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Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach

Li, Jing, Fang, Hong, Song, Wenyan
Journal of cleaner production 2019 v.222 pp. 606-621
case studies, decision making, fuzzy logic, mathematical theory, social benefit, solar collectors, stakeholders, supply chain, uncertainty
With the increased sustainable awareness and pressures from stakeholders, enterprises have realized the importance to implement sustainable supply chain management (SSCM) practices to pursue economic, environmental, and social benefits. In this paper, a novel framework is proposed, which identifies SSCM practices as the evaluation criteria for supplier evaluation. Because vague and subjective information often exists in decision-making of supplier evaluation, fuzzy-based approaches are frequently used to manipulate such vagueness and subjectivity. However, the previous fuzzy methods do not consider randomness in decision making and they require prior information. Thus, an extended TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method is developed in this paper for sustainable supplier selection, which integrates the advantage of cloud model theory in manipulating uncertainty of randomness (intrapersonal uncertainty) and the merit of rough set theory in flexibly handling interpersonal uncertainty without extra information. Additionally, an integrated weighting method considering both subjective and objective weights is proposed to determine comprehensive weights of criteria. Finally, a case study of sustainable photovoltaic modules supplier selection is conducted to show the effectiveness of the proposed method.