Behavioral intention among gen z an analysis of digital banking adaptation factors in Jabodetabek

Authors

  • Diva Akiela Fahlerie Zea Fakultas Ekonomi dan Bisnis, Universitas Indonesia, Indonesia
  • Rizal Edy Halim Fakultas Ekonomi dan Bisnis, Universitas Indonesia, Indonesia

DOI:

https://doi.org/10.61511/jane.v1i2.2024.1117

Keywords:

performance expectancy, effort expectancy, facilitating conditions, behavioral intention, digital banking adoption

Abstract

Background: Many traditional banking arrangements have changed as a result of the financial sector's new technological revolution. One method the company seeks to provide consumers with more value is by delivering digital transformations that are especially designed to match their needs and preferences and that use mobile devices such as cell phones to access banking services. This study aims to examine the effect of performance expectancy and effort expectancy to behavioral intention of adopting digital banking. Method: This study collects data from 243 respondents aged 17 to 27 who live in Jabodetabek area, had experienced to do offline transaction, and have at least one digital bank account. Partial Least Squares Structural Equation Modeling (PLS-SEM) was then used to process the data collected. Findings: The findings of this study shows that shows that effort expectancy has a positive effect on behavioral intention on using digital banking. Meanwhile, performance expectations do not have a significant positive effect on behavioral intention. Conclusion: The results of the research may be used to develop a strategic plan and put recommendations into practice to better understand user intentions to use digital banks.

References

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125-138. https://doi.org/10.1016/j.jretconser.2017.08.026

Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118-143. https://doi.org/10.1287/isre.6.2.118

Cziesla, T. (2014). A literature review on digital transformation in the financial service industry. In Proceedings of the Bled eConference, Bled, Slovenia, 1–5 June. https://domino.fov.um.si/proceedings.nsf/Proceedings/9E0B8C345E951A62C1257CF5002CCE7C/$File/03_Cziesla.pdf

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1002. https://doi.org/10.1287/mnsc.35.8.982

Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30. https://doi.org/10.1080/07421222.2003.11045748

Deng, X., Huang, Z., & Cheng, X. (2019). FinTech and sustainable development: Evidence from China based on P2P data. Sustainability, 11, 6434. https://doi.org/10.3390/su11226434

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2010). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12. https://doi.org/10.1016/j.lrp.2013.01.001

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling. SAGE Publications, 46, 184–185.

Hilal, A., & Varela-Neira, C. (2022). Understanding consumer adoption of mobile banking: Extending the UTAUT2 model with proactive personality. Sustainability, 14(22), 14708. https://doi.org/10.3390/su142214708

Malhotra, N., & Birks, D. F. (2007). Marketing research: An applied approach. London: Prentice Hall.

Mckinsey & Company. (2021). Joining the next generation of digital banks in Asia. Retrieved December 3, 2021, from https://www.mckinsey.com/industries/financial-services/our-insights/joining-the-next-generation-of-digital-banks-in-asia

Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222. https://doi.org/10.1287/isre.2.3.192

PwC. (2018). Digital banking in Indonesia by Pricewaterhouse Coopers. Retrieved June 10, 2020, from https://www.pwc.com/id/en/publications/assets/financialservices/digital-banking-survey-2018-pwcid.pdf

Sardana, V., & Singhania, S. (2018). Digital technology in the realm of banking: A review of literature. International Journal of Research in Finance and Management, 1(2), 28–32. https://www.researchgate.net/publication/329514279

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124-143.

Vally, S., & Shankar, C. (n.d.). Factors that affect the digital banking adoption in Hyderabad city—UTAUT model approach. European Journal of Molecular & Clinical Medicine. https://ejmcm.com/article_1781_b9de29fb5de9214a848ea77c6bcca226.pdf

Venkatesh, V. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology 1. MIS Quarterly, 36(1), 157-178. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2002388

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003

Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26, 760-767. https://doi.org/10.1016/j.chb.2010.01.013

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Published

2024-08-31

How to Cite

Zea, D. A. F., & Halim, R. E. (2024). Behavioral intention among gen z an analysis of digital banking adaptation factors in Jabodetabek. Journal of Entrepreneurial Economic, 1(2), 118–128. https://doi.org/10.61511/jane.v1i2.2024.1117

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