant and positive influence on customer loyalty (Chikazhe et al., 2020;Dimyati, 2018). Females were found to be more loyal than males at higher levels of trust in the banking environment (Ndubisi, 2006). Women were found to be more loyal than men to Greece's financial, retailing, entertainment and transportation services (Dimitriades, 2006). Women and men differ in terms of buying behaviours. Women tend to be more involved in purchasing activities than men. As a result, women develop stronger connections with brands than men do. This makes women more loyal to particular brands than men. Similarly, it is observed that the customer satisfaction-loyalty link is stronger in women than men (Gonçalves & Sampaio, 2012). Based on these observations, it is logical to expect that the customer satisfaction-loyalty relationship will be stronger in females than males. Therefore, it is posited that:

H 4: The effect of customer satisfaction on loyalty is stronger in female than male consumers
Previous studies have confirmed that customer satisfaction has a positive influence on customer loyalty (El-Adly, 2019). Results from a study by Bhatt and Bhatt (2016) reveal that age positively influences customer satisfaction and loyalty. Consumers with higher education can easily conduct and enjoy searching for new information concerning products more than lowerincome consumers do. As such, higher-income consumers can easily shift from one particular brand to the other unlike lower-income consumers who tend to be stuck with certain brands because they cannot afford other brands. This makes lower-income consumers more loyal to brands than higher-income consumers. As such, the effect of customer satisfaction on loyalty tends to be stronger among lower-income than higher-income consumers (Gonçalves & Sampaio, 2012). Therefore, it is hypothesised that:

H 5: The effect of customer satisfaction on loyalty is stronger in older than younger consumers
Customer loyalty is positively influenced by customer satisfaction (Chiguvi & Guruwo, 2017). Extant literature shows notable differences in consumer purchase behaviour between older and younger consumers. Younger consumers are more energetic and consider more brands when making purchase decisions than older consumers consider. Older consumers usually choose wellestablished brands, avoiding newer brands because the ability to process purchasing information decreases as consumers grow older. As such, older consumers are more loyal to particular brands than younger consumers are. Similarly, the relationship between customer satisfaction and loyalty is stronger in older than younger consumers (Gonçalves & Sampaio, 2012). In this regard, it is plausible to propose that:

H 6: The effect of customer satisfaction on loyalty is stronger in less educated than consumers that are more educated
Prior studies have shown that customer satisfaction has a positive relationship with customer loyalty (Asongu et al., 2020;Kamboj & Singh, 2018). The impact of income on consumer purchase decisions is significant. Thus, higher-income consumers have less barriers when choosing brands. They can easily try new things. Hence, they are less loyal than lower-income consumers are. The effect of customer satisfaction on loyalty is stronger in consumers with higher than lower income (Gonçalves & Sampaio, 2012). Based on this discussion, it makes sense to assume that the customer satisfaction-loyalty relationship is stronger in consumers with lower than higher income. Likewise, it is proposed that:

H 7: The effect of customer satisfaction on loyalty is stronger in lower-income than higher-income consumers
Evidence from the existing body of literature shows a lack of empirical evidence on service quality and corporate images as mediators of the relationship between customer satisfaction and loyalty. Furthermore, the moderating effects of gender, age, education and income on the relationship between customer satisfaction and loyalty have not been accorded notable scholarly attention. It is therefore necessary to propose the research model in Figure 1. Figure 1 shows that customer satisfaction influences loyalty. The proposed model also suggests that service quality and corporate image mediate the effect of customer satisfaction on loyalty. The model also proposes that gender, age, education and income moderate the effect of customer satisfaction on loyalty.

Research methodology
This section focuses on the questionnaire design and measures, sampling and data collection methods.

Questionnaire design and measures
Appendix A shows items that were used to measure customer satisfaction (Sat), service quality (Qual), corporate image (Imag) and customer loyalty (Loy) based on the Likert scale which ranged from 1 (Strongly disagree) to 5 (Strongly agree). The study borrowed items from previous related studies and modified them to suit the current study (Avkiran, 1994;Cronin & Taylor, 1992). The items for all constructs focused on perceptions of bank customers.

