Dubey, R, Gunasekaran, A and Papadopoulos, T (2024) Benchmarking operations and supply chain management practices using Generative AI: Towards a theoretical framework. Transportation Research Part E: Logistics and Transportation Review, 189. ISSN 1366-5545

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Abstract

Generative Artificial Intelligence (Gen AI) is an up-and-coming technological innovation that has the potential to revolutionise businesses and create significant value. Despite garnering excitement from some quarters, there are still people who are sceptical about its benefits and even fearful of its impact, particularly in the supply chain context, where it is not yet fully understood. To help academics and practitioners better understand the practical implications of Gen AI in benchmarking supply chain management practices, we propose a theoretical toolbox. This toolbox draws from ten popular organisational theories and provides a comprehensive framework for evaluating the usefulness of Gen AI. By expanding theoretical boundaries, the toolbox provides a deeper understanding of the practical applications of Gen AI for researchers and practitioners in supply chain management.

Item Type:	Article
Uncontrolled Keywords:	Generative AI; Benchmarking; Artificial Intelligence; Supply Chain Management; Organisational Theories; 0102 Applied Mathematics; 0103 Numerical and Computational Mathematics; 1507 Transportation and Freight Services; Logistics & Transportation
Subjects:	H Social Sciences > HF Commerce > HF5001 Business H Social Sciences > HF Commerce > HF5001 Business > HF5410 Marketing. Distribution of Products
Divisions:	Liverpool Business School
Publisher:	Elsevier
SWORD Depositor:	A Symplectic
Date Deposited:	29 Jul 2024 12:55
Last Modified:	29 Jul 2024 12:55
DOI or ID number:	10.1016/j.tre.2024.103689
URI:	https://researchonline.ljmu.ac.uk/id/eprint/23797

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