A truly sustainable organization needs to take the economic, environmental and social dimensions of sustainability into account. Although the economic and environmental dimensions of sustainability have been examined by many scholars and practitioners, thus far, the social dimension has been received less attention in literature and in practice, in particular in developing countries. Social sustainability enables other sustainability initiatives and overlooking this dimension can have a serious adverse impact across supply chains. To address this issue, this study proposes a framework for investigating the social sustainability of supply chains in manufacturing companies. To show the applicability and efficiency of the proposed framework, a sample of 38 experts was used to evaluate and prioritize social sustainability criteria, using a multi-criteria decision-making method called the ‘best worst method’ (BWM). The criteria are ranked according to their average weight obtained through BWM. The respondents view ‘contractual stakeholders influence’ as the most important social sustainability criterion. The results of this study help industry managers, decision-makers and practitioners decide where to focus their attention during the implementation stage, to increase social sustainability in their organizational supply chain and move towards sustainable development.

Assessing the social sustainability of supply chains using Best Worst Method

Sustainability is hinged on innovation. The importance of sustainable innovation management in sustainable supply chain management (SSCM) cannot be underestimated. Studies on SSCM have emphasised t...

A supply chain sustainability innovation framework and evaluation methodology

The supplier selection plays an important role in supplier chain management. How to evaluate the performance of suppliers is still an open issue. Multi-criteria decision-making (MCDM), due to its ability of solving multi-source information problem, has become a quite effective tool. Currently, the analytic network process (ANP) and Entropy weight are employed to solved MCDM problems. However, these techniques ignore the one-sidedness of the single weighting method and cannot deal with the uncertainties of input data. In this paper, a new evidential ANP methodology based on game theory is proposed to efficiently address supplier management under uncertain environment. First, ANP and entropy weight are employed to obtain the subjective and objective weights of criteria. Second, based on decision-making trial and evaluation laboratory (DEMATEL) and game theory, the comprehensive weight of ANP and entropy weight can be determined. Game theory is employed to combine the merits of subjective weight and objective weight, and DEMATEL is adopted to adjust the weight of criteria to make the result more reasonable. Finally, evidence theory is adopted to deal with the uncertainties of input data and get the supplier selection result. A case study is given to demonstrate the proposed modeling process. By comparing with the existing methods, we demonstrate that the proposed model has many advantages and it shows the efficiency and rationality in supplier selection problem.

Evidential Supplier Selection Based on DEMATEL and Game Theory

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their de...

/pdf/social-sustainable-supplier-evaluation-and-selection-a-group-49jwn1fip0.pdf

Social sustainable supplier evaluation and selection: a group decision-support approach

Multicriteria decision making (MCDM) has become one of the most frequently applied decision making methodologies in various fields. However, uncertainty is inevitably involved in the process of MCDM due to the subjectivity of humans. To address this issue, a novel evidential fuzzy MCDM method, called EFMCDM, is proposed by integrating Dempster–Shafer theory with belief entropy. In particular, each criterion can be modeled as evidence, and all the alternatives compose the frame of discernment in the framework of Dempster–Shafer theory. To generate more appropriate basic probability assignments (BPAs) of the criteria, the EFMCDM method considers both the subjective and objective weighting of the criteria that are leveraged in MCDM problems. Thereafter, the classic Dempster's rule of combination is leveraged to fuse the multiple pieces of evidence into composite evidence. On this basis, the alternatives are ranked to determine the optimal alternative. In addition, the EFMCDM method can quantitatively model uncertainty and help to decrease the uncertainty caused by subjective human cognition to improve decision making. Finally, the rationality, effectiveness, and robustness of the EFMCDM method are demonstrated through experimental evaluations.

EFMCDM: Evidential Fuzzy Multicriteria Decision Making Based on Belief Entropy

Supplier selection is one of the critical problems in supply chain systems. Within the last decades, by the emergence of sustainability concept, companies have been motivated to enhance their supplier’s sustainability and move toward sustainable development. This paper proposes a structured and integrated decision model for evaluating sustainable suppliers in the context of telecom industry by combining analytical hierarchy process (AHP) and improved grey relational analysis (IGRA) approaches. The proposed model employs AHP for calculating sustainability criteria weights and IGRA for ranking suppliers. Moreover, a sensitivity analysis is also performed to demonstrate the robustness of the model. In this research, the sustainable supplier selection problem of the telecom industry in the southern part of Iran was investigated, showing the effectiveness and applicability of this proposed integrated approach.

Xuping Wang

Papers

Integrating sustainability into supplier selection with analytical hierarchy process and improved grey relational analysis: a case of telecom industry