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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">PBES</journal-id><journal-title-group><journal-title>Proceedings of Business and Economic Studies</journal-title></journal-title-group><issn>2209-2641</issn><eissn>2209-265X</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/pbes.v8i3.11187</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Evaluation of Resilient Suppliers Based on the Improved Z-number - ORESTE Method</title><url>https://artdesignp.com/journal/PBES/8/3/10.26689/pbes.v8i3.11187</url><author>TangLeyi,GengXiuli</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>8</volume><issue>3</issue><history><date date-type="pub"><published-time>2025-07-15</published-time></date></history><abstract>Objective: Existing research mainly relies on quantitative indicators. However, the subjectivity of qualitative indicators and the problem of their difficulty in quantification limit the comprehensiveness of evaluation. Therefore, a resilience supplier evaluation method based on the improved Z-number-ORESTE is proposed. Methods: Through the construction of a multi-tiered evaluation index system incorporating supplier capabilities, resources, strategic aspects, and resilience, Z-numbers are harnessed to signify qualitative indicators. An advanced Z-number distance metric is implemented, meticulously considering the impact exerted by the reliability portion of Z-numbers on information risk. The refined ORESTE ranking algorithm introduces the concepts of strong and weak orderings and capitalizes on the Borda assignment function. This approach facilitates a more precise appraisal of the performance of alternative solutions. By amalgamating the improved Z-number distance measurement approach with the ORESTE ranking methodology for multi-attribute decision-making, it becomes feasible to more efficiently assess the recovery capacities and adaptability of suppliers in the face of unforeseen incidents and risks. Results: Through the analysis of the comprehensive performance of the existing suppliers of a certain electronics enterprise, the results regarding the suppliers’ recovery capabilities and adaptability when facing unexpected events and risks are obtained. Eventually, the suppliers that are in line with the long-term development strategy of the enterprise are selected. Conclusion: This evaluation system has verified its feasibility and effectiveness. Moreover, the system is capable of effectively identifying and selecting resilient suppliers, providing more reliable decision-making support for the enterprise’s supply chain management.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Nazari-Shirkouhi S, Tavakoli M, Govindan K, et al., 2023, A Hybrid Approach Using Z-Number DEA Model and Artificial Neural Network for Resilient Supplier Selection. 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