Columbia, MO Columbia, MO 65211

Transcription

1 Impacts of customers' perceptions on internet banking use with a smart phone Hyun Shik Yoon Luis Occeña University of Missouri University of Missouri Columbia, MO Columbia, MO ABSTRACT In recent years, a smart phone has become a useful platform to easily access banking services. However, compared to regular Internet banking using a personal computer, the adoption of a smart phone for Internet banking might be more vulnerable with regard to security. In this study, we first identify two dimensions: security and usability, and empirically test their role as determinants that affect Internet banking use with a smart phone (IBUS). Second, we investigate whether or not security and usage can possibly interact with each other to influence IBUS. Results indicate: (1) security issues were found to be a significant determinant of IBUS; (2) Perceived Usefulness (PU) and Perceived Ease of Use (PEU) as usability had significant effects on IBUS; (3) PU and PEU moderated the relation between users perception toward security and IBUS; and (4) Users perception toward security moderated the relation between PU/PEU and IBUS. Keywords: Internet banking, Smart phone, Security, Perceived ease of use, perceived usefulness Background INTRODUCTION Recently, developments in information technology and the subsequent evolution of Internet banking have changed the ways in which banks implement their business and consumers conduct their everyday banking activities [1] [2]. Internet banking enables customers to conduct a wide range of banking transactions electronically through the bank s website anytime and anywhere. However, consumers have shown reluctance to complete simple online transactions due to security concerns and perceived risk, which is posited as a critical obstacle to consumer acceptance of Internet banking [3]. Therefore, despite an increase in the number of Internet users and advantages of Internet banking for customers, the growth rate of those who adopt Internet banking has not risen as strongly as expected [4] [5] [6]. The interaction between customers and banks has been substantially improved by using ATMs, phone banking and, more recently, mobile banking with a smart phone. Smart phones have become an especially useful platform to easily access banking services. These banking activities may include: retrieving an account balance, transferring money between a user s accounts, and making a payment. However, compared to regular Internet banking using a personal computer, the adoption of a smart phone for Internet banking might be more vulnerable with regard to security since the development of the smart phone has been driven by market demand, focusing on new features such as attractive design and ease of use [7]. Therefore, customers perception toward security could be an important factor that influences Internet banking use with a smart phone. Although many researchers have studied customers security perceptions [8] [9], there is no research to find factors such as perceived security and usability including perceived ease of use and perceived usefulness that influence Internet banking use with a smart phone. Recently, although many customers have perceived the risk in using a smart phone, they have been willing to use the phone for Internet banking because of the device features (i.e., usability). Therefore, it is very important and meaningful for researchers to determine whether or not the perceptions toward the device, such as perceived ease of use and perceived usefulness, moderate the relation between perceived security and Internet banking use with a smart phone. In addition, the reverse perspective should be considered at the same time; that is, it should be determined whether or not perceived security moderates the relation between the usability and Internet banking use with a smart phone. Purpose of the Study First, in this study, we identify two dimensions: security and usability and empirically test their role as determinants that affect Internet banking use with a smart phone. Second, we investigate whether or not the security and the usability can possibly interact with each other to influence Internet banking use with a smart phone. That is, the role of the security and the usability as moderators is investigated. LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT This section reviews the theoretical framework for this study, including security dimension and usability dimension with the moderating effects as well as develops the research hypotheses as follows. Security Dimension The concept of consumer-perceived security has been widely dealt with in e-channels using IT devices and has been shown to influence customers behavior and attitude [10]. In order to discuss perceived security, we need to describe this concept. Perceived lack of security is defined as a perceived potential loss due to fraud or a hacker compromising the security of Internet banking ([9], p.2). Under this definition, in the context of Internet banking threats can be made either through network and data transaction attacks or through unauthorized access to the account by ways of false or defective authentication. Therefore, consumer-perceived security might be concerned with many issues from financial losses to privacy problems. Many consumers believe that they are vulnerable to identity theft while using the Internet banking services [9]. Processing financial transactions on the Internet presents numerous risks for consumers, over and Spring 2014 Journal of Computer Information Systems 1

