Igor Fedorko
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Effort expectancy and social influence factors as main determinants of performance expectancy using electronic banking
Banks and Bank Systems Volume 16, 2021 Issue #2 pp. 27-37
Views: 1389 Downloads: 478 TO CITE АНОТАЦІЯThis study is aimed at determining the effect of expected effort and social influence factors on expected performance when using internet banking. The study adapts the constructs and definitions from the UTAUT model in the context of the adaptation of online banking technology. With regard to the nature of the variables analyzed, the following statistical tests and methods were used: calculation of average values using descriptive statistics; multiple linear regression analysis – to interpret associations between quantitative variables. Banks, as well as users of these banking services in the online environment, are the subject of research. The survey sample consists of 454 men and women and reflects the profile of online consumers across different countries of the European Union. The results of this study show the impact of the social influence construct on the respondents’ behavior when using electronic banking. The expected effort factor in the study significantly affects the expected performance factor, which can be characterized by original research, which showed that the effect of perceived ease of use on behavioral intent and use is incompatible with the degree of system complexity.
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Analysis of selected technology acceptance model constructs and their impact on user behavior
Nowadays, when the Internet is a regular part of people’s life in competitive conditions, it is essential to emphasize user feelings about the products, especially in the context of web pages. The study aims to clarify the significance of selected Technology Acceptance Model elements concerning user behavior in the web area. The study applied an exploratory method using an anonymous questionnaire in electronic form (Likert scale). This study’s respondents were website users, visitors, or internet users within the EU. Adequacy of the research sample was measured using Cronbach’s alpha and Kaiser-Meyer-Olkin (226 respondents). This paper proposed factors that impact user behavior. The quality of the website content factor contains two other variables: the quality of information (QI-Q5) and its availability (AI-A3). The design quality factor is composed of four elements: appearance (AP1-AP5), website findability (F1-F4), website navigation (N1-N3), and website access and usability (AU1-AU4). In addition, the paper selected the perceived usefulness factor (USEF1), the factor of perceived ease of use (EOU1-EOU3), and the attitude to use the website (ATT1). This study calculated the values of the Pearson correlation coefficients and used the lower triangle method to obtain the resulting coefficient values. The analysis results show that the simplicity of use and page orientation does not affect the actual use of the website. The study’s outcome is a model that identifies the impact of individual factors on user behavior in the context of user experience.
Acknowledgment
This paper was supported by the Slovak Research and Development Agency under Contract no. APVV-21-0188. This paper was also supported by VEGA 1/0488/22.