- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
For financial institutions mobile banking has represented a breakthrough in terms of remote banking services. However, many customers remain uncertain due to its security. This study develops a technology acceptance model that integrates the innovation diffusion theory, perceived risk and trust in the classic TAM model in order to shed light on what factors determine user acceptance of mobile banking applications. The participants had to examine a mobile application of the largest European bank. In the proposed model, an approach to external influences was included, theoretically and originally stated by Davis et al. (1989). The proposed model was empirically tested using data collected from an online survey applying structural equation modeling (SEM). The results obtained in this study demonstrate how attitude determine mainly the intended use of mobile apps, discarding usefulness and risk as factors that directly improve its use. Finally, the study shows the main management implications and identifies certain strategies to reinforce this new business in the context of new technological advances.
Limitations and future lines of research
This article presents a series of limitations that should be debated and that generate new lines of research for the future. Firstly, limitations were found in the selected sample; participating users in the sample limited the interaction with the tool to the viewing of a video, through which they then answered questions in a survey. In this sense, our research has focused on the measurement of an intention, not on measuring actual behavior. Consequently, our work could be extended in the future with real experience with use of the real tool, making pertinent comparisons between intention and behavior, assessing the possible prior expectations of users and the effects on them once the user has actually interacted with the mobile application. Furthermore, methodological limitations were also found when conducting research, since the total sample was fairly small. In this regard, we have to remain cautious when generalizing the results of this research since it uses a small-sized sample In order to overcome this limitation, the sample should be extended and/or approaching other modeling tools based on covariance which are more appropriate for samples of this size, such as the partial least square (PLS) modeling technique. Therefore, in future studies, it would be advisable to try to improve the representativeness and thus, the greatest potential for generalization of results from a larger sample nationwide.