2 above the transaction process itself being perceived as risky [11]. In the Internet environment, criminal acts can be performed with extremely high speed, and without any physical contact [12]. If an unauthorized person is able to get access to a user s Internet banking portfolio, tremendous financial information might be in jeopardy and there might be a lot of financial losses. Hence, the most important categories of Internet banking are likely to be security risk related to the potential loss because of deficiencies in the operating system or misappropriation of funds through illegal external access [13] [14] [15] [16]. As the number of products and services have offered through the Internet grows rapidly, customers are concerned about security issues. According to previous research [1] [2] [9] [11] [12] [17] [18], security issues have proven important barriers to the use of online services. Basically, customers want to control what kind of data is collected, for what purposes, for how long data is recorded, and how and for what purposes their data is processed [19]. Therefore, we can conclude that customers perceived security concern is a critical factor that influences Internet banking use with a smart phone. We propose that: H1: A customer s perceived security concern will negatively influence Internet banking use with a smart phone. Usability Dimension Internet banking can often times be a more effective way to utilize bank transactions than traditional offline banking, due to many benefits that it offers. Some of these benefits are faster transaction speed, little to no cost for transaction fees, and increased information transparency [6] [9] [20]. Therefore, these benefits can influence the customer s perception of Internet banking use. In addition, since the Internet is more common and standardized nowadays, the public has become increasingly comfortable in using it. Hence, in the planning and development of Internet banking, banks have paid attention to practical functions and extended key features considering usability factors [9]. For the usability dimension, we can identify perceived usefulness (PU) and perceived ease of use (PEU) as important factors influencing Internet banking use with a smart phone. In order to understand the concepts of PU and PEU, we need to discuss the Technology Acceptance Model (TAM). TAM is an adaptation of the theory of reasoned action (TRA) by Ajzen and Fishbein [21] and was mainly designed for modeling user acceptance of information technology [22]. This model hypothesizes that system use is directly determined by behavioral intention to use, which is in turn influenced by users attitudes toward using the system and PU of the system. Attitudes and PU are also affected by PEU. PU, reflecting a person s belief in the use of the technology, is helpful in improving productivity, and PEU is a person s belief that using the technology might be free of effort [23]. Therefore, these determinants are also easy for system developers to understand and can be specifically considered during system requirement analysis and other system development stages. These factors are common in technologyusage settings and can be applied widely to solve the acceptance problem. In terms of PU, there is also extensive research in the information systems community that provides evidence of its significant effect on usage intention [9] [24] [25] [26]. The ultimate reason people utilize Internet banking is that they find the systems useful to their banking transactions. Extensive research over the past decade provides evidence of the significant effect of PEU on usage intention, either directly or indirectly through its effect on PU. In order to make the Internet banking systems more useful, the systems need to be both easy to learn and easy to use [27]. Information technologies that are easy to use will be less threatening to the individual [28]. This implies that PEU is expected to have a positive influence on users perception of credibility in transactions with Internet banking [25] [29]. Thus, we conclude that PU and PEU have a direct effect on Internet banking use with a smart phone. In addition, PEU has an indirect effect on Internet banking use with a smart phone via PU; that is, PU mediates the relation between PEU and Internet banking use with a smart phone. We propose that: H2a: A customer s perceived