H1a:Perceived usefulness has positive effect on customers attitude towards the usage of e-banking services. Confirmatory factor analysis (CFA) measurement model. Table 2. Qureshi et al. For instance, a user may perceive that internet banking is more risky than ATM. (2010), the sample size should be 1520 observations per variable for generalization purposes. However, given other convergent validity tests above the cut of value, the average variance extracted value of 0.423 for perceived usefulness has no significant impact on further analysis. Even though this research is unique with regard to the application of structural equation modeling as well as the usage of the integration of two well-known technology acceptance models (theory of planned behavior and technology acceptance model) and three additional important factors from the view point of Ethiopian banking customers, the major limitations include: Exclusion of the voice of non-users (those who are not using e-banking), as the electronic banking service delivery channels covered in this research, are so broad and not specific to each e-banking channel there is a possibility that the different factors considered influencing e-banking usage behavior as well as the challenges identified may be for a certain part of e-banking channels and not the whole of it. Based on the recommendations of Joseph et al. Poon (2008) and Azouzi (2009) on their study also supports that young and computer literate respondents are using or are willing to use electronic banking. In the following section, the structural path estimate results of the re-specified structural model are discussed below with respect to each construct incorporated in the research model. H1b:Perceived usefulness has positive effect on customers intention to use e-banking services. Therefore, the main objective of this study is to identify the factors that affect the usage of electronic banking services among the banking customers (only users) in Ethiopia. Table 1. In line with the finding of this study, Yaghoubi and Bahmani (2010) on their empirical study and Davis (1989) on his technology acceptance theory indicated that perceived ease of use does not have a direct impact on intention to use, although it affects the attitude and perceived usefulness, which in turn leads to greater acceptance of online banking. About ScienceDirectShopping cartContact and supportTerms and conditionsPrivacy policy. In line with this, in this study, normal probability test and histogram was used to assess the normality of the data (attached under the appendix part) and the result indicated that there is no significant departure from normality, however, slight departure is expected in social science researches (Pallant, 2011). This finding refers to the fact that while consumers get more information about e-banking, the more informative they become about the benefits it offers. Availability of quality internet/network connection (AQIC). Thus, future researchers should consider these limitations as an opportunity and should, therefore, include the views of non-users as well as conducting comparative studies focusing on differences in adoption behavior between the different forms of e-banking service delivery channels (such as ATM, internet banking and mobile banking). Goodness of fit measure results of the CFA measurement model, Table 4. Summary of direct effect results of the structural model, Table A2. (2004) also identified that the amount of information users have on online banking is the most influential factor explaining the use of online banking services. H1c:Perceived usefulness mediates the positive effect of perceived ease of use on attitude towards e-banking usage. In line with this, a study conducted by Padachi et al. However, due to the individuals low level of e-banking usage practice, the relationship between behavioral intention and actual usage practice is less than the relationship between attitude and behavioral intention. (2014) on their study found that consumers level of education and information communication technology knowledge impacts their acceptance of e-banking services (Tater et al., 2011 and Abrehe, 2015). The second step involves the assessment of the structural model which shows the relationships between the constructs. H9b: Intention mediates the relationship between attitude toward the behavior and usage behavior, H9c: Intention mediates the relationship between subjective norm and usage behavior, H9d: Intention mediates the relationship between perceived behavior control and usage behavior, H9e: Intention mediates the relationship between perceived usefulness and usage behavior, H9f: Intention mediates the relationship between perceived risk and usage behavior. My decision to use e-banking is influenced by my family.

