Explainable Analytics for Operational Research

K. de Bock (), K. Coussement and A. de Caigny
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K. de Bock: Audencia Business School

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Abstract: The steep rise of analytics and AI in Operational Research (OR) is reflected by its increasing number of academic publications (Hindle et al. 2020) as well as the excitement amongst commercial organizations, governments, and communities to create value from their data. In this feature cluster, we invited authors to submit high-quality contributions addressing theoretical and algorithmic developments advancing the theory and methodology of explainable analytics and AI within OR, as well as real-world innovative implementations in business and society in areas as marketing and sales, supply chain management, education, production and service operations, medicine, bioinformatics, (financial) risk, and fraud.

Keywords: explainable AI; XAI; explainable analytics; interpretabability (search for similar items in EconPapers)
Date: 2024-09
Note: View the original document on HAL open archive server: https://hal.science/hal-04571846
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Published in European Journal of Operational Research, 2024, 317 (2), ⟨10.1016/j.ejor.2024.04.015⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04571846

DOI: 10.1016/j.ejor.2024.04.015

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