usefulness will positively influence Internet banking use with a smart phone. H2b: A customer s perceived ease of use will positively influence Internet banking use with a smart phone. H2c: A customer s perceived ease of use will positively and indirectly influence Internet banking use with a smart phone via perceived usefulness. Moderating Effect A moderating effect occurs when the effect of an independent variable on a dependent variable varies according to the level of another variable [30]. This effect has been widely involved in behavioral research in order to find variety conditions that influence the strength of the relation between a predictor and an outcome. In this study, moderating effects exist between usability and security dimensions. They are described in detail below. As we discussed in section 2.1, much research has supported that customers perceived security concern influences the use of electronic channels such as e-commerce or Internet banking. However, there is a phenomenon that cannot be explained by the previous research. Recently, although many customers have perceived the risk in using IT devices such as smart phones, they are willing to use those devices because of their ease of use or usefulness. For example, there are many smart phone users, and they have perceived the vulnerabilities of the phone against malicious attackers while using a smart phone for Internet banking. They have perceived that they might lose sensitive information such as bank account numbers by using the device. However, many of them have been still willing to use a smart phone for Internet banking. In this case, the previous research could not explain this situation. Therefore, we have to consider PEU and PU as a moderator between customers perceived security concern and Internet banking use with a smart phone. In addition, we have to consider the reverse situation. Although customers have PEU and PU toward Internet banking with a smart phone, some of them have not been willing to use Internet banking due to their security concerns. As a result, we need to consider customers perceived security concern as a moderator between the usability dimension and Internet banking use with a smart phone. Hence, we propose the following hypotheses: H3a: A customer s perceived usefulness will moderate the relation between his/her perceived security concern and Internet banking use with a smart phone. H3b: A customer s perceived security concern will moderate the relation between his/her perceived 2 Journal of Computer Information Systems Spring 2014

3 usefulness and Internet banking use with a smart phone. H3c: A customer s perceived security concern will moderate the relation between his/her perceived ease of use and Internet banking use with a smart phone. Research Model RESEARCH DESIGN AND METHOD Based on these hypotheses, our research model includes two dimensions (i.e., security and usability) and builds upon previous work by including moderating effects between these two dimensions. The model is shown in Figure 1. Research Method Measures of the construct The instrument was designed to include a two-part questionnaire as presented in Appendix 1. The first part includes nominal scales, and the second part includes seven-point Likert scales, ranging from disagree strongly (1) to agree strongly (7). The first part is demographic information and was used to collect data about respondents characteristics including gender, age, education, and experience of Internet usage. The second part of the questionnaire was used to measure the constructs of PU, PEU, customers perceived security and Internet banking use with a smart phone. In this survey, Internet banking use with a smart phone includes two means of access, either applications or a regular web browser. In order to ensure content validity of the scales, the items chosen to represent the concept for the constructs were mainly adapted from prior studies [31]. One advantage of using the TAM to examine the acceptance of Internet banking with a smart phone is that it has a well-validated measurement inventory [22]. Items for PEU (4 items) and PU (4 items) were taken from the previously validated inventory and modified to fit the specific technology, that is, a smart phone. In terms of measuring customers perceived security, it was adapted from the instrument defined by the previous research and included four items [13] [24]. Internet banking use with a smart phone was adapted and modified from the measurements defined by Cheng et al. [24], containing two items. Data collection In this study, we selected residents who are older than 20 years old, and are living in Columbia, Missouri for the sample population. A variety of ages were collected for enhancing the external validity. For deployment of the survey instrument, we visited public organizations such as a public senior center, a library, a church and so on and deployed the survey instruments in the organizations. A total of 160 questionnaires were distributed, among which 131 questionnaires were collected and used in the analysis. The response rate was 81.9%. Table 1 shows the demographic distribution of the sample. 58.8% of respondents were male, and 41.2% were female. Most of TABLE 1. Demographic statistics of respondents Demographic Category Frequency (%) 20 years old 30 years old 75 (57.3) Age 31 years old 40 years old 43 (32.8) Older than 40 years old 13 (9.9) Gender Female 54 (41.2) Male 77 (58.8) Several times a day 104 (79.4) Frequency of Internet usage Daily 21 (16.0) Weekly 6 (4.6) Monthly N/A FIGURE 1. Research Model Spring 2014 Journal of Computer Information Systems 3

