Exploresearch (ISSN: 3048-815X) ( Vol. 03 | No. 3 | July - September, 2026 )

Acceptance and Uptake of Digital Credit by Owner-Managed Micro, Small, and Medium-sized Enterprises (MSMEs) at La Nkwantanang-Madina Municipality

Author: David Yaw Mordey, Bismark Stephen Kumah, Toby Nana Kwasi Afosah-Nyarko, Joseph Kofi Mensah & Karl Mark Arhin

Owner-managed micro, small, and medium-sized enterprises (MSMEs) are characterised by substantial financing gaps, which impede their growth prospects and their contribution to employment creation and poverty alleviation. While digital lending offers businesses the opportunity to address the challenge of ever-rising financing constraints in emerging markets, the factors predicting digital credit adoption by MSME owner-managers are understudied. This study examined the determinants of digital credit adoption among owner-managed MSMEs in Ghana using an extended Technology Acceptance Model (E-TAM). This quantitative study obtained data from 336 MSMEs operating at the La Nkwantanang-Madina Municipality and analysed the data using partial least squares structural equation modelling (PLS-SEM). The findings show that perceived usefulness and perceived ease of use significantly and positively influence behavioural intention, while perceived cost has a significant negative effect. Perceived risk, however, does not significantly affect behavioural intention. The model explains 47.9% of the variance in behavioural intention, which in turn explains 41.4% of the variance in actual digital credit uptake. The findings suggest the need to develop MSME-tailored digital credit facilities through special arrangements between governments and service providers, anchored on reduced transaction costs, desirable loan amounts, and user-friendly systems. This study is a groundbreaking attempt that incorporates cost and risk into the TAM for digital credit adoption at the organisational level in an emerging market.

Mordey, D., Kumah, B., Nyarko, T., Mensah, J. & Arhin, K. (2026). Acceptance and Uptake of Digital Credit by owner-managed Micro, Small, and Medium-sized Enterprises (MSMEs) at La Nkwantanang-Madina Municipality. Exploresearch, 03(03), 01–15. https://doi.org/10.62823/exre/03.03.246

