Artificial Intelligence and Buyer–Supplier Relationships in Procurement
Evidence from TECNO Mobile Nigeria
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Abstract
This study investigates the influence of Artificial Intelligence (AI) applications on buyer–supplier relationship quality in Nigeria's mobile manufacturing sector, with specific reference to TECNO Mobile Nigeria. Drawing on the Commitment-Trust Theory of Relationship Marketing (Morgan & Hunt, 1994), the study operationalises AI through three proxies: Predictive Analytics (PA), Automation of Processes (AP), and AI Risk Management (AIR). A survey research design was adopted, and structured questionnaires were administered to 250 employees and supply chain partners purposively selected from TECNO Mobile's procurement, logistics, IT, and supplier management functions. Data were analysed using descriptive statistics (frequencies, means, standard deviations) and one-sample t-tests benchmarked against the scale's neutral midpoint (μ₀ = 3.00). All three null hypotheses were rejected at p < 0.001. Predictive Analytics recorded an aggregate mean of 3.88 (SD = 0.34; t(249) = 40.53), Automation of Processes 3.91 (SD = 0.36; t(249) = 40.05), and AI Risk Management 3.92 (SD = 0.36; t(249) = 40.47), all significantly above the neutral midpoint. Findings confirm that respondents perceive each AI dimension as positively and meaningfully contributing to trust, efficiency, transparency, and long-term relational stability with suppliers. The study contributes empirical evidence from an under-studied domain in the AI-supply chain literature, Nigeria's mobile manufacturing sector, and offers practical guidance for practitioners and policymakers pursuing AI-enabled supply chain transformation in emerging economies.
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Copyright (c) 2026 Dennis Ejike Onyishi, Conference Ekeutomhinye, Linda Chinelo Agbasianya, Chima Roland Obiora, Abdulquddus Olanrewaju Abdulyaqeen, Ayo David Adeyemi (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
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