Financial Technology Adoption and Supply Chain Performance of Selected Federal Ministries, Departments, and Agencies in Nigeria
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The persistent reliance on manual Requisition-to-Pay (R2P) processes within Nigerian Federal MDAs has institutionalized transactional friction, manifesting in chronic contractor payment delays and stifled operational liquidity. This study examined the impact of Financial Technology (FinTech) adoption focusing on Electronic Payment and Remittance Systems (EPRS), Digital Supply Chain Finance (DSCF), Blockchain-Based Smart Contracts (BBSC), and Big Data Analytics & AI Risk Assessment (BDAR) on Supply Chain Performance (SUCP) at selected Nigerian Federal MDAs. Using a descriptive survey research design, data were collected from 188 strategic stakeholders across five key organizations (Central Bank of Nigeria (CBN), the Bureau of Public Procurement (BPP), the Federal Medical Centre (FMC), Abuja, the National Health Insurance Authority (NHIA), and the Federal Ministry of Works) via a structured questionnaire, achieving a 78.7% response rate. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for analysis. The findings revealed that Big Data Analytics & AI Risk Assessment (BDAR) (β = 0.336, p < 0.001), Blockchain-Based Smart Contracts (BBSC) (β = 0.310, p < 0.001), and Electronic Payment and Remittance Systems (EPRS) (β = 0.173, p = 0.028) significantly and positively affect supply chain performance. However, Digital Supply Chain Finance (DSCF) showed no significant effect (β = 0.139, p = 0.086), suggesting that such financing models are yet to mature within the Nigerian public sector landscape. The study concluded that technological synergy is critical for institutional resilience, explaining 79.2% of the variance in performance. Aligning with Nigeria's Digital Economy Strategy (2020–2030), these findings underscored the urgent need for accelerated FinTech integration in public sector procurement to drive efficiency, transparency, and inclusive economic growth. Recommendations include prioritizing investment in AI-driven predictive analytics and implementing blockchain for automated, immutable contract execution to minimize errors and build trustless systems.
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