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Kiani Mavi R, Zarbakhshnia N, Kiani Mavi N, Kazemi S. Clustering sustainable suppliers in the plastics industry: A fuzzy equivalence relation approach. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 345:118811. [PMID: 37659368 DOI: 10.1016/j.jenvman.2023.118811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 08/03/2023] [Accepted: 08/11/2023] [Indexed: 09/04/2023]
Abstract
Nowadays, pure economic supply chain management is not commonly contemplated among companies (especially buyers), as recently novel dimensions of supply chains, e.g., environmental, sustainability, and risk, play significant roles. In addition, since companies prefer buying their needs from a group of suppliers, the problem of supplier selection is not solely choosing or qualifying a supplier from among others. Buyers, hence, commonly assemble a portfolio of suppliers by looking at the multi-dimensional pre-determined selection criteria. Since sustainable supplier selection criteria are often assessed by linguistic terms, an appropriate clustering approach is required. This paper presents an innovative way to implement fuzzy equivalence relation to clustering sustainable suppliers through developing a comprehensive taxonomy of sustainable supplier selection criteria, including supply chain risk. Fifteen experts participated in this study to evaluate 20 suppliers and cluster them in the plastics industry. Findings reveal that the best partitioning occurs when the suppliers are divided into two clusters, with 4 (20%) and 16 (80%) suppliers, respectively. The four suppliers in cluster one are performing better in terms of the capability of supplier/delivery, service, risk, and sustainability criteria such as environment protection/management, and green innovation. These factors are critical in clustering and selecting sustainable suppliers. The originality of this study lies in developing an all-inclusive set of criteria for clustering sustainable suppliers and adding risk factors to the conventional supplier selection criteria. In addition to partitioning the suppliers and determining the best-performing ones, this study also highlights the most influential factors by analysing the suppliers in the best cluster.
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Affiliation(s)
- Reza Kiani Mavi
- School of Business and Law, Edith Cowan University, Joondalup, WA, 6027, Australia.
| | - Navid Zarbakhshnia
- Department of Management, Monash Business School, Monash University, Caulfield, Victoria, Australia
| | - Neda Kiani Mavi
- School of Business and Law, Edith Cowan University, Joondalup, WA, 6027, Australia
| | - Sajad Kazemi
- Doctoral Student, Graduate School of Management, Saint Petersburg State University, Russia
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Asghar A, Khan KA, Albahar MA, Alammari A. An optimized multi-attribute decision-making approach to construction supply chain management by using complex picture fuzzy soft set. PeerJ Comput Sci 2023; 9:e1540. [PMID: 37705663 PMCID: PMC10495944 DOI: 10.7717/peerj-cs.1540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 07/25/2023] [Indexed: 09/15/2023]
Abstract
Supplier selection is a critical decision-making process for any organization, as it directly impacts the quality, cost, and reliability of its products and services. However, the supplier selection problem can become highly complex due to the uncertainties and vagueness associated with it. To overcome these complexities, multi-criteria decision analysis, and fuzzy logic have been used to incorporate uncertainties and vagueness into the supplier selection process. These techniques can help organizations make informed decisions and mitigate the risks associated with supplier selection. In this article, a complex picture fuzzy soft set (cpFSS), a generalized fuzzy set-like structure, is developed to deal with information-based uncertainties involved in the supplier selection process. It can maintain the expected information-based periodicity by introducing amplitude and phase terms. The amplitude term is meant for fuzzy membership, and the phase term is for managing its periodicity within the complex plane. The cpFSS also facilitates the decision-makers by allowing them the opportunity to provide their neutral grade-based opinions for objects under observation. Firstly, the essential notions and set-theoretic operations of cpFSS are investigated and illustrated with examples. Secondly, a MADM-based algorithm is proposed by describing new matrix-based aggregations of cpFSS like the core matrix, maximum and minimum decision value matrices, and score. Lastly, the proposed algorithm is implemented in real-world applications with the aim of selecting a suitable supplier for the provision of required materials for construction projects. With the sensitivity analysis of score values through Pythagorean means, it can be concluded that the results and rankings of the suppliers are consistent. Moreover, through structural comparison, the proposed structure is proven to be more flexible and reliable as compared to existing fuzzy set-like structures.
