A novel TODIM based on prospect theory to select green supplier with q-rung orthopair fuzzy set
Abstract
Green supply chain has developed rapidly due to the advocacy of ecological civilization, and choosing a proper green supplier is a crucial issue. Considering the fuzziness of evaluation information and the psychological states of decision makers (DMs) in selecting process, a novel TODIM based on prospect theory with q-rung orthopair fuzzy set (q-ROFS) is proposed. The novel TODIM concerns both the perceived transformed probability weighting function and the differences in risk attitudes. A new distance, which concerns the herd mentality, is carried out to measure the perceived difference of the q-ROFS. Besides, a new systematic evaluation index system, named as PCEM (Product, Cooperation ability, Environment, Market), has been established. A case related to pork supplier companies is presented and fully demonstrates the effectiveness of the novel TODIM when compared with the extended one, the intuitionistic fuzzy TODIM, the Pythagorean fuzzy TODIM as well as the TOPSIS with q-ROFS. Finally, a series of comparative analyses illustrate the advantages of the proposed TODIM.
First published online 4 September 2020
Keyword : TODIM, prospect theory, q-rung orthopair fuzzy set, green supplier selection
How to Cite
Tian, X., Niu, M., Zhang, W., Li, L., & Herrera-Viedma, E. (2021). A novel TODIM based on prospect theory to select green supplier with q-rung orthopair fuzzy set. Technological and Economic Development of Economy, 27(2), 284-310. https://doi.org/10.3846/tede.2020.12736
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Dagdeviren, M., Yavuz, S., & Kilinc, N. (2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications, 36(4), 8143–8151. https://doi.org/10.1016/j.eswa.2008.10.016
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Gomes, L. F. A. M., & Lima, M. M. P. P. (1992). From modeling individual preferences to multicriteria ranking of discrete alternatives: A look at prospect theory and the additive difference model. Foundations of Computing and Decision Sciences, 17(3), 171–184.
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Humphreys, P., McCloskey, A., McIvor, R., Maguire, L., & Glackin, C. (2006). Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process. International Journal of Production Research, 44(12), 2379–2419. https://doi.org/10.1080/00207540500357476
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Kang, H. Y., Lee, A. H. I., & Yang, C. Y. (2012). A fuzzy ANP model for supplier selection as applied to IC packaging. Journal of Intelligent Manufacturing, 23(5), 1477–1488. https://doi.org/10.1007/s10845-010-0448-6
Kannan, D., Jabbour, A. B. L. D. S., & Jabbour, C. J. C. (2014). Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company. European Journal of Operational Research, 233(2), 432–447. https://doi.org/10.1016/j.ejor.2013.07.023
Klassen, R. D. (1993). The integration of environmental issues into manufacturing: Toward an interactive open-systems model. Production and Inventory Management Journal, 34(1), 82–88.
