AI-Driven Supply Chain Transformation in Bangladesh: An Integrated Multitech Approach and Empirical Evaluation of Readiness to Adopt

Abstract

Bangladesh's industrial supply chains are spanning Ready-Made Garments, pharmaceuticals, FMCG, logistics sectors continue to be hampered by structural bottlenecks, information asymmetry, and siloed operations, even as global markets shift toward Industry 4.0/5.0 digital integration. While individual technologies such as Generative AI, blockchain, IoT, predictive analytics, and robotics have been studied separately, few frameworks integrate them into a single operational architecture, and no prior South Asian study has empirically compared adoption readiness across university students, academic faculty, and industry professionals. This study addresses that gap using a cross-sectional survey of 257 respondents, analyzed through the lens of the Technology Acceptance Model (TAM) and Resource-Based View (RBV). Results show high Perceived Usefulness (cost reduction, M=3.96; risk reduction, M=3.79) and strong Individual Readiness (M=3.99), positively correlated with usefulness (r=.665, p<.001). However, Organizational Readiness was markedly lower (M=3.26), driven by talent shortages (44.4%) and capital constraints (36.6%) - revealing an "Awareness-Execution Paradox" between individual enthusiasm and institutional capacity. Chi-square tests confirmed significant perception gaps between professionals and students on local AI awareness (p<.001) and integration ease (p=.049). The study proposes a five-layer Unified Multitech Smart Supply Chain Framework and offers practical implications for academia, industry, and policymakers seeking to accelerate digital supply chain transformation in Bangladesh.