4 TABLE 2. Correlation matrix and AVEs for constructs Squared Root of AVEs and Correlation Composite Internet Construct Cronbach s α Reliability Mean S.D. AVE PEU PU Security banking Use PEU PU Security Internet banking Use the respondents (90.1%) were between 20 years old and 40 years old. Approximately, 10% of respondents were over the age of 40. In terms of frequency of Internet usage, most people (95.4%) used the Internet several times a day or daily. All respondents had owned their smart phone and used Internet banking services with a smart phone. DATA ANALYSIS AND RESULTS We used Partial Least Squares (PLS), specifically SmartPLS 2.0 to analyze the date [32]. A set of emergent theories with different variables was put in place to explain the purpose and benefits of Internet banking with a smart phone. The variables and configuration of the system need to be considered concurrently to assess such models [33]. Generally speaking, covariancebased structural equation models assume multivariate normal distributions [34]. However, the measures might be skewed according to studies pertaining to human personality and beliefs, and might not meet assumptions for multivariate normality required by covariance-based structural equation modeling techniques. Under such conditions, Chin, Peterson, and Brown [35] recommend the use of Partial Least Squares (PLS) path modeling over the traditional covariance-based structural equation modeling approach, since PLS employs a componentbased approach for model estimation and is not highly demanding on sample size and residual distribution. These reasons make the technique avoid inadmissible solutions and factor indeterminacy. In addition, in terms of covariance-based structural equation models, it is a full-information procedure. As a result, one incorrectly identified structural path or one construct having weak measures might affect all other estimates throughout the covariance-based structural equation model. Therefore, it is more significant for researchers to use PLS path modeling when trying to estimate a larger complex model dealing with human attitudes and behaviors. Measurement Validation We assessed convergent and discriminant validity of the measurements by two criteria: (1) each item should have a higher loading on its hypothesized construct than other constructs, and (2) the square root of each construct s Average Variance Extracted (AVE) should be greater than its correlations with other constructs [36]. First, in accordance with the guidelines of Gefen, Karahanna and Straub [37], we conducted a PLS confirmatory analysis. The result shows that items have much higher self-loadings than cross-loadings (Appendix 2). Second, we evaluate each construct s AVE and the AVE s square root is greater than the construct s cross correlation with other constructs (Table 2). All latent constructs have an AVE higher than 0.5 and it shows that all constructs in this study have adequate convergent validity [33]. Second, in order to confirm that there is adequate discriminant validity among the various constructs, the correlations FIGURE 2. Model Testing Results 4 Journal of Computer Information Systems Spring 2014

5 among the various latent constructs are also reported in Table 2. In the diagonal element of Table 2, we show the square root of the average variance extracted by each of these latent constructs. As shown in Table 2, the square root of the AVE (italic and bold region) by each of the latent variables is higher than the correlation between the latent variable and all the other latent variables. This demonstrates that the different latent variables extract a higher share of variance from their own indicators than from other latent variables. Since the measurement model is satisfactory, we can proceed to test the structural model. In addition, the composite reliability scores were highly satisfactory which exceed the recommended level of 0.70 [38]. The Cronbach s alphas values were also used to establish the convergent validity of the constructs. They range from to and all values are much greater than the recommended value of 0.7, suggesting adequate measurement reliability. Next, we discuss the structural model results that are used to test the hypotheses. Model Testing Figure 2 shows the model testing result. The model accounts for 56.2% of