Koplin, J., Seuring, S., & Mesterharm, M. (2007). Incorporating sustainability into supply management in the automotive industry – the case of the Volkswagen AG. Journal of Cleaner Production, 15(11–12), 1053–1062. https://doi.org/10.1016/j.jclepro.2006.05.024
Krohling, R. A., Pacheco, A. G. C., & Siviero, A. L. T. (2013). IF-TODIM: An intuitionistic fuzzy TODIM to multi-criteria decision making. Knowledge-Based Systems, 53, 142–146. https://doi.org/10.1016/j.knosys.2013.08.028
Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170. https://doi.org/10.1016/j.jclepro.2010.03.020
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Liang, D. C., Zhang, Y. R. J., Xu, Z. S., & Jamaldeen, A. (2019). Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry. Applied Soft Computing, 78, 583–594. https://doi.org/10.1016/j.asoc.2019.03.006
Liang, H. M., Wang, X., & Dong, Y. C. (2018). A prospect theory-based method for fusing the individual preferenceapproval structures in group decision making. Computers & Industrial Engineering, 117, 237–248. https://doi.org/10.1016/j.cie.2018.01.001
Liu, P. D., & Liu, J. L. (2018). Some q‐Rung orthopai fuzzy bonferroni mean operators and their application to multi‐attribute group decision making. International Journal of Intelligent Systems, 33(2), 315–347. https://doi.org/10.1002/int.21933
Liu, Y. T., Dong, Y. C., Liang, H. M., Chiclana, F., & Herrera-Viedma, E. (2019). Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information. IEEE Transactions on Systems Man and Cybernetics: Systems, 40(10), 1981–1992. https://doi.org/10.1109/TSMC.2018.2874942
Min, H., & Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21(9), 1222–1238. https://doi.org/10.1108/EUM0000000005923
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Pérez, I. J., Cabrerizo, F. J., & Herrera-Viedma, E. (2010). A mobile decision support system for dynamic group decision making problems. IEEE Transactions on Systems Man and Cybernetics Part A: Systems and Humans, 40(6), 1244–1256. https://doi.org/10.1109/TSMCA.2010.2046732
Qin, J. D., Liu, X. W., & Pedrycz, W. (2015). An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowledge-Based Systems, 86, 115–130. https://doi.org/10.1016/j.knosys.2015.05.025
Ren, P. J., Xu, Z. S., & Gou, X. J. (2016). Pythagorean fuzzy TODIM approach to multi-criteria decision making. Applied Soft Computing, 42, 246–259. https://doi.org/10.1016/j.asoc.2015.12.020
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Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2010). A fuzzy multicriteria approach for evaluating environmental performance of suppliers. International Journal of Production Economics, 126(2), 370– 378. https://doi.org/10.1016/j.ijpe.2010.04.029
Awasthi, A., Govindan, K., & Gold, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106–117. https://doi.org/10.1016/j.ijpe.2017.10.013
Bai, C., & Sarkis, J. (2010a). Green supplier development: Analytical evaluation using rough set theory. Journal of Cleaner Production, 18, 1200–1210. https://doi.org/10.1016/j.jclepro.2010.01.016
Bai, C., & Sarkis, J. (2010b). Integrating sustainability into supplier selection with grey system and rough set methodologies. International Journal of Production Economics, 124(1), 252–264. https://doi.org/10.1016/j.ijpe.2009.11.023
Bala, A., Muñoz, P., Rieradevall, J., & Ysern, P. (2008). Experiences with greening suppliers. The Universitat Autònoma de Barcelona. Journal of Cleaner Production, 16(15), 1610–1619. https://doi.org/10.1016/j.jclepro.2008.04.015
Bin, L., & Hong-jun, L. (2010). A research on supplier assessment indices system of green purchasing. In 2010 International Conference on Measuring Technology and Mechatronics Automation, 1, 314–317. IEEE. https://doi.org/10.1109/ICMTMA.2010.694
Buyukozkan, G., & Cifci, G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62(2), 164–174. https://doi.org/10.1016/j.compind.2010.10.009
Buyukozkan, G., & Cifci, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000–3011. https://doi.org/10.1016/j.eswa.2011.08.162
Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of suppliers based on using the R’AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101–129. https://doi.org/10.1016/j.jclepro.2018.02.186
