{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T11:13:13Z","timestamp":1771067593301,"version":"3.50.1"},"reference-count":78,"publisher":"Emerald","issue":"15","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,9]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>As environmental protection and sustainable development become more widely recognized, greater emphasis has been placed on the significance of green supplier selection (GSS), which can support businesses both upstream and downstream in enhancing their environmental performance while preserving their strategic competitiveness. Therefore, this paper aims to propose a new framework to study GSS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>Firstly, this paper establishes a GSS evaluation criteria system including product competitiveness, green performance, quality of service and enterprise social responsibility. Secondly, based on the spherical fuzzy sets (SFSs), the Average Induction Ordered Weighted Averaging Operator-Criteria Importance Through Inter Criteria Correlation (AIOWA-CRITIC) method is used to determine the subjective and objective weights and the combination of weights are determined by game theory. In addition, the GSS framework is constructed by the Cumulative Prospect Theory-Technique for Order Preference by Similarity to Ideal Solution (CPT-TOPSIS) method. Finally, the validity and robustness of the framework is verified through sensitivity comparative and ablation analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>The results show that Y3 is the most promising green supplier in China. This study provides a feasible guidance for GSS, which is important for the greening process of the whole supply chain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>Under spherical fuzzy sets, AIOWA and CRITIC are used to determine weights of indicators. CPT and TOPSIS are combined to construct a decision model, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/k-04-2024-1110","type":"journal-article","created":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T03:21:42Z","timestamp":1725420102000},"page":"7868-7903","source":"Crossref","is-referenced-by-count":2,"title":["An integrated decision-making model for green supplier selection based on AIOWA-CRITIC and CPT-TOPSIS: a case study of China"],"prefix":"10.1108","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5301-6565","authenticated-orcid":true,"given":"Hui","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Management Engineering, Qingdao University of Technology , ,","place":["Qingdao, China"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3265-2369","authenticated-orcid":true,"given":"Chen","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Management Engineering, Qingdao University of Technology , ,","place":["Qingdao, China"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3706-431X","authenticated-orcid":true,"given":"Simeng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Management Engineering, Qingdao University of Technology , ,","place":["Qingdao, China"]}]}],"member":"140","published-online":{"date-parts":[[2024,9,5]]},"reference":[{"issue":"5","key":"2025120921572889700_ref001","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1080\/01969722.2022.2067633","article-title":"A fuzzy analysis approach to green-resilient supplier selection in electronic manufacturing systems","volume":"54","author":"Abedian","year":"2023","journal-title":"Cybernetics and 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