A Hesitant Fuzzy Linguistic TOPSIS Model to Support Supplier Segmentation
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William Viana Borges
Francisco Rodrigues Lima Junior
Jurandir Peinado
Luiz Cesar Ribeiro Carpinetti
Abstract
Objective: this study proposes a hesitant fuzzy linguistic TOPSIS model for supplier segmentation based on economic, environmental, and social criteria. Proposal: the model classifies suppliers in a segmentation matrix considering their capabilities and willingness to collaborate. It was implemented using Microsoft Excel© and applied to a hydropower plant. Two employees of the company chose a set of segmentation criteria, assigned weights to these criteria, and evaluated the performance of suppliers. In the pilot application, the performance of six suppliers was analyzed and ranked according to 28 criteria. The classification results were endorsed by the decision-makers involved. Conclusion: the model provides consistent results and can assist managers in designing development programs aimed at improving the economic, environmental, and social performance of suppliers. Additionally, it can support group decisions under uncertainty and hesitation, allows the use of linguistic expressions, and does not limit the amounts of criteria or alternatives.
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How to Cite
Borges, W. V., Lima Junior, F. R., Peinado, J., & Carpinetti, L. C. R. (2021). A Hesitant Fuzzy Linguistic TOPSIS Model to Support Supplier Segmentation. Journal of Contemporary Administration, 26(6), e210133. https://doi.org/10.1590/1982-7849rac2022210133.en
Section
Methodological Articles
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References
Akman, G. (2015). Evaluating suppliers to include green supplier development programs via fuzzy c-means and VIKOR methods. Computers & Industrial Engineering, 86(1), 69-82. https://doi.org/10.1016/j.cie.2014.10.013
Aloini, D., Dulmin, R., Mininno, V., & Zerbino, P. (2019). Leveraging procurement-related knowledge through a fuzzy-based DSS. Journal of Knowledge Management, 23(1), 1077-1104. https://doi.org/10.1108/JKM-10-2018-0614
Bai, C., Rezaei, J., & Sarkis, J. (2017). Multicriteria green supplier segmentation. IEEE Transactions on Automation Science and Engineering, 64(4), 515-528. https://doi.org/10.1109/TEM.2017.2723639
Beg, I., & Rashid, T. (2013). TOPSIS for hesitant fuzzy linguistic term sets. International Journal of Intelligent Systems, 28(1), 1162-1171. https://doi.org/10.1002/int.21623
Bemelmans, J., Voordijk, H., Vos, B., & Buter, J. (2012). Assessing buyer-supplier relationship management: Multiple case-study in the Dutch Construction Industry. Journal of Construction Engineering and Management, 138(1), 163–176. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000418
Bertrand, J. W. M., & Fransoo, J. (2002). Operations management research methodologies using quantitative modeling. International Journal of Operations and Production Management, 22(2), 241-264. https://doi.org/10.1108/01443570210414338
Bianchini, A., Benci, A., Pellgrini, M.P., & Rossi, J. (2019). Supply chain redesign for lead-time reduction through Kraljic purchasing portfolio and AHP integration. Benchmarking: An International Journal, 26(1), 1194-1209. https://doi.org/10.1108/BIJ-07-2018-0222
Borges, W. V., & Lima, F. R. Junior (2020). Modelos de suporte à decisão para segmentação de fornecedores: Uma revisão sistemática da literatura. Anais do Congresso Brasileiro de Engenharia de Produção (CONBREPRO), Ponta Grossa., PR, Brasil, 10. Retrieved from https://aprepro.org.br/conbrepro/2020/anais/arquivos/09252020_140959_5f6e2af7ae0a7.pdf
Boujelben, M. A. (2017). A unicriterion analysis based on the PROMETHEE principles for multicriteria ordered clustering. Omega, 69(1), 126-140. https://doi.org/10.1016/j.omega.2016.08.007
