Three-way group decisions under hesitant fuzzy linguistic environment for green supplier selection

Ma, Weimin; Lei, Wenjing; Sun, Baiqing

doi:10.1108/k-09-2019-0602

Cited by 24 publications

(11 citation statements)

References 52 publications

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“…In [175], a group consensus decision-making model was developed to help choosing the best green supplier for electronics manufacturing. Ma et al [176] proposed a three-way group decision-making approach to address the selection of the green supplier by extending the decision-theoretic rough sets into hesitant fuzzy linguistic environment. Chen et al [177] applied the six sigma quality indices to the evaluation of suppliers based on their process yields and quality levels.…”

Section: Other Supplier Selection Methodsmentioning

confidence: 99%

“…Moreover, the interval type-2 fuzzy sets and the intuitionistic fuzzy sets are also frequently used by researchers to deal with the vagueness and uncertainty of performance evaluations in GSES, which have appeared in 10 and 9 articles, respectively. Considering that decision makers incline to give their opinions with linguistic expressions, some linguistic computing methods have been utilized in the green supplier evaluation process recently, which include the intervalvalued intuitionistic uncertain linguistic set [62,91,156], the hesitant fuzzy linguistic term set [174,176], the cloud model theory [79,138], and the interval 2-tuple linguistic variable [147].…”

Section: Green Supplier Evaluation Methodsmentioning

confidence: 99%

“…Green manufacturing [17,19,23,31,37,43,49,51,52,66,77,79,85,95,117,124,125,132,133,141,143,151,157,173,175,176,184,189,191,197] 30 Green packing and labeling [19, 21, 27, 30, 32, 51, 52, 58, 72-74, 77, 79, 85, 112, 124, 135, 146, 152, 168, 181, 195] 22 Green certifications [20, 25, 30, 32, 33, 42, 43, 55, 77, 81, 85, 99, 113, 118, 124, 136, 138, 139, 146, 151, 152, 161-163, 174, 175, 189, 191, 195, 204] 30 Green logistics …”

Section: Green Competenciesmentioning

confidence: 99%

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Green Supplier Evaluation and Selections: A State-of-the-Art Literature Review of Models, Methods, and Applications

Zhang

Liu

et al. 2020

Mathematical Problems in Engineering

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The role of green supplier evaluation and selection (GSES) in supply chain management is increasingly appreciated due to the intensification of competition, raising public consciousness, and environmental issues. To improve GSES, a large number of approaches have been proposed in the past decades. However, few attempts have been made to systematically review and classify the literature in this field. The objective of this study is to afford a comprehensive review of the studies which aim to develop models and methods in helping enterprises to assess and select the right green suppliers. To achieve this goal, a total of 193 journal articles extracted from the Scopus database over the period of 2009 to 2020 were chosen and reviewed. These publications were classified into ten categories based on their adopted GSES models and analyzed concerning the evaluation criteria, criteria weighting methods, and performance evaluation methods. Moreover, a bibliometric analysis was conducted according to the frequency of supplier selection methods, citation number, publication year, journal, country, and application area. This study supports practitioners, managers, and researchers in effectively recognizing and applying the GSES models to enhance organizational competitiveness and provides an insight into its state of the art.

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Section: Other Supplier Selection Methodsmentioning

confidence: 99%

Section: Green Supplier Evaluation Methodsmentioning

confidence: 99%

Section: Green Competenciesmentioning

confidence: 99%

See 1 more Smart Citation

Green Supplier Evaluation and Selections: A State-of-the-Art Literature Review of Models, Methods, and Applications

Zhang

Liu

et al. 2020

Mathematical Problems in Engineering

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“…Sen et al (2018) applied intuitionistic-TOPSIS, intuitionisticmulti-objective optimization method by ratio analysis (MOORA) and intuitionistic-GRA. Ma et al (2020) proposed an extension of the rough set into the hesitant fuzzy linguistic set to SVS. Liang and Chong (2019) adopted hesitant fuzzy qualitative flexible multiple criteria (QUALIFLEX) for green SS for a mega project in China.…”

Section: Sustainable Vendor Assessmentmentioning

confidence: 99%

A stochastic fuzzy multi-criteria group decision-making for sustainable vendor selection in Indian petroleum refining sector

