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Original Articles

The two-stage utility function with an aspiration to mass data and uncertain linguistic environment in multiple experts multiple criteria decision making

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 2500-2517 | Received 09 Apr 2021, Accepted 13 Oct 2021, Published online: 16 Dec 2021

References

  • Alon, S., & Schmeidler, D. (2014). Purely subjective maxmin expected utility. Journal of Economic Theory, 152, 382–412. https://doi.org/10.1016/j.jet.2014.03.006
  • Arora, R., & Garg, H. (2019). Group decision-making method based on prioritized linguistic intuitionistic fuzzy aggregation operators and its fundamental properties. Computational and Applied Mathematics, 38(2), 36–67. https://doi.org/10.1007/s40314-019-0764-1
  • Bentley, R. A., O'Brien, M. J., & Brock, W. A. (2014). Mapping collective behavior in the big-data era. The Behavioral and Brain Sciences, 37(1), 63–76. https://doi.org/10.1017/S0140525X13000289
  • Besharati, B., Azarm, S., & Kannan, P. K. (2006). A decision support system for product design selection: A generalized purchase modeling approach. Decision Support Systems, 42(1), 333–350. https://doi.org/10.1016/j.dss.2005.01.002
  • Cables, E., Lamata, M. T., & Verdegay, J. L. (2016). RIM-reference ideal method in multicriteria decision making. Information Sciences, 337–338, 1–10. https://doi.org/10.1016/j.ins.2015.12.011
  • Carvalho, F. R., & Abe, J. M. (2018). Decision Rules. In A Paraconsistent Decision-Making Method. Smart Innovation, Systems and Technologies (vol. 87, pp. 37–40). Cham: Springer. https://doi.org/10.1007/978-3-319-74110-9_3.
  • El Sayed, M. A., Baky, I. A., & Singh, P. (2020). A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision making problem. OPSEARCH, 57(4), 1374–1403. https://doi.org/10.1007/s12597-020-00461-w
  • Feng, B., & Lai, F. (2014). Multi-attribute group decision making with aspirations: A case study. Omega (United Kingdom), 44, 136–147. https://doi.org/10.1016/j.omega.2013.07.003
  • Galanis, P. (2018). The Delphi method. Archives of Hellenic Medicine, 35(4), 564–570. https://doi.org/10.1093/med:psych/9780190243654.003.0007
  • Garg, H. (2020). Linguistic interval-valued pythagorean fuzzy sets and their application to multiple attribute group decision-making process. Cognitive Computation, 12(6), 1313–1337. https://doi.org/10.1007/s12559-020-09750-4
  • Garg, H., & Kumar, K. (2019a). Linguistic interval-valued atanassov intuitionistic fuzzy sets and their applications to group decision making problems. IEEE Transactions on Fuzzy Systems, 27(12), 2302–2311. https://doi.org/10.1109/TFUZZ.2019.2897961
  • Garg, H., & Kumar, K. (2019b). Multiattribute decision making based on power operators for linguistic intuitionistic fuzzy set using set pair analysis. Expert Systems. https://doi.org/10.1111/exsy.12428
  • Gou, X., Xu, Z., Liao, H., & Herrera, F. (2020). Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare. Journal of the Operational Research Society. https://doi.org/10.1080/01605682.2020.1806741
  • Gu, J., Zheng, Y., Tian, X., & Xu, Z. (2021). A decision-making framework based on prospect theory with probabilistic linguistic term sets. Journal of the Operational Research Society, 72(4), 810–879. https://doi.org/10.1080/01605682.2019.1701957
  • Huang, M., Qian, X., Fang, S. C., & Wang, X. (2016). Winner determination for risk aversion buyers in multi-attribute reverse auction. Omega (United Kingdom), 59, 184–200. https://doi.org/10.1016/j.omega.2015.06.007
  • Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. American Economic Review, 93(5), 1449–1475. https://doi.org/10.1257/000282803322655392
  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263. https://doi.org/10.2307/1914185
  • Laming, D. (2011). Fechner’s law: Where does the log transform come from? In Fechner’s legacy in psychology: 150 Years of elementary psychophysics (vol. 23, pp. 15–171). Seeing perceiving. https://doi.org/10.1163/ej.9789004192201.i-214
  • Leonor Plá, M., Casasús, T., Liern, V., & Carlos Pérez, J. (2018). On the importance of perspective and flexibility for efficiency measurement: Effects on the ranking of decision-making units. Journal of the Operational Research Society, 69(10), 1640–1652. https://doi.org/10.1057/s41274-017-0250-3
  • Li, G., Kou, G., & Peng, Y. (2018). A group decision making model for integrating heterogeneous information. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(6), 982–992. https://doi.org/10.1109/TSMC.2016.2627050
  • Liao, H., & Wu, X. (2020). DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria decision making. Omega, 94, 102058. https://doi.org/10.1016/j.omega.2019.04.001