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H6a:Attitude has positive direct effect on customers intention to use e-banking. insead knowledge suggested that the statistical test or resulting p-value is less meaningful as sample sizes become large (greater than 250) or the number of observed variables becomes large (greater than or equal to 30) and in this case the researcher should expect significant p-value result. Therefore, it implies that perceived usefulness appears to be the more important direct predictor of users attitude towards e-banking usage. Intention is hypothesized to act as a mediator between all relationships of exogenous variables and actual usage behavior. I have generally received enough information about e-banking. Correlation squared and average variance extracted matrix (Discriminant validity) of the constructs included in the research model. Availability and quality of internet connection is a prerequisite for the adoption of e-banking services. An empirical analysis, 169-193, Customer adoption of banking technology in private banks of India, Understanding information technology usage: A test of competing models, A theoretical extension of the technology acceptance model: Four longitudinal field studies, User acceptance of information technology: Toward a unified view, Factors affecting the adoption of online banking an integration of technology acceptance model and theory of planned behavior, Behavioral approach to policy making of the internet banking industry: The evaluation of factors influenced on the customers adoption of internet banking services, Analysis of factors influencing customers intention to the adoption of e-banking service channels in Bahir Dar city, Ethiopia: An integration of TAM, TPB and PR. Based on these reviews, the most appropriate theory and significant factors that influence usage of e-banking from bank customers viewpoint were determined and a model of the factors inducing customers usage of electronic banking service is developed which is as shown below in Figure 1. The effect of perceived risk on customers usage or adoption of e-banking services has been validated in many prior studies such as (Yitbarek & Zeleke, 2013; Lee, 2008; Olatokun & Owoeye, 2012; Abenet, 2010; and Nasri, 2011). Confirmatory factor analysis result of the measurement model. I encourage others to use e-banking services. Using e-banking is clear and understandable. It is one of the factors that affect users adoption of e-banking and it can be viewed through several dimensions such as security risk and privacy risk. Or contact our The tables also indicate the average monthly income category of respondents and it revealed that most of them have an average monthly net income of between 4000 and 6000 (44%) Ethiopian birr. E-banking can enable me to get more banking services. Even the integrated model itself may not sufficient to get more predictive power because Aboelmaged and Gebba (2013) on their study suggested that the integrated model of TAM and TPB constructs have low predictive power with regard to users adoption of new technology and hence they recommend that future researchers should include more variables beyond TAM and TPB when predicting e-banking adoption. There is also broad research that presents evidence of the significant impact of perceived usefulness on user acceptance of e-banking. H1b:Perceived usefulness has positive effect on customers intention to use e-banking services. On the other hand, a p-value of below 0.05 indicates that the two covariance matrices are statistically different and shows problems with model fitness (Joseph et al., 2010). Finally, the tables revealed that due to their perception of high risk about e-banking (mean=3.618 and std.dev=1.378), awareness problem (mean=3.049 and std.dev=1.240) and problem of accessing internet or network connection, users e-banking usage practice is average (mean=3.032 and std.dev=1.00).This implies that bank customers are not using e-banking service delivery channels frequently and always or in other words they are not fully utilizing the service. H6b:Attitude mediates the positive effect of perceived usefulness on intention to use e-banking services, H6c:Attitude mediates the positive effect of perceived ease of use on intention to use e-banking services. In the conceptual model developed, constructs are identified as either exogenous or endogenous. The type of research applied in this study is explanatory in nature. In addition, structured interview was conducted with e-banking department heads or managers of each respective banks in order to collect qualitative data that can able to substantiate the data collected using a structured questionnaire. By continuing you agree to the use of cookies. There is extensive empirical evidence that supports the significant effect of subjective norms on the intention to use e-banking services (Khanifar et al., 2012; Al-Smadi, 2012; Yitbarek & Zeleke, 2013). The Internet/network connection enables me to access the banks website 7days a week and 24hours a day. Secondary data obtained from related-published journals, online articles, books and international conference papers were also used. (Please check your downloads folder shortly for your download). Hence, an application perceived to be easier to use than another is more likely to be accepted by users. The data analyzed using Structural Equation Modeling revealed that perceived usefulness, perceived ease of use, attitude towards e-banking, perceived behavioral control, subjective norms, behavioral intention, awareness as well as the availability of internet/network connection have a significant positive impact on users e-banking usage practice. Using e-banking for my banking