Purpose: This study aimed to consolidate the major determinants of continuance intention to use mobile payments by employing meta-analysis.Design/Methodology/Approach : The application of systematic inclusion/exclusion criteria resulted in the retrieval of 54 journal articles relating to the subject chosen for this study. An in-depth literature analysis helped identify the various antecedents of continuance intention to use mobile payments. A weighted analysis followed by a meta-analysis based on 193 bivariate correlations paved the way for developing the mobile payment continuance intention model (MPCIM). Meta Essentials 1.5 was used for analysis.

Findings: The primary predictor of continuing to intend to use mobile payments is satisfaction, which is followed by expectation of effort and expectation of performance. Perceived behavioral control was found to have the least consolidated effect on the desire to continue using mobile payments; whereas, perceived risk had no significant combined effect.Practical

Implications: The impact of the primary factors of continued desire to use mobile payments will be consolidated and presented to regulatory bodies, service providers, and other interested parties.Originality/

Value: We have made an effort to close this gap by doing a meta-analysis of the primary factors that determine whether or not a person would continue to want to utilize mobile payments.

1. Ahmed, I. S., & Ali, A. Y. (2017). Determinants of continuance intention to use mobile money transfer: An integrated model. Journal of Internet Banking and Commerce, 22(S7), 1–24. http://www.icommercecentral.com
2. Ali, K. A., & Subramanian, R. (2023). Determinants of continuance intention to use MBPS: A meta-analysis. In S. Banerjee, B. Pal, D. Mohanti, D. Chanda, & Y. Abichandani (eds.), Emerging business models: A twenty first century perspective (1st ed., pp. 14–33). Bloomsbury.
3. Ali, K. A., & Subramanian, R. (2024). Current status of research on mobile banking: An analysis of literature. Vision, 28(1), 7–18. https://doi.org/10.1177/09722629211073268
4. Bailey, A., Pentina, I., Mishra, A. S., & Mimoun, M. S. (2017). Mobile payments adoption by US consumers: An extended TAM. International Journal of Retail & Distribution Management, 45(6), 626–640. https://doi.org/10.1108/IJRDM-08-2016-0144
5. Baptista, G., & Oliveira, T. (2016). A weight and a meta-analysis on mobile banking acceptance research. Computers in Human Behavior, 63, 480–489. https://doi.org/10.1016/j.chb.2016.05.074
6. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectationconfirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
7. Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2009). Introduction to metaanalysis. John Wiley & Sons. https://doi.org/10.1002/9780470743386
8. Cao, X., Yu, L., Liu, Z., Gong, M., & Adeel, L. (2018). Understanding mobile payment users' continuance intention: A trust transfer perspective. Internet Research, 28(2), 456–476. https://doi.org/10.1108/IntR-11-2016-0359
9. Chen, Y., Mandler, T., & Meyer-Waarden, L. (2021). Three decades of research on loyalty programs: A literature review and future research agenda. Journal of Business Research, 124, 179–197. https://doi.org/10.1016/j.jbusres.2020.11.057
10. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587
11. 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. https://doi.org/10.1287/mnsc.35.8.982
12. de Albuquerque, J. P., Diniz, E. H., & Cernev, A. K. (2016). Mobile payments: A scoping study of the literature and issues for future research. Information Development, 32(3), 527–553. https://doi.org/10.1177/0266666914557338
13. De Oliveira Santini, F., Ladeira, W. J., Sampaio, C. H., Perin, M. G., & Dolci, P. C. (2019). A meta-analytical study of technological acceptance in banking contexts. International Journal of Bank Marketing, 37(3), 755–774. https://doi.org/10.1108/IJBM-04-2018-0110
14. Franque, F. B., Oliveira, T., & Tam, C. (2023). Continuance intention of mobile payment: TTF model with trust in an African context. Information Systems Frontiers, 25, 775–793. https://doi.org/10.1007/s10796-022-10263-8
15. Franque, F. B., Oliveira, T., Tam, C., & de Oliveira Santini, F. (2021). A meta-analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31(1), 123–158. https://doi.org/10.1108/INTR-03-2019-0103
