Service Quality and Customer Satisfaction in Banks with reference to Commercial Bank of Ethiopia, Gondar Emelda LILIAN University of Gondar,Ethiopia & Freda Gnanaselvam University of Gondar,Ethiopia This paper examines the impact of service quality leading to satisfied bank customers. For the services rendered by banks to their clients they do not necessarily charge a direct price. In banking sector new technologies are being introduced where fierce competition arises leading to demanding customers. Such changing climates have presented an unmatched set of challenges for banks. As a result, for banks to survive the competition customer satisfaction is considered necessary. The present study is undertaken in Commercial Bank of Ethiopia in Gondar, to assess the satisfaction of customers in the banking sector. Working with a sample of 185 educated and employed clients of Commercial Bank of Ethiopia in Gondar, the researchers administered a questionnaire to assess the satisfaction of customers. By means of AMOS the data was analyzed using Structural Equation Modeling (SEM) method. Confirmatory factor analysis of measurement models indicate adequate goodness of fit after a few items was eliminated through modification indices verifications. The results show that technological climate and remedial climate were the two components of service quality dimensions that satisfied bank customers. Thus improving the use of technology and improved problem handling mechanisms are highly recommended for quality service and customer satisfaction. Keywords: banking sector, service quality, customer satisfaction, Ethiopia. Introduction The economic growth and development of Ethiopia has been influenced and accelerated by the expansion of the banking system. The Ethiopian banking industry has shown enormous growth during the past decades. Banking is a service industry that delivers its services to the clients. A satisfied client is the best person to generate positive word of mouth for a bank. The banking industry just like any other financial services is facing a rapidly changing market. As a result new technologies are introduced creating trepidation of economic uncertainties. Fierce competition, more demanding customers and the changing climate have presented an unparalleled set of challenges (Lovelock, 2001). It is extremely important that banks are able to retain their clients in such a competitive scenario. Customer satisfaction is the key to long term success of any organization (Peppers & Rogers, 2005). Keeping the importance of customer satisfaction in mind, banks need to maintain stable and close relationships with their customers. Banks recognize the fact that delivery of quality service to customers is essential for success and survival in today s global and competitive banking environment (Wang, Han, & Wen, 2003). Banks may not be able to provide superior services to the customers unless customer expectations are known (Leverin & Liljander, 2006). Customer expectations can be known through the knowledge of satisfaction levels of customers (Jham & Khan, 2009). This necessitates the measurement of customer satisfaction level. Customer satisfaction cannot be measured unless the factors affecting customer satisfaction are determined. This necessitates an in-depth study about the factors affecting customer satisfaction. Customer satisfaction is a person s feelings of pleasure or disappointment that result from comparing a product s perceived performance (or outcome) to their expectations. (Oliver, 1980) Satisfaction can be broadly characterized as a post-purchase evaluation of product quality given pre-purchase expectations. (Anderson & Sullivan, 1993) From this it is understood to measure satisfaction, it is necessary to measure www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 81
both expectations at the time of purchase and reactions. It can be said that customer satisfaction is the attitude of the clients. The link between service quality and customer satisfaction has been submitted by service quality researchers (Bitner and Hubbert,1994; Bolton and Drew, 1994), as well as the links between quality, customer satisfaction, customer retention and profitability (Storbacka et al., 1994). The connection between service quality and corporate profitability is now seen to depend on high levels of customer satisfaction, the successful targeting of quality customers and the retention of those customers. Greater customer satisfaction has also been linked to higher returns and faster company growth (Fornell, Mithas, Morgeson, & Krishnan, 2006). Customer satisfaction is influenced by several factors like employee responsiveness, appearance of tangibles, social responsibility, services innovation, positive word-of-mouth, competence technology and reliability. The study has identified various factors