Index

ABSTRACT

The purpose of the study is to understand how effective customer complaint handling procedure among Ghanaian rural banks enhances customer satisfaction. A cross-sectional research on 72 rural banks and 3,622 rural banking customers through questionnaire is conducted. The sample framework included customers of the rural banks who frequently visit the bank premises for transactions and have accounts with the bank for at least 5 years. Responses are analyzed using Chi-square goodness of fit test, ANOVA, multiple regression and Pearson moment correlation. The regression results predicted that effective complaint handling procedures among rural banks will significantly influence the level of satisfaction among customers. The Pearson-moment correlation as well confirms that there exist a significant and stronger relationship between complaint handling procedures and customer satisfaction among rural banking. This study focuses on rural banking customer service management and satisfaction in Ghana. The area of complaint handling processes among rural banks remains a gap in previous literature which needed to be filled.

Keywords:Customer satisfaction, Rural banks, Complaint handling, Consumer behavior, Service management, Ghana.

JEL Classification: D10; D11; D12.

DOI: 10.20448/802.62.285.297

Citation | Nkrumah, Nana Kwame Edmund; Obeng Ernest; Akoto Linda Serwah; Oswin Aganda Anaba (2019). Examining Complaint Handling Processes among Ghanaian Rural Banks and its Influence on Customer Satisfaction. International Journal of Economics, Business and Management Studies, 6(2): 285-297.

Copyright: This work is licensed under a Creative Commons Attribution 3.0 License

Funding : This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

History : Received: 19 July 2019 / Revised: 21 August 2019 / Accepted: 26 September 2019 / Published: 1 November 2019.

Publisher: Online Science Publishing

1. INTRODUCTION

Rural banking in Ghana can be traced as far back as 1976. The first rural bank in Ghana, Agona Nyakrom Rural bank was purposely established to extend financial services to the rural folks, especially, providing micro-credit to farmers and petty traders who were not captured in the conventional banking circle (Tsamenyi and Shazad, 2008). Today, the concept of rural banking has been widely spread in every corner of Ghana. As at the end of 2018, the number of licensed rural banks in Ghana stood at 144 (Bank of Ghana, 2018).  The unprecedented growth of rural banks in Ghana over the years may be an indication of a positive financial service delivery, reputation over the years and their socio-economic contribution to the rural population and the economy of Ghana large. Be as it may be, the financial sector in Ghana is quite broad and complex in structure. Amidst the abnormal growth of both licensed and unlicensed micro-finance institutions, savings and loans institution as well as other non-banking financial institution with similar mandates of providing financial services to folks in deprived rural areas, one can only expect rural banks to map up strategies to maintain their customer base.

Banking competition in Ghana remains quite stiffer whiles customers have become sophisticated with their financial service demands. The pace of technological innovation has also become a bigger challenge for smaller banks to meet customer expectation. In all this, there is no doubt that, customer satisfaction remains a key component in service delivery. According (Kotler and Keller, 2006) most customers feel dissatisfied if organizations do not meet their service expectations. As service satisfaction is relative to individuals, the responsibility falls within the realms of the organization to understand the service needs of their customers. The study of McDougall and Levesque (2000) asserted that improvement of organizations’ service reliability and service quality can be improved customer satisfaction. Customers whose expectations are mostly meant remain loyal and accustomed to the services of the organization. In the long run, such customers are likely to recommend the service to others hence creating a pool of loyal customers and increase in market share. Achieving the best customer satisfaction level therefore means that the complaints of customers’ complaint and feedback must be welcomed by service providers and given the necessary attention (McCole, 2004).