Che, Z. H. (2011). Clustering and selecting suppliers based on simulated annealing algorithms. Computers & Mathematics with Applications, 63(1), 228-238. https://doi.org/10.1016/j.camwa.2011.11.014
Day, M., Magnan, G. M., & Moeller, M. M. (2010). Evaluating the bases of supplier segmentation: A review and taxonomy. Industrial Marketing Management, 39(4), 625–639. https://doi.org/10.1016/j.indmarman.2009.06.001
Demir, L., Akpinar, M. E., Araz, C., & Ilgin, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114(1), 479-487. https://doi.org/10.1016/j.eswa.2018.07.071
Elkington, J. (2000). Cannibals with forks: The triple bottom line of 21st Century Business. Journal of Business Ethics, 23, 229–231. https://doi.org/10.1023/A:1006129603978
Guarnieri, P. (2015). Síntese dos principais critérios, métodos e subproblemas da seleção de fornecedores multicritério. Revista de Administração Contemporânea, 19(1), 1-25. https://doi.org/10.1590/1982-7849rac20151109
Haghighi, P. S., Morad, M., & Salahi, M. (2014). Supplier segmentation using fuzzy linguistic preference relations and fuzzy clustering. I. J. Intelligent Systems and Applications, 5(1), 76-82. https://doi.org/10.5815/IJISA.2014.05.08
Jharkharia, S., & Das, C. (2019). Low carbon supplier development: A fuzzy c-means and fuzzy formal concept analysis based analytical model. Benchmarking: An International Journal, 26(1), 73-96. https://doi.org/10.1108/BIJ-03-2018-0074
Kaur, H., & Singh, S. P. (2021). Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. International Journal of Production Economics 231. https://doi.org/10.1016/j.ijpe.2020.107830
Lambert, D., & Schwieterman, M. (2012). Supplier relationship management as a macro business process. Supply Chain Management, 17(3), 337-352. https://doi.org/10.1108/13598541211227153
Lima, F. R. Junior, & Carpinetti, L. C. R. (2016). Combining SCOR® model and fuzzy TOPSIS for supplier evaluation and management. International Journal of Production Economics, 174(1), 128-141. https://doi.org/10.1016/j.ijpe.2016.01.023
Lima, F. R., Junior, Osiro, L., & Carpinetti, L. C. (2014). A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21(1), 194-209. https://doi.org/10.1016/j.asoc.2014.03.014
Lo, S., & Sudjatmika, F. V. (2015). Solving multi-criteria supplier segmentation based on the modified FAHP for supply chain management: A case study. Soft Computing, 20(12), 4981-4990. https://doi.org/10.1007/s00500-015-1787-1
Magalhães, W.R. (2020). Proposição e aplicação de um modelo para priorização de risco baseado em FMEA e Hesitant Fuzzy-TOPSIS (Dissertation). Universidade Tecnológica Federal do Paraná, Curitiba, PR, Brasil.
Medeiros, M., & Ferreira, L. (2018). Development of a purchasing portfolio model: An empirical study in a Brazilian hospital. Journal Production Planning & Control, 29(7), 571-585. https://doi.org/10.1080/09537287.2018.1434912
Onar, S. C., Oztaysi, B., Kahraman, C. (2014). Strategic decision selection using hesitant fuzzy TOPSIS and interval type-2 fuzzy AHP: A case study. International Journal of Computational Intelligence Systems, 7)5), 1002-1021. https://doi.org/10.1080/18756891.2014.964011
Osiro, L., Lima, F. R. Junior, & Carpinetti, L. C. R. (2014). A fuzzy logic approach to supplier evaluation for development. International Journal of Production Economics, 153(1), 95-112. http://dx.doi.org/10.1016/j.ijpe.2014.02.009
Osiro, L., Lima, F. R. Junior, & Carpinetti, L. C. R. (2018). A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics. Journal of Cleaner Production, 183(1), 964–978. https://doi.org/10.1016/j.jclepro.2018.02.197
Park, J., Shin, K., Chang, T., & Park, J. (2010). An integrative framework for supplier relationship management. Industrial Management & Data Systems, 110(4), 495-515. https://doi.org/10.1108/02635571011038990
Parkouhi, S. V., Ghadikolaei, A. S., & Lajimi, H. F. (2019). Resilient supplier selection and segmentation in grey environment. Journal of Cleaner Production, 207(1), 1123-1137. https://doi.org/10.1016/j.jclepro.2018.10.007
