Analysis of selected technology acceptance model constructs and their impact on user behavior
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DOIhttp://dx.doi.org/10.21511/im.18(3).2022.07
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Article InfoVolume 18 2022, Issue #3, pp. 72-83
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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.
- Keywords
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JEL Classification (Paper profile tab)M15, M31, L86
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References50
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Tables7
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Figures5
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- Figure 1. Research model
- Figure 2. Information quality factor
- Figure 3. Availability of information factor
- Figure 4. Perceived simplicity factor
- Figure 5. Final model of user experience
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- Table 1. Findability factor of the website
- Table 2. Navigation factor of the website
- Table 3. Access and usability factor of the website
- Table 4. Perceived usefulness factor
- Table 5. Attitude factor to use the selected website
- Table 6. Website content quality factor
- Table 7. Statistical evaluation
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- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
- Akhter, A., Karim, Md. M., Jannat, S., & Islam, K. M. A. (2022). Determining factors of intention to adopt internet banking services: A study on commercial bank users in Bangladesh. Banks and Bank Systems, 17(1), 125-136.
- Bačík, R., Gavurova, B., Fedorko, I., & Fedorko, R. (2021). Website quality factor as a multidimensional construct and its impact on the use of e-banking. Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, 9(1), 542-557.
- Balcerzak, P. A., & Pietrzak, B. M. (2017). Digital Economy in Visegrad Countries. Multiple-criteria Decision Analysis at Regional Level in The Years 2012 and 2015. Journal of Competitiveness, 9(2), 5-18.
- Bartok, O. (2018). The Use of CSR in E-Commerce as a Way to Compete. Journal of Competitiveness, 10(4), 5-20.
- Booth, P. (1989). An Introduction to Human-Computer Interaction (Psychology Revivals). London: Psychology Press.
- Castaneda, J. A., Munoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384-396.
- Civelek, M., Ključnikov, A., Kmeco, Ľ., & Hamarneh, I. (2021). The Influences of the Usage of Marketing Communication Tools on Innovations of the Functional Areas of Businesses: Perspectives for the Mining Industry. Acta Montanistica Slovaca, 26(4), 685-697.
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
- Dentzel, Z. (2014). How the Internet Has Changed Everyday Life. In Change: 19 Key Essays on How the Internet Is Changing Our Lives.
- Dix, A. (2017). Human-computer interaction, foundations and new paradigms. Journal of Visual Languages & Computing, 42, 122-134.
- Dumas, F. J., & Janice, C. R. (1993). A Practical Guide to Usability Testing. USA: Westport: Greenwood Publishing Group Inc.
- Fard, А. (2022). 15 Steps to Understand & Influence User Behavior: A Deep Dive. Adamfard.
- Fischer, G. (2001). User Modeling in Human-Computer Interaction. User Modeling and User-Adapted Interaction, 11(1-2), 65-86.
- Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
- Fusilier, M., Durlabhji, S., & Cucchi, A. (2008). An Investigation of the Integrated Model of User Technology Acceptance: Internet User Samples in Four Countries. Journal of Educational Computing Research, 38(2), 155-182.
- Garrett, J. J. (2011). The Elements of User Experience: User-Centered Design for the Web and Beyond (2nd ed.). Berkeley, CA: New Riders.
- Gavurova, B., Bacik, R., Fedorko, R., & Nastisin, L. (2018). The customer’s brand experience in the light of selected performance indicators in the social media environment. Journal of Competitiveness, 10(2), 72-84.
- Gounaris, S., Koritos, C., & Vassilikopoulou, K. (2010). Person-place congruency in the internet banking context. Journal of Business Research, 63(9-10), 943-949.
- Graham, E. (2018). The Republic of Games: Textual Culture between Old Books and New Media. McGill-Queen’s Press.
- Hassenzahl, M. (2011). User Experience and Experience Design. In Encyclopedia of Human-Computer Interaction. The Interaction Design Foundation.
- Hassenzhal, M. (2007). To do or not to do: differences in user experience and retrospective judgments depending on the presence or absence of instrumental goals. Interacting with computers, 19(4), 429-437.
- Hotjar team. (2021). How tracking user behavior on your website can improve customer experience.