Sampling and data collection
The target population of this study were customers of four major banks in Chinhoyi town in Zimbabwe. Chinhoyi was chosen because of its convenient location. It was easily accessible to the researchers. Similarly, there is a reasonable proportion of banks operating in Chinhoyi.
A cross-sectional survey of bank customers was conducted using self-administered questionnaires which were randomly distributed to bank customers as they walked out of their respective banks. The respondents were given approximately 30 minutes to complete the questionnaires. Out of a total of 400 distributed questionnaires, 308 were returned and usable. Table 1 indicates the demographic characteristics of bank customers who participated in the study.
The basic characteristics of respondents, as depicted in Table 1 show that there were more female (54.5%) than male (45.5%) respondents. The majority (86.1%) of the respondents were aged between 20 to 49 years. The respondents had attained the following levels of education: Certificate 21.1%, Diploma 29.2%, Bachelor's degree 32.1%, Master's degree 11% and Doctoral degree 6.5%. The majority (91.9%) of the respondents were earning less than US$1500 per month.

Data validation
Data were validated using data normality test, non-response bias test, common method bias (CMB) analysis, convergent validity and discriminant validity.

Data normality test
Normality tests was conducted to establish if data was normally distributed (Gupta et al., 2019;Park, 2015). The normality test is essential as it indicates which type of inferential statistics researchers should use as during data analysis (Ahad et al., 2011;Mbah & Paothong, 2015). Z-scores were used to check for data normality. The scores were computed in SPSS version 22. The Z-scores (n = 308) for all the variables and items fell within the range −3.29 and +3.29 with a statistical significance of p ≤ 0.001. This suggests that data were approximately normally distributed (Arbuckle, 2009;Pallant, 2010;Razali & Wah, 2011).

Non-response bias
Non-response bias is a type of bias caused by differences between respondents and nonrespondents (Berg, 2005;Lahaut et al., 2002). It is important to carry out a non-response bias test because failure to respond by selected participants reduces the sample size and this affects the generalisability of research findings (Studer et al., 2013). The method by Armstrong and Overton (1977) was used to check for non-response bias. Using this method, means of each of the items of the last half of the responses were compared against those of the first half of the responses. No significant differences were noted in the means for the two waves of the responses. This indicates that the study did not suffer from non-response bias.

CMB
CMB is a result of differences in responses that emanate from the instrument itself instead of predispositions of the respondents that the instrument tries to uncover (Siemsen et al., 2010). Furthermore, the CMB elucidates the measurement error that is complicated by the sociability of participants who intend to offer positive answers (MacKenzie & Podsakoff, 2012). CMB influences item validity and reliability, and the covariation between latent constructs (Min et al., 2016). CMB was assessed using Harman's single factor test. Exploratory factor analysis was conducted in SPSS version 22, fixing the number of factors at 1. Previous studies (e.g., Kim et al., 2013) suggest that the presence of a single factor with a variance explained greater than 50% suggests that there is CMB. The solution gave a factor with a variance explained of 39.66%. This implies that CMB was not a threat to this study.

Convergent validity
Convergent validity was assessed using measurement model fit indices, Cronbach's alpha reliability, composite reliability, standardised factor loadings, individual item reliabilities (squared multiple correlations), critical ratios and average variance extracted. Table 2 indicate that minimum conditions for the measurement model fit indices were satisfied. Results in Table 3 show that minimum conditions for convergent validity were achieved since all standardised factor loadings were above the recommended 0.6 cut-off point (McQuitty & Wolf, 2013). Critical ratios were appropriately large and significant at p < 0.001. Individual item reliabilities, composite reliabilities and Cronbach's alpha values were all acceptable as they were above 0.6 (Hair et al., 2010). Critical ratios were large enough and significant at p < 0.001. All constructs had average variance extracted above 0.5 as indicated in Table 4 (Field et al., 2012;Park, 2015).

Discriminant validity
Results in Table 4 show that the condition for discriminant validity was achieved. All AVEs (diagonal elements) were above the squared inter-construct correlations, (Field, 2009;Park, 2015). H2 was also tested using SEM. Model fit indices were acceptable: χ2/DF = 2.43; GFI = 0.917; AGFI = 0.909; NFI = 0.929; TLI = 0.923; CFI = 0.932; RMSEA = 0.45. Results show that the path customer satisfaction → service quality → customer loyalty is significant (path coefficient = 0.218, p = 0.015). The coefficient of the direct path customer satisfaction → customer loyalty has been reduced to 0.570 when service quality is included as a mediator. This suggests that service quality partially mediates the effect of customer satisfaction on customer loyalty. Therefore, H2 was supported.