Pedroso, C. B., Tate, W. L., Silva, A. L. da, & Carpinetti, L. C. R. (2021). Supplier development adoption: A conceptual model for triple bottom line (TBL) outcomes. Journal of Cleaner Production 314. https://doi.org/10.1016/j.jclepro.2021.127886
Pelissari, R., Oliveira, M. C., Abackerli, A. J., Ben-Amor, S., & Assumpção, M. R. P. (2018). Techniques to model uncertain input data of multi-criteria decision-making problems: A literature review. Intl. Trans. in Op. Res 00, 1-37. https://doi.org/10.1111/itor.12598
Rashidi, K., Noorizadeh, A., Kannan, D., & Cullinane, K. (2020). Applying the triple bottom line in sustainable supplier selection: A meta-review of the state-of-the-art. Journal of Cleaner Production 269. https://doi.org/10.1016/j.jclepro.2020.122001
Restrepo, R., & Villegas, J. G. (2019). Supplier evaluation and classification in a Colombian motorcycle assembly company using data envelopment analysis. Academia Revista Latinoamericana de Administración, 32(2), 159-180. https://doi.org/10.1108/ARLA-04-2017-0107
Rezaei, J., & Lajimi, H. F. (2019). Segmenting supplies and suppliers: Bringing together the purchasing portfolio matrix and the supplier potential matrix. International Journal of Logistics Research and Applications, 22(4), 419-436. https://doi.org/10.1080/13675567.2018.1535649
Rezaei, J., & Ortt, R. (2013a). Multi-criteria supplier segmentation using a fuzzy preference relations based AHP. European Journal of Operational Research, 225(1), 75-84. https://doi.org/10.1016/j.ejor.2012.09.037
Rezaei, J., & Ortt, R. (2013b). Supplier segmentation using fuzzy logic. Industrial Marketing Management, 42(4), 507-517. https://doi.org/10.1016/j.indmarman.2013.03.003
Rezaei, J., Kadzinski, M., Vana, C., & Tavasszy, L. A. (2017) Embedding carbon impact assessment in multi-criteria supplier segmentation using ELECTRE TRI-rC. Annals of Operations Research. https://doi.org/10.1007/s10479-017-2454-y
Rezaei, J., Wang, J., & Tavasszy, L. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42(23), 9152-9164. https://doi.org/10.1016/j.eswa.2015.07.073
Rodríguez, R. M., Martinez, L., & Herrera, F. (2012). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109-119. https://doi.org/10.1109/tfuzz.2011.2170076
Saltelli, A., Aleksankina, K., Becker, W., Fennell, P., Ferretti, F., Holst, N., & Wu, Q. (2019). Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices. Environmental modelling & software, 114(1), 29-39. https://doi.org/10.1016/j.envsoft.2019.01.012
Santos, L. F. O. M., Osiro, L., & Lima, R. H. P. (2017). A model based on 2-tuple fuzzy linguistic representation and Analytic Hierarchy Process for supplier segmentation using qualitative and quantitative criteria. Expert Systems with Applications, 79(1), 53-64. https://doi.org/10.1016/j.eswa.2017.02.032
Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69(1), 87-100. https://doi.org/10.1016/j.eswa.2016.10.031
Seuring, S., & Muller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. https://doi.org/10.1016/j.jclepro.2008.04.020
Torres-Ruiz, A., & Ravindran, R. (2018). Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. Journal of Cleaner Production, 172(1), 4478-4493. https://doi.org/10.1016/j.jclepro.2017.10.304
Aloini, D., Dulmin, R., Mininno, V., & Zerbino, P. (2019). Leveraging procurement-related knowledge through a fuzzy-based DSS. Journal of Knowledge Management, 23(1), 1077-1104. https://doi.org/10.1108/JKM-10-2018-0614
Bai, C., Rezaei, J., & Sarkis, J. (2017). Multicriteria green supplier segmentation. IEEE Transactions on Automation Science and Engineering, 64(4), 515-528. https://doi.org/10.1109/TEM.2017.2723639
Beg, I., & Rashid, T. (2013). TOPSIS for hesitant fuzzy linguistic term sets. International Journal of Intelligent Systems, 28(1), 1162-1171. https://doi.org/10.1002/int.21623
