Based on the recommendations of Joseph et al. The sampling population was defined as customers of Ethiopian commercial banks who are using at least one form of e-banking channels. 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). 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.
who will be happy to help. 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. In general, as recommended by Joseph et al. The best predictor of behavior is intention. (2010), the sample size should be 1520 observations per variable for generalization purposes. (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. The implication is that the more the customers become aware about e-banking service delivery channels (having enough information about its benefit and how to use it); the better becomes their actual usage behavior.
The necessary sample size was estimated based on the number of independent variables. Did you know that with a free Taylor & Francis Online account you can gain access to the following benefits? Therefore, the main objective of this study is to identify factors that affect customers usage of electronic banking services. H5b:Perceived risk has negative effect on customers e-banking usage behavioral. The significant impact of perceived ease of use on usage intention from the preceding research provided evidence that it is either directly or indirectly through its effect on perceived usefulness and attitude that perceived ease of use would have a positive effect on users perception of credibility in their interaction with the e-banking systems (Al-Smadi, 2012; Qureshi et al., 2008; Olatokun & Owoeye, 2012; Aderonke & Charles, 2010; Singh, 2012; Poursaleh & Parhizgar, 2014).
I have the knowledge to use e-banking services. (2010) and Tabachnick and Fidell (2007). In line with this Al-Smadi (2012) suggested that an integrated model may provide more explanatory power than the individual use of TAM and TPB. Accordingly, all the average variance extracted (AVE) values of two constructs are greater than their respective squared correlation result. The discriminant validity of the constructs which shows the extent to which a construct is truly distinct from other constructs is tested and presented under the appendix section (Table A3). Accordingly, the goodness of fit indices and the result of the structural relationship (Figure 3) between the exogenous and endogenous latent constructs as discussed above are presented below.
H4b:Perceived behavioral control has positive effect on customers e-banking usage behavior.
In line with this Pikkarainen et al. 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. support team who will be happy to help. In addition to its impact on attitude and behavioral intention, perceived ease of use has also a positive effect on perceived usefulness. Once the data is collected, coded, entered and cleaned; it goes through both descriptive and quantitative data analysis techniques. In line with this, a study conducted by Padachi et al.
People also read lists articles that other readers of this article have read. 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. There are numerous related past studies that have found a significant relationship between intention and behavior (I. Ajzen, 1985, 1991; Tan et al., 2012; Venkatesh et al., 2003). People shape their attitude positive or negative when they think a particular technology is beneficial and require less effort to deal (Khurshid et al., 2014). H3:Subjective norm has positive effect on customers intention to use e-banking services. 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). ScienceDirect is a registered trademark of Elsevier B.V. Click here to go back to the article page. 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. As stated in the research methodology part, the existence of discriminant validity among the construct is evaluated by comparing the average variance extracted of two constructs with their respective squared correlation estimate and the average variance extracted value should be greater than their squared correlation result for a truly distinct construct (Joseph et al., 2010). This result is supported by the Technology Acceptance Model (TAM) developed by Davis (1989) because this theory of technology acceptance stated that perceived ease of use and perceived usefulness directly and positively affect the attitudes towards the acceptance of a given information system. Based on the results discussed above it is possible to conclude that perceived behavioral control, behavioral intention, subjective norms, attitude towards use, perceived usefulness, perceived ease of use, availability of internet/network connection and awareness have a significant positive impact on customers usage of e-banking service delivery channels, however, perceived risk has a negative significant impact. 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. High-income clients and those who are computer and internet literate are more likely to use e-banking services (Poon, 2008 and Annin et al., 2013). 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. Accordingly, it indicated that more than half of the respondents are males (243, 57.9%). I always use e-banking to pay my living expenses. This would deepen the knowledge of the factors which influence either positively or negatively the customers attempt to use electronic banking services. In my opinion, it is desirable to use e-banking.
Kamel and Hassen (2003) stated that perceived risk is among the factors that negatively affect consumers intention and their e-banking service usage behavior. Factors affecting bank customers usage o . 6. 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).
H1c:Perceived usefulness mediates the positive effect of perceived ease of use on attitude towards e-banking usage. This finding indicates that the better the customers attitude (developing positive feeling) towards e-banking, the more becomes their behavioral intention to use the service. H2b:Perceived ease of use has positive effect on customers perceived usefulness of e-banking usage. 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. With regard to age category, majority of the respondents are young with the age category of 1832 (75.7%). 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. I have received enough information about the benefits of e-banking.
Further, all banks should aggressively create continuous awareness to the society with regard to the usage and benefits (usefulness) of e-banking services by using different media.
Then, based on the results in step one, the data were analyzed in step two by applying Structural Equation Modeling (SEM) using Maximum Likelihood Estimation. Secondary data obtained from related-published journals, online articles, books and international conference papers were also used.
