Service Quality and Customer Satisfaction: An Application of Internet Banking in Turkey

Service Quality and Customer Satisfaction: An Application of Internet Banking in Turkey Merve Kılıç, Fatih University, Turkey Abstract: In the changing world the distribution of the services has also changed. The people have started to do their own services via internet instead of going to the service place. This can be called technology based self service. After this development companies have started to offer their services electronically, for example, internet banking, e-commerce, e-buying. The technology based service has brought in new concepts, such as e-service quality, e-satisfaction, e-loyalty etc. This study aims to measure the effects of perceived quality of internet banking on customer satisfaction level. This study shows that the most frequently used services are to have information about account, to transfer money, to pay bill, to make credit card transactions etc. Trust dimension was the most important factor that affects the perceived quality of internet banking service. According to the another result obtained from the study accessibility, trust, credibility, and web interface variables affect satisfaction level of internet banking customers positively. Furthermore, the satisfaction level of internet banking customer has not been affected by the demographic variables, such as, gender, age, income level, and education level. If the distribution of the sample analyzed, it can be seen that internet banking customers are generally young and highly educated. Keywords: Internet banking, e-service quality, satisfaction, confirmatory factor analysis (CFA), exploratory factor analysis (EFA). Introduction Today s highly competitive and global world has made the differentiation very difficult for companies. This has led service companies to investigate other ways to obtain competitive advantage. Significant research has been reported in the literature aiming to conceptualize and measure service quality. The most acceptable instrument for service quality measurement among researchers, practitioners, and managers is SERVQUAL (Parasuman et al., 1985, 1988, 1991, 1994). The proliferation of internet applications during the past few years has had a significant impact on the services industry. Traditional brick-and-mortar service firms, which started offering their products to wider audiences via this new channel as internet services, found themselves competing with pure dot.com companies, spawned by exploiting the rapid technological advances (Santouridis et al., 2009). As a result, service quality term has changed especially because of absence of physical tangibles and human interaction. Therefore, the services provided 393

via internet must support all the processes that the customer would expect in the corresponding physical encounters with company personnel. Since 1990s a new research area which is focusing on the measurement of internet service quality has emerged. This study investigates the relationship between service quality and customer satisfaction. Internet service quality will be examined by using an instrument, which is based on SERVQUAL and consists of six dimensions, namely assurance, quality of information, responsiveness, web assistance, empathy and reliability. Today s globalized and competitive world made very difficult to obtain competitive advantage for service companies. High quality is one of the most important factors for sustaining competitiveness. The most prominent instrument for service quality measurement for researchers, practitioners, and manager is SERVQUAL. It is also applicable to internet banking. This study aims to extend the knowledge related to service quality and customer satisfaction by examining the banking context in Turkey and to determine the impact of internet banking service quality on customers satisfaction. Jayawardhena (2004) s scale is used to determine this relationship. SERVQUAL had been modified and five dimensions related to internet service quality emerged, namely, access, web interface, trust, attention, credibility. Following the discussion above, the present study s aims are to: Identify the key dimensions of internet banking service quality as perceived by customers, Chart the internet service quality profile as perceived by bank customers in Turkey, Determine the impact of internet banking service quality dimensions on customer satisfaction. Literature Review Traditional banks satisfy the needs of their customers by delivering a range of banking service products, mostly in face-to-face encounters. However, incremental technical progress has facilitated the remote delivery of banking services, gradually reducing human contact, initially by telephone banking followed by e-banking. E-banking meant that customers could transact with a bank s computer network electronically. During the early stages of e-banking, dedicated ( private ) dial up networks were perceived to be more secure than public networks (e.g. the Internet). However, with the development of Internet security features, private deal up networks became redundant and prohibitively expensive (Jayawardhena, 2004). So, firms aiming to excel by developing and delivering services of high quality through the internet face new challenges, which are not evident in traditional brick-and-mortar provided services. The most important differences between these two types of service settings have been highlighted by Cox and Dale (2001), Gouranis and Dimitriadis (2003) and Long and McMellon (2004) as being (Santouridis et al., 2009): 394