Chen, K. L., Yeh, C. C., & Huang, J. C. (2014). Supplier selection using a hybrid model for 3C industry. Journal of Business Economics and Management, 15(4), 631–645. https://doi.org/10.3846/16111699.2013.807870
Chen, Y. S., Lai, S. B., & Wen, C. T. (2006). The influence of green innovation performance on corporate advantage in Taiwan. Journal of Business Ethics, 67(4), 331–339. https://doi.org/10.1007/s10551-006-9025-5
Chiou, T. Y., Chan, H. K., Lettice, F., & Chung, S. H. (2011). The influence of greening the suppliers and green innovation on environmental performance and competitive advantage in Taiwan. Transportation Research Part E: Logistics and Transportation Review, 47(6), 822–836. https://doi.org/10.1016/j.tre.2011.05.016
Dagdeviren, M., Yavuz, S., & Kilinc, N. (2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications, 36(4), 8143–8151. https://doi.org/10.1016/j.eswa.2008.10.016
Del Moral, M. J., Chiclana, F., Tapia, J. M., & Herrera-Viedma, E. (2018). A Comparative study on consensus measures in group decision making. International Journal of Intelligent Systems, 33(8), 1624–1638. https://doi.org/10.1002/int.21954
Du, W. S., & Hu, B. Q. (2017). Dominance-based rough fuzzy set approach and its application to rule induction. European Journal of Operational Research, 261(2), 690–703. https://doi.org/10.1016/j.ejor.2016.12.004
Fallahpour, A., Olugu, E. U., Musa, S. N., Wong, K. Y., & Noori, S. (2017). A decision support model for sustainable supplier selection in sustainable supply chain management. Computers and Industrial Engineering, 105, 391–410. https://doi.org/10.1016/j.cie.2017.01.005
Fan, Z. P., Zhang, X., Chen, F. D., & Liu, Y. (2013). Extended TODIM method for hybrid multiple attribute decision making problems. Knowledge-Based Systems, 42, 40–48. https://doi.org/10.1016/j.knosys.2012.12.014
Grisi, R. M., Guerra, L., & Naviglio, G. (2010). Supplier performance evaluation for green supply chain management. In Business Performance Measurement and Management (pp. 149–163). Springer. https://doi.org/10.1007/978-3-642-04800-5_10
Gomes, L. F. A. M., & Lima, M. M. P. P. (1991). TODIM: basic and application to multicriteria ranking of projects with environmental impacts. Foundations of Computing and Decision Sciences, 16(4), 113–127.
Gomes, L. F. A. M., & Lima, M. M. P. P. (1992). From modeling individual preferences to multicriteria ranking of discrete alternatives: A look at prospect theory and the additive difference model. Foundations of Computing and Decision Sciences, 17(3), 171–184.
Hsu, C. W., & Hu, A. H. (2009). Applying hazardous substance management to supplier selection using analytic network process. Journal of Cleaner Production, 17(2), 255–264. https://doi.org/10.1016/j.jclepro.2008.05.004
Hsu, C. W., Kuo, T. C., Chen, S. H., & Hu, A. H. (2013). Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. Journal of Cleaner Production, 56, 164–172. https://doi.org/10.1016/j.jclepro.2011.09.012
Humphreys, P., McCloskey, A., McIvor, R., Maguire, L., & Glackin, C. (2006). Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process. International Journal of Production Research, 44(12), 2379–2419. https://doi.org/10.1080/00207540500357476
Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Lecture Notes in Economics and Mathematical Systems: Vol. 186. Multiple Attribute Decision Making (pp. 58–191). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48318-9_3
Kang, H. Y., Lee, A. H. I., & Yang, C. Y. (2012). A fuzzy ANP model for supplier selection as applied to IC packaging. Journal of Intelligent Manufacturing, 23(5), 1477–1488. https://doi.org/10.1007/s10845-010-0448-6
Kannan, D., Jabbour, A. B. L. D. S., & Jabbour, C. J. C. (2014). Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company. European Journal of Operational Research, 233(2), 432–447. https://doi.org/10.1016/j.ejor.2013.07.023
Klassen, R. D. (1993). The integration of environmental issues into manufacturing: Toward an interactive open-systems model. Production and Inventory Management Journal, 34(1), 82–88.
