An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains
Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitaliza...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co. Ltd.
2021-01-01
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| Series: | Sustainable Operations and Computers |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666412721000301 |
| _version_ | 1797976469497970688 |
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| author | Madjid Tavana Akram Shaabani Debora Di Caprio Maghsoud Amiri |
| author_facet | Madjid Tavana Akram Shaabani Debora Di Caprio Maghsoud Amiri |
| author_sort | Madjid Tavana |
| collection | DOAJ |
| description | Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method. |
| first_indexed | 2024-04-11T04:51:22Z |
| format | Article |
| id | doaj.art-b0a66b5c13bd4b3c9d2553e710a7337f |
| institution | Directory Open Access Journal |
| issn | 2666-4127 |
| language | English |
| last_indexed | 2024-04-11T04:51:22Z |
| publishDate | 2021-01-01 |
| publisher | KeAi Communications Co. Ltd. |
| record_format | Article |
| series | Sustainable Operations and Computers |
| spelling | doaj.art-b0a66b5c13bd4b3c9d2553e710a7337f2022-12-27T04:37:35ZengKeAi Communications Co. Ltd.Sustainable Operations and Computers2666-41272021-01-012149169An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chainsMadjid Tavana0Akram Shaabani1Debora Di Caprio2Maghsoud Amiri3Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, USA; Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, Paderborn, Germany; Corresponding author at: Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, PA 19141, United States.Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, IranDepartment of Economics and Management, University of Trento, ItalyDepartment of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, IranDigital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method.http://www.sciencedirect.com/science/article/pii/S2666412721000301Digital supply chainSupplier selectionFuzzy setBest-worst methodConsensus ranking |
| spellingShingle | Madjid Tavana Akram Shaabani Debora Di Caprio Maghsoud Amiri An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains Sustainable Operations and Computers Digital supply chain Supplier selection Fuzzy set Best-worst method Consensus ranking |
| title | An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains |
| title_full | An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains |
| title_fullStr | An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains |
| title_full_unstemmed | An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains |
| title_short | An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains |
| title_sort | integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains |
| topic | Digital supply chain Supplier selection Fuzzy set Best-worst method Consensus ranking |
| url | http://www.sciencedirect.com/science/article/pii/S2666412721000301 |
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