The lack of physical tangibles and human interaction in the internet case. Therefore the quality of the website becomes the moment of truth. The customer s greater control over the service delivery process when the transaction executed on the internet, due to the absence of front-line personnel. The possibility of internet services to be available 24 hours a day, seven days a week, without geographically restricted. On the other hand, traditional services operate on specific hours and usually attract local customers. The lower switching costs for the customer of an internet service, since competition is only a few keystrokes away. The need of the internet service customer to have a level of computer literacy, which is not the case in the traditional services settings. The aforementioned difference had their impact on research efforts to conceptualize and measure internet service quality. Given its popularity in measuring traditional service quality, it comes as no surprise that SERVQUAL was considered by several researchers as the first obvious choice for also measuring internet service quality. SERVQUAL-based research on internet service quality is an ongoing process. Nevertheless, scholars have reached a point where there is a wide consensus on the following three issues (Santouridis et al., 2009): 1. The measurement of customer expectations from internet services at this stage is problematic due to the relatively recent advent of e-commerce and therefore the possible lack of knowledge of web standards by customers. 2. The original SERVQUAL dimension of tangibles is deemed irrelevant and therefore should not be measured. This dimension, which is based on physical facilities, equipment and the appearance of personnel, can be considered of minor importance in the internet services context due to the absence of physical and face-to-face interaction. 3. The remaining four dimensions of the original SERVQUAL instrument are also applicable in the internet services context but acquire a new meaning. There is a very little doubt that there is a casual relationship between customer perceived service quality and satisfaction. Perceived quality of internet banking service quality is determined by relevant beliefs. Perceived usefulness and perceived ease of use have a direct effect on the satisfaction level of customers. Researchers also verified the casual relationship between trust and satisfaction level (Suh and Han, 2002). Methodology Research Instrument The field research was conducted using a structured questionnaire, based on the work of Jayawardhena (2004), whose aim was to develop a conceptual framework to measure internet banking service quality. He started by developing an item pool, which had the original 395

SERVQUAL model (Parasuraman et al., 1998) as its starting point. Some of the SERVQUAL items were revised and some of them were deleted to make this scale applicable to the internet banking phenomena. Also some complementary items were added to this scale. Its final version consists 23 items measuring five dimensions. Access: Empower customers to utilize the service through a number of points of entry and the ability to carry out a wide range of transactions. Web interface: Maintenance of a Web site that enhances the overall browsing experience of customers. Trust: Inspire confidence among customers by providing a prompt and information rich service. Attention: Provision of an accurate personalized service to customers. Credibility: Delivering the promised service to customers at all times. Hypotheses of the Study There is a causal relationship between customer perceived service quality and satisfaction. We can develop our hypotheses as: H1: Access perception of customers devoted to internet banking service has an effect on their satisfaction level. H2: Web interface has an effect on customers satisfaction level. H3: Trust perception of customers devoted to internet banking services has an effect on their satisfaction level. H4: Attention perception of customers devoted to internet banking services has an effect on their satisfaction level. H5: Credibility of internet banking services has an effect on customers satisfaction level. 396

Figure 1. Hypothesized internet service quality and customer satisfaction The questionnaire that was used for this research consisted of four sections (Appendix A): 1) Internet banking usage behavior: This section aimed to measure the amount of years customers are using internet banking and the frequency of usage of internet banking services of customers. 2) Customer perceived quality measurement. This section includes 23 items of Jayawardhena (2004) scale measuring the following dimensions: Accessibility: six items. Trust: five items. Credibility: four items. Web Interface: four items. Attention: four items. A five point Likert-scale was used, where the possible answers ranged from Strongly Disagree (1) to Strongly Agree (5). 3) Customer satisfaction measurement. This section includes three questions which aimed to measure general satisfaction of level of internet banking customers. Customer satisfaction: three items. A five point Likert-scale was used again for this section, where the possible answers ranged from Strongly Disagree (1) to Strongly Agree (5). 397

4) Customer demographics. The questions in this section aimed to capture the gender, age educational level, income, occupation of internet banking of the survey participants. Pilot test The questionnaire was submitted to bankers for in-depth discussions. It was also submitted to a sample of ten people to measure its understandability of the items of the questionnaire. This process was fruitful, since they confirmed the cognitive relevance of the questionnaire to banks internet services. They did not suggest any change such as dropping any of the existing items, or adding any item. The original scale which comprised 23 items was used for the analysis. Sample and Data Collection The survey for the research presented in this study was conducted in Turkey. The questionnaire was sent via mail to internet banking customers. The survey took place between October 2009 and December 2009 on the internet. The respondents were asked as a filtering oral question to establish whether they use their bank s internet service or not. Respondents answering yes this question could fill the questionnaire. This question provided the respondents who have used the web services at least one. The resulting sampling comprises 284 valid questionnaires, a size that is satisfactory by taking into consideration the use rate of internet banking in Turkey. Demographic Characteristics of the Respondents The basic demographic characteristics of the respondents are summarized in Table 1. Male respondents totaled 52.8%. Most of the respondents monthly income ranged from 1001 TL to 3000 TL. The sample is rather towards relatively young and highly educated people. 398