like physical appearance technology convenience, problem handling and personnel that are influenced by customer satisfaction in Gondar Branches of Commercial Bank of Ethiopia. Literature Review According to Tse and Wilton (1988) Customer satisfaction is, the consumer s response to the evaluation of the perceived discrepancy between prior expectations and the actual performance of the product perceived after its consumption. Prabhakaran and Satya (2003) mentioned that customer is the king. Heskett et al. (1997) argued that profit and growth are stimulated primarily by customer loyalty. Ndubisi (2005), Gee et al. (2008) and Pfeifer (2005) pointed out that the cost of serving a loyal customer is five or six times less than a new customer. Researchers including Tariq and Moussaoui (2009), Han et al. (2008) and Ehigie (2006) found that loyalty is a direct outcome of customer satisfaction. Generally it can be seen if the customers are satisfied with the provided goods or services, the probability that they use the services again increases. Also, satisfied customers will most probably talk enthusiastically about their buying or the use of a particular service; this will lead to positive advertising (File and Prince, 1992). Hanzaee and Sadeghi (2010) validated a measurement model for customer satisfaction evaluation in e- banking service quality based on different service quality models and theories such as technology acceptance model, theory of reasoned action and theory of planned behavior. The paper provided a model of seven factors for customer satisfaction on the following dimensions - convenience, accessibility, accuracy, security, usefulness, bank image, and web site design. Al-Eisa and Alhemoud (2009) attempted to identify the most salient attributes that influence customer satisfaction with retail banks in Kuwait and determined the level of the overall satisfaction of the customers of these banks. Shin and Elliott (2001) proposed a multiple-attribute approach that was employed from a convenient sample of customers of retail banks in Kuwait. The most crucial attributes for predicting customer satisfaction were fast service, courtesy and helpfulness of employees and availability of self-banking services. The factors affecting customer satisfaction in the Spanish e-banking services were studied by Casaló, Flavián, and Guinalíu (2008). Structural equation modeling was used to find the factors. The major factor which emerged affecting customer satisfaction was website usability. The determinants of online banking customer satisfaction in the Finnish retail banking context was conducted by Pikkarainen K, Pikkarainen T, Karjaluoto, and Pahnila (2006). Factor analysis followed by a confirmatory factor analysis was used to test the validity of the model in an online banking context. The survey results supported three factors website content, ease of use of the websites, and accuracy. www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 82
Objectives Customer satisfaction and customer retention are the most important challenges faced by most of the banking sectors. A systematic and coherent approach had been adopted for the research study. Hence following objectives were formed: 1. To study the various service quality dimension in banking industry. 2. To identify the service quality dimension that satisfies bank customers. Statement of the Problem Due to fierce competition amongst various banks in Ethiopian context there is requirement to provide better value service to their customers so that customers can become loyal. Customer satisfaction and customer retention are the most important challenges faced in banking sector. Significance The findings of the study will be useful to the policy makers of the commercial bank of Ethiopia to provide quality services to create better customer satisfaction. It will help the policy makers to upgrade the banking system with high technology by creating a high rate of customer loyalty. The study will assist academicians/researchers in broadening the study on customer satisfaction. Scope and Limitations The more diverse the profiles of the respondents more will be the insights into the construct of customer satisfaction for the Ethiopian banking sector. If the profiles of the respondents were more diverse, the researcher might have received more insights into customer satisfaction for Ethiopian banking sector from the interviews. The researchers might have generated more factors leading to customer satisfaction. The study is conducted only in Gondar Town and did not address customers of commercial bank of Ethiopia of other areas. Research Framework This study examines the impact of service quality dimensions which are personnel, technology convenience, problem handling and physical atmosphere are stated as independent variables and customer satisfaction is dependent variable. Personnel Problem Handling Technology Customer Satisfaction Convenience Physical Atmosphere Figure 1: Research Framework Hypothesis: H01: All service quality dimensions are related positively to customer satisfaction. Research Methodology Descriptive research design was adopted for the study. The population of the research is composed of educated and employed bank account holders of Commercial Bank of Ethiopia in Gondar. The data was www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 83
