Author
Listed:
- OBI-Johnson Goodness Chinyere
(PhD Procurement Management Student)
- Prof. Suleiman A. S. Aruwa
(Institute of Governance and Development Studies, Nasarawa State University, Keffi-Nigeria.)
Abstract
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.
Suggested Citation
OBI-Johnson Goodness Chinyere & Prof. Suleiman A. S. Aruwa, 2026.
"Financial Technology Adoption and Supply Chain Performance of Selected Federal Ministries, Departments, and Agencies in Nigeria,"
International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(2), pages 931-948, February.
Handle:
RePEc:bjf:ijltem:v:15:y:2026:i:2:a:2094
DOI: 10.51583/IJLTEMAS.2026.15020000083
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:ijltem:v:15:y:2026:i:2:a:2094. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.