Table 1. Characteristics of respondents Characteristics n % Characteristics n % Gender Income Level Male 134 52.8 Under 1000 TL 37 13 Female 150 47.2 1001-2000 TL 116 40.8 Age 2001-3000 TL 72 25.4 18-25 81 28.5 3001-4000 TL 41 14.4 26-33 151 53.2 4001-8000 TL 15 5.3 34-41 34 12 8001 and over 3 1.1 42-49 12 4.2 50 and over 6 2.1 Education Level High School 3 1.1 Associate Degree 9 3.2 Bachelor Degree 146 51.4 Master s Degree 97 34.2 Doctoral Degree 29 10.2 The Most Preferred Bank for Internet Banking Service and Use Time The question, which bank the customers most frequently use for internet banking services, is also asked to determine the most preferred bank for this service. Most of the respondents use Garanti Bank s internet banking service in this research. The question, how many months the customers use the internet banking services, is asked to identify the using behavior of the customers. 44.8% percent of the total sample use internet banking service more than 48 months and so more than four years. Internet banking service has started to become popular at the beginning of 2000s. Because of its ease use and comfort of not going to branch of bank internet banking service has became very popular in a short time period. 399

Table 2. The most preferred bank for internet banking service Table 3. The used time of internet banking service 400

Use of Internet Banking Services The frequency of use of internet banking services of respondents has been presented in Table 4. Table 4. Use of Internet Banking Services Internet Banking Service Taking Information about Account Money Transfer Foreign Currency Transaction Stock Transactions Credit Card Transactions Never Use Rarely Use Occasionally Use Permanently Use Frequency Percentage Frequency Percentage Frequency Percentage Frequency Percentage 8 2.8 20 7 39 13.7 219 76.4 24 8.5 17 6 71 25.0 172 60.6 197 69.4 45 15.8 20 7.0 22 7.7 243 85.6 19 6.7 12 4.2 10 3.5 43 15.1 13 4.6 51 18.0 177 62.3 Repo 253 89.1 19 6.7 8 2.8 4 1.4 Investment 171 60.2 33 11.6 36 12.7 44 15.5 Account Transactions Utility and Bill 34 12 25 8.8 48 16.9 177 62.3 Pay Bonds and T- Bills 250 88 18 6.3 8 2.8 8 2.8 Leasing and 251 88.4 20 7.0 10 3.5 3 1.1 Loan Transactions Taking Information about Product and Services 123 43.3 68 23.9 64 22.5 29 10.2 The most frequently used internet banking services are taking information about account, money transfer, credit card transactions, and utility and bill pay as presented in Table 4. Most of the respondents use other internet banking services rarely or ever. 401

Data analysis and results Empirical analysis of the instrument In this research, the scale of Jayawardhena (2004) was tested again to determine its validity for internet banking users in Turkey. To operationalise the constructs, the properties of the measures are considered: reliability (internal consistency of operationalisation) and validity (content, construct, convergent, and discriminant validity). The instrument that will be developed in this study consists of 5 scales (23 items). Table 5 presents the descriptive statistics for the scales that have to be empirically tested and validated. The following subsections will detail how the reliability and validity of these scales are evaluated. Table 5. Descriptive Statistics Item No. 1 2 3 4 5 6 1.Accessibility Mean 4.30 4.07 4.05 4.29 4.33 4.37 SD 0.048 0.056 0.054 0.047 0.044 0.05 2. Trust Mean 4.42 3.85 4.21 3.54 4.43 SD 0.043 0.056 0.048 0.055 0.046 3.Credibility Mean 4.4 4.00 3.99 3.72 SD 0.053 0.051 0.054 0.064 4. Web Interface Mean 4.23 4.04 3.6 3.85 SD 0.051 0.051 0.055 0.053 5. Attention Mean 3.92 3.88 3.67 3.8 SD 0.051 0.05 0.063 0.052 SD = Standard Deviation Item analysis of Internet Banking Service Quality Scale This is a method to check the appropriateness of the items assigned to the scales and it considers the correlation of each item with each scale. This method has been generally used to evaluate the assignment of items to scales for developing an instrument. So, this analysis was conducted in 402