transaction is convenient. With regard to the different factors, most of the scholars include in their study limited variables. This implies that difficulty in using online systems is becoming less of a concern as they are increasingly user-friendly. This implies that not married or single customers have better e-banking usage practice as compared to married and divorced counter parts which is in line with Izogo et al. E-banking can be simply defined to mean a process where banks create a platform for its customers to generally access information and to transact businesses electronically through an electronic device without necessarily being present at the bank (Annin et al., 2013). (2004) the amount of information about e-banking (particularly internet banking) and its benefit is a determinant factor in motivating customers to use e-banking services. As indicated by its higher beta coefficient in the table above, the effect of perceived usefulness on users attitude towards e-banking is more than that of perceived ease of use. who will be happy to help. This suggests that majority of the e-banking users are young or in other words young customers have better e-banking usage practice as compared to old customers. Using e-banking services allows me to control my finance more effectively. H4a:Perceived behavioral control has positive effect on customers intention to use e-banking services. I have the required resources to use e-banking services. A well-structured questionnaire was used to collect the relevant information. Finally, the table shows the occupational status of respondents and it revealed that more number of respondents (185, 44%) were government employees which indicate that government employees have better e-banking usage practice as compared to others. Figure 2. As shown above (Table 4), except for chi-square which indicates significance p-value, all the goodness of fit measure fit indices are above their respective minimum cut of value (Joseph et al., 2010). Accordingly, based on the above justification, the researcher has developed an extension of the Technology Acceptance Model and Theory of Planned Behavior integrated model by incorporating additional constructs such as awareness, perceived risk and availability and quality of internet/network connection from the extant literature review. (2010) and Tabachnick and Fidell (2007). Security risk is generally associated with loss of personnel data or money and errors in transactions whereas privacy risk is associated with violation of customers privacy such as disseminating customer information to other (Featherman & Pavlou, 2002). This implies that the usefulness perception of e-banking users is highly and significantly influenced by their perception towards the easiness or user-friendly of the technology. The construct perceived usefulness has a direct positive and significant effect on users attitude towards e-banking and on their behavioral intention to use e-banking services which is in line with the technology acceptance model developed by Davis (1989). The effect of perceived ease of use on users attitude towards e-banking is also significant and it implies that the higher perceived ease of utilizing a particular e-banking service delivery channels makes it more likely that the individual will have a positive feeling toward using it.

International, Influence of individual, organizational and system factors on attitude of online banking users, Factors affecting adoption of mobile banking technology in Kenya: A case of bank customers within Nakuru municipality, E-Banking: A case study of askari commercial bank Pakistan, Analyzing the factors that influence the adoption of internet banking in Mauritius, An empirical investigation of mobile banking adoption in developing countries, Consumer acceptance of online banking: An extension of the technology acceptance model, Factors affecting the intention to use internet banking services, Users adoption of e-banking services: The Malaysian perspective, Customer acceptance of online banking in developing economies, Customer perspectives on e-business value: Case study on internet banking, Integrating TAM and TPB with perceived risk to measure customers acceptance of internet banking, An empirical investigation of the determinants of users acceptance of e-banking in Singapore (a technology acceptance model), University of Cincinnati: Routledge Taylor and Francis Group, Mobile phone banking usage behavior: An Australian perspective, Applying the TAM to understand the factors affecting use of online banking in the Pescadores, The adoption of online banking in Malaysia. support team who will be happy to help. H4b:Perceived behavioral control has positive effect on customers e-banking usage behavior. These entire tests were performed with SPSS plus AMOS version 21 and Excel is used to calculate AVE and Construct Reliability (CR). This integration is credible fill limitation of previous empirical studies and so that to increase the body of knowledge in this area and to apply structural equation modeling (SEM) method of analysis. If you have a problem obtaining your download, click Table A1. Further, this finding implies that e-banking users are not confident in electronic banking services. Therefore, this implies that availability of internet/network connection is the more important predictor of consumers actual e-banking usage behavior in Ethiopia. (2010) suggested that in order to evaluate the acceptability of the model, the researcher should report one absolute fit index (RMSEA or SRMR), one incremental fit index (CFI or TLI), one goodness of fit index (CFI or TLI) and one badness of fit index (RMSEA or SRMR) together with Chi-Square and its associated degrees of freedom.