variance in perceived usefulness and 47.3% of variance in Internet banking use. As hypothesized, Internet banking use with a smart phone is significantly determined by PU (β=.222, p<.05), PEU (β=.398, p<.001), and perceived security concern (β=-.281, p<.05). Therefore, H1, H2a, and H2b were supported. To examine whether or not PU mediates the effect of PEU on Internet banking use, we added PU as a mediator between PEU and Internet banking use in this model (Figure 3). The PLS result showed that the link from PEU to PU is significant and the link from PU and Internet banking use is also significant. According to Baron and Kenny [30], this result shows that the influences of PEU on Internet banking use is fully mediated by PU, providing support for H2c as well. Moderating effect testing When the moderating influence is tested, this influence should be modeled by creating a new variable that is the product of the variable which is being moderated (X) and the variable which is moderating (Z). This interaction term (XZ) is then entered into the equation model after the linear main effects on the outcome (Y) of the moderating (Z) and moderated variables (X) are estimated. If the effect of XZ is statistically significant, then the effect of X on Y is dependent upon the levels of Z. Therefore, to test the moderating effects proposed by H3a, H3b and H3c, we followed a product-indicator approach [35]. We created two interaction variables (i.e., the interaction variable between PU and perceived security and the interaction variable between PEU and perceived security) by cross-multiplying the items of PU and perceived security and PEU and perceived security. After creating two interaction variables, we tested whether or not the interaction variables influence internet banking use with a smart phone. In addition, we tried to reduce multicollinearity by standardizing all of the items before multiplication [39]. As shown in Figure 2, all interaction effects we expected are significant: interaction between PU and perceived security (β=-.483, p<0.001), and interaction between PEU and perceived security (β=-.535, p<0.001). Based on these results, we found that consumers security concern moderated the impact of PU on Internet banking use with a smart phone such that impact to PU on Internet banking use with a smart phone is lower at higher levels of customers perceived security. For instance, if the standardized value of perceived security concern is increased by 1, the regression coefficient between PU and Internet banking use with a smart phone will decrease by 0.483, or vice versa. To further validate the interaction effect, we estimated the effect size (f²) by comparing the value of R² between the main effect and the interaction effect [35]. 1 The effect size of the interaction is 0.168, which shows a medium to large effect [40]. Hence, we found significant interaction effects supporting H3a, H3b, and H3c. In summary, our data analysis results provide support to all of the hypotheses. DISCUSSION Determinants that Affect Internet Banking Use with a Smart Phone The first purpose of this study is to examine the role of customers perceived security, PU, and PEU as determinants that affect Internet banking use with a smart phone. As we discussed, security issues have proven important barriers to the use of online services [1] [2] [9] [11] [12]. Therefore, we expected that customers perceived security negatively influences Internet banking use with a smart phone. In this study, perceived security issues were found to be a significant determinant of Internet banking use with a smart phone (H1). This is a meaningful result that has both theoretical and practical significance. As mentioned before, Internet banking using a smart phone tends to be more vulnerable to malicious attacks than the regular Internet banking using a personal computer [7]. Therefore, perceived security exhibits a strong explanatory power on Internet banking use with a smart phone. The security issues derived from technology uncertainty include theft of sensitive personal information such as bank account numbers and social security number by malicious hackers [41]. In order to prevent security problems, advanced techniques including strong authentication procedures, encrypted transactions, and privacy seals can be considered for utilization 1. f2 = [R2 (interaction model) - R2 (main effect model)] / [1 - R2 (interaction model)] FIGURE 3. Mediating effect of PU between PEU and Internet banking use with a smart phone Spring 2014 Journal of Computer Information Systems 5