order to ascertain whether items had been appropriately assigned. Table 6 presents the correlation matrix for the 5 scales and their measurement items. As is readily apparent from Table 6, the items were highly correlated with the scales they intend to measure. Any correlation score less than 0.5 indicate that the associated items cannot explain adequately the variance with the rest of the items in that scale. All of the correlation values in Table 6 were greater than 0.5, indicating that all items were appropriately assigned to scales. The items with correlation scores of lower than 0.5 do not share adequate variance with the rest of the items in that scale, which in turn should be omitted from the scale. There is not any item with an inadequate correlation value which less than 0.5 in this analysis. Table 6. Item to scale correlation matrix* Item No. 1 2 3 4 5 6 1.Accessibility 0.775** 0.717** 0.756** 0.698** 0.793** 0.601** 2. Trust 0.710** 0.807** 0.834** 0.707** 0.707** 3.Credibility 0.623** 0.849** 0.878** 0.612** 4. Web Interface 0.811** 0.812** 0.77** 0.708** 5. Attention 0.785** 0.770** 0.686** 0.770** **.Correlation is significant at the 0.01 level (2-tailed) *.Correlation is significant at the 0.05 level (2-tailed) Reliability The reliability of the scale is related to the homogeneity of their items. It is a measure of the ability to produce the same results on repeated trials. Cronbach s alpha is commonly used to measure the internal consistency of the scales. It is based on the average correlation between items within a test. Because intercorrelations among test items are maximized when all items measure the same construct, Cronbach's alpha indirectly indicates the degree to which a set of items measures a single unidimensional latent construct. Thus, alpha is most appropriately used when the items measure different substantive areas within a single construct. When data have a multidimensional structure, Cronbach's alpha will usually be low. In conslusion, Cronbach's alpha is not a statistical test - it is a coefficient of reliability (or consistency). In order initially to assess the internal consistency of the scales correlation matrix was constructed for each scale. There was not any correlation problem according to this correlation 403

analysis. All items were highly correlated with scales which they were related to. Cronbach s alpha was then calculated for each scale (Cronbach, 1951). Although an alpha value of 0.7 and higher is often considered the criterion for internally consistent established scales (Hair et al., 1998). Table 7 presents the Cronbach s alpha values of the scales developed. All the scale measures of Internet Banking Service Quality are over 0.7. So, the values of Cronbach s Alpha are satisfactory which shows construct reliability. This establishes the internal consistency of the dimensions being studied and is reliable for this research. Table 7. Internal consistency of the scales Scales Number of items Number of deleted items Cronbach s alpha 1.Accessibility 6 No 0.815 2. Trust 5 No 0.807 3.Credibility 4 No 0.719 4. Web Interface 4 No 0.778 5. Attention 4 No 0.738 Validity Validity is the degree to which a test measures what it claims to measure. If the test is not valid, then results cannot be accurately interpreted and applied. In this survey, the validity of the instrument was assessed by investigating its content, construct, convergent and discriminant validity. Content validity, is based on the extent to which a measurement reflects the specific intended domain of content (Carmines and Zeller, 1991). The content validity of the survey instrument was established in several steps. First, an extensive review of quality management literature was undertaken to develop the questionnaire items. Next, preliminary questionnaire items were discussed with a number of professionals who are working in banks. Finally, a pilot study was conducted with ten people to determine the understandability of the questions in the survey. Some changes were made in the questions by taking into considerations the suggestions of the respondents in this pilot study. Construct validity, extent to which a set of measured variables actually represents the theoretical latent construct those variables are designed to measure. The construct validity can be assessed by factor analysis. Factor analysis is a correlational technique to determine meaningful clusters of shared variance. Factor Analysis should be driven by a researcher who has a deep and genuine 404