Awareness refers to the amount of information consumers have about e-banking and its benefit (Pikkarainen et al., 2004) or it refers to the degree to which the users are informed about the existence of the new technological innovation (Fonchamnyo, 2013). Perceived behavioral control refers to an individuals perceptions of the presence or absence of the requisite resources or opportunities necessary for performing a behavior (Ajzen, 1985).The significant effect of perceived behavioral control on e-banking usage was investigated by a number of scholars (Yitbarek & Zeleke, 2013; Khanifar et al., 2012; Al-Smadi, 2012; Yaghoubi & Bahmani, 2010). Therefore, in this study, it is hypothesized that: H9a: Intention has positive direct effect on customers actual usage behavior. Note 1: Values below the diagonal indicates the Average Variance Extracted (AVE) whereas values above the diagonal indicate correlation squared matrix. Hence in this study, it is hypothesized that: H2a:Perceived ease of use has positive effect on customers attitude to use e-banking services. Similarly, Baraghani (2008) on his empirical study found that perceived usefulness is predicted by perceived ease of use and his finding imply that consumers use e-banking for the benefits and also due to its easiness to use it. According to Pikkarainen et al. Reliability between 0.6 and 0.7 may be acceptable provided that other indicators of a models construct validity are good. Several prior studies were confirmed the impact of the availability and quality of internet and network connection on e-banking usage (Amini et al., 2011; Pikkarainen et al., 2004; Al- Somali et al., 2011) and in this study, it is hypothesized that: H8a:Availability and Quality of internet connection has a significant effect on customers e-banking usage behavior. (2007) to identify factors affecting the adoption of e-banking found that there is a statistically significant relationship between awareness and the usage of internet banking. 5 Howick Place | London | SW1P 1WG. The table 1 shows the demographic profile of respondents. Customers are not willing to take any risk, and as a result they want to keep away from risks. (2008), Olatokun and Owoeye (2012), Aderonke and Charles (2010), and Poursaleh and Parhizgar (2014). An individual will hold a favorable attitude toward a given behavior if he/she believes that the performance of the behavior will lead to mostly positive outcomes. (2010) and Tabachnick and Fidell (2007) suggested that variables having a correlation coefficient of 0.9 and above are subjected to multicollinearity problem. H9a: Intention has positive direct effect on customers actual usage behavior. For example, studies conducted by Al-Smadi (2012), Baraghani (2008), and Yitbarek and Zeleke (2013) concerning the factors that affect the adoption of e-banking among bank customers by integrating TAM and TPB revealed that perceived usefulness, perceived ease of use, subjective norms, perceived behavioral control and attitude have a positive and significant impact on customers behavioral intention and thereby on their actual e-banking usage or adoption behavior. (2010) on their study identified that poor internet facility and network as well as the high cost of internet has a significant direct and indirect impact on customers usage of card banking. Hence, based on these justifications, and by giving allowance for errors and non-response rates, a total of 600 (40 variables*15 observation for each variable) respondents were considered as the acceptable sample size for the current study. Kamel and Hassen (2003) stated that perceived risk is among the factors that negatively affect consumers intention and their e-banking service usage behavior. This implies that males have better e-banking usage experience as compared to females. Hence for the current study, it is hypothesized that: H7a:Awareness has positive effect on customers e-banking usage behavior. The result of all these tests as presented below in the appendix section (Table A1) indicated that all the construct reliability and Cronbachs alpha test results are above the minimum threshold cut of value of 0.7 and above (Joseph et al., 2010). In line with this, Edwin et al. ScienceDirect is a registered trademark of Elsevier B.V. Click here to go back to the article page. There is a possibility that I face problems while making transactions using e-banking channels. Accordingly, in this study having a sample size of 420 and 40 indicators, the presence of significant p-value has no significant impact on the fitness of the model. However, based on the above criteria samples were taken from seven banks such as commercial bank of Ethiopia, Dashen Bank S.C, Wogagen bank S.C, United Bank S.C, Abyssinia Bank S.C, Abay Bank S.C and Zemen Bank S.C. Of which one is government bank (commercial bank of Ethiopia) and the remaining six are private banks. However, among these much of questionnaires distributed only 495 were returned which gives a response rate of 82.5% but after removing those incomplete questionnaires, the actual sample size used for analysis in this study were 420 respondents (70%). Similarly, Stevens (2009) also suggested that the large chi-square values may be due, at least in part, to the large sample size, rather than to any substantial misspecification of the model. I usually use e-banking services for banking transaction activities. Similarly, Al-Smadi (2012) found that perceived usefulness and perceived ease of use has a positive and significant impact on customers attitude toward electronic banking services.