Akhtar

Ahmad

2021

BIJ

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PurposeThis paper aims to select key criteria for sustainable vendor assessment and spare-parts supplies in the Indian petroleum refining sector using stochastic fuzzy technique for order of preference by similarity to ideal solution (SFTOPSIS).Design/methodology/approachThe criteria for sustainable vendor evaluation and selection are identified from the review of the literature and further; it is finalized using the Delphi method. Eight supply chain (SC) experts from the Indian petro refining sector were identified as having more than five years of experience and agreed to participate in this study (known as decision-makers (DM)). Five vendors supplying spare-parts are shortlisted from the market with the discussion and consent of procurement experts from petroleum refineries. Subsequently, criteria and vendors are rated based on relative importance in linguistic terms from the group of eight DMs. As ratings involve uncertainties in the decision-making, the SFTOPSIS method is applied to determine criteria weight and vendor ranking at a distinct significance level (α). The ranking of the vendors is obtained for sustainable supply of spare-parts in the Indian petro refining sector using the SFTOPSIS method.FindingsThe ranking of sustainable vendors is obtained through the integrated application of the fuzzy and stochastic approach to capture the uncertainties in the ratings of DMs. The sensitivity analysis is carried out at distinct confidence limits of a normal distribution to obtain a robust ranking of the vendors. In this paper, a case application of SFTOPSIS in the Indian petro refining sector is presented in which key criteria and the vendor ranking are found to be changing with confidence limit for sustainable vendor evaluation.Practical implicationsThe fuzziness and randomness in relative ratings collects from a group of DMs are taken in the proposed methodology. The distinct approaches are compared with changing significance-level under stochastic, fuzzy and deterministic TOPSIS to acquire robustness in the ranking. The proposed SFTOPSIS model can be useful to practitioners from the petroleum sector.Originality/valueThe originality of the paper contributes to an application of the SFTOPSIS method that is the extension of FTOPSIS in the petro refining sector of a developing country. The sensitivity analysis with distinct significance-level shows the uncertainties in the collected ratings from the DMs that supports robustness in the ranking. It might be helpful for SC professionals from the petro refining sector, who assess the rank of the vendors at different confidence limits for sustainable supply of spare-parts. Further research in the petroleum industry from emerging economies needs to be undertaken to broaden its scope and applicability.

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“…Gao et al [ 9 ] suggested an innovative probabilistic linguistic consensus decision framework based on the consensus measure and feedback mechanism to choose the optimal green supplier. Ma et al [ 10 ] brought a three-way group decision methodology by extending a decision–theoretic rough set into hesitant fuzzy linguistics to evaluate the most-satisfying supplier. Further, in order to comprehensively analyze the literature on green supplier selection, Zhang et al [ 11 ] developed a comprehensive overview of green supplier evaluation and selection through summarizing and analyzing the research from 2009 to 2020 and providing some novel research directions and challenges.…”

Section: Introductionmentioning

confidence: 99%

Fermatean Fuzzy Schweizer–Sklar Operators and BWM-Entropy-Based Combined Compromise Solution Approach: An Application to Green Supplier Selection

Wei

Meng

Run-zhang

et al. 2022

Entropy

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The Fermatean fuzzy set (FFS) is a momentous generalization of a intuitionistic fuzzy set and a Pythagorean fuzzy set that can more accurately portray the complex vague information of elements and has stronger expert flexibility during decision analysis. The Combined Compromise Solution (CoCoSo) approach is a powerful decision-making technique to choose the ideal objective by fusing three aggregation strategies. In this paper, an integrated, multi-criteria group-decision-making (MCGDM) approach based on CoCoSo and FFS is used to assess green suppliers. To begin, several innovative operations of Fermatean fuzzy numbers based on Schweizer–Sklar norms are presented, and four aggregation operators utilizing the proposed operations are also developed. Several worthwhile properties of the advanced operations and operators are explored in detail. Next, a new Fermatean fuzzy entropy measure is propounded to determine the combined weight of criteria, in which the subjective and objective weights are computed by an improved best-and-worst method (BWM) and entropy weight approach, respectively. Furthermore, MCGDM based on CoCoSo and BWM-Entropy is brought forward and employed to sort diverse green suppliers. Lastly, the usefulness and effectiveness of the presented methodology is validated by comparison, and the stability of the developed MCGDM approach is shown by sensitivity analysis. The results shows that the introduced method is more stable during ranking of green suppliers, and the comparative results expound that the proposed method has higher universality and credibility than prior Fermatean fuzzy approaches.

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Three-way group decisions under hesitant fuzzy linguistic environment for green supplier selection

Cited by 24 publications

References 52 publications

Green Supplier Evaluation and Selections: A State-of-the-Art Literature Review of Models, Methods, and Applications

Green Supplier Evaluation and Selections: A State-of-the-Art Literature Review of Models, Methods, and Applications

A stochastic fuzzy multi-criteria group decision-making for sustainable vendor selection in Indian petroleum refining sector

Fermatean Fuzzy Schweizer–Sklar Operators and BWM-Entropy-Based Combined Compromise Solution Approach: An Application to Green Supplier Selection

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