6 in Internet banking systems. In terms of practical implication, therefore, when designing Internet banking systems, additional attention should be paid to address this security issue considering smart phones weakness toward malicious hacking. PU and PEU as usability might positively influence Internet banking use with a smart phone since many previous studies have posited that they are significant factors affecting acceptance of an information system. Using a smart phone is a typical usage of an information system and provides more comfortable and easier access to Internet banking. In this research, these two factors had significant effects on Internet banking use with a smart phone (H2a and H2b); that is, this implies that the perceived benefit is the important positive predictor of Internet banking use with a smart phone. The Effects of Security and Usage Dimension as Moderators The second purpose of this study is to investigate whether or not customers security concern, PU, and PEU can possibly interact with each other to influence Internet banking use with a smart phone. This study is differentiated from previous research by including these interaction effects. When considering the simple causal relation provided by previous research, we cannot explain complex situations in the current business environment. For instance, several studies found that perceived security concern negatively affects IT adoption. In this case, we cannot explain the situation to show that many people are willing to use Internet banking with a smart phone because of its usability even though they recognize vulnerability of security in using Internet banking with a smart phone. As mentioned above, in real situations, although many consumers have perceived the risk of e-channels such as e-commerce and Internet banking using IT devices, they have been willing to use those e-channels with them because of their ease of use or usefulness. In our research, we found that PU and PEU moderate the relation between users perception toward security and Internet banking use with a smart phone. Like this expectation, the reverse situation might be supported; that is, we can expect that users perception toward security moderates the relation between PU/PEU and Internet banking use with a smart phone. It is another important implication that we include interaction effects between customers security concern and usability of Internet banking with a smart phone into the research model in order to explain sophisticated situations in the current business environment. Practical Implication IMPLICATIONS The development of Internet technology with a smart phone is continuing to change the way business is done. This study has focused on the nature of Internet banking with a smart phone. Internet banking is becoming one of the most important channels for online transaction and many customers have used their smart phone for Internet banking. Therefore, in response to global trends with customers using a smart phone, banks have to better understand their customers and respond quickly to market developments. In view of competition in the banking industry, it is important for banks to get a critical market share in the early stage of the product lifecycle. Therefore, it is important to understand the current adoption of Internet banking with a smart phone and to identify impacts of adopters perception toward security or usability issues on Internet banking with a smart phone. Theoretical Implication This study has two main implications for future Internet banking research. First, the empirical results show that both security concerns and usability have significant effects on Internet banking use with a smart phone. According to the risk theory of consumer behavior [42], Bauer indicated that benefits are often accompanied with risk. Therefore, this study supports the theory. In addition, it might be worth investigating the casual relationship between usability dimension and security dimension. This study provides a corner stone to develop further understanding of this causal relationship among antecedents that can influence Internet banking use with a smart phone. Second, this research was to investigate the interaction effects between security concerns and usability on Internet banking use with a smart phone. The result shows interaction effects we expected are significant. Generally speaking, we cannot explain sophisticated customers behavior in using Internet banking by focusing on simple regression, correlation, or causal relations provided previous research. Several studies found that security concern has negative impact on customers belief, attitude, or intention in using IT adoption [9] [12] [15] [27] [29]. In reality, there are cases in which people are weighing costs and benefits and are willing to make trade-offs between security concerns and usability. These critical tradeoffs where a customer is weighing the importance of different factors and their role in making decisions to utilize or not utilize Internet banking with a smart phone have not evaluated in previous research. This study shows that there are significant interactions between these two dimensions that can be representative of trade-off in a smart phone adoption for Internet banking. CONCLUSIONS This study proposed an empirical model on Internet banking use, which incorporates bank customers perception