It refers to an individuals perception of social pressure to perform or not to perform the behavior in question (Ajzen, 1988, p. 132). Demographic profile of respondents. Overall, using e-banking services is advantageous. According to the previous research studies usefulness is the subjective probability that the application of a new technology would improve the way a user could complete a given task (Singh, 2012). Concerning the context of the path diagram, even though, a number of prior studies (Al-Smadi, 2012; Yitbarek & Zeleke, 2013; Yaghoubi & Bahmani, 2010; Olatokun & Owoeye, 2012; Khanifar et al., 2012; Liao et al., 2010; Moga, 2010; Poursaleh & Parhizgar, 2014; Yaghoubi & Bahmani, 2011) were conducted by considering behavioral intention as an endogenous variable, in this study actual usage behavior was used as the ultimate endogenous or dependent variable because Bagozzi (2007) justified that intention may not be representative enough of actual use, because the time period between intention and adoption could be full of uncertainties and other factors that might influence an individuals decision to adopt a technology, rather he stated that actual usage behavior should be used as a dependent variable and should be predicted by behavioral intention. (2012) in Nigeria and Abrehe (2015) in Ethiopia. By closing this message, you are consenting to our use of cookies. The effect of availability of internet/network connection on consumers actual usage behavior is more than other variables.

3099067 In relation to marital status more than half of the respondents are single or not married (238, 56.7%). Using e-banking for banking transactions is a wise idea. Correlation matrix among the latent constructs, Table A3. Similarly, a study conducted by Auta (2010) to identify factors affecting e-banking adoption among bank customers also found that a shortage of telecommunication facilities are among the major factors that influence consumers adoption of e-banking. With regard to the variance extracted in each construct except perceived usefulness all the remaining constructs have average variance extracted of above the minimum cut of value of 0.5 as recommended by Joseph et al. This shows respondents positive response to these constructs whereas the mean value of above 3.0 for the construct perceived risk implies that users have high-risk perception about e-banking. All this results implies that the measurement model is valid and can proceed to further structural model testing. The best predictor of behavior is intention. I often use e-banking services for banking transaction activities. Although it provides various benefits for both banks and customers, low level of customers adoption of electronic banking services is noted in Ethiopia (Garedachew, 2010). (2010) in SEM, a two-step approaches than a single-step approach was used. All these technology acceptance theories as well as the findings in this study implies that the better users have positive behavioral intention to continue and increase its usage than branch-based traditional banking, the more become their actual usage practice and vice versa. Similarly, the effect of subjective norms or social influence on users behavioral intention to adopt e-banking services was tested and the result showed that behavioral intention is directly, positively and significantly influenced by subjective norms (Ajzen, 1988). digital integration insead knowledge Accessing financial information using e-banking channels is secure. Registered in England & Wales No. In line with this Ismail and Osman (2012) on their study investigated that e-banking usage is associated with clients income. For example, a study conducted by Yaghoubi and Bahmani (2011) to evaluate the causality of TPB factors on influencing customers adoption of e-banking services using structural equation modeling shows that attitude, perceived behavioral control and subjective norm have significant positive effects on behavioral intention to use e-banking. When this research was conducted, there are 16 commercial banks in Ethiopia. The effect of perceived ease of use on perceived usefulness and individuals attitude towards e-banking service delivery channels was tested and the result indicated that perceived ease of use has a positive significant direct effect. I prefer to go to the bank branch to do my banking transaction for security reason. Finally, the influence of behavioral intention to use e-banking on users actual usage behavior was tested and the finding reveals that users actual usage behavior is directly and positively influenced by their behavioral intention which is in line with Theory of Reasoned Action (TRA) Proposed by Fishbein & Ajzen (1975), The Theory of Planned Behavior (TPB) proposed by I. Ajzen (1988), the Decomposed Theory of Planned Behavior (DTPB) proposed by Taylor and Todd (1995), Technology Acceptance Model (TAM) proposed by Davis (1989) and Extended Technology Acceptance Model (ETAM) developed by Venkatesh and Davis (2000). In addition, the multicollinearity test result attached in the appendix part (Table A2) indicated that the maximum correlation between constructs is 0.542 which implies that there is no multicollinearity problem among the variables because Joseph et al. holi gaane ke stop non mp3
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