collected using simple random sampling method. Questionnaire survey method was used for data collection on the bank s service quality and customer satisfaction. From the 200 questionnaires that were sent out, 189 were returned, representing a response rate of 94.5%. After elimination of cases having incomplete data and extreme values 185 questionnaires were accepted as valid and included in the evaluations. Measures used in the study are adapted from the previous studies in the literature. The questionnaire was statistically tested using SPSS 16. Confirmatory factor analysis was conducted by Amos 20 for all scales. Analysis and Findings Demographic Characteristics: Descriptive statistics is performed to analyze the profile of the respondents demographic responses. Demographic characteristics of the respondents such as age, gender and marital status were analyzed. Table 1 shows the Demographic profile of respondents. Table 1 Personal profile of clients of commercial bank of Ethiopia Clients Personal Profile Frequency Percentage N= 185 Statistics Age 21-30 10 5.4 31-40 53 28.6 Mean 2.95 41-50 58 31.4 Std. Deviation.922 Above 50 64 34.6 Gender Male 106 57.3 Mean 1.43 Female 79 42.7 Std. Deviation.496 Marital Status Unmarried 83 44.9 Mean 1.55 Married 102 55.1 Std. Deviation.499 Source: Based on Primary Survey. The study shows that 34.6 percent of the respondents were from the age group of above 50 years. A high of 57.3 percent of the respondents were male and 55.1 percent were married customers. From the mean scores, age of the respondents has been perceived as the highest value in personal profile dimensions. Social Characteristics: Social characteristic is an important factor to assess the level of service quality of the banks. The respondent s family type, size of family, education, work experience and income were analyzed and is depicted in Table 2. Table 2 Social profile of clients of commercial bank of Ethiopia Clients Social Profile Frequency N= Percentage 185 Family Type Nuclear 86 46.5 Joint 88 47.6 Extended 11 5.9 Family Size Below 5 members 95 51.4 5 10 members 75 40.5 Above 10 members 15 8.1 Education Diploma 2 1.1 UG Degree 113 61.1 PG Degree 70 37.8 Statistics Mean 1.59 Std. Deviation.602 Mean 1.57 Std. Deviation.640 Mean 2.37 Std. Deviation.505 www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 84
Work Experience Below 5 years 136 73.5 Mean 1.30 5 10 years 42 22.7 Std. Deviation. 537 Above 10 years 7 3.8 Monthly Income Below 5000 Birr * 87 47 Mean 1.69 5000 to 10000 Birr * 69 37.3 Std. Deviation.729 Above 10000 Birr * 29 15.7 * Source: Based on Primary Survey. Birr Ethiopian Currency It was found from the study that 47.6 percent of the respondents were from joint families closely followed by 46.5 percent of the respondents who were from nuclear families. The family size of less than 5 members of the respondents was 51.4 percent. A high of 61.1 percent of the respondents had under graduate education and 73.5 percent of the respondents had work experience of less than 5 years. Majority of the respondents were having a monthly income of less than Birr 5000. In the social profile, the mean scores, of the respondents education was found to have the highest value. KMO and Bartlett's Test KMO and Bartlett's Test was examined for customers of the commercial bank of Ethiopia. The factorability of the 27 items related to bank customers was examined and the KMO value found was (.541 >.5) which indicates that factor analysis is useful for the present data (Cerny and Kaiser, 1977). The Second test is Bartlett's Test of Sphericity, where p value must be less than 0.001. Bartlett's Test of Sphericity ( 2 = 1.340, p.000) indicated that the present data is useful for factor analysis. Factor Loading Technology and innovation are transforming the financial services industry these days rapidly. The service satisfaction of customers are reflected through the Eigen values that represent the amount of variance associated with each component for clients of the bank that is printed in Table 3. Table 3 Factor loadings and communalities based on a principle components analysis (N = 185) Service Satisfaction variables Customers of CBE Component 1 2 3 Communalities My bank offers secured net banking services SST3.617.468 My bank offers effective Phone banking SST4.506.292 Front line employees are responsible SSP2.527.580 Personal bankers update the new products SSP5.577.332 My bank offers superior services than other banks SSC3.566.322 My bank has pleasant ambience SSA2.586.433 My bank provides effective redressal mechanism SSH1.703.574 My bank has provides sufficient compensation SSH2.665.444 My bank provides solutions in time SSH3.534.329 The bank has knowledgeable personnel SSP1.562.563 Bank Executives are courteous towards customer SSP3.534.408 Eigen values 3.456 2.657 2.539 Percentage of total variance 12.801 9.842 9.405 Source: Based on Computed Data www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 85
