CASHLESS PAYMENT ADOPTION AND GENERATION Z CONSUMPTION BEHAVIOUR

THE ROLES OF IMPULSIVE BEHAVIOUR AND SOCIAL INFLUENCE IN PALEMBANG, INDONESIA

Authors

  • Faradila Meirisa Universitas Multi Data Palembang
  • Devita Maharani Universitas Multi Data Palembang

DOI:

https://doi.org/10.61397/mfc.v4i2.609

Keywords:

cashless payments; Generation Z; impulsive behaviour; social influence; consumption behaviour

Abstract

The rapid diffusion of cashless payment technologies has changed the way consumers complete everyday transactions. This study examines the relationships among cashless payment adoption, impulsive behaviour, social influence, and consumption behaviour among Generation Z in Palembang, Indonesia. A quantitative cross-sectional survey was conducted with 450 respondents, and the proposed relationships were analysed using partial least squares structural equation modelling (PLS-SEM). The reported measurement results indicate that the four constructs meet the study’s stated thresholds for internal consistency and convergent validity; the reported heterotrait–monotrait ratios are also below .90. In the structural model, cashless payment adoption is positively associated with impulsive behaviour (β = .608, t = 18.085, p < .001), social influence (β = .457, t = 8.438, p < .001), and consumption behaviour (β = .344, t = 5.241, p < .001). Impulsive behaviour is positively associated with social influence (β = .425, t = 7.462, p < .001) and consumption behaviour (β = .257, t = 3.008, p = .003). The path from social influence to consumption behaviour is positive but does not reach the conventional .05 significance level (β = .189, t = 1.906, p = .057). The findings suggest that the association between cashless payment adoption and consumption behaviour is more consistently reflected in the psychological pathway represented by impulsive behaviour than in the direct social-influence pathway. Because indirect effects were not reported, the study does not establish mediation. The results should be interpreted in light of the cross-sectional design and the need to reconcile inconsistencies in the source demographic narrative.

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Ajzen, I. (2005). Attitudes, personality and behavior (2nd ed.). Open University Press.

Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79–95. https://doi.org/10.1007/s11747-019-00695-1

Arli, D., Tan, L. P., Tjiptono, F., & Yang, L. (2018). Exploring consumers’ purchase intention toward green products in an emerging market: The role of consumers’ perceived readiness. International Journal of Consumer Studies, 42(4), 389–401. https://doi.org/10.1111/ijcs.12432

Badgaiyan, A. J., & Verma, A. (2015). Does urge to buy impulsively differ from impulsive buying behaviour? Assessing the impact of situational factors. Journal of Retailing and Consumer Services, 22, 145–157. https://doi.org/10.1016/j.jretconser.2014.10.002

Beatty, S. E., & Ferrell, M. E. (1998). Impulse buying: Modeling its precursors. Journal of Retailing, 74(2), 169–191. https://doi.org/10.1016/S0022-4359(99)80092-X

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921

Bhuiyan, M. R. I., Akter, M. S., & Islam, S. (2024). How does digital payment transform society as a cashless society? An empirical study in the developing economy. Journal of Science and Technology Policy Management, 16(4), 756–774. https://doi.org/10.1108/JSTPM-10-2023-0170

Boden, J., Maier, E., & Wilken, R. (2020). The effect of credit card versus mobile payment on convenience and consumers’ willingness to pay. Journal of Retailing and Consumer Services, 52, Article 101910. https://doi.org/10.1016/j.jretconser.2019.101910

Broekhoff, M.-C., & van der Cruijsen, C. (2024). Less cash, more splash? A meta-analysis on the cashless effect. Journal of Retailing, 100(3), 382–403. https://doi.org/10.1016/j.jretai.2024.05.003

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.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

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

Dholakia, U. M. (2000). Temptation and resistance: An integrated model of consumption impulse formation. Psychology & Marketing, 17(11), 955–982. https://doi.org/10.1002/1520-6793(200011)17:11%3C955::AID-MAR2%3E3.0.CO;2-J

Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online celebrities’ Instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behavior, 68, 1–7. https://doi.org/10.1016/j.chb.2016.11.009

Feinberg, R. A. (1986). Credit cards as spending facilitating stimuli: A conditioning interpretation. Journal of Consumer Research, 13(3), 348–356. https://doi.org/10.1086/209074

