{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T12:40:09Z","timestamp":1780663209191,"version":"3.54.1"},"reference-count":77,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2018,3,12]],"date-time":"2018-03-12T00:00:00Z","timestamp":1520812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2018,3,12]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Performance assessment of green supply chain management (GSCM) requires a systematic approach because of its interdisciplinary and multi-objective nature. The purpose of this paper is to propose a model to the performance assessment of GSCM.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>A model is proposed, grounded on a literature review on GSCM performance, after which the causal relationships and prioritization of the sub-criteria are analyzed by fuzzy Decision Making Trial and Evaluation Laboratory technique in a company operating in the cement industry.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>An integrated holistic performance assessment model incorporating specifically six criteria and 21 sub-criteria is applied, which represents causal relationships and prioritization of sub-criteria.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>The proposed model can be generalized, because an integrative framework can be used in future empirical studies to analyze performance of GSCM. However, the causal relationships and prioritization among sub-criteria are analyzed based on the needs and capabilities of the individual company; therefore, the causal relationships found are company specific.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The proposed model can be hired and implemented by companies striving for GSCM. This model allows companies to assess their current GSCM performance, analyze causal relationships, and prioritize sub-criteria.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>Several studies have analyzed performance assessment in green supply chains; however, to the best of the authors\u2019 knowledge, no study has taken an approach to performance assessment in GSCM that combines environmental, economics\/financial, logistics, operational, organizational and marketing in the same framework. In addition, the cause-effect relationships identified will be the base for performance improvement.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/imds-03-2017-0121","type":"journal-article","created":{"date-parts":[[2018,1,22]],"date-time":"2018-01-22T07:23:03Z","timestamp":1516605783000},"page":"412-431","source":"Crossref","is-referenced-by-count":80,"title":["Fuzzy DEMATEL-based green supply chain management 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