The first three variables contributed to 32.05 % variance with the first component accounting for 12.8% of the variance. Sixteen items in total were eliminated as they did not contribute to a simple factor structure and failed to meet a minimum criteria of having a primary factor loading of.3 or above. All the statements that loaded on the three factors are given in Table 3. These three factors are labeled as Technological climate, Remedial climate and Personnel climate. Factor Association with other dependent factors The factor loading of the service quality variables included in the three factors and its reliability coefficient, the Eigen value and the per cent of variation explained by the service quality factors are presented in Table 4. Table 4 Factor Association with other dependent factors Dimensions Component Factor Loading Eigen values Percentage of Variance Cumulative Percentage My bank offers efficient core banking system SST1 3.456 11.989 12.801 12.801 Technology My bank has wide spread ATM networks SST2 2.657 9.842 22.643 My bank offers secured net banking services SST3 2.539 9.405 32.048 My bank offers effective mobile banking SST4 1.804 6.681 38.729 My bank offers user friendly services SST5 1.533 5.679 44.409 The bank has knowledgeable personnel SSP1 1.475 7.808 5.465 49.873 Personnel Convenience Front line employees are responsible SSP2 1.303 4.828 54.701 Bank Executives are courteous towards the customer SSP3 1.197 4.432 59.132 Top Management is easily accessible SSP4 1.057 3.915 63.047 Personnel bankers update the new products SSP5 1.02 3.779 66.827 My bank offers prompt service SSP6 0.904 3.349 70.176 My bank offers customer friendly environment SSP7 0.852 3.157 73.333 My bank is located in a convenient place SSC1 0.83 4.153 3.074 76.407 www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 86
My bank has flexible working hours SSC2 0.79 2.927 79.334 My bank offers superior services than other banks SSC3 0.726 2.689 82.023 My bank offers shorter processing time SSC4 0.673 2.491 84.514 My bank speedy recovery of network failures SSC5 0.578 2.139 86.653 My bank offers efficient utility services SSC5 0.556 2.06 88.713 My bank premises has spacious parking SSA1 0.51 2.403 1.889 90.602 Physical Atmosphere My bank has pleasant ambience SSA2 0.443 1.642 92.245 My bank has good seating arrangement SSA3 0.415 1.538 93.783 My bank has optimum counters SSA4 0.379 1.405 95.187 My bank has good physical layout & interiors SSA5 0.356 1.319 96.507 My bank hall is spacious enough to accommodate many customers SSA5 0.3 1.111 97.617 My bank provides effective redressal mechanism SSH1 0.254 0.644 0.939 98.556 My bank has provides Problem sufficient compensation SSH2 0.223 0.824 99.381 Handling SSH3 0.167 0.619 100 Source: Based on Computed Data The researchers have found the highest Eigen value (11.989) in technology dimension. It carries five service quality variables like: My bank offers efficient core banking system, My bank has wide spread ATM networks, My bank offers secured net banking services, My bank offers effective mobile banking, My bank offers user friendly services. Within that technology dimension they give more focus on how banks are challenging and implementing in latest technology. It received the highest Eigen value among all thirty six service quality variables. Confirmatory measurement model A confirmatory measurement model was tested for all latent constructs to validate the instruments used and test for Goodness Of Fit (GOF). The GOF indices used in this study are chi square ( 2 ), normed 2 ( 2 /df), Goodness Fit Index (GFI), Root mean square error of approximation (RMSEA). Measurement and structural modeling was duly tested for it goodness of fit (GOF) indicators as stated earlier. Deletions of items were done accordingly with suggestions of modification indices. The goodness of fit of all www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 87