Nikbin et al. (2011) defined Customer complaints as the experience shared by customers about an organization failure to deliver their services as expected or failure to meet the expectations of customer demand. This complaint according to Tronvoll (2012) can either be formal or informal report of a specific bad experience the customer may have encountered with a particular services or products. Frequent customer complaints, if not well handled is likely to have an adverse effect on business growth in the long term as asserted by Robert (2012). Organizations that fail to address customer issues, invest interest in effective procedures for handling complaints, develop easy feedback channels or failure to create avenue to handle critical customer issues may damage the company’s brand and reputation. Awara (2010) reveals that many customers can be lost due to ineffective customer complaints handling procedure and consequently lead to a drop in market share. On the other hand, Robert (2012) suggested that when organizations retain effective procedures of handling customer complaints, the level of customer attrition reduces whiles customer satisfaction, company sales, loyalty and retention level increases. Considering the increasingly fast-paced competition for excellent customer service amongst financial service providers, handling customer complaints effectively cannot be underestimated in the quest to improve customer satisfaction. According to Morrisson and Huppertz (2010) organizations who fail to effectively handle customer complaints may lose the loyalty of numerous customers. It is expected that a single dissatisfied customer can cause a chain reaction where a large number of customers could be lost as well.  Customers form the backbone of business growth; hence their interest must be treated with every detail of attention. As it is popularly said “the customer is always right” hence customer satisfaction must be the utmost priority of all business organizations.

Customers of most banks in Ghana are increasingly becoming self-aware of the need for quality of service. The current crackdown by the Bank of Ghana (BOG) on universal banks due to their inability to meet the minimum capital requirement and the shutdown of many micro-finance institutions due to failure to meet regulatory requirements has left many customers wondered if there is any faith left in the Ghanaian banking sector. This negative impression currently developed by major stakeholders in the financial sector, particularly, the customers, travel beyond the scope of universal banks and microfinance institutions but as well the rural banking business. These current happenings therefore place a major responsibility on the shoulders of rural banks in Ghana. Thus, the current happenings in the financial sector must send a strong signal to rural banks to come clear with their major mandates and develop strategies that will make them stand unique and strong. It is as well ultimately important for existing rural banks to re-assure customers of their genuity and dedication towards the delivery of the best financial services in such difficult time of financial imbalances in the banking system.

In Ghana, rural banks are mostly considered as traditionally primitive banks due to the failure of most rural banks in adopting modern banking technologies in their service delivery, their locations and perceptions on the type of customers they serve. In as much as rural banking has existed in Ghana for the past 43years, it is a public knowledge that most rural banks are yet to meet the standard conventional banking systems and standards. Considering the current stiffness of banking competitions in Ghana, this study seeks to understand how rural banks have adjusted over the years in the quest to improve their financial service delivery in terms of handling complaint and the degree of customer satisfaction with such service.Studies on rural banking services and operations is quite broad. Most of these studies seek to enumerate the challenges, prospect and mandate of rural banks aid in poverty alleviation. Few recent studies have also addressed customer service management among rural banks (Owusu-Frimpong, 2008; Abawiera et al., 2014; Gyamfi et al., 2016; Ofosu et al., 2016; Attu, 2018) . Be as it maybe be, these studies were directed towards a specific location of rural banks (i.e. Kumasi, Accra, Sunyani etc.) unlike this current study which focuses on a broader perspective by studying the entire rural banking system in Ghana. Again, this study narrowed the scope of customer service management to rural banking complaint handling processes which has currently not been addressed by previous studies. The main idea for the study is to predict the satisfaction level of customers through effective customer complaint handling.

2. LITERATURE REVIEW

2.1. Handling and Managing Customer Complaints

Customer complaint behavior (CCB) has mostly been described as a dynamic adjustment process which is which is mostly related to post-purchase behavior of customers. A complaint provides a guideline or road map for service recovery and an opportunity to understand customer needs, educate the customer, improve loyalty and build a better brand in the eyes of the customer. According to Tronvoll (2012) further describes complaint as an action taken by an individual involving the communication of negative experience regarding a product or service. Customer complaint is based on perception and it is formed mostly after the customer experienced a dissatisfaction with a service (Morrisson and Huppertz, 2010). Hoyer and McInnis (2010) supports similar assertion and opined that complaint can be related customers’ feedback which is mostly influenced by dissatisfaction. Referring to the definitions, complaints as broadly defined are articulations of dissatisfactions that are expressed by customers to businesses with the aim of communicating a bad experience in the past and how it may be rectified. Hansen et al. (2009) argues that complaint is highly attributed to the service sector due to the subjectivity level of service delivery hence failure to deliver quality service to just one customer can go a long way to affect business outcome. Anderson (1994) indicated that complaint handling procedures is very critical aspect of marketing and forms one of the major pillars of building and expanding customer shares.  Ineffective complaint management procedures have the potentials to adversely affect customer satisfaction or loyalty hence organizations should encourage and create easy channels for customers to complain (Tronvoll, 2012).

