scholarly journals Research on Sustainable Supplier Selection Based on the Rough DEMATEL and FVIKOR Methods

2020 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Jing Zhang ◽  
Dong Yang ◽  
Qiang Li ◽  
Benjamin Lev ◽  
Yanfang Ma
Keyword(s):  
Supplier Selection ◽  
Success Factors ◽  
Evaluation Criteria ◽  
Sustainable Supply Chain ◽  
Social Dimensions ◽  
Linguistic Terms ◽  
Critical Success ◽  
Sustainable Supplier Selection ◽  
Fuzzy Linguistic ◽  
Supplier Selection Problem

In competitive global markets, sustainable suppliers are critical success factors for sustainable supply chain operations. Sustainable supplier selection must be based on a complex network of numerous indicators and experts’ fuzzy linguistic terms. Considering the correlation between the evaluation criteria and the ambiguity of the criteria values, this paper proposes combining the rough DEMATEL method and the fuzzy VIKOR (FVIKOR) method to solve sustainable supplier selection problem. We determine 15 sustainable supplier evaluation criteria from economic, environmental and social dimensions. We also apply the rough DEMATEL method to determine the weight of evaluation indicators that are interrelated or even conflicting and use the FVIKOR method to determine supplier rankings by converting the fuzzy linguistic terms into precise information. The practicability of the proposed method is verified by an example of sustainable supplier selection.

scholarly journals AN INTEGRATED MULTI-CRITERIA DECISION-MAKING FRAMEWORK FOR SUSTAINABLE SUPPLIER SELECTION UNDER PICTURE FUZZY ENVIRONMENT

2020 ◽  
Vol 26 (3) ◽  
pp. 573-598 ◽  
Author(s):  
Juan-juan Peng ◽  
Chao Tian ◽  
Wen-yu Zhang ◽  
Shuai Zhang ◽  
Jian-qiang Wang
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Multi Criteria Decision Making ◽  
Sustainable Supply Chain ◽  
Vikor Method ◽  
Minimization Principle ◽  
Fuzzy Environment ◽  
Sustainable Supplier Selection ◽  
Exponential Entropy

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.

scholarly journals Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS)

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1152
Author(s):  
Pratibha Rani ◽  
Arunodaya Raj Mishra ◽  
Raghunathan Krishankumar ◽  
Abbas Mardani ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Fuzzy Set ◽  
Supplier Selection ◽  
Assessment Method ◽  
Selection Problem ◽  
Assessment Process ◽  
Hesitant Fuzzy Set ◽  
Uncertain Information ◽  
Sustainable Supply Chain ◽  
Sustainable Supplier Selection ◽  
Supplier Selection Problem

The selection of sustainable supplier is an extremely important for sustainable supply chain management (SSCM). The assessment process of sustainable supplier selection is a complicated task for decision experts due to involvement of several qualitative and quantitative criteria. As the uncertainty is commonly occurred in sustainable supplier selection problem and hesitant fuzzy set (HFS), an improvement of Fuzzy Set (FS), has been proved as one of the efficient and superior ways to express the uncertain information arisen in practical problems. The present study proposes a novel framework based on COPRAS (Complex Proportional Assessment) method and SWARA (Step-wise Weight Assessment Ratio Analysis) approach to evaluate and select the desirable sustainable supplier within the HFSs context. In the proposed method, an extended SWARA method is employed for determining the criteria weights based on experts’ preferences. Next, to illustrate the efficiency and practicability of the proposed methodology, an empirical case study of sustainable supplier selection problem is taken under Hesitant Fuzzy (HF) environment. Further, sensitivity analysis is performed to check the stability of the presented methodology. At last, a comparison with existing methods is conducted to verify the strength of the obtained result. The final outcomes confirm that the developed framework is more consistent and powerful than other existing approaches.