Finstad, K. (2010). Response interpolation and scale sensitivity: Evidence against 5-point scales. Journal of Usability Studies, 5(3), 104–110.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

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., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2018). Advanced issues in partial least squares structural equation modeling. Sage.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8

Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565–580. https://doi.org/10.1007/s00180-012-0317-1

Iyer, G. R., Blut, M., Xiao, S. H., & Grewal, D. (2020). Impulse buying: A meta-analytic review. Journal of the Academy of Marketing Science, 48(3), 384–404. https://doi.org/10.1007/s11747-019-00670-w

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185

Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223. https://doi.org/10.1287/isre.13.2.205.83

Liébana-Cabanillas, F., Singh, D., Kalinić, Z., & Carvajal-Trujillo, E. (2021). Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: A multi-analytical approach. Information Technology and Management, 22, 133–161. https://doi.org/10.1007/s10799-021-00328-6

MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Quarterly, 35(2), 293–334. https://doi.org/10.2307/23044045

Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61, 404–414. https://doi.org/10.1016/j.chb.2016.03.030

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Prelec, D., & Loewenstein, G. (1998). The red and the black: Mental accounting of savings and debt. Marketing Science, 17(1), 4–28. https://doi.org/10.1287/mksc.17.1.4

Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617–1643. https://doi.org/10.1080/09585192.2017.1416655

Ringle, C. M., Wende, S., & Becker, J.-M. (2022). SmartPLS 4. SmartPLS. https://www.smartpls.com

Rook, D. W. (1987). The buying impulse. Journal of Consumer Research, 14(2), 189–199. https://doi.org/10.1086/209105

Rook, D. W., & Fisher, R. J. (1995). Normative influences on impulsive buying behavior. Journal of Consumer Research, 22(3), 305–313. https://doi.org/10.1086/209452

Runnemark, E., Hedman, J., & Xiao, X. (2015). Do consumers pay more using debit cards than cash? An experiment. Electronic Commerce Research and Applications, 14(5), 285–291. https://doi.org/10.1016/j.elerap.2015.03.002

Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology & Marketing, 39(5), 1035–1064. https://doi.org/10.1002/mar.21640

See-To, E. W. K., & Ngai, E. W. T. (2019). An empirical study of payment technologies, the psychology of consumption, and spending behavior in a retailing context. Information & Management, 56(3), 329–342. https://doi.org/10.1016/j.im.2018.07.007

Slade, E., Williams, M., & Dwivedi, Y. K. (2014). Devising a research model to examine adoption of mobile payments: An extension of UTAUT2. The Marketing Review, 14(3), 310–335. https://doi.org/10.1362/146934714X14024779062036

Slade, E., Williams, M., Dwivedi, Y. K., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209–223. https://doi.org/10.1080/0965254X.2014.914075

Soman, D. (2001). Effects of payment mechanism on spending behavior: The role of rehearsal and immediacy of payments. Journal of Consumer Research, 27(4), 460–474. https://doi.org/10.1086/319621

Thaler, R. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199–214. https://doi.org/10.1287/mksc.4.3.199

Thomas, M., Desai, K. K., & Seenivasan, S. (2011). How credit card payments increase unhealthy food purchases: Visceral regulation of vices. Journal of Consumer Research, 38(1), 126–139. https://doi.org/10.1086/657331

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

Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022

Verplanken, B., & Herabadi, A. (2001). Individual differences in impulse buying tendency: Feeling and no thinking. European Journal of Personality, 15(S1), S71–S83. https://doi.org/10.1002/per.423

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

Zhang, K. Z. K., Benyoucef, M., & Zhao, S. J. (2016). Building brand loyalty in social commerce: The case of brand microblogs. Electronic Commerce Research and Applications, 15, 14–25. https://doi.org/10.1016/j.elerap.2015.12.001

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Published

2026-11-06

How to Cite

Meirisa, F., & Maharani, D. (2026). CASHLESS PAYMENT ADOPTION AND GENERATION Z CONSUMPTION BEHAVIOUR: THE ROLES OF IMPULSIVE BEHAVIOUR AND SOCIAL INFLUENCE IN PALEMBANG, INDONESIA. Multifinance, 4(2), 66–78. https://doi.org/10.61397/mfc.v4i2.609