  1. Abbott, B. O. (2020). Financial Technology and Credit Usage Among Small and Medium Enterprises in Kisumu Central Business District, Kenya [Master’s thesis]. University of Nairobi.
  2. Ahiabenu, K. (2021). Mapping Mobile Money Loan Ecosystem: Insights from Ghana. 2021 14th CMI International Conference—Critical ICT Infrastructures and Platforms (CMI), 1–8. https://doi.org/10.1109/CMI53512.2021.9663800
  3. 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
  4. Awal, I. M. (2018). 75% Businesses Fail after 3 Years. Retrieved from Https://Www.Modernghana.Com/News/780532/75-Businesses-Fail-after-3-Years.Html. https://thebftonline.com/2018/business/education/rate-of-business-failure-unacceptable-awal/
  5. Bandura, A. (1977). Social Learning Theory. Prentice-Hall.
  6. Bank of Ghana. (2022). Annual Report and Financial Statements 2022. Bank of Ghana.
  7. Chaudhari, T., Linge, A. A., Kakde, B. B., & Singh, M. (2023). Empirical Evaluation of Technology Acceptance Model for Predicting Actual Usage of Mobile Payment Apps. Empirical Economics Letters, 22(Special Issue 3), 402–414. https://doi.org/10.5281/zenodo.7951826
  8. Chin, K. Y., Zakaria, Z., Purhanudin, N., & Pin, C. T. (2021). A Paradigm of TAM Model in SME P2P Financing. International Journal of Economics and Management, 15(3), 397–414.
  9. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates.
  10. Consultative Group to Assist the Poor. (2023). An Ecosystem Approach to Consumer Protection: What, Why and How? https://www.cgap.org/topics/collections/digital-credit
  11. Cronbach, L. J. (1951). Coefficient Alpha and the Internal Structure of Tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
  12. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–339.
  13. 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), 982–100.
  14. Featherman, M. S., & Pavlou, P. A. (2003). Predicting E-Services Adoption: A Perceived Risk Facets Perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3
  15. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley.
  16. Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  17. Frimpong, S. E., Agyapong, G., & Agyapong, D. (2022). Financial Literacy, Access to Digital Finance and Performance of SMEs: Evidence from the Central Region of Ghana. Cogent Economics & Finance, 10(1). https://doi.org/10.1080/23322039.2022.2121356
  18. Ghana Statistical Service. (2016). Integrated Business Establishment Survey: Regional Spatial Business Report. Ghana Statistical Service.
  19. Gupta, U., Agarwal, B., & Nautiyal, N. (2022). Financial Technology Adoption: A Case of Indian MSMEs. Finance: Theory and Practice, 26(6), 192–211. https://doi.org/10.26794/2587-5671-2022-26-6-192-211
  20. Gyimah, K. N., Akande, J. O., & Muzindutsi, P.-F. (2022). Lending Methodologies and SMEs’ Access to Finance in Ghana: The Mediating Role of Credit Reference Information. Cogent Business & Management, 9(1). https://doi.org/10.1080/23311975.2022.2143075
  21. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.).
  22. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
  23. Harman, H. H. (1967). Modern Factor Analysis (2nd ed.). University of Chicago Press.
  24. 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. https://doi.org/10.1007/s11747-014-0403-8
  25. 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
  26. Kaffenberger, M., Totolo, E., & Soursourian, M. (2018). A Digital Credit Revolution: Insights from Borrowers in Kenya and Tanzania. Consultative Group to Assist the Poor.
  27. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision Under Risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
  28. Kamau, C. G. (2021a). Availability of Finance, Finance Costs, and Business Success in Kenya: Focus on the Small and Micro Enterprises. EPRA International Journal of Economics, Business and Management Studies, 8(8), 26–30. https://doi.org/10.5281/zenodo.6846807
  29. Kamau, C. G. (2021b). Digital Credit in Kenya: A Survey of Costs, Uses and Borrowers’ Considerations in Relation to Loan Uptake. East African Journal of Business and Economics, 3(1), 164–172. https://doi.org/10.37284/eajbe.3.1.402
  30. Kelly, A. E., & Palaniappan, S. (2023). Using a Technology Acceptance Model to Determine Factors Influencing Continued Usage of Mobile Money Service Transactions in Ghana. Journal of Innovation and Entrepreneurship, 12(1), 34. https://doi.org/10.1186/s13731-023-00301-3
  31. Lambon-Quayefio, M., Manjeer, U., & Udry, C. (2021). The Impact of a Digital Credit for Small-Scale Farmers in Ghana. Innovations for Poverty Action. https://poverty-action.org/study/impact-digital-credit-small-scale-farmers-ghana
  32. Ministry of Finance and Economic Planning. (2020). Digital Financial Services Policy. Government of Ghana.
  33. Ministry of Finance and Economic Planning. (2022). National Financial Inclusion and Development Strategy (NFIDS) 2018–2023. Ministry of Finance and Economic Planning.
  34. Ministry of Trade and Industry. (2023). MSME & Entrepreneurship Policy. Government of Ghana. https://moti.gov.gh/v2/Project/Msme-Entrepreneurship-Policy/
  35. Ngulale, M. E. (2020). Digital Credit Borrowing and the Financial Risk Exposure of Micro and Small Enterprises in Nairobi City County, Kenya [Master’s thesis]. Kenyatta University.
  36. Nurqamarani, A. S., Soegiarto, E., & Nurlaeli, N. (2021). Technology Adoption in Small-Medium Enterprises Based on Technology Acceptance Model: A Critical Review. Journal of Information Systems Engineering and Business Intelligence, 7(2), 162–172.