Bemelmans, J., Voordijk, H., Vos, B., & Buter, J. (2012). Assessing buyer-supplier relationship management: Multiple case-study in the Dutch Construction Industry. Journal of Construction Engineering and Management, 138(1), 163–176. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000418
Bertrand, J. W. M., & Fransoo, J. (2002). Operations management research methodologies using quantitative modeling. International Journal of Operations and Production Management, 22(2), 241-264. https://doi.org/10.1108/01443570210414338
Bianchini, A., Benci, A., Pellgrini, M.P., & Rossi, J. (2019). Supply chain redesign for lead-time reduction through Kraljic purchasing portfolio and AHP integration. Benchmarking: An International Journal, 26(1), 1194-1209. https://doi.org/10.1108/BIJ-07-2018-0222
Borges, W. V., & Lima, F. R. Junior (2020). Modelos de suporte à decisão para segmentação de fornecedores: Uma revisão sistemática da literatura. Anais do Congresso Brasileiro de Engenharia de Produção (CONBREPRO), Ponta Grossa., PR, Brasil, 10. Retrieved from https://aprepro.org.br/conbrepro/2020/anais/arquivos/09252020_140959_5f6e2af7ae0a7.pdf
Boujelben, M. A. (2017). A unicriterion analysis based on the PROMETHEE principles for multicriteria ordered clustering. Omega, 69(1), 126-140. https://doi.org/10.1016/j.omega.2016.08.007
Che, Z. H. (2011). Clustering and selecting suppliers based on simulated annealing algorithms. Computers & Mathematics with Applications, 63(1), 228-238. https://doi.org/10.1016/j.camwa.2011.11.014
Day, M., Magnan, G. M., & Moeller, M. M. (2010). Evaluating the bases of supplier segmentation: A review and taxonomy. Industrial Marketing Management, 39(4), 625–639. https://doi.org/10.1016/j.indmarman.2009.06.001
Demir, L., Akpinar, M. E., Araz, C., & Ilgin, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114(1), 479-487. https://doi.org/10.1016/j.eswa.2018.07.071
Elkington, J. (2000). Cannibals with forks: The triple bottom line of 21st Century Business. Journal of Business Ethics, 23, 229–231. https://doi.org/10.1023/A:1006129603978
Guarnieri, P. (2015). Síntese dos principais critérios, métodos e subproblemas da seleção de fornecedores multicritério. Revista de Administração Contemporânea, 19(1), 1-25. https://doi.org/10.1590/1982-7849rac20151109
Haghighi, P. S., Morad, M., & Salahi, M. (2014). Supplier segmentation using fuzzy linguistic preference relations and fuzzy clustering. I. J. Intelligent Systems and Applications, 5(1), 76-82. https://doi.org/10.5815/IJISA.2014.05.08
Jharkharia, S., & Das, C. (2019). Low carbon supplier development: A fuzzy c-means and fuzzy formal concept analysis based analytical model. Benchmarking: An International Journal, 26(1), 73-96. https://doi.org/10.1108/BIJ-03-2018-0074
Kaur, H., & Singh, S. P. (2021). Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. International Journal of Production Economics 231. https://doi.org/10.1016/j.ijpe.2020.107830
Lambert, D., & Schwieterman, M. (2012). Supplier relationship management as a macro business process. Supply Chain Management, 17(3), 337-352. https://doi.org/10.1108/13598541211227153
Lima, F. R. Junior, & Carpinetti, L. C. R. (2016). Combining SCOR® model and fuzzy TOPSIS for supplier evaluation and management. International Journal of Production Economics, 174(1), 128-141. https://doi.org/10.1016/j.ijpe.2016.01.023
Lima, F. R., Junior, Osiro, L., & Carpinetti, L. C. (2014). A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21(1), 194-209. https://doi.org/10.1016/j.asoc.2014.03.014
Lo, S., & Sudjatmika, F. V. (2015). Solving multi-criteria supplier segmentation based on the modified FAHP for supply chain management: A case study. Soft Computing, 20(12), 4981-4990. https://doi.org/10.1007/s00500-015-1787-1
Magalhães, W.R. (2020). Proposição e aplicação de um modelo para priorização de risco baseado em FMEA e Hesitant Fuzzy-TOPSIS (Dissertation). Universidade Tecnológica Federal do Paraná, Curitiba, PR, Brasil.