(Confirmatory Factor Analysis) CFAs, measurement models and structural models followed accepted standards levels of normed 2 of <2, RMSEA (<.08) and GFI (>.95). In this study the assessment of universal fit pertaining to the three factor model was examined. The result of the measurement model is given in Table 5. Table 5 Goodness-of-fit indices for the three-factor model Latent construct No of items before CFA No of items after CFA Chi square Df C/df GFI CFI NFI RMSEA Technological Climate 6 2 Remedial Climate 3 3 6.222 8.778.984 1.000.944 0.000 Personnel Climate 2 - Source: Based on Computed Data The findings of parameter estimates and critical ratios for hypothesized structural model in Table 6 provides some direction for commercial banks in Gondar to concentrate on improving technology and problem handling mechanism in order to win customer commitment and satisfaction. Improving service quality is the needed ingredient to increase banking customer satisfaction in banking sector. Figure 2: Hypothesised model. The observed (items) and unobserved (factors) in the hypothesised model are illustrated in Figure 2, Technological climate and Remedial climate are the two components of service quality dimensions that satisfied bank customers. From the hypotheses we can conclude that only two service quality dimensions: technology and problem handling are related positively towards customer satisfaction. Table 6 Parameter estimates and critical ratios for hypothesized structural model Hypotheses Estimate SE CR p-value Hypotheses (Direction) SSH1 Remedial Climate 1.000 Unidentified SSH2 Remedial Climate.521.135 3.869 *** Asserted (+ve) www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 88
SSH3 Remedial Climate.728.178 4.086 *** Asserted (+ve) SST3 Technological Climate 1.000 Unidentified SST4 Technological Climate.650.640 1.015.310 Not asserted (+ve) Note: ***, ** and * denotes significantly at 1%, 5% and 10% level of significant respectively. Source: Based on Computed Data Conclusion Customer satisfaction is one of the major parameters for the service providers in the Ethiopian banking sector. Customer satisfaction cannot be measured unless the factors affecting customer satisfaction are determined. This required an exploratory study to find the factors contributing to customer satisfaction in banking. The paper tried to address the research gap of customer satisfaction in commercial banks if Ethiopia. The authors have made an attempt to understand the construct of customer satisfaction and to explore the factors which affect service quality and customer satisfaction. To be successful in banking sector, banks must provide quality service to their customers that atleast meet or better if it exceeds their expectation and this study provides some sort of guidelines to the policy makers (managers) of banks to take appropriate decisions to improve the quality of services in Ethiopian banking sector. Banks can offer training to their employee which will help them to give personalized quality service which will also help to implement an empathetic approach. References Al-Eisa, A. S., & Alhemoud, A. M. (2009). Using a multiple-attribute approach for measuring customer satisfaction with retail banking services in Kuwait. International Journal of Bank Marketing, 294-314. Anderson, E., & Sullivan, M. (1993). The antecedents and consequences of customer s satisfaction for firms. Marketing Science, 125-143. Bitner, M.J. and Hubbert, A.R., Encounter satisfaction versus overall satisfaction versus quality, London: Sage Publications, Inc. 1994. Bolton, R. N., & Drew, J. H. (1995). Factors influencing customers assessments of service quality and their invocation of a service warranty. Advances in services marketing and management, 4, 195-210. Casaló, L. V., Flavián, C., & Guinalíu, M. (2008). The role of satisfaction and website usability in developing customer loyalty and positive word-of-mouth in the e-banking services. International Journal of Bank Marketing, 399-417. Cerny C.A., & Kaiser, H.F. (1977). A study of a measure of sampling adequacy of factor -analytic correlation matrices. Multivariate Behavioral Research, 12 (1), 43-47. Eakuru, N., & Mat, N. K. (2008). The Application of Structural Equation Modeling (SEM) in Determining the Antecedents of Customer Loyalty in Banks in South Thailand. The Business Review, Cambridge, 129-139. Ehigie, B. O. (2006). Correlates of customer loyalty to their banks: a case study in Nigeria. International Journal of Bank Marketing, 494-508. File, K. M., & Prince, R. A. (1992). Positive word of mouth: Customer Satisfaction and buyer behaviour. International Journal of Bank Marketing,, 25-29. Fornell, C., Mithas, S., Morgeson, F. V., & Krishnan, M. S. (2006). Customer satisfaction and stock prices: High returns, low risk. Journal of Marketing, 3-14. Gee, R., Coates, G., & M., N. (2008). Understanding and profitably managing customer loyalty. Marketing Intelligence and planning, 359-374. www.theinternationaljournal.org > RJSSM: Volume: 07, Number: 02, June 2017 Page 89
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