interest in relevant theory in order to get optimal value from choosing the right type of factor analysis and interpreting the factor loadings. Factor analysis finds relationships or natural connections where variables are maximally correlated with one another and minimally correlated with other variables and then groups the variables accordingly. There are two types of factor analysis, called as exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA explores the data and provides the researcher with information about how many factors are needed to represent the data. With EFA, all measured variables are related to every factor by a factor loading estimate. CFA is similar to EFA in some respects, but philosophically it is quite different. With CFA, the researcher must specify both the number of factors that exist for a set of variables and which factor each variable will load on before results can be computed. Thus, the statistical technique does not assign variables to factors. Instead, the researcher makes this assignment based on the theory being tested before any results can be obtained. Moreover, a variable is assigned to only a single factor (construct), and cross-loadings are not assigned (Hair et al., 1998). Given the nature of this study, both EFA and CFA would have to be employed to assess construct validity. First, EFA was performed and each scale was subjected to factor analysis separately. The results of EFA are represented in Table 8. Those results indicate that all of the items constituting each factor had factor loadings that were greater than 0.5. The scales with factor loadings of 0.5 or greater are considered very significant (Hair et al., 1998). In this study, a factor loading of 0.5 was used as the threshold value. The EFA results showed that the items in all of the 5 scales formed a single factor. Table 8. Factor analysis of each scale Factor Loadings Scales Number of Factors MSA* Total eigen values 1 2 3 4 5 6 % variance explained 1 1 0.855 3.162 0.775 0.717 0.756 0.698 0.793 0.601 52.694 2 1 0.794 2.849 0.710 0.807 0.834 0.707 0.707 56.974 3 1 0.690 2.255 0.623 0.849 0.878 0.612 56.365 4 1 0.780 2.412 0.812 0.811 0.770.708 60.300 5 1 0.736 2.272 0.785 0.770 0.770 0.686 56.790 *Kaiser-Meyer-Olkin Measure of Sampling Adequacy The second stage is also known as testing the measurement model where Internet Banking Service Quality scales were tested using the first-order confirmatory factor model to assess construct validity using the maximum likelihood method. The results of confirmatory factor analysis were parallel to the results of exploratory factor analysis. Table 9 shows the results of the 405

confirmatory factor analysis. It provides the following model statistics for the assessment of goodness-of-fit: x 2 statistics, its associated degrees of freedom, p-value of significance, GFI, AGFI, CFI, and Tucker-Lewis index. This analysis has been made AMOS 5.0 program. Accessibility has a chi-square value of 19.2 (degrees of freedom=9 and p-value<0.05), with the x 2 /df ratio having a value of 2.13, which is nearer to 2 (it should be between 0 and 3 with lower values indicating a better fit). The goodness-of-fit index (GFI) was 0.978 and the adjusted goodness-of-fit index was 0.948. These scores are very close to 1.0 (a value of 1.0 indicates perfect fit). The comparative fit index (CFI) was 0.979, while Tucker-Lewis coefficient was 0.966. All indices are close to a value of 1.0 in CFA indicating that the measurement models provide good support for the factor structure determined through the EFA. Trust has a chi-square value of 2.3 (degrees of freedom=3 and p-value>0.05), with the x 2 /df ratio having a value of 0.76, which is nearer to 0 (it should be between 0 and 3 with lower values indicating a better fit). The goodness-of-fit index (GFI) was 0.997 and the adjusted goodness-offit index was 0.975. These scores are very close to 1.0 (a value of 1.0 indicates perfect fit). The comparative fit index (CFI) was 0.999, while Tucker-Lewis coefficient was 0.996. All indices are close to a value of 1.0 in CFA indicating that the measurement models provide good support for the factor structure determined through the EFA. Credibility has a chi-square value of 0.5 (degrees of freedom=2 and p-value>0.05), with the x 2 /df ratio having a value of 0.25, which is nearer to 0 (it should be between 0 and 3 with lower values indicating a better fit). The goodness-of-fit index (GFI) was 0.999 and the adjusted goodness-of-fit index was 0.995. These scores are very close to 1.0 (a value of 1.0 indicates perfect fit). The comparative fit index (CFI) was 1.000, while Tucker-Lewis coefficient was 1.015. All indices are close to a value of 1.0 in CFA indicating that the measurement models provide good support for the factor structure determined through the EFA. Web Interface has a chi-square value of 0.4 (degrees of freedom=2 and p-value>0.05), with the x 2 /df ratio having a value of 0.2, which is nearer to 0 (it should be between 0 and 3 with lower values indicating a better fit). The goodness-of-fit index (GFI) was 0.999 and the adjusted goodness-of-fit index was 0.996. These scores are very close to 1.0 (a value of 1.0 indicates perfect fit). The comparative fit index (CFI) was 1.000, while Tucker-Lewis coefficient was 1.016. All indices are close to a value of 1.0 in CFA indicating that the measurement models provide good support for the factor structure determined through the EFA. Attention has a chi-square value of 0.8 (degrees of freedom=2 and p-value>0.05), with the x 2 /df ratio having a value of 0.4, which is nearer to 0 (it should be between 0 and 3 with lower values indicating a better fit). The goodness-of-fit index (GFI) was 0.982 and the adjusted goodness-offit index was 0.912. These scores are very close to 1.0 (a value of 1.0 indicates perfect fit). The 406