on security and usability of Internet banking with a smart phone, considering interaction effects between two dimensions. We believe that the proposed model provides an integrated view of customers behavior toward Internet banking use with a smart phone and provide significant explanation of a complex phenomenon in the current business environment. This study is not without limitations. In our research model, we did not consider other variables such as gender, age, and national culture differences. For example, differences in national culture can affect customers belief, attitude, and behavior in using Internet banking with a smart phone. In some countries in Asia, collectivism might affect human behavior related to security issues. In this case, this result cannot be generalized to those countries. Hence, the study should be conducted in other countries in order to support the results. Another issue is that we did not consider social classes of samples based on their income and occupation. Different classes might have different behavior toward Internet banking use. By comparing different results from different classes, we might have a more significant result on Internet banking use with a smart phone. 6 Journal of Computer Information Systems Spring 2014

7 APPENDIX 1. QUESTIONNAIRE Part 1. Demographic Information A. Please tell us your age: 20 years old 30 years old 31 years old 40 years old Older than 41 years old B. Please tell us your educational background: Completed elementary school Completed high school or middle school Attending college or university Completed bachelor degree Attending or completed master or doctoral degree C. How do you identify: Male Female D. Please tell us your race/ethnicity: African American Asian American Latino/Hispanic Native American White Multi-racial/Bi-racial Other E. How often do you use the Internet? Several times a day Daily Weekly Monthly Never F. Do you have a smart phone? Yes No G. Have you ever experienced Internet banking by using a smart phone? Yes No Part 2. Internet Banking Use with a Smart Phone A. Perceived usefulness Using a smart phone enables me to accomplish my tasks more quickly. Using a smart phone is useful. Using a smart phone allows me to do things better. Using a smart phone makes me more efficient. B. Perceived ease of use Learning to use a smart phone is easy. It is easy to use a smart phone to accomplish my banking tasks. It is easy for me to become skillful at using a smart phone. It is easy to me to let a smart phone do what I want. C. Perceived security concern A smart phone implements security measures to protect users. I feel safe in making any transaction by using a smart phone. A smart phone is a secure device through which to send sensitive information. I am not concerned about the privacy of my personal information during a transaction by a smart phone. D. The Internet banking use with a smart phone I am using the Internet banking with a smart phone more often than others. I am using currently and will continue to use the Internet banking with a smart phone. APPENDIX 2. CONFIRMATORY FACTOR ANALYSIS RESULTS Security PU PEU Internet Banking Use Security Security Security Security PU PU PU PU PEU PEU PEU PEU Internet Banking Use Internet Banking Use Spring 2014 Journal of Computer Information Systems 7

8 REFERENCES [1] Eriksson, K., Kerem, K., and Nilsson, D., The adoption of commercial innovations in the former Central and Eastern European markets: The case of internet banking in Estonia, International Journal of Bank Marketing (26:3), 2008, [2] Sayar, C. and Wolfe, S., Internet banking market performance: Turkey versus the UK, International Journal of Bank Marketing (25:3), 2007, [3] AlGhamdi, R., Drew, S., and Al-Ghaith, W., Factors Influencing E-Commerce Adoption by Retailers in Saudi- Arabia: A Qualitative Analysis, The Electronic Journal of Information Systems in Developing Countries (47:7), 2011, [4] White, H. and Nteli, F., Internet banking in the UK: Why are there not more customers?, Journal of Financial Services Marketing (9:1), 2004, [5] Alsajjan, B. and Dennis, C., Internet banking acceptance model: Cross-market examination, Journal of Business Research (63:9), 2010, [6] Xue, M., Hitt, L.M., and Chen, P., Determinants and Outcomes of Internet Banking Adoption, Management science (57:2), 2011, [7] Landman, M., Managing smart phone security risks, Proceedings of 2010 Information Security Curriculum Development Conference, Kennesaw, Georgia, 2010, [8] Pikkarainen, T., et al., Consumer acceptance of online banking: an extension of the technology acceptance model, Internet research (14:3), 2004, [9] Lee, M., Factors influencing the adoption of Internet banking: An integration of TAM and TPB with perceived risk and perceived benefit, Electronic Commerce Research and Applications (8:3), 2009, [10] Grabner-Kräuter, S. and Faullant, R., Consumer acceptance of internet banking: the influence of internet trust, International Journal of Bank Marketing (26:7), 2008, [11] Einwiller, S. and Will, M., The role of reputation to engender trust in electronic markets, Proceedings of the 5th International Conference on Corporate Reputation, Identity, and Competitiveness, Paris, France, [12] Cheung, C.M.K. and Lee, M.K.O., Understanding consumer trust in Internet shopping: A multidisciplinary approach, Journal of the American Society for Information Science and Technology (57:4), 2006, [13] Littler, D. and Melanthiou, D., Consumer perceptions of risk and uncertainty and the implications for behaviour towards innovative retail services: The case of Internet Banking, Journal of Retailing and Consumer Services (13:6), 2006, [14] Rotchanakitumnuai, S. and Speece, M., Barriers to Internet banking adoption: a qualitative study among corporate customers in Thailand, International Journal of Bank Marketing (21:6), 2003, [15] Kim, C., Mirusmonov, M., and Lee, I., An empirical examination of factors influencing the intention to use mobile payment, Computers in Human Behavior (26:3), 2010, [16] Schneier, B., Secrets and lies: digital security in a networked world, Wiley, Indianapolis, Indiana, [17] Chang, H. and Abdul Hamid, M., An empirical investigation of Internet banking in Taiwan, Global Journal of Business Research (4:2), 2010, [18] Chang, H. and Chen, S., Consumer perception of interface quality, security, and loyalty in electronic commerce, Information & Management (46:7), 2009, [19] Kobsa, A., Tailoring Privacy to Users Needs, Lecture Notes in Coputer Science (21:9), 2001, [20] Yiu, C.S., Grant, K., and Edgar, D., Factors affecting the adoption of Internet Banking in Hong Kong implications for the banking sector, International Journal of Information Management (27:5), 2007, [21] Ajzen, I. and Fishbein, M., Attitudes and the attitudebehavior relation: Reasoned and automatic processes, European review of social psychology (11:1), 2000, [22] Davis, F.D., Bagozzi, R.P., and Warshaw, P.R., User acceptance of computer technology: a comparison of two theoretical models, Management science 1989, [23] Taylor, S. and Todd, P.A., Understanding information technology usage: A test of competing models, Information Systems Research (6:2), 1995, [24] Cheng, T., Lam, D.Y.C., and Yeung, A.C.L., Adoption of internet banking: an empirical study in Hong Kong, Decision Support Systems (42:3), 2006, [25] Wang, Y.S., et al., Determinants of user acceptance of Internet banking: an empirical study, International Journal of Service Industry Management (14:5), 2003, [26] Chang, H.H. and Abdul Hamid, M.R.B., An empirical investigation of Internet banking in Taiwan, Global Journal of Business Research (4:2), 2010, [27] Gu, J.C., Lee, S.C., and Suh, Y.H., Determinants of behavioral intention to mobile banking, Expert Systems with Applications (36:9), 2009, [28] Moon, J.W. and Kim, Y.G., Extending the TAM for a World- Wide-Web context, Information & Management (38:4), 2001, [29] Lin, H.F., An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledgebased trust, International Journal of Information Management (31:3), 2011, [30] Baron, R.M. and Kenny, D.A., The moderator mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, Journal of personality and social psychology (51:6), 1986, [31] Kerlinger, F. and Lee, H., Foundations of behavioral research, 4th ed, Cambridge University Press, Cambridge, England, [32] Ringle, C.M., Wende, S., and Will, A., SmartPLS (Opensource software), 2.0 (beta) edition ed, Hamburg, Germany, [33] Hair, J., et al., Multivariate Data Analysis, 6th ed, Pearson Prentice Hall, Saddle River, NJ, [34] Fornell, C. and Bookstein, F.L., Two structural equation models: LISREL and PLS applied to consumer exit-voice theory, Journal of Marketing Research (19:1), 1982, [35] Chin, W.W., Peterson, R.A., and Brown, S.P., Structural equation modeling in marketing: some practical reminders, The Journal of Marketing Theory and Practice (16:4), 2008, Journal of Computer Information Systems Spring 2014

9 [36] Fornell, C. and Larcker, D.F., Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing research (48:1), 1981, [37] Gefen, D., Karahanna, E., and Straub, D.W., Inexperience and experience with online stores: The importance of TAM and trust, Engineering Management, IEEE Transactions on (50:3), 2003, [38] Bagozzi, R.P. and Yi, Y., On the evaluation of structural equation models, Journal of the Academy of Marketing Science (16:1), 1988, [39] Aiken, L.S., West, S.G., and Reno, R.R., Multiple regression: Testing and interpreting interactions, Sage Publications, [40] Cohen, J., Statistical power analysis for the behavioral sciences, 2nd ed, Lawrence Erlbaum Associates, Hillsdale, NJ, [41] Yousafzai, S.Y., Pallister, J.G., and Foxall, G.R., A proposed model of e-trust for electronic banking, Technovation (23:11), 2003, [42] Bauer, R.A., Consumer behavior as risk taking. In dynamic marketing for a changing world., American Marketing Association, Chicago, Spring 2014 Journal of Computer Information Systems 9