16. Gadhiya, P., & Panchal, N. (2021). Young women's continuance intentions to use communication and social media apps. Indian Journal of Marketing, 51(3), 41–55. https://doi.org/10.17010/ijom/2021/v51/i3/158063
17. Handarkho, Y. D. (2021). Understanding mobile payment continuance usage in physical store through social impact theory and trust transfer. Asia Pacific Journal of Marketing and Logistics, 33(4), 1071–1087. https://doi.org/10.1108/APJML-01-2020-0018
18. Higgins, J. P., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta-analyses. British Medical Journal, 327, 557–560. https://doi.org/10.1136/bmj.327.7414.557
19. Hossain, M. A., Hossain, M. S., & Jahan, N. (2018). Predicting continuance usage intention of mobile payment: An experimental study of Bangladeshi customers. Asian Economic and Financial Review, 8(4), 487–498. https://doi.org/10.18488/journal.aefr.2018.84.487.498
20. 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
21. Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2021). A meta-analysis of the UTAUT model in the mobile banking literature: The moderating role of sample size and culture. Journal of Business Research, 132, 354–372. https://doi.org/10.1016/j.jbusres.2021.04.052
22. Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology, 21(1), 1–23. https://doi.org/10.1057/palgrave.jit.2000056
23. Kaur, S., Nim, D., & Jaggi, S. (2022). Relationship between humor in advertising and attitude towards ads : A meta-analysis. Indian Journal of Marketing, 52(3), 8 20. https://doi.org/10.17010/ijom/2022/v52/i3/160366
24. Liébana-Cabanillas, F., Molinillo, S., & Ruiz-Montañez, M. (2019). To use or not to use, that is the question: Analysis of the determining factors for using NFC mobile payment systems in public transportation. Technological Forecasting and Social Change, 139, 266–276. https://doi.org/10.1016/j.techfore.2018.11.012
25. Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2019). An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. International Journal of Human-Computer Interaction, 35(10), 886–898. https://doi.org/10.1080/10447318.2018.1507132
26. Linge, A., Singh, M., Kakde, B., & Punjani, K. K. (2022). Application of the theory of planned behaviour to predict college students online purchase intention : A systematic review and meta-analysis. Indian Journal of Marketing, 52(12), 39–57. https://doi.org/10.17010/ijom/2022/v52/i12/172561
27. Liu, Z., Ben, S., & Zhang, R. (2019). Factors affecting consumers' mobile payment behavior: A meta-analysis. Electronic Commerce Research, 19(3), 575–601. https://doi.org/10.1007/s10660-019-09349-4
28. Maduku, D. K. (2016). Fostering m-banking continuance intention: The role of trust in banks, self-efficacy, and mobile network quality. In, 10th International business conference (pp. 186–196). https://www.researchgate.net/publication/311582707
29. Mahajan, Y., Kaul, N., & Sharma, S. (2023). A systematic literature review of quasiexperimental studies on consumer behavior in the sustainability domain. Indian Journal of Marketing, 53(8), 25–46. https://doi.org/10.17010/ijom/2023/v53/i8/172974
30. Mensah, I. K. (2019). Predictors of the continued adoption of WECHAT mobile payment. International Journal of E-Business Research (IJEBR), 15(4), 1–23. https://doi.org/10.4018/IJEBR.2019100101
31. Mensah, I. K., Chuanyong, L., & Zeng, G. (2020). Factors determining the continued intention to use mobile money transfer services (MMTS) among university students in Ghana. International Journal of Mobile Human Computer Interaction (IJMHCI), 12(1), 1–21. https://doi.org/10.4018/IJMHCI.2020010101
32. Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ, 339. https://doi.org/10.1136/bmj.b2535
33. Pal, A., Herath, T., De', R., & Rao, H. R. (2020). Contextual facilitators and barriers influencing the continued use of mobile payment services in a developing country: Insights from adopters in India. Information Technology for Development, 26(2), 394–420. https://doi.org/10.1080/02681102.2019.1701969
34. Park, M., Jun, J., & Park, H. (2017). Understanding mobile payment service continuous use intention: An expectation - Confirmation model and inertia. Quality Innovation Prosperity, 21(3), 78–94. https://doi.org/10.12776/QIP.V21I3.983