comparative fit index (CFI) was 0.965, while Tucker-Lewis coefficient was 1.016. All indices are close to a value of 0.896 in CFA indicating that the measurement models provide good support for the factor structure determined through the EFA. Table 9. Initial confirmatory factor analysis results Dimension Number of Indicators x 2 df p-value GFI AGFI CFI TLI AVE 1. Accessibility 6 19.2 9 0.023 0.978 0.948 0.979 0.966 0.53 2. Trust 5 2.3 3 0.309 0.997 0.975 0.999 0.996 0.57 3. Credibility 4 0.5 2 0.774 0.999 0.995 1.000 1.015 0.56 4. Web Interface 4 0.4 2 0.810 0.999 0.996 1.000 1.016 0.60 5. Attention 4 0.8 2 0.05 0.982 0.912 0.965 0.896 0.57 Convergent validity is the extent to which indicators of Internet Banking Service Quality converge or share a high proportion of variance in common (Hair et al., 1998). Table 9 also shows that most of the indices are within the acceptable range for each construct. All the individual factor loadings were found to be highly significant, giving support to convergent validity. Average variance extracted (AVE) has been also calculated. These AVE scores are shown in Table 9. The values of AVE were higher than the recommended value of 0.50, providing further support to convergent validity of scales. The standardized regression weights for all variables constituting each dimension were also to be significant (p<0.01), as shown in Table 10. 407

Table 10. Confirmatory factor analysis of Internet Banking Service Quality Description Regression Weight t-value* Description Regression Weight t-value* Scale 1: Accessibility Scale 2: Trust Item 1 0.724 - Item 1 0.542 - Item 2 0.638 9.323 Item 2 0.726 8.064 Item 3 0.693 10.204 Item 3 0.858 8.104 Item 4 0.624 9.419 Item 4 0.587 7.025 Item 5 0.746 11.045 Item 5 0.587 8.538 Item 6 0.511 7.764 Scale 3: Credibility Scale 4: Web Interface Item 1 0.452 - Item 1 0.750 - Item 2 0.792 7.260 Item 2 0.752 10.270 Item 3 0.896 6.939 Item 3 0.666 9.448 Item 4 0.448 5.508 Item 4 0.575 8.321 Scale 5: Attention Item 1 0.659 - Item 2 0.642 8.765 Item 3 0.629 6.964 Item 4 0.758 7.965 Note-Fixed for estimation; *all values are significant at the 0.01 level Discriminant validity is extent to which a construct is truly distinct from other constructs both in terms of how much it correlates with other constructs and how distinctly measured variables represent only this single construct (Hair et al., 1998). Discriminant validity describes the degree to which operationalization is not similar to (diverges from) other operationalizations that is 408

theoretically should not be similar to. A successful evaluation of discriminant validity shows that a test of a concept is not highly correlated with other tests designed to measure theoretically different concepts (www.wikipedia.org). Table 11. Assessment of discriminant validity Test # Description Chi-squared model Chi-squared unconstrained model Difference 1 Accessibility-Trust 133.7 250.9 117.2 2 Accessibility-Credibility 83.7 191.1 107.4 3 Accessibility-Web Interface 83.5 150.1 66.4 4 Accessibility-Attention 53.5 127.9 74.4 5 Trust-Credibility 99 246.4 147.4 6 Trust-Web Interface 81.7 191.8 110.1 7 Trust-Attention 97.3 196.7 99.4 8 Credibility-Web Interface 52.9 153.5 100.6 9 Credibility-Attention 74.6 170.4 95.8 10 Web Interface-Attention 50.5 116.7 66.2 The conservative approach for establishing discriminant validity compares the AVE estimates for each construct with the squared interconstruct correlations associated with that factor. Some AVE estimates from Table 9 are less than the corresponding interconstruct squared correlation estimates in Table 12 (above the diagonal). There are some problems with discriminant validity for Internet Banking Service Quality scale. 409

