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Digital Twins and AI Predictive Analytics: Enhancing Predictive Logistics Capabilities for Operational and Sustainable Supply Chain Performance in African Contexts

Domain:

digital infrastructuresocioeconomic

Record type:

paper
Creator:
BouEL KADIRI Kenza
Publisher:
Alt
Host:avatar
This study examines how Digital Twin adoption and AI-based predictive analytics influence predictive logistics capabilities, which in turn drive operational and sustainable supply chain performance among African firms. Drawing on Dynamic Capabilities Theory and Resource-Based View, a mediated structural model is tested using PLS-SEM on survey data from 250 supply chain managers across Morocco, South Africa, Kenya, and Nigeria. Results confirm significant direct effects of Digital Twins (β=0.42, p<0.01) and AI analytics (β=0.38, p<0.01) on predictive capabilities, with full mediation to performance outcomes (R²=0.67 for operational, 0.59 for sustainable). Findings underscore technology-driven resilience in emerging markets, offering implications for logistics practitioners and policymakers.​

Visit

doi.orgrevues.imist.ma

Licenses

Creative Commons Attribution Non Commercial 4.0 Internationalhttps://creativecommons.org/licenses/by-nc/4.0/legalcode

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