In all these, customer complaint management remains key to in improving satisfaction levels. Complaint management is the way in which companies systematically handle problems in customer relations. Hansen et al. (2009) explained complaint management as the receipt, investigation, settlement and prevention of customer complaints and recovery of the customer. Tronvoll (2012) argued that complaint management processes can be likened to organization’s management information systems with a major goal of stabilizing business- customer relationships.  Complaint is a sign of dissatisfaction and be as it may be, almost all organizations experience some degree of customer dissatisfaction hence understanding how to effectively manage it remains a critical concern (Ndubisi and Ling, 2006).

2.2. Customer Satisfaction

According to Fornell et al. (1996) customer satisfaction is an aggregate evaluation of organization’s service delivery based on the total purchase and consumption experience of customers over a period of time. In context, customer satisfaction describes the difference between expectation and perceived quality.  If the expectation is lower than perceived quality, satisfaction will be high and customers will recognize the product and vice versa.

The concepts of customer satisfaction over the years has been built on two significant theories. Thus, the cognitive and affective theory.  As the cognitive theory considers the after purchasing experience by evaluating the satisfaction of the product as compared to others, the affective theory focuses more on the emotional attachment towards consuming a particular product (Oliver, 2010; Chavan and Ahmad, 2013). In any case, satisfaction is the fulfilment of both the cognitive and affective needs of customers. Thus, creating good customer experience through the product that will lead to emotional attachment by the customer to the product. 
Most authors have argued that that customer satisfaction is a simultaneous combination of both cognitive and affective evaluation (Clerfeuille et al., 2008; Bena, 2010).

The outcome of any successful business depends on the number of customers it served hence businesses must be more strategic in their quest to provide services for customers. Hill et al. (2007) believes that Customer satisfaction is a barometer that predicts the future customer behavior, hence need for business to specific product or service features and perceptions of quality among consumers. According to Zeithaml and Bitner (2003) satisfaction is highly linked to customers’ emotional responses. Thus, quality perception of a particular product or services can provide company benefits like customer loyalty and trust over a longer period of time. Satisfaction affects purchasing and this improves business profits and growth as well. Satisfied customers mostly buy more and recommend the service to others. In the long run a network of satisfied customers is built and market share expanded (Hague and Hague, 2016). Tao (2014) opined that it is impossible for business organizations to expand without effective implementation and channels to address customer issues and complaints.

2.3. Complaints Handling and Customer Satisfaction

According to Bodey and Grace (2006) it is cost- efficient if organizations create channels and encourage dissatisfied customers to complain as it improves service quality and loyalty. Complaints entails a lot of details from the customers that businesses can consider to improve their services in the future. These is not limited to areas such as product design, quality control and improvement of marketing strategies (Bolkan et al., 2010).  Bodey and Grace (2006) argues that if the company can disseminate consumer direct complaint information in the organization and create remedies to preserve it, customer satisfaction will be elevated.

Companies have the chance to rectify numerous challenges customer face if customers are given the opportunity to have easy communication access to the organization (Guo et al., 2016). When dissatisfied customers fail to complain, companies lose the opportunity to rectify existing problems hence market share is diminished. Dick and Basu (1994) argue that customers exhibit different levels of commitment and loyalty based on the behavior and attitudes of the service provider towards solving reported issues.  Rowley (2005) advices firms with large customer base to develop strategies oriented on strengthening relations with its customers. 