Table 12. Construct Correlation Matrix Accessibility Trust Attention Web Interface Credibility Accessibility 1 0.68 0.5 0.52 0.56 Trust 0.828** 1 0.58 0.49 0.58 Attention 0.709** 0.765** 1 0.47 0.57 Web Interface 0.723** 0.701** 0.687** 1 0.43 Credibility 0.748** 0.759** 0.756** 0.656** 1 **Correlation is significant at 0.01 level (two-tailed) Values below the diagonal correlation estimates among constructs, diagonal elements are construct variances, and values above diagonal are squared correlations. Item analysis of Satisfaction Scale The satisfaction scale that is developed by Yang et al. (2004) was used in this research. In this research, the scale of Yang et al. (2004) was tested again to determine its validity. To operationalise the constructs, the properties of the measures are considered: reliability (internal consistency of operationalisation) and validity. The reliability of the satisfaction scale is analyzed and the Cronbach s Alpha has been found as 0.91. It is greater than the threshold value of 0.7. This establishes the internal consistency of the dimensions of satisfaction scale is reliable for this research. Table 13. Internal Consistency of Satisfaction Scale Scales Number of items Number of deleted items Cronbach s alpha Satisfaction 3 No 0.914 Factor loadings of the items are also analyzed. All factor loadings are greater than the 0.8 for this scale. All the individual factor loadings were found to be highly significant, giving support to 410

convergent validity. Satisfaction factor s degrees of freedom is equal to zero. It is under identified. So it s GFI, AGFI, CFI, and TLI indexes can not be calculated. Its average variance extracted can be calculated. This value is higher than 0.8. Satisfaction scale has convergent validity according to its AVE value. Table 14. Factor Loadings of Satisfaction Scale Factor Loadings Scales Number of Factors MSA* Total eigen values 1 2 3 % variance explained AVE Satisfaction 1 0.73 2.563 0.924 0.950 0.899 85.42 0.853 *Kaiser-Meyer-Olkin Measure of Sampling Adequacy Multiple Regression Analysis Multiple regression analysis was conducted with internet banking customer satisfaction as dependent variable, testing the effect of internet service quality (accessibility, trust, credibility, web interface, and attention) and the control variables (gender, age, education, and income). The results of regression analysis are exhibited in Table 15, presenting the standardized beta, t- value, significance levels, and VIF (Variation Inflation Factors). Some of the VIF values are higher than the 3 points limit suggested in Social Science literature that indicates multicollinearity problem in the analysis. The amount of variance explained by the set of predictors in overall customer satisfaction is 0.668. The values of standardized betas reveal that accessibility (std.beta = 2.669, p < 0.05), trust (std.beta = 3.966, p < 0.05), credibility (std.beta = 1.573, p < 0.05), and web interface (std.beta = 2.543, p < 0.05) are significantly and positively related. Discussion and Conclusion The work presented in this study focused on the investigation of internet service quality and its impact on customer satisfaction, by examining the internet banking sector in Turkey. The field research was conducted using a structured questionnaire, which was based on the work of Jayawarhena (2004), and had SERVQUAL as its starting point. Accessibility, trust, credibility, web interface, and attention have been verified as being the dimensions on which service quality measurement can be based. 411

Table 15. Results of Multiple Regression Analysis Overall Satisfaction (Dependent Variable) Std. Beta t Significance VIF Gender (Female) -0.034-0.923 0.357 1.156 Age 0.027 0.675 0.500 1.322 Education (Bachelor Degree) -0.02-0.059 0.953 1.083 Income -0.01-0.023 0.982 1.324 Accessibility 0.181 2.669 0.008 3.926 Trust 0.282 3.966 0.000 4.302 Credibility 0.217 1.573 0.000 3.189 Web Interface 0.139 2.543 0.012 2.557 Attention 0.097 3.542 0.117 3.220 Adjusted R-Square 0.668 Significance of the Model 0.000 In this study, Jayawardhena s quality of internet banking service has been retested to see its applicability in Turkey. The reliability and validity of this scale have been measured with collected data set. This scale has internal consistency, construct, and convergent validity. But some problems have been determined about the discriminant validity. The relationships between quality dimensions and customer satisfaction level have been also measured with regression analysis. Accessibility, trust, web interface, and attention dimensions have a significant positive relationship with customer satisfaction. The survey respondents ranked trust as the highest performed dimension. Four of five dimensions have a significant effect on overall customer satisfaction, with trust being the most important predictor. This information can be proved valuable for bank managers; trust was the most important factor to increase the perceived quality of customers of internet banking. The effects of some demographics, such as, age, income level, education level, and, gender on overall customer satisfaction have been also analyzed. There is not any significant relationship between those demographics and overall customer satisfaction level. 412

