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asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
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Published: 31 August 2022

An Assessment of The Effect of Mobile Money Services on The Profitability of The Banking Sector in Zambia

Austin Mwange, Pimpa Kasongola, Ayanda Meyiwa

ZCAS University, Indo-Zambia Bank, University of Kwa Zulu Natal

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, management journal

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doi

10.31014/aior.1992.05.03.443

Pages: 139-152

Keywords: Mobile Money, Banking Sector, Profitability, Interest Income, Return on Equity

Abstract

The aim of the study was to investigate the effect of mobile money services on Zambia’s banking sector profitability. Profitability was proxied by Return on equity (ROE) and Gross interest income (GII). Using the Johansen Cointegration approach on quarterly data for the period 2012Q1 to 2021Q4, the results suggest a positive relationship between mobile money services and commercial banks’ profitability. Based on the results, the study recommends that there is need for commercial banks to continuously align their operational models with emergent innovative services in the sector while also appealing to regulators to collectively design regulatory frameworks that are responsive to developing sector trends.

References

  1. Adaba, G. B. & Ayoung, D. A., 2017. The Development of a Mobile Money Service: An Exploratory Actor-Network Study. Information Technology for Development, pp. 668-686.

  2. Adams, D. A., Nelson, R. R. & Todd, P. A., 1992. Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication. MIS Quarterly, 16(2), p. 227–247.

  3. Ajzen, I. & Fishbein, M., 1980. Understanding Attitude and Predicting Social Behavior. New Jersey: Prentice-Hall.

  4. Akinyemi, B. E. & Mushunje, A., 2020. Determinants of Mobile Money Technology Adoption in Rural Areas of Africa. Cogent Social Sciences, 6(1), pp. 1-21.

  5. Andrade, A. D. & Urquhart, C., 2010. The Affordances of Actor-Network Theory in ICT for Development Research. Information Technology & People, Volume 23, p. 352–374.

  6. Aron, J., 2018. Mobile Money and the Economy: A Review of the Evidence. The World Bank Research Observer, 33(2), p. 135–188.

  7. Bank of Ghana, 2017. Impact of Mobile Money on the Payment System in Ghana: An Econometric Analysis, Accra: Bank of Ghana.

  8. BoZ, 2020. FinScope 2020 Topline Findings, Lusaka: Bank of Zambia (BoZ).

  9. Callon, M., 1999. Some Elements of a Sociology of Translation: Domestication of the Scallops and the Fishermen of St Brieuc Bay. In M. Biagioli (Ed.), The science studies reader (pp. 67–83). London: Routledge.

  10. Callon, M., 2001. Actor Network Theory. International Encyclopedia of the Social & Behavioral Sciences, pp. 62-66.

  11. Chauhan, S., 2015. Acceptance of Mobile Money by Poor Citizens of India: Integrating Trust into the Technology Acceptance Model. Info, 17(3), pp. 58-68.

  12. Chen, J. & Adams, C., 2005. User Acceptance of Mobile Payments: A Theoretical Model for Mobile Payments. Newcastle upon Tyne, International Conference on Electronic Business (ICEB).

  13. Chipa, N. & Mwanza, B. G., 2021. Factors Impeding Mobile Money Expansion in Zambia. International Journal of Engineering and Management Research, 11(1), pp. 178-186.

  14. Cooper, B. et al., 2019. Zambia Payments Diagnostic, Cape Town: Cenfri.

  15. Crabbe, M., Standing, C., Standing, S. & Karjaluoto, H., 2009. An Adoption Model for Mobile Banking in Ghana. International Journal of Mobile Communications, 7(5), pp. 515-543.

  16. Cresswell, K. M., Worth, A. & Sheikh, A., 2010. Actor-Network Theory and its Role in Understanding the Implementation of Information Technology Developments in Healthcare. BMC Medical Informatics and Decision Making, 10(67), pp. 1-11.

  17. Cresswell, K. M., Worth, A. & Sheikh, A., 2010. Actor-Network Theory and its Role in Understanding the Implementation of Information Technology Developments in Healthcare. BMC Medical Informatics and Decision Making, 10(67), pp. 1-11.

  18. Czarniawska, B., 2003. Narratives in Social Science Research. London: Sage.

  19. Davis, F. D., 1989. Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13(3), pp. 319-340.

  20. De Vaus, D. A., 2001. Research Design in Social Research. London: Sage.

  21. Deloitte, 2014. Banking Disrupted: How Technology is Threatening the Traditional European Retail Banking Model, London: Deloitte.

  22. Engle, R. F. & Granger, C. W., 1987. Co-integration and Error Correction: Representation Estimation and Testing. Econometrica, Volume 55, pp. 251-276.

  23. Farooq, S., 2020. Mitigating Common Fraud Risks: Best Practices for the Mobile Money Industry, London: Global System for Mobile Communications (GSMA).

  24. Flamini, V., McDonald, C. & Schumacher, L., 2009. The Determinants of Commercial Bank Profitability in Sub-Saharan Africa. IMF Working Paper Series, 9(15), pp. 1-30.