Structural equation modelling
H3 was also tested using SEM. Model fit indices (χ2/DF = 2.52; GFI = 0.906; AGFI = 0.910; NFI = 0.920; TLI = 0.914; CFI = 0.921; RMSEA = 0.46) fell with acceptable ranges. Results show that the path customer satisfaction → corporate image → customer loyalty is significant (path coefficient = 0.250, p = 0.002). Thus, the coefficient of the direct path customer satisfaction → customer loyalty has been reduced to 0.340 when the corporate image is included as a mediator. This suggests that corporate image partially mediates the effect of customer satisfaction on customer loyalty. Therefore, H3 was supported.

Moderated regression
Moderated regression analysis was used to test H4, H5, H6 and H7. Results are summarised in Table 5. Results show that coefficients for the interaction terms (Customer satisfaction × Gender, Customer satisfaction × Age, Customer satisfaction × Education, and Customer satisfaction × Income) were insignificant (p > 0.05). This suggests that gender, age, education and income do

Theoretical implications
In the marketing literature, despite the call for improvement of customer satisfaction to increase customer loyalty (Chawla & Joshi, 2017;Dimyati, 2018;Gong & Yi, 2018), there is a need to incorporate other variables to further strengthen this relationship. Service quality and corporate image play a significant role in services marketing especially within the banking sector (Liat et al., 2017;Teka & Sharma, 2017).
There is little evidence in the extant literature of studies that have examined the mediating effects of service quality and image on the customer satisfaction-loyalty relationship. More so, empirical literature is inconclusive about the moderating effects of consumers' demographic characteristics on the customer satisfaction-loyalty relationship. Therefore, the study was carried out to narrow this existing knowledge gap in services marketing literature. The study shows that customer satisfaction, service quality and image are critical factors that influence customer loyalty within the banking environment.
Service quality was found to partially mediate the effect of customer satisfaction on customer loyalty. Results imply that service quality plays a crucial part in the relationship between customer satisfaction and customer loyalty. This suggests that when predicting customer loyalty, both customer satisfaction and service quality should be taken into consideration. This finding enriches the understanding of the relationship between customer satisfaction and customer loyalty.
Similarly, the study found that corporate image partially mediates the effect of customer satisfaction on customer loyalty. Thus, the corporate image also plays an important role in the customer satisfaction-loyalty relationship. The implication of this is that, when explaining customer loyalty, both customer satisfaction and image should be taken into account. This finding expands the literature on the relationship between customer satisfaction and customer loyalty. The study also established that gender, age, level of education and income do not moderate the effect of customer satisfaction on loyalty. Thus, demographic variables do not play a significant role in the relationship between customer satisfaction and loyalty within the banking sector.

Practical implications
To increase customer loyalty, banks are encouraged to address issues to do with customer satisfaction, service quality as well as corporate image. Thus, banks are recommended to consider a set of these factors together as predictors of customer loyalty instead of considering customer satisfaction, service quality and image in isolation. Accordingly, banks are advised to increase customer loyalty by addressing the following altogether: First, banks should ensure customer satisfaction through, inter alia, providing adequate service, meeting customer expectations and fulfilling customer promises. Second, it is recommended that banks improve service quality. This can be achieved by, for example, by ensuring that workers are presentable, offering prompt service to customers, providing personal service and understanding needs of their customers. Third, banks are advised to work on improving their corporate images. This can be done by, for example, offering innovative and pioneer products, being ethical when doing business and being responsive to customers.

Conclusion
The purpose of the study was to examine the mediators and moderators of the effect of customer satisfaction on loyalty. The study found that service quality and corporate image each partially mediates the effect of customer satisfaction on customer loyalty. Organisations that deliver superior service quality and improve corporate image strengthen the relationship between customer satisfaction and loyalty. Demographic factors like gender, age, education and income do not influence the effect of customer satisfaction on loyalty within the banking sector.
The study has limitations that provide reasonable grounds to conduct further studies. For example, the study was only conducted in one sector and in one country. This makes it difficult to generalise the findings. Therefore, it is recommended that further studies be conducted in other sectors and in other markets in order to improve the generalisability of the findings.