{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:49:22Z","timestamp":1776336562468,"version":"3.51.2"},"reference-count":40,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T00:00:00Z","timestamp":1681171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"university of Jeddah, Jeddah, Saudi Arabia","award":["UJ\u201421\u2014ICL\u20143"],"award-info":[{"award-number":["UJ\u201421\u2014ICL\u20143"]}]},{"name":"university of Jeddah, Jeddah, Saudi Arabia","award":["IIP#1849213"],"award-info":[{"award-number":["IIP#1849213"]}]},{"name":"university of Jeddah, Jeddah, Saudi Arabia","award":["DRL-2026584"],"award-info":[{"award-number":["DRL-2026584"]}]},{"name":"NSF-EPSCoR-RII Track-1: Kentucky Advanced Manufacturing Partnership for Enhanced Robotics and Structures","award":["UJ\u201421\u2014ICL\u20143"],"award-info":[{"award-number":["UJ\u201421\u2014ICL\u20143"]}]},{"name":"NSF-EPSCoR-RII Track-1: Kentucky Advanced Manufacturing Partnership for Enhanced Robotics and Structures","award":["IIP#1849213"],"award-info":[{"award-number":["IIP#1849213"]}]},{"name":"NSF-EPSCoR-RII Track-1: Kentucky Advanced Manufacturing Partnership for Enhanced Robotics and Structures","award":["DRL-2026584"],"award-info":[{"award-number":["DRL-2026584"]}]},{"name":"NSF","award":["UJ\u201421\u2014ICL\u20143"],"award-info":[{"award-number":["UJ\u201421\u2014ICL\u20143"]}]},{"name":"NSF","award":["IIP#1849213"],"award-info":[{"award-number":["IIP#1849213"]}]},{"name":"NSF","award":["DRL-2026584"],"award-info":[{"award-number":["DRL-2026584"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JTAER"],"abstract":"<jats:p>Multi-criteria ABC classification is a useful model for automatic inventory management and optimization. This model enables a rapid classification of inventory items into three groups, having varying managerial levels. Several methods, based on different criteria and principles, were proposed to build the ABC classes. However, existing ABC classification methods operate as black-box AI processes that only provide assignments of the items to the different ABC classes without providing further managerial explanations. The multi-criteria nature of the inventory classification problem makes the utilization and the interpretation of item classes difficult, without further information. Decision makers usually need additional information regarding important characteristics that were crucial in determining the managerial classes of the items because such information can help managers better understand the inventory groups and make inventory management decisions more transparent. To address this issue, we propose a two-phased explainable approach based on eXplainable Artificial Intelligence (XAI) capabilities. The proposed approach provides both local and global explanations of the built ABC classes at the item and class levels, respectively. Application of the proposed approach in inventory classification of a firm, specialized in retail sales, demonstrated its effectiveness in generating accurate and interpretable ABC classes. Assignments of the items to the different ABC classes were well-explained based on the item\u2019s criteria. The results in this particular application have shown a significant impact of the sales, profit, and customer priority as criteria that had an impact on determining the item classes.<\/jats:p>","DOI":"10.3390\/jtaer18020044","type":"journal-article","created":{"date-parts":[[2023,4,12]],"date-time":"2023-04-12T03:49:17Z","timestamp":1681271357000},"page":"848-866","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["An Explainable Artificial Intelligence Approach for Multi-Criteria ABC Item Classification"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0066-2333","authenticated-orcid":false,"given":"Alaa Asim","family":"Qaffas","sequence":"first","affiliation":[{"name":"MIS Department, College of Business, University of Jeddah, Jeddah 23218, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0161-6646","authenticated-orcid":false,"given":"Mohamed-Aymen","family":"Ben HajKacem","sequence":"additional","affiliation":[{"name":"LARODEC Lab, ISG Tunis, University of Tunis, Le Bardo 2000, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4014-8264","authenticated-orcid":false,"given":"Chiheb-Eddine","family":"Ben Ncir","sequence":"additional","affiliation":[{"name":"MIS Department, College of Business, University of Jeddah, Jeddah 23218, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0999-5385","authenticated-orcid":false,"given":"Olfa","family":"Nasraoui","sequence":"additional","affiliation":[{"name":"Knowledge Discovery & Web Mining Lab, University of Louisville, Louisville, KY 40292, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,11]]},"reference":[{"key":"ref_1","first-page":"827274","article-title":"Multiple criteria ABC analysis with FCM clustering","volume":"2013","author":"Keskin","year":"2013","journal-title":"J. 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