3. METHODOLOGY

The study adopted a cross sectional survey with a quantitative approach in analyzing data. As of June 2018, the number of licensed rural banks in Ghana stood at 144. The Ashanti region had the highest number of rural banks of 26 whiles the Upper East region had 4, thus, the least number of rural banks in Ghana. The entire rural banking sector constituted the population for the study; however, 80 rural banks were selected. The study included all 6 rural banks in Accra, the capital city of Ghana, however, whiles the remaining 74 were evenly casted from 9 other regions. The sampled number of rural banks based on the regions is illustrated in Table 1.

Source: Field study, 2019.

Data was conveniently collected through the use of questionnaires. All variables were measured with a 5-point Likert scale. A total of 4000 questionnaires were distributed to respondents in a space of 5months. However, the analysis of this study is based on the responses of 3, 622 customers of the respective banks. Customers who qualify as respondents must have hold an operational account for not less than 5years and frequently visits the bank for at least twice a month. With the help of SPSS 20.0, Pearson Product-Moment Correlation and Multiple Regression Model was used to predict the relationship between the variables.

3.1. Multiple Regression Model

The study proposes 6 (six) different independent variables measuring customer complaint handling procedures. The independent variables include complaint handling, service recovery, service quality, service failure, service guarantee and perceived failure.

In measuring customer complaint, the study adopted the construct of Homburg and Fürst (2005); Maxham and Netemeyer (2002) 4-item questionnaire which has been applied in measuring “customer satisfaction with complaint handling”. In line with previous literature, the measurement of the other variables are as follows: Service recovery (adopted from McCollough et al. (2000)); Service quality (Adopted from Rothenberger et al. (2008)); Service failure (Adopted from Chuang et al. (2012)); Service guarantee (Adopted from Chuang et al. (2012) and Perceived value (Adopted from Yang and Peterson (2004)). All items were measured on a 5-item Likert scale.

The construct of Levesque and McDougall (1996); Fornell et al. (1996) was adopted as the measurement proxy of customer satisfaction. This is a multi-item constructs that predicts how satisfied a customer felt with banking products and service delivery. A 5-point Likert scale was ranging from “1 very unsatisfied” to “5very satisfied” was used as a measurement of the customer’s perception and overall satisfaction of the rural banking service management.

The multiple linear regression is generally given as:

Where:

CSAT = Rural bank's customer service satisfaction.

CMPH = Satisfaction with complaint handling processes among rural banks.

SVCR = Service recovery.

SVCQ = Rural banking service quality.

SVCF = Rural banking service failure.

SVCG = Rural banks' service guarantee.

PCV = Perceived service value of rural banks.

α represents the intercept, e represents the error terms and β1, β2, β3, β4, β5, β6 represent the regression coefficients of the independent variables.

4. DISCUSSION OF FINDINGS

The findings of this study are presented in the form of frequency tables. Chi-square test of independence and t-test was as well used to complement the interpretation of the data collected.

4.1. Demography of Respondents

Variables such as gender, educational level, area of employment and years of business with the bank constituted the demography information.

Source: Field study, 2019.

As presented in the Table 2, majority of 64% of respondents constituted female customers whiles the remaining 36% constituted male respondents. Most respondents were found to have some level of education. Thus, 41% of the respondents have completed the senior high school/junior high school or its equivalent. Gone are the days when rural folks were found to have a minimum education qualification, however, this study proved otherwise. Be as it may be, 954 of the customers, constituting 25% had no formal education whiles 1113 representing 31% were school dropout. Only 3% of the respondents, representing the minority of customers had a graduate degree and or its equivalent.

A total of 1522 (42%) of the respondents, representing the majority of customers has transacted various businesses with the rural banks in 5-10years, an indication that most customers have a long-standing relationship with the bank. With regards to the area of business, the majority of customers representing 77% of the respondent were found to work in the informal sector. Considering the mandate of rural banks, there is no doubt that the majority of the customers fall within the informal sector.