Technology has been changing day by day, and so the needs and wants of the people. To be successful in the business world and to be competitive companies should give importance to quality. They should increase the quality level of their business. With increased perceived quality the satisfaction level of customer will also increase. Quality is very important to differentiate yourself as a company in such a competitive business world. Limitations of the Study and Further Research Although the results provide insights into the relationship between overall customer satisfaction level and perceived quality of internet banking service, there are several limitations to this study. First limitation was about the chosen sample for this research. In order to safely generalize the above analysis results it is necessary to confirm the instrument s validity, reliability and applicability with a larger sample. Most of the respondents had bachelor degree and were young (age between 26 and 31). Therefore, the results might differ with other participant populations. Future studies should include various populations to increase the internal and external validity. This study also can be performed in different cultural contexts with higher or lower internet penetration rates. So, researchers could build on this study by extending it to other countries. Research related to other countries would gain us deep insights about the service quality of internet banking applications. Second, time period of this study was restrictive. Longitudinal studies could also help extend the validity of these findings. Finally, this study verified the research model by surveying internet banking users. Internet banking service has been chosen because it manipulates the most sensitive personal information. The research model of this study can be applied to other kinds of internet service contexts (e.g. online shops, information portals etc. References Cox, J., and B.G. Dale. "Managing Service Quality." Service quality and E-commerce: An exploratory analysis. 11.2 (2001): 121-131. Cronbach, L.J. "Psychometrika." Coefficient of alpha and internal structure of tests. 16.3 (1951): 297-334. Gounaris, S., and S. Dimitriadis. "Journal of Services Marketing." Assessing service quality on the web: Evidence from business-to-consumers portals. 17.5 (2003): 529-548. Hair, J.F., R.E. Anderson, R.L. Tatham, and W.C. Black. Multivariate Data Analysis. 5. Upper Saddle Row: NJ: Prentice Hall, 1998. 413

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Appendix A. Table 16. Quality of Internet Banking Service Scale Dimension Item/Variable Variable Name Accessibility 1. I can log into my account at Bank X every time and Web pages download quickly. Fast 2. I can speak with a person (either through remotely using a telephone or in person at a branch) at Bank X in case I have problems with my account. Via Other 3. There are email links and/or a web based query facilities so that I can to get in touch with Bank X. Via Web 4. I can retrieve a significant amount of information and transaction details on my account with Bank X. Details 5. Bank X s account enables me to carry out a wide range of transactions. Functionality 6. I can log into my account at Bank X s from anywhere in the world using any computer, there is no need to install additional plugins. Anywhere Trust 1. When I access my account I feel secure, Bank X s web site instills confidence. Confidence 2. Bank X is prompt in responding to my queries/requests Prompt 3. Bank X s Web site contains relevant information (Account details, operations and security arrangements) they are both useful and explained in an easy to understand language. Information 4. Bank X s Web site contains a comprehensive FAQ (Frequently Asked Questions) section to help/guide me for my common problems. Help 5. I can determine my own passwords (which are unique and easy to remember) to log into my account Bank X. Login Credibility 1. Bank X s service is truly 24*7, there are no occasions when the Web site is inaccessible. Service 24*7 2. Bank X delivers the service exactly as promised. Promise Service 3. Bank X will always provide the service at the promised time. Promise Time 4. It is easy to apply for additions to my account with Bank X and help is easily available. Additions Web Interface 1. Navigating within Bank X s Web sites is very easy, hyperlinks and pages are logically laid out. Navigation 2. Bank X s web site is updated regularly. Update 3. Bank X s Web site incorporates a good colour scheme, easy on the eye, visually attractive and incorporates an effective layout. Visual 4. Bank X s Web site includes interactive features (including a demo) which are very useful. Features Attention 1. Bank X understands the needs of their customers. Understand 2. Bank X is very accurate in their responses to my queries/requests. Accurate Response 3. Bank X s systems are able to provide me with personalized newsletters/alerts that recommend new products, etc. to help me to keep my costs down and maximize my returns. Provide 4. Bank X s responses to my queries/problems are personalized. Personal 415