Abstract
This study investigates factors influencing the adoption of an enhanced M-PESA security system among agents in Nairobi County, amidst growing concerns about vulnerabilities in mobile payment systems. With mobile commerce thriving globally, particularly in developing regions, the integration of robust security measures becomes paramount. The focus on M-PESA, a dominant player in the mobile money market, suggests the urgency of fortifying transactional security to prevent fraud and unauthorized access, challenges accentuated by the reliance on basic authentication methods like PINs. Utilizing the Technology Acceptance Model (TAM) as the theoretical framework, this research examines the impact of perceived vulnerability, response cost, response efficacy, self-efficacy, and both intrinsic and extrinsic rewards on security system uptake. The methodology involved a predictive correlational study design, gathering data from 375 M-PESA agents in Nairobi via structured questionnaires, ensuring a representative sample through a clustered sampling approach. Regression analysis was employed to quantify the influence of each factor. Results indicate that perceptions of vulnerability and personal confidence (self-efficacy) in handling security measures significantly predict the willingness to adopt enhanced security solutions. Interestingly, intrinsic rewards influenced adoption positively, reflecting a motivation rooted in personal satisfaction and responsibility, while extrinsic rewards and perceived response efficacy showed no significant impact. These findings suggest that enhancing M-PESA agents' self-efficacy and addressing their perceived vulnerabilities could be more effective than offering external incentives.
Keywords
References
- Ahmed, W., Rasool, A., Javed, A. R., Kumar, N., Gadekallu, T. R., Jalil, Z., & Kryvinska, N. (2021). Security in next generation mobile payment systems: A comprehensive survey. IEEE Access, 9, 115932–115950.Google Scholar ↗
- Ajibade, P., & Mutula, S. M. (2020). Big data, 4IR and electronic banking and banking systems applications in South Africa and Nigeria. Banks and Bank Systems, 15(2), 187.Google Scholar ↗
- Alhassan, A., Li, L., Reddy, K., & Duppati, G. (2020). Consumer acceptance and continuance of mobile money: Secondary data insights from Africa using the technology acceptance model. Australasian Journal of Information Systems, 24. http://journal.acs.org.au/index.php/ajis/article/view/2579Google Scholar ↗
- Alkhowaiter, W. A. (2020). Digital payment and banking adoption research in Gulf countries: A systematic literature review. International Journal of Information Management, 53, 102102.Google Scholar ↗
- Bojjagani, S., Sastry, V. N., Chen, C.-M., Kumari, S., & Khan, M. K. (2023). Systematic survey of mobile payments, protocols, and security infrastructure. Journal of Ambient Intelligence and Humanized Computing, 14(1), 609–654. https://doi.org/10.1007/s12652-021-03316-4DOI ↗Google Scholar ↗
- de Luna, I. R., Montoro-Ríos, F., Martínez-Fiestas, M., & Casado-Aranda, L.-A. (2020). Analysis of a mobile payment scenario: Key issues and perspectives. In Impact of mobile services on business development and e-commerce (pp. 22–47). IGI Global. https://www.igi-global.com/chapter/analysis-of-a-mobile-payment-scenario/238245Google Scholar ↗
- Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593.Google Scholar ↗
- GSMA. (2024). The State of the Industry Report on Mobile Money 2024 (pp. 1–90).Google Scholar ↗
- Hameed, M. A., & Arachchilage, N. A. G. (2021). The role of self-efficacy on the adoption of information systems security innovations: A meta-analysis assessment. Personal and Ubiquitous Computing, 25(5), 911–925. https://doi.org/10.1007/s00779-021-01560-1DOI ↗Google Scholar ↗
- Jepkemboi, C. L. (2018). Enhancing Security of Mpesa Transactions by Use of Voice Biometrics. Journal of Banking Fraud, 10(1).Google Scholar ↗
- Kumar, S., Biswas, B., Bhatia, M. S., & Dora, M. (2021). Antecedents for enhanced level of cyber-security in organisations. Journal of Enterprise Information Management, 34(6), 1597–1629.Google Scholar ↗
- Marandu, E. E., Kealesitse, B., & Motswaborwa, C. (2022). Predicting Intention and Actual Use of Mobile Money Using the Technology Acceptance Model: The Case of University of Botswana Students. https://www.researchgate.net/profile/Calvin-Motswaborwa/publication/368757289_Predicting_Intention_and_Actual_Use_of_Mobile_Money_Using/links/63f891c257495059453e6d3e/Predicting-Intention-and-Actual-Use-of-Mobile-Money-Using.pdfGoogle Scholar ↗
- Motswaborwa, C. (2020). Predicting intention and actual use of mobile money using the technology acceptance model: The case of University of Botswana students. http://ithuteng.ub.bw/handle/10311/2469Google Scholar ↗
- Nam, T. (2019). Understanding the gap between perceived threats to and preparedness for cybersecurity. Technology in Society, 58, 101122.Google Scholar ↗
- Owiti, S. O., Ogara, S., & Rodrigues, A. (2023). Contributing Factors to Mobile Financial Fraud within Kenya. EPRA International Journal of Research and Development (IJRD), 8(1), 32–39.Google Scholar ↗
- Pal, A., Herath, T., & Rao, H. R. (2021). Why do people use mobile payment technologies and why would they continue? An examination and implications from India. Research Policy, 50(6), 104228.Google Scholar ↗
- Rashidi, F. U., Mohsini, M. H., & Mega, B. (2024). A framework for security improvement on usage of mobile money application based on iris biometric authentication method. Information Security Journal: A Global Perspective, 1–13. https://doi.org/10.1080/19393555.2024.2347240DOI ↗Google Scholar ↗
- Safaricom. (2024). Audited Results for 2023 Financial Year.Google Scholar ↗
- Shahad, A.-T., & Al-Haija, Q. A. (2024). Secure Mobile Payment (SMP): Challenges and Potential Solutions. International Journal of Intelligent Systems and Applications in Engineering, 12(11s), 103–120.Google Scholar ↗
- Sungi, S., Osiro, M., & Odhiambo, T. (2022). M-Pesa and Transnational Organized Crime: Causes and Facilitation Factors. https://www.researchgate.net/profile/Simeon-Sungi/publication/362656905_M-Pesa_and_Transnational_Organized_Crime_Causes_and_Facilitation_Factors/links/62f67c49c6f6732999c68c0e/M-Pesa-and-Transnational-Organized-Crime-Causes-and-Facilitation-Factors.pdfGoogle Scholar ↗
- Tabrizchi, H., & Kuchaki Rafsanjani, M. (2020). A survey on security challenges in cloud computing: Issues, threats, and solutions. The Journal of Supercomputing, 76(12), 9493–9532. https://doi.org/10.1007/s11227-020-03213-1DOI ↗Google Scholar ↗
- Tuwei, D., & Tully, M. (2021). The role of change agents in the adaptation and use of mobile money services in Kenya. Journal of African Media Studies, 13(1), 89–102. https://doi.org/10.1386/jams_00035_1DOI ↗Google Scholar ↗
- Wang, F., Shan, G. B., Chen, Y., Zheng, X., Wang, H., Mingwei, S., & Haihua, L. (2020). Identity authentication security management in mobile payment systems. Journal of Global Information Management (JGIM), 28(1), 189–203.Google Scholar ↗
- Williams, M. D. (2021). Social commerce and the mobile platform: Payment and security perceptions of potential users. Computers in Human Behavior, 115, 105557.Google Scholar ↗