4.2. Descriptive Analysis Using One Sample Mean T-test

The one sample mean t-test was used to ascertain the relative significance of the variables. This statistical test was necessitated in order to ascertain the significance of the variables used in the study.  A 95% significance level was used to investigate the relation between the exogenous and endogenous variables. The Table 3 shows the results of a one sample t-test on the specific customer complaints by customers of the rural banks. The results of a 9-item measurement of customer complaints are presented in the Table 3.

The one sample t-test statistic value for all the (9) items measuring customer complaints indicates that only three (3) of the complaints were found to be significant. Thus, the t-test identified excessive transaction charges and delays in the banking hall to be statistically significant, hence represents the three major complaints which are high and likely to be made by customers.

The study as well presented a t-test statistic on the factors that measures rural banking customer satisfaction. The study opines that; customers will be in the great position to give a practical view on their satisfaction if they have come in personal contact with the banks through complaints. The factors that may influence customer satisfaction is presented in the Table 4.

**0. 05% significance level.
Source: Field study, 2019.

0.05** Significance level.
Source: Field study, 2019.

The Table 4 revealed that customers are quite satisfied with the employees of the bank’s response and prompt services to customers. Satisfaction with products and services provided by the banks was also found to be a significant measure of customers’ job satisfaction. As Hill et al. (2007) posits, customer satisfaction is a barometer that predicts the future customer behavior. It is expected that, as customers are satisfied with rural banking products and employee responses to their needs, satisfaction level will be higher. As indicated by the t-test, customers were satisfied with the rural bank's dedication to handle customer service issues.

The study used the Chi-square goodness of fit table to ascertain whether respondents have ever made complaints to their respective rural banks.

Source: Field study, 2019.

As indicated in the table 5 above, Out of the sample total, 2607 respondents, thus, seventy-two percent (72%) of customers have made complaints to the rural bank with respect to their services delivery whilst the remaining twenty-eight (28%) never made any complaint to the banks. The Chi-square goodness of fit results from the table below additionally reveals a significant difference between the observed and the expected frequency of responses from respondents (i.e. P-value=0.000<0.05). This as a result confirms that, customers of the respective rural banks do make complaints if any, with respect to the services rendered to them by the bank.

The model summary is as well presented in the Table 6. The model summary table shows the goodness of fit statistics of the model which as a result indicates whether the model is a good fit. The table below gives an R-value (coefficient of correlation) which measures the strength of the relationship between the response variable (Customer satisfaction) and the explanatory variables (service recovery, service quality, satisfaction with complaint handling procedures, service failure, service guarantee, and perceived value). The analysis of the table as a result gives the R-value of 0.542 which indicates a strong positive correlation or relationship between the customer satisfaction and the dimensions of customer complaints handling by the rural banks. In addition, the model summary table gives an R-square value of 0.294, which implies that about 29.4% of the variability in the dependent variable (customer satisfaction) is explained by the variability in the independent variables (service recovery, service quality, switching cost, service failure, service guarantee, and perceived value).

The model summary table further indicated an adjusted R-square value of 0.280 which means that, 28.0% of the R-square value is corrected to produce a better estimate of the true population.  This results prove that the model is an appropriate model or a good fit.

Source: Field study, 2019.

Moreover, in order to assess whether the overall model is significant or not, it is necessary to analyse the variance among the variables. The analysis of variance (ANOVA) tested the null hypothesis that the R-value in the population is equal to zero or in other words, there is no significant relationship between the response variable (Customer Satisfaction) and the predictor variables (service recovery, service quality, satisfaction with complaint handling procedures, service failure, service guarantee, and perceived value). The ANOVA therefore gives a significant value for the regression as 0.000 which is less than the level of significance 0.05 (i.e. P<0.05). This therefore indicates that, the regression model made up of “Customer Satisfaction” as the response variable and “service recovery, service quality, service failure, service guarantee, satisfaction with complaint handling and perceived value” as independent variables are significantly fit. This brings out the implication that, there exist a significant relationship between the dependent variable (Customer Satisfaction) and the explanatory variables (service recovery, service quality, satisfaction with complaint handling procedures, service failure, service guarantee, and perceived value). The Table 7 presents the findings of the ANOVA.