35. Patil, P. P., Rana, N. P., & Dwivedi, Y. K. (2019). Digital payments adoption research: A metaanalysis for generalising the effects of attitude, cost, innovativeness, mobility and price value on behavioural intention. In A. Elbanna, Y. K. Dwivedi, D. Bunker, & D. Wastell, (eds.), Smart working, living and organising. TDIT 2018. IFIP advances in information and communication technology (Vol. 533, pp. 194–206). Springer. https://doi.org/10.1007/978-3-030-04315-5_14
36. Rana, N. P., Dwivedi, Y. K., & Williams, M. D. (2015). A meta-analysis of existing research on citizen adoption of e-government. Information Systems Frontiers, 17(3), 547–563. https://doi.org/10.1007/s10796-013-9431-z
37. Reddy, T. T., & Rao, B. M. (2021). Determinants of continuance intention to use mobile wallet services : Light users vs heavy users. Indian Journal of Marketing, 51(2), 29–42. https://doi.org/10.17010/ijom/2021/v51/i2/157549
38. Sabirali, K. P., & Mahalakshmi, S. (2023). Corporate sustainability practices: A systematic literature review and bibliometric analysis. Vision: The Journal of Business Perspective. https://doi.org/10.1177/09722629231203125
39. Sardana, V., Mohapatra, A. K., Singhania, S., & Chakrabarti, D. (2024). Changing dynamics of banking landscape : What do we know and what lies ahead? Prabandhan: Indian Journal of Management, 17(1), 8–23. https://doi.org/10.17010/pijom/2024/v17i1/173288
40. Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and Informatics, 32(1), 129–142. https://doi.org/10.1016/j.tele.2014.05.003
41. Shaikh, A. A., Karjaluoto, H., & Chinje, N. B. (2015). Consumers' perceptions of mobile banking continuous usage in Finland and South Africa. International Journal of Electronic Finance (IJEF), 8(2–4), 149–168. https://doi.org/10.1504/IJEF.2015.070528
42. Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33, 100823. https://doi.org/10.1016/j.elerap.2018.100823
43. Sharma, S., Sharma, R., Kayal, G., & Kaur, J. (2022). Digital banking : A meta-analysis approach. Indian Journal of Marketing, 52(5), 41–68. https://doi.org/10.17010/ijom/2022/v52/i5/169416
44. Shetty, P., & Poornima, Y. (2023). Major antecedents of electronic customer relationship management (E-CRM) studies in the Indian banking sector : A systematic review. Indian Journal of Marketing, 53(10), 45–59. https://doi.org/10.17010/ijom/2023/v53/i10/170594
45. Shetty, S., Chaudhuri, M. S., & Shetty, A. (2022). The nexus of corporate social responsibility and consumer perception : Systematic review of the evidence. Indian Journal of Marketing, 52(7), 25–42. https://doi.org/10.17010/ijom/2022/v52/i7/170537
46. Singh, S. (2020). An integrated model combining the ECM and the UTAUT to explain users' post-adoption behaviour towards mobile payment systems. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.2695
47. Suurmond, R., van Rhee, H., & Hak, T. (2017). Introduction, comparison, and validation of meta-essentials: A free and simple tool for meta-analysis. Research Synthesis Methods, 8(4), 537–553. https://doi.org/10.1002/jrsm.1260
48. Talwar, S., Dhir, A., Khalil, A., Mohan, G., & Islam, A. K. (2020). Point of adoption and beyond. Initial trust and mobile-payment continuation intention. Journal of Retailing and Consumer Services, 55, 102086. https://doi.org/10.1016/j.jretconser.2020.102086
49. Tan, E., & Lau, J. L. (2016). Behavioural intention to adopt mobile banking among the millennial generation. Young Consumers, 17(1), 18–31. https://doi.org/10.1108/YC-07-2015-00537
50. Tan, X., Zhao, X., Zou, Y., & Zhang, M. (2022). Survival of the fittest: A meta-analysis of users' mobile payment adoption. WHICEB 2022 Proceedings. https://aisel.aisnet.org/whiceb2022/57
51. Thalhath, P. (2022). Antecedents and outcomes of brand love in Indian context: A systematic literature review. International Journal of Indian Culture and Business Management (IJICBM), 27(3), 384–399. https://doi.org/10.1504/IJICBM.2022.126938
52. 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
53. Wang, S. (2020). A multigroup study of continuance intention of mobile banking in China. International Journal of Transitions and Innovation Systems, 6(3), 265–291. https://doi.org/10.1504/IJTIS.2020.107491
54. Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085–1091. https://doi.org/10.1016/j.dss.2012.10.034
55. Zhou, T. (2014). Understanding the determinants of mobile payment continuance usage. Industrial Management & Data Systems, 114(6), 936–948. https://doi.org/10.1108/IMDS-02-2014-0068