EMPIRICAL STUDY OF AI APPLICATIONS IN MINIMIZING SUPPLY CHAIN SHORTAGES DURING CRISES

Abstract

This study investigates the application of Artificial Intelligence (AI) to assist in ameliorating supply chain shortages due to crises, with emphasis upon the mediating mechanism of the supply chain agility. The study is based on Dynamic Capabilities Theory which provides a usable model under which AI assists the ability of a company to ameliorate shortages directly and indirectly through the development of agile operational capabilities. A quantitative survey based methodology has been used and data collected from 208 supply chain professionals in Industrial and Logistics sectors. The data has been analyzed by the SmartPLS technique of Structural Equation Modelling (PLS-SEM). The findings of this research, yield a direct equationally significant positive value attached to relationship between AI application and amelioration of supply chain shortages. Also, that supply chain agility is a significant partial mediator, implying inter alia that the effect of AI is to a considerable degree reliant upon the greater ability for a company to react and adapt, inter alia. There are implications gained in the study for managers with strong empirical evidence that investment in significant strategic AI development is not as opined by ne´ advocates a mere play in operational efficiency but an investment of serious import in resiliency in crises. Empirically, the study adds further credence to the building knowledge in operations management in its exploration of the ‘how’ of the performance gains of operation linked with AI, which it presents as the basis of a model suited to further exploration in future research which has a validity.