An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection

Author(s):  
Babak Aslani ◽  
Meysam Rabiee ◽  
Madjid Tavana
2019 ◽  
Vol 11 (10) ◽  
pp. 2820 ◽  
Author(s):  
Xiaodong Wang ◽  
Jianfeng Cai ◽  
Jichang Xiao

Sustainable supplier selection has become a strategic activity to enhance the competitiveness of sustainable supply chain management. Research on sustainable supplier selection is considering increasingly more practical factors, such as the uncertainty of decision context and the fuzzy recognition of experts. Evaluation values on different criteria with different characteristic should be represented in their suitable information types to reflect the characteristic accurately and represent experts’ judgments entirely. Moreover, it is difficult, or costly, to build a decision criteria set in which all criteria are independent to each other because of the interaction of technical, economic, environmental and social factors. Therefore, the aim of this paper is to propose a novel decision-making framework for sustainable supplier selection which considers the interaction among criteria with heterogeneous decision information. The proposed framework can not only allow the experts to express their judgments completely, but also improve the efficiency of decision-making. First, a normalized dominance decision matrix based on normalized closeness is built with the heterogeneous decision matrix. Then, a defined discrete Choquet integral multi-criteria distance measure is used to compute the comprehensive associated closeness and rank the alternative sustainable suppliers. This framework provides a new way to handle the interaction among criteria for sustainable supplier selection from the perspective of multi-criteria distance measure, and a novel methodology to solve the problems that the evaluation values cannot be aggregated directly. Finally, an example is given to illustrate the proposed framework for sustainable supplier selection with a comparison analysis.


2019 ◽  
Vol 11 (19) ◽  
pp. 5413 ◽  
Author(s):  
Patchara Phochanikorn ◽  
Chunqiao Tan

The increase of environmental pollution has led to the rise of sustainable awareness in recent years. This trend has motivated various industries to recognize the importance of implementing sustainable supply chain practices to seek economic, environmental and social advantages. From a sustainability perspective, selecting a suitable supplier is the main component of modern enterprises. It is also a challenging problem since several criteria concerning supplier selection are interdependent with a complex character. Therefore, the contribution of this paper is a new extension to multi-criteria decision-making model (MCDM) under an intuitionistic fuzzy environment for sustainable supplier selection (SSS) based on sustainable supply chain management SSCM practices. It consists of intuitionistic fuzzy set theory (IFS) with a decision making trial and evaluation laboratory (DEMATEL) combined with an analytic network process (ANP) to identify uncertainties and interdependencies among criteria as well as analyzing the criteria weights. We modified Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to evaluate and rank the desired level of sustainable supplier performance. The suggested approach is conducted by a case study from the Thailand palm oil industry. Results show that the proposed model not only can find the most suitable sustainable supplier, but also the enterprises can aid their suppliers in improving sustainability by using the proposed method and can improve enterprises’ socio-environmental performance, which is key to achieving sustainable development.


2020 ◽  
Vol 26 (3) ◽  
pp. 573-598 ◽  
Author(s):  
Juan-juan Peng ◽  
Chao Tian ◽  
Wen-yu Zhang ◽  
Shuai Zhang ◽  
Jian-qiang Wang

Sustainable supplier selection (SSS) is an important part of sustainable supply chain management (SSCM). In this paper, an integrated multi-criteria decision-making (MCDM) framework, based on the picture fuzzy exponential entropy, and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method, is proposed to manage SSS problems. Firstly, the evaluation criteria of SSS, including economic, environmental and social, is established. This can be evaluated in the form of the actual data or linguistic terms provided by suppliers and experts respectively in an actual decision-making process. Then, according to the translated scales, all the evaluation information can be converted into picture fuzzy numbers (PFNs). Secondly, the picture fuzzy exponential entropy is defined. Moreover, based on the entropy’s minimization principle, the defined picture fuzzy exponential entropy is used to determine the weight of the SSS’s criteria. Thirdly, the extended VIKOR method, which combines the grey correlation coefficient, is utilized to select a suitable supplier. This method avoids the shortcomings of the traditional VIKOR method in data mining and solves the conflict between SSS criteria. Finally, the feasibility and effectiveness of the proposed integrated decision framework are verified by an experiment, as well as a sensitivity analysis and comparative analysis.


2018 ◽  
Vol 10 (8) ◽  
pp. 2622 ◽  
Author(s):  
Huiyun Lu ◽  
Shaojun Jiang ◽  
Wenyan Song ◽  
Xinguo Ming

With the growing awareness of environmental and social issues, sustainable supply chain management (SSCM) has received considerable attention both in academia and industry. Supplier selection plays an important role in the successful implementation of sustainable supply chain management, because it can influence the performance of SSCM. Sustainable supplier selection is a typical multi-criteria decision-making problem involving subjectivity and vagueness. Although some previous researches of supplier selection use fuzzy approaches to deal with vague information, it has been criticized for requiring much priori information and inflexibility in manipulating vagueness. Moreover, the previous methods often omit the environmental and social evaluation criteria in the supplier selection. To manipulate these problems, a new approach based on the rough set theory and ELECTRE (ELimination Et Choix Traduisant la REalité) is developed in this paper. The novel approach integrates the strength of rough set theory in handling vagueness without much priori information and the merit of ELECTRE in modeling multi-criteria decision-making problem. Finally, a case study of sustainable supplier selection for solar air-conditioner manufacturer is provided to demonstrate the application and potential of the approach.


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