• Disha Sharma Amity Business School, Amity University Chhattisgarh, India
  • Yashwant Kumar Vaid Information Technology, Manager- Bigmint Technologies Private Limited, India


M-Payment, UTAUT2, Consumer adoption, Perceived credibility, millennials, Generation Z


M-Payment seems to be one of the most preferable services to adopt by the customers, which can provide the customers with a better service to enhance the effectiveness of transactions. As the progression of M-Payment is directly proportional to the adoption of M-Payment. The purpose behind this research paper is to acknowledge the assimilated factors affecting the adoption of M-Payment and validate the effect of the same with the integrated variables of the Unified Theory of Acceptance and Use of Technology (UTAUT2 extended and expended model on the parameters of Behavioral Intentions and Use Behavior. In the present study, we acknowledged a sample of 163 consumers from Raipur, Chhattisgarh, and applied ‘Structure Equation Modelling (SEM)’ technique to examine the research objective. Furthermore, factor analysis, model fit, and regression techniques are applied to acquire the result. The results mainly showed that behavioral intention is positively and significantly influenced by facilitating conditions and perceived credibility, whereas behavioral intention, in turn, has a significant influence and impact on the use of behavior. An M-Payment system can work more effectively by concentrating more on credibility and facilitating conditions. The present study can also be useful for service providers and regulators   in developing effective M-payment implementing strategies and designs. Finally, in the last section, we discussed the research limitations and future research scope.


Download data is not yet available.


Abubakar, F. M., & Ahmad, H. (2014). Determinants of behavioural intention to use e-payment system in Nigerian retail industry: A conceptual extension of UTAUT with concern for customers. International Journal of Contemporary Business Management, 1(1), 87-93.

Adil, M. S., & Hamid, K. bin A. (2017). Impact of individual feelings of energy on creative work involvement: A mediating role of leader-member exchange. Journal of Management Sciences, 4(1), 1–21.

Akhlaq, A., & Ahmed, E. (2013). The effect of motivation on trust in the acceptance of internet banking in a low income country. International Journal of Bank Marketing, 31(2), 115–125.

Akinci, S., Aksoy, Ş., & Atilgan, E. (2004). Adoption of internet banking among sophisticated consumer segments in an advanced developing country. International Journal of Bank Marketing, 22(3), 212–232.

Al-Saedi, K., Al-Emran, M., Abusham, E., & El-Rahman, S. A. (2019). Mobile payment adoption: A systematic review of the UTAUT model. 2019 International Conference on Fourth Industrial Revolution, ICFIR 2019, 1–5.

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110.

Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125–138.

Alarcón, D., Sánchez, J. A., & De Olavide, U. (2015, October). Assessing convergent and discriminant validity in the ADHD-R IV rating scale: User-written commands for average variance extracted (AVE), composite reliability (CR), and heterotrait-monotrait ratio of correlations (HTMT). Retrieved from Spanish STATA meeting (Vol. 39). http://www.xxxxxx

Alkhowaiter, W. (2016, September). The power of Instagram in building small businesses. In Conference on e-Business, e-Services and e-Society (pp. 59-64). Springer, Cham.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

Anstey, K. J., Luszcz, M. A., & Sanchez, L. (2001). A reevaluation of the common factor theory of shared variance among age, sensory function, and cognitive function in older adults. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 56(1), 3–11.

Baabdullah, A., Dwivedi, Y., & Williams, M. (2014). Adopting an extended UTAUT2 to predict consumer adoption of M-technologies in Saudi Arabia.

Bacon, D. R., Sauer, P. L., & Young, M. (1995). Composite reliability in structural equations modeling. Educational and Psychological Measurement, 55(3), 394–406.

Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430.

Chai, T., & Draxler, R. R. (2014). Root mean square error (rmse) or mean absolute error (mae)? Arguments against avoiding rmse in the literature. Geoscientific Model Development, 7(3), 1247–1250.

Chen, H., Papazafeiropoulou, A., Chen, T. K., Duan, Y., & Liu, H. W. (2014). Exploring the commercial value of social networks: Enhancing consumers’ brand experience through facebook pages. Journal of Enterprise Information Management, 27(5), 576–598.

Crosse, J. (1999). Sold on cells. Automotive Engineer, 24(5), 34-36.

Cunningham, W. A., Preacher, K. J., & Banaji, M. R. (2001). Implicit attitude measures: Consistency, stability, and convergent validity. Psychological Science, 12(2), 163–170.

Curran, J. M., & Meuter, M. L. (2007). Encouraging existing customers to switch to self-service technologies: Put a little fun in their lives. Journal of Marketing Theory and Practice, 15(4), 283–298.

Dahlberg, T., & Oorni, A. (2007, January). Understanding changes in consumer payment habits-do mobile payments and electronic invoices attract consumers? In 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07) (pp. 50-50).