- Huculová, E. (2018). Porovnanie vybraných metodologických prístupov HTA na národnej úrovni a na úrovni nemocníc. Prešov: eXclusive marketing, 6(4), 53-59.
- Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information & Management, 48(1), 1-8.
- Ključnikov, A., Civelek, M., Vavrečka, V., & Nétek, V. (2021). The Differences in the Usage of Social Media between SMEs operating in the Iron and Mining Industries. Acta Montanistica Slovaca, 26(2), 185-194.
- Koufaris, M. (2002). Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior. New York: Zicklin School of Business.
- Kraft, C. (2012). User Experience Innovation. Centered Design that Works. Apress Berkeley, CA.
- Krug, S. (2006). Don’t Make Me Think! A common sense approach to web usability. California: New Riders Publishing.
- Kwon, O. B., Kim, C. B., & Lee, E. J. (2002). Impact of website information design factors on consumer ratings of web-based auction sites. Behaviour & Information Technology, 21(6), 387-402.
- Lamprecht, E. (2017). The Difference Between UX and UI Design – A Layman’s Guide.
- Law, E., Roto, V., Hassenzahl, M., Vermeeren, A., & Kort, J. (2009). Understanding, scoping and defining user experience: a survey approach. CHI 2009 – User Experience. Boston, MA, USA.
- Lee, M.-C. (2009). 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), 130-141.
- Liao, Z., & Cheung, M. T. (2002). Internet-Based e-Banking and Consumer Attitudes: An empirical study. Information & Management, 39(4), 283-295.
- Marcus, A. (2014). Design, User Experience, and Usability: Theories, Methods, and Tools for Designing the User Experience. Third International Conference DUXU 2014. Heraklion, Crete, Greece.
- Moss, G., Gunn, R., & Heller, J. (2006). Some men like it black, some women like it pink: Consumer implications of differences in male and female website design. Journal of Consumer Behaviour, 5(4), 328-341.
- Muftiasa, A., Sari, D. P., Wibowo, L. A., & Rahayu, A. (2022). Factors influencing decisions of satellite office users in the new normal era: Evidence from Indonesia. Problems and Perspectives in Management, 20(2), 260-268.
- Rahi, S., & Abd.Ghani, M. (2019). Investigating the role of UTAUT and e-service quality in internet banking adoption setting. The TQM Journal, 31(3), 491-506.
- Rouse, W. B. (2005). A theory of enterprise transformation. Systems Engineering, 8(4), 279-295.
- Simionescu, M. (2021). Nowcasting Regional Unemployment Rate in Denmark Using Google Trends to Develop Mining Sector. Acta Montanistica Slovaca, 26(3), 498-511.
- Teo, M., & Tan, T. (2000). Factors influencing the adoption of internet banking. Journal of the Association of Information Systems, 1(1).
- Thakur, B. (2009). Perspectives In Resource Management In Developing Countries (volume IV: Land Appraisal And Development). Concept Publishing Company.
- Thongpapanl, N., & Ashraf, A. (2011). Enhancing online performance through website content and personalization. Journal of Computer Information Systems, 52(1), 3-13.
- Van Schaik, P., & Ling, J. (2008). Modelling user experience with web sites: Usability, hedonic value, beauty and goodness. Interacting with Computers, 20(3), 419-432.
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal Field Studies. Management Science, 46(2), 186-204.
- Venkatesh, V., Davis, G. B., Davis, F. D., & Morris, M. G. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
- Vila, N., & Kuster, I. (2011). Consumer feelings and behaviours towards well designed websites. Information & Management, 48(4-5), 166-177.
- Visinescu, L. L., Sidorova, A., Jones, M. C., & Prybutok, V. R. (2015). The influence of website dimensionality on customer experiences, perceptions and behavioral intentions: An exploration of 2D vs. 3D web design. Information & Management, 52(1), 1-17.
- Wright, P., & Blythe, M. (2007). User experience research as an interdiscipline: Towards a UX Manifesto. In E. Law, A. Vermeeren, M. Hassenzahl, & M. Blythe (Eds.), Towards a UX Manifesto (pp. 65-70). Lancaster, UK.
- Yuen, A. H. K., & Will, W. K. M. (2008). Exploring teacher acceptance of e-learning technology. Asia-Pacific Journal of Teacher Education, 36(3), 229-243.