  25. Fox, J., 2016. Applied Regression Analysis and Generalized Linear Models. 3rd ed. Los Angeles: Sage Publications Inc..

  26. Greenacre, J. & Buckley, R., 2016. Using Trusts to Protect Mobile Money Customers. Singapore Journal of Legal Studies, pp. 59-78.

  27. GSMA, 2010. Mobile Money for the Unbanked: Annual Report 2009, London: Global System for Mobile Communications (GSMA).

  28. GSMA, 2017. The Mobile Economy: Sub-Saharan Africa 2017, London: Global System for Mobile Communications (GSMA).

  29. GSMA, 2019. The Impact of Mobile Money on Monetary and Financial Stability in Sub-Saharan Africa, London: Global System for Mobile Communications (GSMA).

  30. GSMA, 2020. The Mobile Economy: Sub-Saharan Africa 2020, London: Global System for Mobile Communications (GSMA).

  31. Gujarati, D. N., 2004. Basic Econometrics. 4th ed. New York: McGraw-Hill Companies.

  32. Hanseth, O., Aanestad, M. & Berg, M., 2004. Guest Editors’ Introduction: Actor-Network Theory and Information Systems. What’s So Special?. Information Technology & People, Volume 17, pp. 116-123.

  33. Harry, R., Sewchurran, K. & Brown, I., 2014. Introducing a Mobile Payment System to an Emerging Economy’s Mobile Phone Subscriber Market: An Actor Network Perspective.. The Electronic Journal of Information Systems in Developing Countries, 62(4), pp. 1-26 .

  34. Heeks, R. & Stanforth, C., 2007. Understanding e-Government Project Trajectories from an actor-network perspective.. European Journal of Information Systems, Volume 16, pp. 165-177.

  35. Hendrickson, A. R., Massey, P. D. & Cronan, T. P., 1993. On the Test-Retest Reliability of Perceived Usefulness and Perceived Ease of use Scales. MIS Quarterly, 17(2), p. 227–230.

  36. Hu, P. J., Chau, P. Y. K. & Sheng, O. R. L., 1999. Examining the Tehnoogy Acceptance Model using Physician Acceptance of Telemedicine Technology. Journal of Management Information Systems, 16 (2), p. 91–112.

  37. IFC, 2017a. Digital Financial Services: Challenges and Opportunities for Emerging Market Banks, Washington D.C: International Finance Corporation.

  38. IFC, 2017b. IFC Mobile Money Scoping Country Report: Zambia, Washington D.C: International Finance Corporation.

  39. IMF, 2019. Mobile Money Note 2019, Washington D.C: International Monetary Fund (IMF).

  40. IMF, 2020. Financial Access Survey: 2020 Trends and Developments, Washington D.C: International Monetary Fund (IMF).

  41. INTERPOL, 2020. Mobile Money and Organized Crime in Africa, Lyon: INTERPOL.

  42. Jayawardhena, C. & Foley, P., 2000. Changes in the Banking Sector: The Case of Internet Banking in the UK. Internet Research, 10(1), pp. 19-31.

  43. Jeong, H., 2011. An Investigation of User Perceptions and Behavioral Intentions Towards the e-library. Library Collections, Acquisitions, and Technical Services, 35(2-3), pp. 45-60.

  44. Kabala, E. et al., 2018. An Ethnological Analysis of the Influence of Mobile Money on Financial Inclusion: The Case of Urban Zambia. Zambia Social Science Journal, 7(1), pp. 53-76.

  45. Kabala, E. & Seshamani, V., 2016. Mobile Technology and Poverty Reduction In Zambia: A SWOT Analysis. Journal of Economics and Finance, 7(3), pp. 61-74.

  46. Kamukama, N. & Tumwine, S., 2012. Mobile Money Services: A Liquidity Threat to Uganda’s Commercial Banks. African Journal of Accounting, Economics, Finance and Banking Research, 8(8), pp. 33-46.

  47. Klejcie, R. V. & Morgan, D. W., 1970. Determining Sample Size for Research Activities. Educational and Psychological Measurement, Volume 30, pp. 607-610.

  48. Kothari, C. R., 2004. Research Methodology: Methods and Technique. 2nd ed. New Delhi: New Age International Publishers.

  49. Kothari, C. R., 2010. Research Methodology: Methods and Techniques. New Delhi: New Age International Publishers.

  50. KPMG, 2020. The Pulse of FinTech H2 2020 - Global Insight, Amsterdam: KPMG.

  51. Kubuga, K. K. & Konjaang, J. K., 2016. Mobile Money: A Potential Threat to Banks?. International Journal of Computer Applications, 147(4), pp. 30-36.

  52. Ky, S., Rugemintwari, C. & Sauviat, A., 2019. Is fintech good for bank performance? The case of Mobile Money in the East African Community. Working Papers hal-02155077.

  53. Law, J., 1992. Notes on the Theory of the Actor-Network: Ordering, Strategy, and Heterogeneity. System Practice, Volume 54, pp. 379-393.

  54. Lucas, H. C. & Spitler, V. K., 1999. Technology Use and Performance: A Field Study of Broker Workstations. Decision Sciences, 30(2), p. 291–311.