Koplin, J., Seuring, S., & Mesterharm, M. (2007). Incorporating sustainability into supply management in the automotive industry – the case of the Volkswagen AG. Journal of Cleaner Production, 15(11–12), 1053–1062. https://doi.org/10.1016/j.jclepro.2006.05.024
Krohling, R. A., Pacheco, A. G. C., & Siviero, A. L. T. (2013). IF-TODIM: An intuitionistic fuzzy TODIM to multi-criteria decision making. Knowledge-Based Systems, 53, 142–146. https://doi.org/10.1016/j.knosys.2013.08.028
Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170. https://doi.org/10.1016/j.jclepro.2010.03.020
Lee, A. H., Kang, H. Y., Hsu, C. F., & Hung, H. C. (2009). A green supplier selection model for hightech industry. Expert systems with applications, 36(4), 7917–7927. https://doi.org/10.1016/j.eswa.2008.11.052
Liang, D. C., Zhang, Y. R. J., Xu, Z. S., & Jamaldeen, A. (2019). Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry. Applied Soft Computing, 78, 583–594. https://doi.org/10.1016/j.asoc.2019.03.006
Liang, H. M., Wang, X., & Dong, Y. C. (2018). A prospect theory-based method for fusing the individual preferenceapproval structures in group decision making. Computers & Industrial Engineering, 117, 237–248. https://doi.org/10.1016/j.cie.2018.01.001
Liu, P. D., & Liu, J. L. (2018). Some q‐Rung orthopai fuzzy bonferroni mean operators and their application to multi‐attribute group decision making. International Journal of Intelligent Systems, 33(2), 315–347. https://doi.org/10.1002/int.21933
Liu, Y. T., Dong, Y. C., Liang, H. M., Chiclana, F., & Herrera-Viedma, E. (2019). Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information. IEEE Transactions on Systems Man and Cybernetics: Systems, 40(10), 1981–1992. https://doi.org/10.1109/TSMC.2018.2874942
Min, H., & Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21(9), 1222–1238. https://doi.org/10.1108/EUM0000000005923
Mishra, A. R., & Rani, P. (2018). Biparametric information measures-based TODIM technique for interval-valued intuitionistic fuzzy environment. Arabian Journal for Science and Engineering, 43(6), 3291. https://doi.org/10.1007/s13369-018-3069-6
Peng, X. D., Dai, J. G., & Garg, H. (2018). Exponential operation and aggregation operator for q‐rung orthopair fuzzy set and their decision‐making method with a new score function. International Journal of Intelligent Systems, 33(11), 2255–2282. https://doi.org/10.1002/int.22028
Pérez, I. J., Cabrerizo, F. J., & Herrera-Viedma, E. (2010). A mobile decision support system for dynamic group decision making problems. IEEE Transactions on Systems Man and Cybernetics Part A: Systems and Humans, 40(6), 1244–1256. https://doi.org/10.1109/TSMCA.2010.2046732
Qin, J. D., Liu, X. W., & Pedrycz, W. (2015). An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowledge-Based Systems, 86, 115–130. https://doi.org/10.1016/j.knosys.2015.05.025
Ren, P. J., Xu, Z. S., & Gou, X. J. (2016). Pythagorean fuzzy TODIM approach to multi-criteria decision making. Applied Soft Computing, 42, 246–259. https://doi.org/10.1016/j.asoc.2015.12.020
Shaw, K., Shankar, R., Yadav, S. S., & Thakur, L. S. (2012). Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Systems with Applications, 39(9), 8182–8192. https://doi.org/10.1016/j.eswa.2012.01.149
Szmidt, E., & Kacprzyk, J. (2000). Distances between intuitionistic fuzzy sets. Fuzzy Sets and Systems, 114(3), 505–518. https://doi.org/10.1016/S0165-0114(98)00244-9
Tam, M. C. Y., & Tummala, V. M. R. (2001). An application of the AHP in vendor selection of a telecommunications system. Omega, 29(2), 171–182. https://doi.org/10.1016/S0305-0483(00)00039-6
Tian, X. L., Kou, G., & Zhang, W. K. (2020). Geographic distance, venture capital and technological performance: evidence from chinese enterprises. Technological Forecasting and Social Change, 158, 120155. https://doi.org/10.1016/j.techfore.2020.120155
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