An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics

Green supply chain management considers the environmental effects of all activities related to the supply chain, from obtaining raw materials to the final delivery of finished goods. Selecting the right supplier is a critical decision in green supply chain management. We propose a fuzzy green suppli...

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Bibliographic Details
Published in:Environmental science and pollution research international 2021-10, Vol.28 (38), p.53953-53982
Main Authors: Tavana, Madjid, Shaabani, Akram, Santos-Arteaga, Francisco J., Valaei, Naser
Format: Article
Language:English
Subjects:
Aquatic Pollution
Asphalt
Atmospheric Protection/Air Quality Control/Air Pollution
Case studies
Component and supplier management
Criteria
Earth and Environmental Science
Ecotoxicology
Entropy (Information theory)
Environment
Environmental Chemistry
Environmental effects
Environmental Health
Environmental management
Environmental science
Evaluation
Manufacturing industry
Multiple objective analysis
Optimization
Ranking
Raw materials
Research Article
Reverse logistics
Suppliers
Supply chain management
Supply chain sustainability
Supply chains
Waste Water Technology
Water Management
Water Pollution Control
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Summary:Green supply chain management considers the environmental effects of all activities related to the supply chain, from obtaining raw materials to the final delivery of finished goods. Selecting the right supplier is a critical decision in green supply chain management. We propose a fuzzy green supplier selection model for sustainable supply chains in reverse logistics. We define a novel hierarchical fuzzy best-worst method (HFBWM) to determine the importance weights of the green criteria and sub-criteria selected. The fuzzy extension of Shannon’s entropy, a more complex evaluation method, is also used to determine the criteria weights, providing a reference comparison benchmark. Several hybrid models integrating both weighting techniques with fuzzy versions of complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA), and the technique for order of preference by similarity to ideal solution (TOPSIS) are designed to rank the suppliers based on their ability to recycle in reverse logistics. We aggregate these methods’ ranking results through a consensus ranking model and illustrate the capacity of relatively simple methods such as fuzzy COPRAS and fuzzy MOORA to provide robust rankings highly correlated with those delivered by more complex techniques such as fuzzy MULTIMOORA. We also find that the ranking results obtained by these hybrid models are more consistent when HFBWM determines the weights. A case study in the asphalt manufacturing industry is presented to demonstrate the proposed methods’ applicability and efficacy.
ISSN:0944-1344
1614-7499
1614-7499
DOI:10.1007/s11356-021-14302-w