  55. Lumba, H., 2017. Lusaka City Market: All Time Trading Center. Lusaka: Times of Zambia.

  56. Maino, R., Massara, A., Perez-Saiz, H. & Sharma, P., 2019. FinTech in Sub-Saharan African Countries: A Game Changer?, Washington D.C: International Monetary Fund (IMF).

  57. Mawejje, J. & Lakuma, P. C. E., 2017. Macroeconomic Effect of Mobile Money in Uganda, Kampala: Economic Policy Research Center (EPRC).

  58. Mbiti, I. & Weil, D. N., 2011. Mobile Banking: The Impact of M-PESA in Kenya. NBER Working Paper Series No. 17129, June.

  59. Mintz-Roth, M., 2018. The Gender and Age Dimensions of Mobile Money Adoptions in Zambia, Nairobi: FSD Kenya.

  60. Mishkin, F. S., 2011. The Economics of Money, Banking and Financial Markets. 5th ed. Toronto: Pearson Canada.

  61. Musah, A., Anokye, F. K. & Gakpetor, E. D., 2018. The Effect of Interest Rate Spread on Bank Profitability in Ghana. European Journal of Business, Economics and Accountancy, 6(1), pp. 27-39.

  62. Muthiora, B. & Bahia, K., 2020. The Mobile Money Regulatory Index 2019, London: Global System for Mobile Communications (GSMA).

  63. Nampewo, D., Tinyinondi, G. A., Kawooya, D. R. & Ssonko, G. W., 2016. Determinants of Private Sector Credit in Uganda: the Role of Mobile Money. Financial Innovation, 2(13), pp. 1-16.

  64. Ngoma,C., & Chanda, C., 2022. Pass-Through from Policy Rate to Retail Interest Rates in Zambia. Available at: http://publication.aercafricalibrary.org/handle/123456789/3369 [accessed on 15/07/2022]

  65. Njele, C. C. & Phiri, J., 2021. International Journal of Business and Management. Factors Affecting Usage of Mobile Money Services and Their Impact on Financial Inclusion: Case of Lusaka Province, 16(7), pp. 104-118.

  66. Otieno, et al., 2016. Challenges Facing the Use and Adoption of Mobile Phone Money Services. World Journal of Computer Application and Technology, 4(1), pp. 8-14.

  67. Pikkarainen, T., Pikkarainen, K. & Karjaluoto, H., 2004. Consumer Acceptance of Online Banking: An Extension of the Technology Acceptance Model. Internet Research-Electronic Networking Applications and Policy, 14(3), p. 224–235.

  68. Prout, A., 1996. Actor-Network Theory, Technology and Medical Sociology: An Illustrative Analysis of the Metered Dose Inhaler.. Sociology of Health and Illness, Volume 18, pp. 198-219.

  69. PwC, 2016. What is FinTech?, New York: PricewaterhouseCoopers (PwC).

  70. Samuel, T. & Wamalwa, P., 2019. The Effect of Mobile Money on Banking Sector Stability in Kenya, Nairobi: Kenya Bankers Association.

  71. Saunders, M., Lewis, P. & Thornhill, A., 2009. Research Methods for Business Students. 5th ed. London: Pearson Education Limited.

  72. Singh, S. K., Basuki, B. & Setiawan, R., 2021. The Effect of Non-Performing Loan on Profitability: Empirical Evidence from Nepalese Commercial Banks. Journal of Asian Finance, Economics and Business, 8(4), p. 709–716.

  73. Skan, J., James, D. & Luca, G., 2016. FinTech and the Evolving Landscape: Landing Points for the Industry. Dublin: Accenture.

  74. Suri, T. & Jack, W., 2016. The Long-Run Poverty and Gender Impacts of Mobile Money. Science, 354(6317), pp. 1288-1292.

  75. Szajna, B., 1994. Software Evaluation and Choice: Predictive Evaluation of the Technology Acceptance Instrument. MIS Quarterly, 18(3), p. 319–324.

  76. Thapa, D., 2011. The Role of ICT Actors and Networks in Development: The Case Study of a Wireless Project in Nepal. The Electronic Journal of Information Systems in Developing Countries, Volume 49, p. 1–16.

  77. Tiriongo, S. & Wamalwa, P., 2020. The Effect of Mobile Money on Banking Sector Stability in Kenya, Nairobi: Kenya Bankers Association.

  78. Venkatesh, V. & Davis, F., 2000. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), pp. 186-204.

  79. Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. G., 2003. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), pp. 425-478.

  80. Wixom, B. H. & Todd, P. A., 2005. A Theoretical Integration of User Satisfaction and Technology Acceptance. Information Systems Research, 16(1), p. 85–102.

  81. Wu, J. H. & Wang, S. C., 2005. What Drives Mobile Commerce? An Empirical Evaluation of the Revised Technology Acceptance Model. Information and Management, 42(5), p. 719–729.

  82. Zgambo, P. & Chileshe, P. M., 2014. Empirical Analysis of the Effectiveness of Monetary Policy in Zambia, Nairobi: COMESA Monetary Institute.