The Impact Of Generative Ai On Supply Chain Decision-Making: Examining The Role Of Data Quality And Ai Explainability

Farha Ghapar* ,
Selvarajah Janathan ,
Thirunavukkarasu Krishnasamy ,
Veera Pandiyan Kaliani Sundram ,
Mohd Firdaus Osman

Abstract

This study investigates the critical roles of data quality and AI explainability in leveraging Generative Artificial Intelligence (AI) for effective supply chain decision-making. High-quality data is essential for reliable AI outputs, ensuring accurate, timely, and comprehensive insights, while explainability enhances trust, transparency, and adoption of AI-generated recommendations. A quantitative research approach was utilized, gathering survey data from supply chain professionals across various industries. The findings demonstrated significant positive correlations between data quality, AI explainability, and the effectiveness of decision-making. Additionally, the interplay between these factors enhanced their combined influence, emphasizing the importance of addressing both aspects concurrently. The study contributes to the supply chain and AI literature by revealing their synergistic effects and providing new insights into optimizing AI-driven decision-making processes. Practical suggestions include establishing strong data governance frameworks and integrating explainable AI models. The research acknowledges limitations, such as sample size and the cross-sectional design, and proposes future research directions, including longitudinal studies and the examination of additional variables. This study highlights the transformative potential of Generative AI in supply chain operations and offers actionable insights for both practitioners and researchers.

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Publication Date

01 September 2026

Article Doi

https://doi.org/10.15405/epsbs.2026.09.52

eBook ISBN

-

Publisher

European Publisher

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Edition Number

1st Edition

Pages

1-1

Subjects

Accounting and Finance, Business and Management, Communication, Law and Governance

Cite this article as:

Ghapar*, F., Janathan, S., Krishnasamy, T., Kaliani Sundram, V. P., & Osman, M. F. (2026). The Impact Of Generative Ai On Supply Chain Decision-Making: Examining The Role Of Data Quality And Ai Explainability. In Y. Naoyuki, A. Peng Hwa, & J. Matthes (Eds.), GLY-Upcoming Volume: Innovating Together: The Convergence of Management, Communication, and The Digital Transformation, vol -. European Proceedings of Social and Behavioural Sciences (pp. 0-0). European Publisher. https://doi.org/10.15405/epsbs.2026.09.52

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