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), 982–1003.

DeFries, J. C., & Fulker, D. W. (1985). Multiple regression analysis of twin data. Behavior genetics, 15(5), 467-473.

Dennis, C., & Jayawardhena, C. (2010). Devising a research model to examine adoption of mobile payments: An extension of UTAUT2. Journal of Customer Behaviour, 9(2), 151–174.

Dewan, S. G., & Chen, L. (2005). Mobile payment adoption in the us: A cross-industry, crossplatform solution. Journal of Information Privacy and Security, 1(2), 4–28.

Di Pietro, L., Guglielmetti Mugion, R., Mattia, G., Renzi, M. F., & Toni, M. (2015). The integrated model on mobile payment acceptance (immpa): An empirical application to public transport. Transportation Research Part C: Emerging Technologies, 56(2015), 463–479.

Eckhardt, A., Laumer, S., & Weitzel, T. (2009). Who influences whom analyzing workplace referents’ social influence on it adoption and non-adoption. Journal of Information Technology, 24(1), 11–24.

El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the unified theory of acceptance and use of technology 2 (UTAUT2). Educational Technology Research and Development, 65(3), 743-763.

Farrell, A. M. (2010). Insufficient discriminant validity: A comment on bove, pervan, beatty, and shiu. Journal of Business Research, 63(3), 324–327.

Fornell, C., & Larcker, D. (1994). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research‏. Advances Methods of Marketing Research, 18(3), 382-388.

Gan, C., Clemes, M., Limsombunchai, V., & Weng, A. (2006). A logit analysis of electronic banking in new zealand. International Journal of Bank Marketing, 24(6), 360–383.

Gao, L., & Waechter, K. A. (2017). Examining the role of initial trust in user adoption of mobile payment services: An empirical investigation. Information Systems Frontiers, 19(3), 525–548.

Hair, J. F., Sarstedt, M., Matthews, L. M., & Ringle, C. M. (2016). Identifying and treating unobserved heterogeneity with fimix-pls: Part i – method. European Business Review, 28(1), 63–76.

Hair, Joseph F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1–2), 1–12.

Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Planning, 45(5–6), 320–340.

Henseler, I., Falkai, P., & Gruber, O. (2010). Disturbed functional connectivity within brain networks subserving domain-specific subcomponents of working memory in schizophrenia: Relation to performance and clinical symptoms. Journal of Psychiatric Research, 44(6), 364-372.

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(1), 115-135.

Hwang, Y., & Kim, D. J. (2007). Customer self-service systems: The effects of perceived web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746–760.

Jakkaew, P., & Hemrungrote, S. (2017, March). The use of UTAUT2 model for understanding student perceptions using Google classroom: A case study of introduction to information technology course. In 2017 International Conference on Digital Arts, Media and Technology (ICDAMT) (pp. 205-209). IEEE.Place of publication: Publisher

Johnson, V. L., Kiser, A., Washington, R., & Torres, R. (2018). Limitations to the rapid adoption of m-payment services: Understanding the impact of privacy risk on m-payment services. Computers in Human Behavior, 79(17), 111–122.

Keramati, A., Taeb, R., Larijani, A. M., & Mojir, navid. (2012). A combinative model of behavioural and technical factors affecting ’mobile’-payment services adoption: An empirical study. Service Industries Journal, 32(9), 1489–1504.

Khan, I. U., Hameed, Z., & Khan, S. U. (2017). Understanding online banking adoption in a developing country: UTAUT2 with cultural moderators. Journal of Global Information Management, 25(1), 43–65.

Kladkleeb, S., & Vongurai, R. (2019). Usage of digital payment systems in the era of Thailand 4.0 for Thai society. UTCC International Journal of Business and Economics, 11(3), 117–144.

Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. L. (2015). Enjoyment and social influence: Predicting mobile payment adoption. Service Industries Journal, 35(10), 537–554.

Larcker, C. F. and D. F. (2012). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 66(1), 37–39.

Laukkanen, P., Sinkkonen, S., & Laukkanen, T. (2008). Consumer resistance to internet banking: Postponers, opponents and rejectors. International Journal of Bank Marketing, 26(6), 440–455.

Lawley, D. N. (1940). VI.—the estimation of factor loadings by the method of maximum likelihood. Proceedings of the Royal Society of Edinburgh, 60(1), 64-82.

Magsamen-Conrad, K., Upadhyaya, S., Joa, C. Y., & Dowd, J. (2015). Bridging the divide: Using UTAUT to predict multigenerational tablet adoption practices. Computers in Human Behavior, 50, 186–196.

Marx, R. W., & Winne, P. H. (1978). Construct interpretations of three self-concept inventories. American Educational Research Journal, 15(1), 99–109.

McDonald, R. P., & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness of fit. Psychological Bulletin, 107(2), 247–255.