Source: Field study, 2019.

Parameter estimates of the variables were further established to determine which of the independent variables included in the model contributed to the dependent variable. The Table 8 shows the output of the regression results.

a. Dependent variable: customer satisfaction.
Source: Field study, 2019.

From the regression results, Service quality recorded the highest beta value of (0.582). This means that, Service quality among all other independent variables is the highest predictor of (Customer satisfaction). Service recovery recorded the second strongest predictor of customer satisfaction with a beta value of 0.512 whilst complaint handling processes among the rural banks recorded a beta of 0.314.

Based on the findings of the regression results, the new model can be estimated as:

CSAT = 1.794 + 0.512SVCR + 0.582SVCQ + 0.314CMPH

The estimated model above indicates that, a unit increase in service recovery will increase customer satisfaction by 0.512 whilst a unit increase in service quality on the other hand will as well increase rural banking customers service satisfaction by 0.582. The regression result also shows that satisfaction with complaint handling by rural banks is a major factor influencing customer satisfaction. The findings indicated that a unit increase in handling of customer complaints will improve satisfaction by 0.314. The findings are in consonance with the study of McCole (2004) who explained customer complaint as an indicator of the degree of consumer dissatisfaction hence unresponsiveness can severely threaten marketing relationships and effectiveness. This study established that, customers were highly satisfied with the complaint handling procedure of their respective rural banks as confirmed by the regression results. Bart and Dirk (2005) posits that companies will lose the opportunity to rectify existing problems when dissatisfied customers fail to complain.

**. Correlation is significant at the 0.05 level (2-tailed).  
Source: Field study, 2019.

Lastly, the Pearson’s Product-Moment correlation analysis as indicated in the table 9 above recorded a correlation coefficient of 0.681, an indication of a strong positive correlation between customer satisfaction and satisfaction with customer complaints handling procedures among rural banks. This positive relation was as well statistically significant at 0.000. 

5. CONCLUSIONS

This current study examines the influence of complaint handling processes of rural banks and its influence on customer satisfaction. The study conveniently selected 3, 622 customers from 80 rural banks across the 10regions of Ghana. A Chi-square goodness of fit test, ANOVA, multiple regression and Pearson moment correlation analysis was used to explain the data collected through the use of questionnaires.

The regression results predicted a positive and statistically significant relationship between customer complaint handling processes among the rural banks and the level of customer satisfaction. Thus, effective complaint handling procedures among rural banks will significantly influence the level of satisfaction among customers. The Pearson-moment correlation as well confirms that there exists a significant and stronger relationship between complaint handling procedures and customer satisfaction in rural banking.

In as much as the study revealed the effectiveness of the complaint handling processes by the rural banks, there is still more room to improve on its customer services delivery. In this time of financial turbulence in the Ghanaian banking sector, rural banks must pay more attention to customer needs and eliminate any form of barriers that may create a bitter impression for their existing customers.  The study advises rural banks in Ghana to keep improving on their service quality by investing in financial innovations and technology. As well, rural banks must consider adopting innovative measures to enhance receiving complaints reliably.  Future studies can consider a qualitative approach in testing the study’s hypothesis.

REFERENCES

 Abawiera, W.C., G. Dwomoh, E. Owusu, S.B. Pinkrah and A. Antwi, 2014. Customer service in rural banks in Ghana: The case of bosomtwe rural banks in the Ashanti Region, Ghana. International Journal of Academic Research in Business and Social Sciences, 4(2): 2222-6990.Available at: https://doi.org/10.6007/ijarbss/v4-i2/654.

Anderson, M., 1994. The relationship between justice and attitudes: An examination of justice effects on event and system-related attitudes. Organizational Behavior and Human Decision Processes, 103(1): 21-36.

Attu, R., 2018. Challenges of rural financial intermediation. The experience of rural banks in Ghana. Goldstreet Business.

