Green supplier selection using multi-criterion decision making under fuzzy environment: A case study in automotive industry

Gupta, Shubham; Soni, Umang; Kumar, Girish

doi:10.1016/j.cie.2019.07.038

Cited by 194 publications

(132 citation statements)

References 85 publications

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“…The results showed that the best choice is purchasing feed. Gupta et al [29] developed a framework that is used to evaluate green supplier selection using an integrated FAHP with the other three techniques namely MABAC, WASPAS, and TOPSIS. The results indicate the optimal green supplier by three techniques are GS-1.…”

Section: Fuzzy Ahp Methodologymentioning

confidence: 99%

“…Even though AHP is commonly used, this algorithm cannot adequately resolve the inherent uncertainties and imprecisions associated with mapping decision maker's perceptions into exact numbers [16]. Hence, numerous previous studies have combined the fuzzy set theory with AHP to solve uncertain issues [26][27][28][29][30][31]. Zhü [32] proposed that fuzzy AHP (FAHP) cannot resolve uncertain questions.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Core Operation in Supply Chain Finance Ecosystem by Integrating the Fuzzy Algorithm and Hierarchical Framework

Lin¹

2020

IJCIS

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Supply chain finance (SCF), which has the key concept of the delivery of credit, is a new type of financial service that can enhance the financial efficiency of a supply chain. Using the transaction records from the core operations (CO) of the members, financers can provide a higher level of cash flow to the ecosystem. Moreover, financial sectors can upgrade their operations through SCF activities. However, while SCF services can help financial sectors improve their operations, there are many risks implied in SCF activities from CO to relative members. Therefore, this paper presents a novel model that applies a combination of triangular fuzzy numbers and the analytic hierarchy process (AHP) to the decision-making process to evaluate the decision behaviors regarding the preference the CO in the smartphone industry supply chain for financers in the SCF service. Academically, the FAHP-based decision-making framework can provide the decision makers and administrators of financial institutions with valuable guidance for measuring the optimal CO of the smartphone industry in the SCF ecosystem. Commercially, the proposed model could provide administrators with a useful tool to assess the optimal CO of the smartphone industry within the SCF ecosystem for financers.

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Section: Fuzzy Ahp Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Core Operation in Supply Chain Finance Ecosystem by Integrating the Fuzzy Algorithm and Hierarchical Framework

Lin¹

2020

IJCIS

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“…Feng et al [40] developed an integrated fuzzy grey TOPSIS method for supplier assessment and selection for a collaborative manufacturing company. Gupta et al [41] utilized an integrated fuzzy AHP with multi-attributive border approximation area comparison (MABAC), weighted aggregated sum-product assessment (WASPAS), and TOPSIS to find the most suitable green suppliers for the automotive industry.…”

Section: Fuzzy Theory In Supplier Selectionmentioning

confidence: 99%

Supplier Selection and Performance Evaluation for High-Voltage Power Film Capacitors in a Fuzzy Environment

et al. 2019

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Rapid advances in technology have shortened the upgrade and replacement cycles in industries such as electronics, household appliances, and communication technologies. Within these industries, high-voltage power film capacitors have become indispensable electrical components due to their good electrical performance and high reliability. The selection and evaluation of suppliers of these capacitors is therefore increasingly important. Suppliers play a crucial role in the electronics industry; the quality of their products determines the degree to which the quality of the final product can be guaranteed. Supplier quality also affects the ability of all the members in a supply chain to control costs. Evaluation by decision-makers is highly significant in the supplier selection process. However, when the opinions of multiple decision-makers are combined, issues such as cognitive differences, fuzzy linguistics, and uncertainty are common. This study presents a supplier performance index SPL and derives the estimates of the index SPL and its statistical properties. The proposed index is not only helpful for the accurate measurement of supplier performance; it can also reduce cognitive differences among evaluators in the decision-making process (that is, the sample variability associated with the Likert scale). Evaluation scores for each criterion for the linguistic labels are converted to triangular fuzzy numbers in order to reduce ambiguity. Subsequently, integrated crisp values are obtained by defuzzification in a fuzzy inference system. A real-world case study of the supplier selection of high-voltage power film capacitors is provided to illustrate the efficacy of the proposed method.

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“…4,5 The MABAC has a straightforward computational procedure, and a sound logic that displays the foundation of rational decision-making. 6,7 Because of its merits, the MABAC method has been extended and used to handle lots of realistic decision-making problems, such as medical treatment service matching, 8 failure mode and effect analysis, 5 supplier evaluation and selection, 9 university web pages evaluation, 7 public evaluation of shared bicycles, 10 nontraditional machining processes selection, 11 and material selection. 12 Therefore, it is natural to utilize the MABAC method to manage the UTAE problems involving comprehensive audit elements.…”

Section: Introductionmentioning

confidence: 99%

Undergraduate teaching audit and evaluation using an extended MABAC method under q ‐rung orthopair fuzzy environment

Gong

Luo

et al. 2020

Int J Intell Syst

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Undergraduate teaching audit and evaluation (UTAE) is a new type of evaluation pattern, which is extremely important for a university to improve its quality assurance system and enhance teaching quality. Selecting an optimal university for benchmarking through UTAE to promote the quality of teaching can be regarded as a complex multicriteria decision making (MCDM) problem. Furthermore, in the process of UTAE, experts' evaluations over the teaching quality of universities are often imprecise and fuzzy due to the subjective nature of human thinking. In this paper, we propose a new UTAE approach based on q-rung orthopair fuzzy sets and the multiattribute border approximation area comparison (MABAC) method for evaluating and selecting the best university for benchmarking. The introduced method deals with the linguistic assessments given by experts by using q-ROFSs, assigns the weights of audit elements based on the indifference threshold-based attribute ratio analysis method, and acquires the ranking of universities with an extended MABAC method. The feasibility and effectiveness of the proposed q-rung orthopair fuzzy MABAC method is demonstrated through a realistic UTAE example. Results show that the UTAE method being proposed is valid and practical for UTAE.

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Green supplier selection using multi-criterion decision making under fuzzy environment: A case study in automotive industry

Cited by 194 publications

References 85 publications

Optimal Core Operation in Supply Chain Finance Ecosystem by Integrating the Fuzzy Algorithm and Hierarchical Framework

Optimal Core Operation in Supply Chain Finance Ecosystem by Integrating the Fuzzy Algorithm and Hierarchical Framework

Supplier Selection and Performance Evaluation for High-Voltage Power Film Capacitors in a Fuzzy Environment

Undergraduate teaching audit and evaluation using an extended MABAC method under q ‐rung orthopair fuzzy environment

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