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Affiliation(s)
- Ali Asghar
- Department of Mathematics, University of Sargodha, Sargodha, Sargodha, Pakistan
| | - Khuram A. Khan
- Department of Mathematics, University of Sargodha, Sargodha, Sargodha, Pakistan
| | - Marwan A. Albahar
- Computer Science Department, Umm Al-Qura University, Mecca, Saudia Arabia
| | - Abdullah Alammari
- Faculty of Education, Curriculums and Teaching Department, Umm Al-Qura University, Makkah, Saudi Arabia
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Pérez-Domínguez L, David LC, Picón LAR, López RR, Yohana SMK. Suppliers selection based on intuitionistic fuzzy dimensional analysis. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-189187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Supplier selection is a crucial activity in the supply chain management, and fundamentally it is a multi-criteria decision-making problem. However, the interaction of the criteria, the uncertain regarding to subjectivity and the imprecise information generally present in the provider selection process is still an open issue. The main purpose of this paper is to arise a new method to support the provider selection process. In this sense, this paper introduces the intuitionistic fuzzy version of dimensional analysis under a group decision making and multi-criteria environment applied to suppliers selection. Likewise, a set of decision makers reveal their preferences about the criteria and options in evaluation by mean of a linguistic grade that are mapped via intuitionistic numbers. Consequently, the importance of each decision maker and criteria is considered in the method. Hence, the methodology assumes that exist a choice better than the rest which is called ideal alternative. Each choice in evaluation, is compared with that ideal to induce an index of similarity. Additionally, the alternative with highest index of similarity is proposed as solution to the supplier selection problem. The method offer a systematic mode to deal with the interrelationship between the criteria attached into the decision making sphere. Finally, a numerical example is addressed to supplier selection to facilitate the understanding of the proposed method.
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Affiliation(s)
- Luis Pérez-Domínguez
- Department of Industrial and Manufacturing Engineering, Universidad Autónoma de Ciudad Juárez, Ave. Del Charro 450 Norte, Ciudad Juarez, Chihuahua, Mexico
| | - Luviano-Cruz David
- Department of Industrial and Manufacturing Engineering, Universidad Autónoma de Ciudad Juárez, Ave. Del Charro 450 Norte, Ciudad Juarez, Chihuahua, Mexico
| | - Luis Alberto Rodríguez Picón
- Department of Industrial and Manufacturing Engineering, Universidad Autónoma de Ciudad Juárez, Ave. Del Charro 450 Norte, Ciudad Juarez, Chihuahua, Mexico
| | - Roberto Romero López
- Department of Industrial and Manufacturing Engineering, Universidad Autónoma de Ciudad Juárez, Ave. Del Charro 450 Norte, Ciudad Juarez, Chihuahua, Mexico
| | - Sánchez-Mojica Karla Yohana
- Departamento de Investigación, Fundación de Estudios Superiores Comfanorte FESC, Avenida 5 15-27, Centro, Cúcuta, Colombia
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Ilyas M, Carpitella S, Zoubir E. Designing supplier selection strategies under COVID-19 constraints for industrial environments. PROCEDIA CIRP 2021; 100:589-594. [PMID: 37090494 PMCID: PMC10110395 DOI: 10.1016/j.procir.2021.05.128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
COVID-19 has been impacting worldwide supply chains causing interruption, closure of production and distribution. This impact has been drastic on the supplier side and, as a consequence of disruptions, strong reductions of production have been estimated. Such a circumstance forces companies to propose innovative best practices of supply chain risk management aimed at facing vulnerability generated by COVID-19 and pursuing industrial improvements in manufacturing and production environments. As a part of supply chain strategy, supplier selection criteria should be revised to include pandemic-related risks. This article aims to propose an answer to such a problem. In detail, a comprehensive tool designed as a hybrid combination of multi-criteria decision-making (MCDM) methods is suggested to manage important stages connected to the production development cycle and to provide companies with a structured way to rank risks and easily select their suppliers. The main criteria of analysis will be first identified from the existent literature. Risks related to COVID-19 will be then analysed in order to elaborate a comprehensive list of potential risks in the field of interest. The Best Worst Method (BWM) will be first used to calculate criteria weights. The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) will be then applied to rank and prioritize risks affecting suppliers. The effectiveness of the approach will be tested through a case study in the sector of automotive industry. The applicability of the designed MCDM framework can be extended also to other industrial sectors of interest.
