Sustainable supplier selection: A ranking model based on fuzzy inference system

By Atefeh Amindoust, Shamsuddin Ahmed, A. Saghafinia, Ardeshir Bahreininejad. Applied Soft Computing, 2012

571 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a3b973a887e878aa6dbf23b23e9a60ba228729a1

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In Management Information Systems

In Management Science and Operations Research

In Strategy and Management

Citations in the corpus

A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context (2015, methodology): “[3] proposed a supplier evaluation selection method based on the fuzzy inference system.”
Sustainable and Resilient Supply Chain Network Design under Disruption Risks (2014, unknown): “, [4–8]) and sustainable transportation (e.”
A supply chain sustainability innovation framework and evaluation methodology (2018, background): “Most studies regarding sustainability have focused on sustainable supply chain management (Bai and Sarkis 2010; Amindoust et al. 2012; Govindan, Khodaverdi, and Jafarian 2013; Azadi et al. 2015; Sarkis and Dhavale 2015; Economic (EC) Sustainable product cost reduction (EC1) Organisations ability to…”
Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process (2015, methodology): “…to increased pressure from government and different types of stakeholders for incorporating social responsibility issues in supply chain activities, few researchers have tried to incorporate social responsibility dimensions in supplier selection problem (Azadnia et al. 2013; Amindoust et al. 2012).”
Application of decision-making techniques in supplier selection: A systematic review of literature (2013, background): “Other Fuzzy preference relations Chen and Chao (2012) Fuzzy Fuzzy inference system Amindoust et al. (2012) Hybridization Fuzzy adaptive resonance theory Keskin et al. (2010)”