The Effect of Technology Acceptance Model (TAM) on Trust toward GrabFood Dine-Out Deals Feature from Generation Z Perspective in Indonesia

Authors

  • Maria Siregar Universitas Lampung

DOI:

https://doi.org/10.66016/jmtm.v1i2.18

Keywords:

Technology Acceptance Model, Trust, Generation Z, GrabFood, GrabFood Dine-Out Deals

Abstract

Digital transformation has significantly reshaped consumer behavior, particularly among Generation Z, a cohort that is highly adaptive to technology yet strongly concerned with issues of security and data privacy. One innovation within the digital food service sector is the GrabFood Dine-Out Deals (DOD) feature, which integrates online voucher purchases with offline dining experiences at partner restaurants. This study aims to analyze the effect of Technology Acceptance Model (TAM) variables—Perceived Usefulness, Perceived Ease of Use, Perceived Security Risk, and Perceived Privacy Risk—on Trust toward the GrabFood Dine-Out Deals feature from the perspective of Generation Z in Indonesia. This research employed a quantitative approach using a survey method involving 300 Generation Z respondents aged 17–28 years. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS software. The results indicate that Perceived Ease of Use, Perceived Security Risk, and Perceived Privacy Risk have significant effects on Trust, while Perceived Usefulness shows a relatively weaker influence. These findings suggest that Generation Z prioritizes ease of use, security, and privacy protection over functional benefits when developing trust in digital dine-in promotional technologies.

References

American Psychological Association. (n.d.). APA divisions. https://www.apa.org/about/division/

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.),

Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology.

MIS Quarterly, 13, 319–340. https://doi.org/10.2307/249008

Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59, 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3

Gupta, S., Dhiman, N., & Priyadarshi, P. (2024). Privacy concerns and trust in digital platforms: Evidence from mobile service users. Journal of Consumer Behaviour, 23, 45–60.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.

Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce.

Decision Support Systems, 44, 544–564. https://doi.org/10.1016/j.dss.2007.07.001

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7, 101–134.

Putka, D. J., & Sackett, P. R. (2010). Reliability and validity. In J. L. Farr & N. T. Tippins (Eds.), Handbook of employee selection (pp. 9–49). Routledge.

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

Wang, Y., & Yi, J. (2022). Trust and perceived risk in mobile service adoption: Evidence from digital platform users.

Telematics and Informatics, 68, 101789. https://doi.org/10.1016/j.tele.2022.101789

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Published

2025-12-15

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