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.
H4a:Perceived behavioral control has positive effect on customers intention to use e-banking services. The standard deviations for most of the variables were less than one which indicates that the item scores for each construct were distributed around the mean score or it shows the normality distribution of the sample. These entire tests were performed with SPSS plus AMOS version 21 and Excel is used to calculate AVE and Construct Reliability (CR).
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 consistent with this finding, Al-Smadi (2012), Baraghani (2008), Yitbarek and Zeleke (2013), and Poursaleh and Parhizgar (2014) on their empirical study investigated that attitude has a positive and significant influence on customers intention to use electronic banking services.
Conceptual framework (own development). Summary of direct effect results of the structural model, Table A2.
Again the implication is that the more the technology is useful (perceived as time-saving, convenient and help to manage banking transactions effectively); the better becomes their attitude and behavioral intention to adopt the technology (e-banking).
Overall, it is easy to use e-banking services. The effect of awareness on customers adoption of e-banking services has been validated in many prior studies such as (Al- Somali et al., 2011; Oye et al., 2009; Safeena & Date, 2010; Geetha and Malarvizih, n.d.; Makosana, 2014; and Azouzi, 2009). This implies that majority of the e-banking users are those who have better average monthly net income. A total of 420 actual users of e-banking services were used as a sample.
It refers to the cognitive representation of a persons readiness to perform a given behavior, and it is considered to be the immediate antecedent of actual usage behavior (Fishbein and Ajzen, 1975). Customers are not willing to take any risk, and as a result they want to keep away from risks. 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.
For example, some researchers conduct their study only by using Technology Acceptance Model (Mir et al., 2013; Davis, 1989; Akinyemi et al., 2013; Jahangir & Begum, 2008) and theory of planned behavior (Yaghoubi & Bahmani, 2011; Gholami et al., 2010;Tan et al., 2010) constructs separately and few studies conducted by integrating Technology Acceptance Model and Theory of Planned Behavior (Al-Smadi, 2012; Yaghoubi & Bahmani, 2010) but although information technology is changing drastically the way in which people live and particularly banks offer their products and services in most developed countries, studies conducted in Ethiopia to identify factors that affect users adoption of new technology (e-banking) are remaining scarce.
Note 1: Values below the diagonal indicates the Average Variance Extracted (AVE) whereas values above the diagonal indicate correlation squared matrix.
here Note 1: *** denotes for significant at 1% significance level, ** denotes for significant at 5% significance level, Note 1: Values below the diagonal indicates the correlation matrix between constructs, Note 2: PU=perceived usefulness, PEU=perceived ease of use, ATU=attitude, AW=awareness, SN=subjective norms, PR=perceived risk, PBC=perceived behavioral control, AQIC=availability of internet/network connection, BI=behavioral intention, AU=actual usage behavior. 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. This is because electronic banking services are in inherently risky environment due to the absence of personal contact, physical product evaluation, warranties, or contracts and the customers usually have difficulties in asking for compensation when transaction error occurs (Al-Smadi, 201 2 and Pavithran et al., 2014). 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. Correlation matrix among the latent constructs, Table A3.
I have generally received enough information about e-banking. The normal distribution forms a straight diagonal line and to check whether the data is normal or not the plotted data values are compared with the diagonal.
The direct as well as the mediating effect of intention on users actual usage behavior has been validated in many prior empirical studies conducted by using Theory of planned behavior (TPB) and Technology acceptance model (TAM) and both suggested that a persons behavior is determined by his/her intention to perform the behavior. The impact of perceived risk on users behavioral intention towards e-banking as well as on their actual usage behavior was hypothesized and tested in the structural research model and the findings showed that perceived risk has a direct negative and significant influence on users behavioral intention to adopt e-banking as well as on their actual usage behavior. It is easy to use e-banking to do banking transactions. 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).
H5b:Perceived risk has negative effect on customers e-banking usage behavioral.
The convergent validity of the measures were tested using factor loadings, Average variance extracted (AVE) and construct reliability and at a minimum all factor loadings and AVE values should be statistically significant and a good rule of thumb is that standardized factor loadings and AVE estimates should be 0.5 or higher (Joseph et al., 2010) whereas its discriminant validity was assessed by comparing the AVE values for any two constructs with the square of correlation estimate between these two constructs and then, to ensure discriminant validity, the average variance extracted estimates should be greater than the squared correlation estimate (Joseph et al., 2010). Reliability between 0.6 and 0.7 may be acceptable provided that other indicators of a models construct validity are good. Krejcie and Morgan (1970) also recommended that for a population having more than 1,000,000 target groups a sample size of 384 is acceptable.