Digital Payment Adoption and its Impact on Working Capital Management Practices among SMEs in Kerala
Keywords:
Digital Payment Adoption; Working Capital Management; SMEs; Kerala; UPI; Technology Acceptance Model; UTAUT; Structural Equation Modeling; Fintech; MSME Financial ManagementAbstract
While the extensive penetration of Unified Payments Interface (UPI), Mobile Wallets, and Point Of Sale (PoS) digital infrastructure has changed the way transaction takes place for Micro Small, and Medium Enterprises (MSMEs) in India, the literature on the extent to which such changes manifest as measurably improved working capital management (WCM) is sparse, especially in the context of regionally unique MSME ecosystems like Kerala's remittance-driven and trade-intensive economy. The TAM, UTAUT and TOE frameworks are integrated and tested as a model for this study where Perceived Usefulness, Perceived Ease of Use, Trust and Security, and Facilitating Conditions become the predictors of Working Capital Management practice efficiency through Digital Payment Adoption with the moderators being firm size. The findings in this study based on a cross‐sectional survey with 420 valid SME owners/managers across 6 districts in Kerala and reliability/validity testing, correlation, multiple regression and SEM highlight that four of the five antecedents significantly predict DPA (R2 = 0.414), and that DPA significantly and substantially predicts WCM practice efficiency (β = 0.559, p < .001; SEM model fit: χ2/df = 0.95, CFI = 0.99, RMSEA = 0.000), whereas the hypothesized moderation of firm size was not statistically supported. The findings provide a good validated framework and understanding of the regionally valid link between fintech adoption and core financial management practice, which then can be applied in MSME policy, fintech literacy programming and for future longitudinal and multi-state replication.
References
1. National Payments Corporation of India (NPCI). (2025). UPI product statistics. NPCI.
2. Ministry of Micro, Small and Medium Enterprises, Government of India. (2024). Annual report 2023-24. MSME Ministry.
3. Government of Kerala, Directorate of Industries and Commerce. (2023). Kerala economic review: MSME sector. Government of Kerala.
4. Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of Business Finance & Accounting, 30(3-4), 573–588.
5. García-Teruel, P. J., & Martínez-Solano, P. (2007). Effects of working capital management on SME profitability. International Journal of Managerial Finance, 3(2), 164–177.
6. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
7. 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.
8. Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322.
9. 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.
10. Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling consumers' adoption intentions of remote mobile payments in the UK. Psychology & Marketing, 32(8), 860–873.
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.
12. Singh, S., & Rana, R. (2017). Study of consumer perception of digital payment mode. Journal of Internet Banking and Commerce, 22(3), 1–14.
13. Shin, H. H., & Soenen, L. (1998). Efficiency of working capital management and corporate profitability. Financial Practice and Education, 8(2), 37–45.
14. Padachi, K. (2006). Trends in working capital management and its impact on firms' performance. International Review of Business Research Papers, 2(2), 45–58.
15. Enqvist, J., Graham, M., & Nikkinen, J. (2014). The impact of working capital management on firm profitability in different business cycles. International Review of Financial Analysis, 32, 36–49.
16. [Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
17. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
18. [18] Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
19. Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.
20. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.
21. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
22. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
23. Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
24. Igolkin, G. (2023). semopy: A Python package for structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal.
25. 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.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Articles published in the Journal of Advanced Multidisciplinary Studies (JAMS) are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), unless otherwise stated. Authors retain copyright of their work and grant JAMS the right of first publication.