Awara, N.F., 2010. Strengthening customer retention through the management of customer relationship in services marketing. Nigeria: University of Calabar (UNICAL).

Bank of Ghana, 2018. Reporting list on the number of rural banks in Ghana. Available from https://www.bog.gov.gh/supervision-a-regulation/register-of-licensed-institutions/rural-banks.

Bart, L. and V.D.P. Dirk, 2005. Predicting customer retention and profitability by using random forests and regression forests techniques. Expert Systems with Applications, 29(2): 472-484.Available at: https://doi.org/10.1016/j.eswa.2005.04.043.

Bena, I., 2010. Evaluating customer satisfaction in banking services. Management, 5(2): 143-150.

Bodey, K. and D. Grace, 2006. Segmenting service “complainers” and “non-complainers” on the basis of consumer characteristics. Journal of Services Marketing, 20(3): 178-187.Available at: https://doi.org/10.1108/08876040610665634.

Bolkan, S., A.K. Goodboy and J.A. Daly, 2010. Consumer satisfaction and repatronage intentions following a business failure: The importance of perceived control with an organizational complaint. Communication Reports, 23(1): 14-25.Available at: https://doi.org/10.1080/08934211003598767.

Chavan, J. and F. Ahmad, 2013. Factors affecting on customer satisfaction in retail banking: An empirical study. International Journal of Business and Management Invention, 2(1): 55-62.

Chuang, S.-C., Y.-H. Cheng, C.-J. Chang and S.-W. Yang, 2012. The effect of service failure types and service recovery on customer satisfaction: A mental accounting perspective. The Service Industries Journal, 32(2): 257-271.Available at: https://doi.org/10.1080/02642069.2010.529435.

Clerfeuille, F., Y. Poubanne, M. Vakrilova and G. Petrova, 2008. Evaluation of consumer satisfaction using the tetra-class model. Research in Social and Administrative Pharmacy, 4(3): 258-271.Available at: https://doi.org/10.1016/j.sapharm.2007.06.020.

Dick, A.S. and K. Basu, 1994. Customer loyalty: Toward an integrated conceptual framework. Journal of the Academy of Marketing Science, 22(2): 99-113.Available at: https://doi.org/10.1177/0092070394222001.

Fornell, C., M.D. Johnson, E.W. Anderson, J. Cha and B.E. Bryant, 1996. The American customer satisfaction index: Nature, purpose, and findings. Journal of Marketing, 60(4): 7-18.Available at: https://doi.org/10.2307/1251898.

Guo, L., S.L. Lotz, C. Tang and T.W. Gruen, 2016. The role of perceived control in customer value cocreation and service recovery evaluation. Journal of Service Research, 19(1): 39-56.Available at: https://doi.org/10.1177/1094670515597213.

Gyamfi, I., O. Amofah and T.C. O., 2016. Customer perception of service quality specifics of rural banks in Kumasi, Ghana. Africa Development and Resources Research Institute Journal, Ghana, 25(4 (3)): 60-69.

Hague, P. and N. Hague, 2016. Customer satisfaction survey: The customer experience through the customer’s eyes. London: Cogent Publication.

Hansen, T., R. Wilke and J. Zaichkowsky, 2009. Managing consumer complaints: Differences and similarities among heterogeneous retailers. International Journal of Retail & Distribution Management, 38(1): 6-23.

Hill, N., G. Roche and R. Allen, 2007. Customer satisfaction: The customer experience through the customer’s eyes. London: Cogent Publishing Ltd.

Homburg, C. and A. Fürst, 2005. How organizational complaint handling drives customer loyalty: An analysis of the mechanistic and the organic approach. Journal of Marketing, 69(3): 95-114.Available at: https://doi.org/10.1509/jmkg.69.3.95.66367.

Hoyer, W.D. and D.J. McInnis, 2010. Consumer behavior. South Western: Cengage Learning.

Kotler, P. and K. Keller, 2006. Marketing management. 12th Edn., Upper Saddle River: Prentice Hall.

