Digital Payment as Everyday Consumption: Consumer Behavior and Generational Differences in QRIS Usage

Anisya  Rahmelia; Mimin Aminah; Megawati Simanjuntak

doi:10.29244/jcfcs.5.1.18-36

Authors

Anisya Rahmelia Faculty of Economics and Management, IPB University
Mimin Aminah Faculty of Economics and Management, IPB University
Megawati Simanjuntak Department of Family and Consumer Sciences, Faculty of Social and Human Ecology, IPB University

DOI:

https://doi.org/10.29244/jcfcs.5.1.18-36

Keywords:

consumer behavior, digital payment, QRIS, Generation X, generation Z, everyday consumption

Abstract

This study aims to describe consumer behavior in the use of Quick Response Code Indonesian Standard (QRIS) as part of everyday digital consumption among Generation X and Generation Z. A quantitative survey approach was employed, involving 175 QRIS users in the Greater Jakarta area. Data were analyzed using descriptive statistics to examine respondent characteristics, usage patterns, and perceptions related to ease of use, loyalty programs, cashless society orientation, perceived risk, trust, satisfaction, and loyalty. The results indicate that QRIS has become embedded in daily consumption activities, with higher usage intensity observed among Generation Z. Overall, respondents report positive perceptions of ease of use and loyalty programs, while perceived risk remains at a moderate level. Differences in behavioral tendencies are observed across generations. Generation X tends to emphasize trust in shaping satisfaction, whereas Generation Z places greater importance on ease of use. Despite these differences, satisfaction is consistently associated with continued usage behavior in both groups. These findings highlight variations in consumer behavior across generations and underscore the importance of consumer education and protection in supporting the effective use of digital payment systems.

References

Andriyani, F., Siagian, B., Suciati, P., & Citra, A. (2025). QRIS Adoption and Utilization: Examining Gen Z’s Digital Payment Behavior Among Indonesian Vocational Students. Jurnal Vokasi Indonesia, 13(1), 7. https://doi.org/10.7454/jvi.v13i1.1233

An, T., Xiao, J. J., Porto, N., & Cruz, L. (2024). Mobile payment, financial behavior and financial anxiety: a multi-group structural equation modeling study. International Journal of Bank Marketing, 43(3), 549–568. https://doi.org/10.1108/IJBM-07-2024-0402

Aspandi, A., Mima, N. L. F., & Rahman, E. S. (2025). Scan, Pay, Eat: A Descriptive Qualitative Study of Generation Z Consumer Behavior and Street Food Vendor Response to QRIS-Based Digital Payments in Indonesia. Journal of Mathematics Instruction, Social Research and Opinion, 4(4), 1025–1034. https://doi.org/10.58421/misro.v4i4.622

Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model Author(s): Anol Bhattacherjee Source. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921

Bhattacherjee, A., Perols, J., & Sanford, C. (2008). Information Technology Continuance: A Theoretic Extension and Empirical Test. Journal of Computer Information Systems, 49(1), 17–26. https://doi.org/10.1080/08874417.2008.11645302

Creswell, J. W., & Creswell, J. D. (2017). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th Edition). SAGE Publications.

Cummins, S., W. Peltier, J., A. Schibrowsky, J., & Nill, A. (2014). Consumer behavior in the online context. Journal of Research in Interactive Marketing, 8(3), 169–202. https://doi.org/10.1108/JRIM-04-2013-0019

Dangelico, R. M., Ceccarelli, G., & Fraccascia, L. (2024). Consumer behavioral intention toward sustainable biscuits: An extension of the theory of planned behavior with product familiarity and perceived value. Business Strategy and the Environment, 33(6), 5681–5702. https://doi.org/10.1002/bse.3774

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Dorce, L. C., da Silva, M. C., Mauad, J. R. C., de Faria Domingues, C. H., & Borges, J. A. R. (2021). Extending the theory of planned behavior to understand consumer purchase behavior for organic vegetables in Brazil: The role of perceived health benefits, perceived sustainability benefits and perceived price. Food Quality and Preference, 91, 104191. https://doi.org/10.1016/j.foodqual.2021.104191

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11

Farzin, M., Sadeghi, M., Yahyayi Kharkeshi, F., Ruholahpur, H., & Fattahi, M. (2021). Extending UTAUT2 in M-banking adoption and actual use behavior: Does WOM communication matter? Asian Journal of Economics and Banking, 5(2), 136–157. https://doi.org/10.1108/ajeb-10-2020-0085

Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. The Bookwatch, NA-NA.

Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage.

Ho, J. C., Wu, C.-G., Lee, C.-S., & Pham, T.-T. T. (2020). Factors affecting the behavioral intention to adopt mobile banking: An international comparison. Technology in Society, 63, 101360. https://doi.org/10.1016/j.techsoc.2020.101360

Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646–664. https://doi.org/10.1108/IJBM-03-2018-0072

Koch, J., Frommeyer, B., & Schewe, G. (2020). Online shopping motives during the COVID-19 pandemic—lessons from the crisis. Sustainability, 12(24), 10247. https://doi.org/10.3390/su122410247

Liébana-Cabanillas, F., Marinkovic, V., Ramos de Luna, I., & Kalinic, Z. (2018). Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach. Technological Forecasting and Social Change, 129, 117–130. https://doi.org/10.1016/j.techfore.2017.12.015

Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance1. Management Information Systems Quarterly, 31(4), 705–737. https://doi.org/10.2307/25148817

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134. https://doi.org/10.1080/10864415.2003.11044275

Putri, J. G. E., & Sutrisno, J. (2025). Determinants of QRIS Adoption Among Generation Z Consumers: The Role of Financial Literacy and Behavioral Control. Indonesian Journal of Digital Business, 5(4), 1609–1621. https://doi.org/10.17509/ijdb.v5i4.96342

Rachmawati, Y. N., Iksanty, I. D., & Fadilah, D. H. (2025). QRIS Adoption In The Millenial Generation: Approach Unified Theory Of Acceptance And Use Of Technology (UTAUT) Theory. International Joint Conference on Arts and Humanities 2024 (IJCAH 2024), 1610–1624. https://doi.org/10.2991/978-2-38476-317-7_153

Rose, S., Hair, N., & Clark, M. (2011). Online Customer Experience: A Review of the Business-to-Consumer Online Purchase Context. International Journal of Management Reviews, 13(1), 24–39. https://doi.org/10.1111/j.1468-2370.2010.00280.x

Sekaran, U., & Bougie, R. (2020). Research Methods for Business: A Skill-Building Approach (8th ed.). Wiley.

Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling Consumers’ Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust. Psychology & Marketing, 32(8), 860–873. https://doi.org/10.1002/mar.20823

Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243–257. https://doi.org/10.1007/s10796-018-9864-5

Venkatesh, V., & Davis, F. D. (2000). 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

Wicaksono, I. (2025). Trust and Satisfaction: The Hidden Drivers of QRIS Adoption and Long-Term Use Among Generation X in Indonesia. Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE), 8(3). https://doi.org/10.31538/iijse.v8i3.7587