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A Reputation-Enhanced Hybrid Approach for Supplier Selection with Intuitionistic Fuzzy Evaluation Information. MATHEMATICS 2019. [DOI: 10.3390/math7030298] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Selecting optimal suppliers in fuzzy environments has become a major challenge for enterprises. Reputation plays an important role in the process of supplier selection because of its fuzziness, dynamicity, and transitivity. In this study, we first present a novel intuitionistic fuzzy sets (IFS)-hyperlink-induced topic search (HITS) method that combines the intuitionistic fuzzy set with the hyperlink-induced topic search (HITS) algorithm to extend the ability of processing fuzzy information in order to obtain post-propagated reputation values of suppliers. Then, we employ the dynamic intuitionistic fuzzy weighted average operator to gain dynamic reputation values and other evaluation attribute values. After that, intuitionistic fuzzy entropy weight method is adopted to acquire more accurate weights for each evaluation attribute. Finally, we employ the Vlsekriterijumska Optimizacija I Kompromisno Resenje method to acquire comprehensive evaluation values of candidate supplier to select optimal suppliers. Two groups of experiments for supplier selection are given to explain feasibility and practicality of the proposed method.
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A novel Multiple Attribute Decision Making approach based on interval data using U2P-Miner algorithm. DATA KNOWL ENG 2018. [DOI: 10.1016/j.datak.2018.03.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study. SUSTAINABILITY 2018. [DOI: 10.3390/su10041066] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Environmentally Friendly Supplier Selection Using Prospect Theory. SUSTAINABILITY 2017. [DOI: 10.3390/su9030377] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Büyüközkan G, Göçer F. Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem. Appl Soft Comput 2017. [DOI: 10.1016/j.asoc.2016.08.051] [Citation(s) in RCA: 127] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Heidarzade A, Mahdavi I, Mahdavi-Amiri N. Supplier selection using a clustering method based on a new distance for interval type-2 fuzzy sets: A case study. Appl Soft Comput 2016. [DOI: 10.1016/j.asoc.2015.09.029] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Opresnik D, Fiasché M, Taisch M, Hirsch M. An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy. INFORMATION TECHNOLOGY & MANAGEMENT 2015. [DOI: 10.1007/s10799-015-0242-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Wan SP, Dong JY. Power geometric operators of trapezoidal intuitionistic fuzzy numbers and application to multi-attribute group decision making. Appl Soft Comput 2015. [DOI: 10.1016/j.asoc.2014.12.031] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Guarnieri P. Síntese dos Principais Critérios, Métodos e Subproblemas da Seleção de Fornecedores Multicritério. RAC: REVISTA DE ADMINISTRAÇÃO CONTEMPORÂNEA 2015. [DOI: 10.1590/1982-7849rac20151109] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
O objetivo do presente artigo é identificar na literatura quais são os principais critérios considerados no processo de decisão, os principais métodos individuais e combinados e os subproblemas da seleção de fornecedores no contexto multicritério. Cabe ressaltar que as tarefas de avaliar e identificar os melhores fornecedores para um novo produto ou serviço são essenciais ao gerenciamento da cadeia de suprimentos (GCS). Para executá-las apropriadamente, considerando-se a natureza multicritério da seleção de fornecedores, torna-se necessária a inclusão de uma abordagem de agregação dos critérios, cuja escolha depende basicamente dos objetivos da decisão, tipos de critérios a serem utilizados e racionalidade do decisor. Para atingir o objetivo proposto, optou-se por utilizar o procedimento da revisão sistemática da literatura que segue o protocolo proposto por Cronin, Ryan e Coughlan (2008), abrangendo artigos publicados nas bases ISI Web of Knowledge e Scopus, no período de 2001 a 2012. Além de sintetizar o conhecimento acerca do tema, o artigo ressalta os principais critérios, métodos e subproblemas da seleção de fornecedores, com isso, contribui ao identificar os aspectos que devem ser desenvolvidos em estudos futuros e ao apresentar aos gestores abordagens existentes para a tomada de decisões relativa à seleção de fornecedores de forma sistematizada.
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Yue Z, Jia Y. A method to aggregate crisp values into interval-valued intuitionistic fuzzy information for group decision making. Appl Soft Comput 2013. [DOI: 10.1016/j.asoc.2012.12.032] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Ding S, Huang H, Yu J, Zhao H. Research on the hybrid models of granular computing and support vector machine. Artif Intell Rev 2013. [DOI: 10.1007/s10462-013-9393-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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