Analysing the critical success factors for implementation of sustainable supply chain management: an Indian case study

DECISION ◽  
2018 ◽  
Vol 45 (1) ◽  
pp. 3-25 ◽  
Author(s):  
Dayal S. Prasad ◽  
Rudra P. Pradhan ◽  
Kunal Gaurav ◽  
Partha P. Chatterjee ◽  
Inderpal Kaur ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Critical Success Factors ◽  
Success Factors ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Sustainable Supply Chain Management ◽  
Critical Success

A multi-objective optimization model for sustainable supply chain network with using genetic algorithm

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Ehtesham Rasi ◽  
Mehdi Sohanian
Keyword(s):  
Supply Chain ◽  
Performance Indicators ◽  
Supplier Selection ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Sustainability Performance ◽  
Multi Objective ◽  
Sustainable Supplier Selection

Purpose The purpose of this paper is to design and optimize economic and environmental dimensions in a sustainable supply chain (SSC) network. This paper developed a mixed-integer linear programing (MILP) model to incorporate economical and environmental data for multi-objective optimization of the SSC network. Design/methodology/approach The overall objective of the present study is to use high-quality raw materials, at the same time the lowest amount of pollution emission and the highest profitability is achieved. The model in the problem is solved using two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system. Findings The differences found between the genetic algorithms (GAs) and the MILP approaches can be explained by handling the constraints and their various logics. The solutions are contrasted with the original crisp model based on either MILP or GA, offering more robustness to the proposed approach. Practical implications The model is applied to Mega Motor company to optimize the sustainability performance of the supply chain i.e. economic (cost), social (time) and environmental (pollution of raw material). The research method has two approaches, namely, applied and mathematical modeling. Originality/value There is limited research designing and optimizing the SSC network. This study is among the first to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system.

Cognitive biases in MCDM methods: an embedded filter proposal through sustainable supplier selection problem

2020 ◽  
Vol 33 (5) ◽  
pp. 947-963
Author(s):  
Nurcan Deniz
Keyword(s):  
Loss Aversion ◽  
Supplier Selection ◽  
Cognitive Biases ◽  
Status Quo ◽  
The Other ◽  
Selection Problem ◽  
Content Type ◽  
Sustainable Supplier Selection ◽  
Comparison Of The Results ◽  
Supplier Selection Problem

PurposeExpert evaluation is the backbone of the multi-criteria decision-making (MCDM) techniques. The experts make pairwise comparisons between criteria or alternatives in this evaluation. The mainstream research focus on the ambiguity in this process and use fuzzy logic. On the other hand, cognitive biases are the other but scarcely studied challenges to make accurate decisions. The purpose of this paper is to propose pilot filters – as a debiasing strategy – embedded in the MCDM techniques to reduce the effects of framing effect, loss aversion and status quo-type cognitive biases. The applicability of the proposed methodology is shown with analytic hierarchy process-based Technique for Order-Preference by Similarity to Ideal Solution method through a sustainable supplier selection problem.Design/methodology/approachThe first filter's aim is to reduce framing bias with restructuring the questions. To manipulate the weights of criteria according to the degree of expected status quo and loss aversion biases is the second filter's aim. The second filter is implemented to a sustainable supplier selection problem.FindingsThe comparison of the results of biased and debiased ranking indicates that the best and worst suppliers did not change, but the ranking of suppliers changed. As a result, it is shown that, to obtain more accurate results, employing debiasing strategies is beneficial.Originality/valueTo the best of the author's knowledge, this approach is a novel way to cope with the cognitive biases. Applying this methodology easily to other MCDM techniques will help the decision makers to take more accurate decisions.

Decision Mechanism for Supplier Selection Under Sustainability

2017 ◽  
Vol 16 (01) ◽  
pp. 87-115 ◽  
Author(s):  
Congjun Rao ◽  
Mark Goh ◽  
Junjun Zheng
Keyword(s):  
Evaluation System ◽  
Supplier Selection ◽  
Three Dimensions ◽  
Sustainable Supply Chain ◽  
Interval Numbers ◽  
Grey Correlation ◽  
Decision Mechanism ◽  
Correlation Degree ◽  
Sustainable Supplier Selection ◽  
Grey Correlation Degree

Against the backdrop of responsible economic development, sustainable supply chain management (SSCM) is key to achieving the sustainable development for enterprise and industry. In this regard, sustainable supplier selection is crucial in SSCM. By integrating the three dimensions of sustainability, economic, environmental and social, this paper presents a new evaluation system for supplier selection from a sustainability perspective. Specifically, we design a decision mechanism for sustainable supplier selection based on linguistic 2-tuple grey correlation degree. In this proposed mechanism, the hybrid attribute values whereby real numbers, interval numbers and linguistic fuzzy variables coexist are transformed into linguistic 2-tuples. A ranking method based on linguistic 2-tuple grey correlation degree is then presented to rank the suppliers. An application example is presented to highlight the implementation, availability and feasibility of the proposed decision making mechanism.

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