Levesque, T. and G.H. McDougall, 1996. Determinants of customer satisfaction in retail banking. International Journal of Bank Marketing, 14(7): 12-20.Available at: https://doi.org/10.1108/02652329610151340.

Maxham, I.J.G. and R.G. Netemeyer, 2002. Modeling customer perceptions of complaint handling over time: The effects of perceived justice on satisfaction and intent. Journal of Retailing, 78(4): 239-252.Available at: https://doi.org/10.1016/s0022-4359(02)00100-8.

McCole, P., 2004. Refocusing marketing to reflect practice: The changing role of marketing for business. Marketing Intelligence & Planning, 22(5): 531-539.Available at: https://doi.org/10.1108/02634500410551914.

McCollough, M.A., L.L. Berry and M.S. Yadav, 2000. An empirical investigation of customer satisfaction after service failure and recovery. Journal of Service Research, 3(2): 121-137.Available at: https://doi.org/10.1177/109467050032002.

McDougall, G.H. and T. Levesque, 2000. Customer satisfaction with services: Putting perceived value into the equation. Journal of Services Marketing, 14(5): 392-410.Available at: https://doi.org/10.1108/08876040010340937.

Morrisson, O. and J.W. Huppertz, 2010. External equity, loyalty program membership, and service recovery. Journal of Services Marketing, 24(3): 244-254.Available at: https://doi.org/10.1108/08876041011040640.

Ndubisi, O.N. and Y.T. Ling, 2006. Complaint behaviour of Malaysian consumers. Management Research News, 29(1/2): 65-76.Available at: https://doi.org/10.1108/01409170610645457.

Nikbin, D., I. Ismail, M. Marimuthu and I. Younis Abu-Jarad, 2011. The impact of firm reputation on customers’ responses to service failure: The role of failure attributions. Business Strategy Series, 12(1): 19-29.Available at: https://doi.org/10.1108/17515631111106849.

Ofosu, A., I. Gyamfi and K.C. Kenny, 2016. Customer satisfaction as a determinant of customer loyalty of rural banks in Kumasi, Ghana. ADDRI Journal of Arts and Social Sciences, Ghana, 13(2): 1-10.

Oliver, R.L., 2010. Satisfaction: A behavioral perspective on the consumer. Armonk, N.Y: M.E. Sharpe.

Owusu-Frimpong, N., 2008. An evaluation of customers' perception and usage of rural community banks (RCBs) in Ghana. International Journal of Emerging Markets, 3(2): 181-196.Available at: https://doi.org/10.1108/17468800810862632.

Robert, L.M., 2012. Customer retention through customer relationship management: The exploration of two-way communication and conflict handling. African Journal of Business Management, 5(9): 3487-3496.

Rothenberger, S., D. Grewal and G.R. Iyer, 2008. Understanding the role of complaint handling on consumer loyalty in service relationships. Journal of Relationship Marketing, 7(4): 359-376.Available at: https://doi.org/10.1080/15332660802516029.

Rowley, J., 2005. The four cs of customer loyalty. Marketing Intelligence & Planning, 23(6): 574-581.Available at: https://doi.org/10.1108/02634500510624138.

Tao, F., 2014. Customer relationship management based on increasing customer satisfaction. International Journal of Business and Social Science, 5(5): 256-263.

Tronvoll, B., 2012. A dynamic model of customer complaining behaviour from the perspective of service-dominant logic. European Journal of Marketing, 46(1/2): 284-305.Available at: https://doi.org/10.1108/03090561211189338.

Tsamenyi, M. and U. Shazad, 2008. The case of rural banks in Ghana". Corporate Governance in Less Developed and Emerging Economies. pp: 311–334.

Yang, Z. and R.T. Peterson, 2004. Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychology & Marketing, 21(10): 799-822.Available at: https://doi.org/10.1002/mar.20030.

Zeithaml, V.A. and M.J. Bitner, 2003. Services marketing - integrating customers focus across the firm. 3rd Edn., Boston: McGraw-Hill.