McHugh, R. K., Daughters, S. B., Lejuez, C. W., Murray, H. W., Hearon, B. A., Gorka, S. M., & Otto, M. W. (2011). Shared variance among self-report and behavioral measures of distress intolerance. Cognitive Therapy and Research, 35(3), 266-275.

Miles, J.N., Shevlin, M., 1998. Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personality and Individual Differences, 25, 85–90.--> This information got deleted without a replacement, so I put it here (with correction), please recheck if it is still needed.

Min, Q., Ji, S., & Qu, G. (2008). Mobile commerce user acceptance study in china: A revisedUTAUT model. Tsinghua Science and Technology, 13(3), 257–264.

Mohammed, A. H., & Ward, T. (2006). The effect of automated service quality on Australian banks’ financial performance and the mediating role of customer satisfaction. Marketing Intelligence and Planning, 24(2), 127–147.

Moorthy, K., Chun T'ing, L., Chea Yee, K., Wen Huey, A., Joe In, L., Chyi Feng, P., & Jia Yi, T. (2020). What drives the adoption of mobile payment? A Malaysian perspective. International Journal of Finance & Economics, 25(3), 349-364.

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(2016), 404–414.

Owusu Kwateng, K., Osei Atiemo, K. A., & Appiah, C. (2019). Acceptance and use of mobile banking: An application of UTAUT2. Journal of Enterprise Information Management, 32(1), 118–151.

Musleh, J. S., Marthandan, G., & Aziz, N. (2015). An extension of UTAUT model for Palestine e–commerce. International Journal of Electronic Business, 12(1), 95-115.

Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User acceptance of mobile apps for restaurants: An expanded and extended UTAUT-2. Sustainability, 11(4), 1210.

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891.

Putri, D. A. (2018, May). Analyzing factors influencing continuance intention of e-payment adoption using modified UTAUT 2 model. In 2018 6th International Conference on Information and Communication Technology (ICoICT) (pp. 167-173). IEEE.

Raman, A., & Don, Y. (2013). Preservice teachers’ acceptance of learning management software: An application of the UTAUT2 model. International Education Studies, 6(7), 157–164.

Raykov, T. (1997). Estimation of composite reliability for congeneric measures. Applied Psychological Measurement, 21(2), 173–184.

Reed, D. L., & Thompson, J. K. (1991). Development and validation of the physical appearance state and trait anxiety scale (PASTAS). Journal of Anxiety Disorders, 5, 323–332.

Rosnidah, I., Muna, A., Musyaffi, A. M., & Siregar, N. F. (2019). Critical factor of mobile payment acceptance in millenial generation: Study on theUTAUT model. Advances in Social Science, Education and Humanities Research, 306(2018), 123–127.

Sharma, K., & Bansal, M. (2013). Using utaut 2 model to predict mobile app based shopping: evidences from india. Journal of Indian Business Research, 5(3), 198–214.

aw, N., & Sergueeva, K. (2019). The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value. International Journal of Information Management, 45, 44–55.

Shevlin, M., & Miles, J. N. (1998). Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personality and Individual differences, 25(1), 85-90.

Sinha, S. K., & Verma, P. (2020). Impact of sales promotion’s benefits on perceived value: Does product category moderate the results? Journal of Retailing and Consumer Services, 52(December 2017), 1-11.

Sivathanu, B. (2019). Adoption of digital payment systems in the era of demonetization in India: An empirical study. Journal of Science and Technology Policy Management, 10(1), 143–171.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2012). User acceptance of information technology: Toward a unified view. JSTOR, 27(3), 425–478.

Venkatesh, V., Sykes, T. A., & Zhang, X. (2011). “Just what the doctor ordered”: A revised UTAUT forEMR system adoption and use by doctors. Proceedings of the Annual Hawaii International Conference on System Sciences, 1–10.

Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D., 2012. USER ACCEPTANCE OF INFORMATION TECHNOLOGY: TOWARD A UNIFIED VIEW. JSTOR 27, 425–478. --> capital letters only the first "U" and ":Toward"

This information got deleted without a replacement. Please recheck and change to a journal format.

Venkatesh, V., Thong, J. Y. L., Chan, F. K. Y., Hu, P. J. H., & Brown, S. A. (2011). Extending the two-stage information systems continuance model: Incorporating utaut predictors and the role of context. Information Systems Journal, 21(6), 527–555.

Zhang, E. M. (2010). Understanding the acceptance of mobile sms advertising among young chinese consumers. Psychology & Marketing, 30(6), 461–469.




How to Cite

Sharma, D. ., & Yashwant Kumar Vaid. (2023). FACTORS AFFECTING M-PAYMENT ADOPTION IN MILLENIALS – TESTING EXTENDED UTAUT2 MODEL. Thailand and The World Economy, 41(2), 40–61. Retrieved from https://so05.tci-thaijo.org/index.php/TER/article/view/265366