Factors Influencing the Adoption of AI-Enhanced Enterprise Resource Planning in Logistics

Beenish Ramzan

doi:10.52812/msbd.118

Authors

Beenish Ramzan Nanjing University of Aeronautics and Astronautics

DOI:

https://doi.org/10.52812/msbd.118

Keywords:

Artificial Intelligence, Enterprise Resource Planning, Logistics, Grey Relational Analysis, Analytical Ordinal Priority Approach

Abstract

This study aims to evaluate and prioritize the critical factors influencing the adoption of AI-enhanced Enterprise Resource Planning (ERP) systems within China’s logistics sector. A hybrid multi-criteria decision-making (MCDM) methodology is employed, integrating the Dynamic Grey Relational Analysis (DGRA) and the Analytical Ordinal Priority Approach (AOPA). Data were collected from 223 logistics professionals via a structured questionnaire, and the factors were ranked based on their distance to an ideal reference and their ordinally derived importance weights. We found Data Security & Privacy to be the most critical factor based on both models. We also found the strong convergence between DGRA and AOPA results confirms the robustness of the ranking. This study provides the first empirically validated, multi-model approach specifically designed to prioritize AI-enhanced ERP factors for the logistics industry.

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