https://doi.org/10.20473/jisebi.7.2.162-172

  1. Özbek, V., Günalan, M., Koç, F., Şahin, N. K., & Kaş, E. (2015). The Effects of Perceived Risk and Cost on Technology Acceptance: A Study on Tourists’ Use of Online Booking. Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 13(2), 227–244. https://doi.org/10.18026/cbusos.49782
  2. Putri, G. A., Widagdo, A. K., & Setiawan, D. (2023). Analysis of Financial Technology Acceptance of Peer-to-Peer Lending Using an Extended Technology Acceptance Model. Journal of Open Innovation: Technology, Market, and Complexity, 9(1).

https://doi.org/10.1016/j.joitmc.2023.100027

  1. Rahadian, A., & Thamrin, H. (2023). Analysis of Factors Affecting MSMEs in Using Fintech Lending as Alternative Financing: Technology Acceptance Model Approach. Brazilian Business Review, 20(3), 301–322. https://doi.org/10.15728/bbr.2023.20.3.4.en
  2. Sharma, S. K., Ilavarasan, P. V., & Karanasios, S. (2024). Small Businesses and FinTech: A Systematic Review and Future Directions. Electronic Commerce Research, 24(1), 535–575. https://doi.org/10.1007/s10660-023-09705-5
  3. Sunardi, R., Hamidah, H., Buchdadi, A. D., & Purwana, D. (2022). Factors Determining Adoption of Fintech Peer-to-Peer Lending Platform: An Empirical Study in Indonesia. The Journal of Asian Finance, Economics and Business, 9(1), 43–51.

https://doi.org/10.13106/jafeb.2022.vol9.no1.0043

  1. Sunardi, R., Suhud, U., Purwana, D., & Hamidah, H. (2021). Examining the Factors Contributing to Fintech Peer-to-Peer Lending Adoption. Journal of Information Systems Engineering and Business Intelligence, 7(2), 91–101. https://doi.org/10.20473/jisebi.7.2.91-101
  2. Thathsarani, U. S., & Jianguo, W. (2022). Do Digital Finance and the Technology Acceptance Model Strengthen Financial Inclusion and SME Performance? Information, 13(8). https://doi.org/10.3390/info13080390
  3. Tiwari, P., & Tiwari, S. K. (2020). Integration of Technology Acceptance Model with Perceived Risk, Perceived Trust and Perceived Cost: Customers’ Adoption of M-Banking. International Journal on Emerging Technologies, 11(2), 447–452.
  4. von Neumann, J., & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton University Press.
  5. Wang, H.-Y., & Wang, S.-H. (2010). Predicting Mobile Hotel Reservation Adoption: Insight from a Perceived Value Standpoint. International Journal of Hospitality Management, 29(4), 598–608. https://doi.org/10.1016/j.ijhm.2009.11.001
  6. Wessels, L., & Drennan, J. (2010). An Investigation of Consumer Acceptance of M-Banking. International Journal of Bank Marketing, 28(7), 547–568.

https://doi.org/10.1108/02652321011085194

  1. World Bank. (2019a). Ghana Digital Economy Diagnostic: Stock-Taking Report. World Bank. https://hdl.handle.net/10986/34366
  2. World Bank. (2019b). Improving Access to Finance for Ghanaian SMEs: Is There a Role for a New Development Finance Institution? World Bank.
  3. World Bank. (2021). The Key to Creating More Jobs in Ghana: Driving Technological Transformation of Micro-, Small and Medium-Sized Enterprises. World Bank. https://www.worldbank.org/en/news/feature/2021/11/24/the-key-to-creating-more-jobs-in-ghana-driving-technological-transformation-of-micro-small-and-medium-sized-enterprises
  4. Wu, J.-H., & Wang, S.-C. (2005). What Drives Mobile Commerce? An Empirical Evaluation of the Revised Technology Acceptance Model. Information & Management, 42(5), 719–729. https://doi.org/10.1016/j.im.2004.07.001.

DOI:

Article DOI: 10.62823/exre/03.03.246

DOI URL: https://doi.org/10.62823/exre/03.03.246

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