Medeiros, M., & Ferreira, L. (2018). Development of a purchasing portfolio model: An empirical study in a Brazilian hospital. Journal Production Planning & Control, 29(7), 571-585. https://doi.org/10.1080/09537287.2018.1434912
Onar, S. C., Oztaysi, B., Kahraman, C. (2014). Strategic decision selection using hesitant fuzzy TOPSIS and interval type-2 fuzzy AHP: A case study. International Journal of Computational Intelligence Systems, 7)5), 1002-1021. https://doi.org/10.1080/18756891.2014.964011
Osiro, L., Lima, F. R. Junior, & Carpinetti, L. C. R. (2014). A fuzzy logic approach to supplier evaluation for development. International Journal of Production Economics, 153(1), 95-112. http://dx.doi.org/10.1016/j.ijpe.2014.02.009
Osiro, L., Lima, F. R. Junior, & Carpinetti, L. C. R. (2018). A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics. Journal of Cleaner Production, 183(1), 964–978. https://doi.org/10.1016/j.jclepro.2018.02.197
Park, J., Shin, K., Chang, T., & Park, J. (2010). An integrative framework for supplier relationship management. Industrial Management & Data Systems, 110(4), 495-515. https://doi.org/10.1108/02635571011038990
Parkouhi, S. V., Ghadikolaei, A. S., & Lajimi, H. F. (2019). Resilient supplier selection and segmentation in grey environment. Journal of Cleaner Production, 207(1), 1123-1137. https://doi.org/10.1016/j.jclepro.2018.10.007
Pedroso, C. B., Tate, W. L., Silva, A. L. da, & Carpinetti, L. C. R. (2021). Supplier development adoption: A conceptual model for triple bottom line (TBL) outcomes. Journal of Cleaner Production 314. https://doi.org/10.1016/j.jclepro.2021.127886
Pelissari, R., Oliveira, M. C., Abackerli, A. J., Ben-Amor, S., & Assumpção, M. R. P. (2018). Techniques to model uncertain input data of multi-criteria decision-making problems: A literature review. Intl. Trans. in Op. Res 00, 1-37. https://doi.org/10.1111/itor.12598
Rashidi, K., Noorizadeh, A., Kannan, D., & Cullinane, K. (2020). Applying the triple bottom line in sustainable supplier selection: A meta-review of the state-of-the-art. Journal of Cleaner Production 269. https://doi.org/10.1016/j.jclepro.2020.122001
Restrepo, R., & Villegas, J. G. (2019). Supplier evaluation and classification in a Colombian motorcycle assembly company using data envelopment analysis. Academia Revista Latinoamericana de Administración, 32(2), 159-180. https://doi.org/10.1108/ARLA-04-2017-0107
Rezaei, J., & Lajimi, H. F. (2019). Segmenting supplies and suppliers: Bringing together the purchasing portfolio matrix and the supplier potential matrix. International Journal of Logistics Research and Applications, 22(4), 419-436. https://doi.org/10.1080/13675567.2018.1535649
Rezaei, J., & Ortt, R. (2013a). Multi-criteria supplier segmentation using a fuzzy preference relations based AHP. European Journal of Operational Research, 225(1), 75-84. https://doi.org/10.1016/j.ejor.2012.09.037
Rezaei, J., & Ortt, R. (2013b). Supplier segmentation using fuzzy logic. Industrial Marketing Management, 42(4), 507-517. https://doi.org/10.1016/j.indmarman.2013.03.003
Rezaei, J., Kadzinski, M., Vana, C., & Tavasszy, L. A. (2017) Embedding carbon impact assessment in multi-criteria supplier segmentation using ELECTRE TRI-rC. Annals of Operations Research. https://doi.org/10.1007/s10479-017-2454-y
Rezaei, J., Wang, J., & Tavasszy, L. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42(23), 9152-9164. https://doi.org/10.1016/j.eswa.2015.07.073
Rodríguez, R. M., Martinez, L., & Herrera, F. (2012). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109-119. https://doi.org/10.1109/tfuzz.2011.2170076
Saltelli, A., Aleksankina, K., Becker, W., Fennell, P., Ferretti, F., Holst, N., & Wu, Q. (2019). Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices. Environmental modelling & software, 114(1), 29-39. https://doi.org/10.1016/j.envsoft.2019.01.012
Santos, L. F. O. M., Osiro, L., & Lima, R. H. P. (2017). A model based on 2-tuple fuzzy linguistic representation and Analytic Hierarchy Process for supplier segmentation using qualitative and quantitative criteria. Expert Systems with Applications, 79(1), 53-64. https://doi.org/10.1016/j.eswa.2017.02.032
Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69(1), 87-100. https://doi.org/10.1016/j.eswa.2016.10.031
Seuring, S., & Muller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. https://doi.org/10.1016/j.jclepro.2008.04.020
Torres-Ruiz, A., & Ravindran, R. (2018). Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. Journal of Cleaner Production, 172(1), 4478-4493. https://doi.org/10.1016/j.jclepro.2017.10.304