  • Liao, H., Wu, X., Mi, X., & Herrera, F. (2020). An integrated method for cognitive complex multiple experts multiple criteria decision making based on ELECTRE III with weighted Borda rule. Omega, 93, 102052. https://doi.org/10.1016/j.omega.2019.03.010
  • Liao, H., Yu, J., Wu, X., Al-Barakati, A., Altalhi, A., & Herrera, F. (2019). Life satisfaction evaluation in earthquake-hit area by the probabilistic linguistic GLDS method integrated with the logarithm-multiplicative analytic hierarchy process. International Journal of Disaster Risk Reduction, 38, 1–11. https://doi.org/10.1016/j.ijdrr.2019.101190
  • Lin, M., Huang, C., & Xu, Z. (2020). MULTIMOORA based MCDM model for site selection of car sharing station under picture fuzzy environment. Sustainable Cities and Society, 53, 101873. https://doi.org/10.1016/j.scs.2019.101873
  • Liu, H., Jiang, L., & Martínez, L. (2018). A dynamic multi-criteria decision making model with bipolar linguistic term sets. Expert Systems with Applications, 95, 104–112. https://doi.org/10.1016/j.eswa.2017.11.015
  • Muchiri, P., Pintelon, L., Gelders, L., & Martin, H. (2011). Development of maintenance function performance measurement framework and indicators. International Journal of Production Economics, 131(1), 295–302. https://doi.org/10.1016/j.ijpe.2010.04.039
  • Oliveira, M. D. N. T., Ferreira, F. A. F., Pérez-Bustamante Ilander, G. O., & Jalali, M. S. (2017). Integrating cognitive mapping and MCDA for bankruptcy prediction in small-And medium-sized enterprises. Journal of the Operational Research Society, 68(9), 985–997. https://doi.org/10.1057/s41274-016-0166-3
  • Pang, Q., Wang, H., & Xu, Z. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Sciences, 369, 128–143. https://doi.org/10.1016/j.ins.2016.06.021
  • Papathanasiou, J., & Ploskas, N. (2018). TOPSIS. In Multiple Criteria Decision Aid. Springer Optimization and Its Applications (vol. 136, pp. 1–30). Cham: Springer. https://doi.org/10.1007/978-3-319-91648-4_1
  • Relich, M., & Pawlewski, P. (2017). A fuzzy weighted average approach for selecting portfolio of new product development projects. Neurocomputing, 231, 19–27. https://doi.org/10.1016/j.neucom.2016.05.104
  • Tiwari, V., Jain, P. K., & Tandon, P. (2016). Product design concept evaluation using rough sets and VIKOR method. Advanced Engineering Informatics, 30(1), 16–25. https://doi.org/10.1016/j.aei.2015.11.005
  • Wang, H., Lu, S., & Zhao, J. (2019). Aggregating multiple types of complex data in stock market prediction: A model-independent framework. Knowledge-Based Systems, 164, 193–204. https://doi.org/10.1016/j.knosys.2018.10.035
  • Wu, X., & Liao, H. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272(3), 1017–1027. https://doi.org/10.1016/j.ejor.2018.07.044
  • Wu, Y., Xu, C., & Zhang, T. (2018). Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China. Energy, 147, 1227–1239. https://doi.org/10.1016/j.energy.2018.01.115
  • Wu, Z., & Xu, J. (2018). A consensus model for large-scale group decision making with hesitant fuzzy information and changeable clusters. Information Fusion, 41, 217–231. https://doi.org/10.1016/j.inffus.2017.09.011
  • Xia, M., & Xu, Z. (2011). Hesitant fuzzy information aggregation in decision making. International Journal of Approximate Reasoning, 52(3), 395–407. https://doi.org/10.1016/j.ijar.2010.09.002
  • Xu, Z. (2007). Multiple-attribute group decision making with different formats of preference information on attributes. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37(6), 1500–1511. https://doi.org/10.1109/TSMCB.2007.904832
  • Xu, Z., & Wang, H. (2017). On the syntax and semantics of virtual linguistic terms for information fusion in decision making. Information Fusion, 34, 43–48. https://doi.org/10.1016/j.inffus.2016.06.002
  • Yan, H. B., Huynh, V. N., Murai, T., & Nakamori, Y. (2008). Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis. Information Sciences, 178(21), 4080–4093. https://doi.org/10.1016/j.ins.2008.06.023
  • Ying, C. S., Li, Y. L., Chin, K. S., Yang, H. T., & Xu, J. (2018). A new product development concept selection approach based on cumulative prospect theory and hybrid-information MADM. Computers & Industrial Engineering, 122, 251–261. https://doi.org/10.1016/j.cie.2018.05.023
  • Yu, D., Kou, G., Xu, Z., & Shi, S. (2021). Analysis of collaboration evolution in AHP research: 1982-2018. International Journal of Information Technology & Decision Making, 20(01), 7–36. https://doi.org/10.1142/S0219622020500406
  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
  • Zeng, D., Zhang, R., Liu, X., Zhong, S., & Shi, K. (2018). Improved results on synchronisation of delayed complex dynamical networks via sampled-data control. International Journal of Systems Science, 49(6), 1242–1255. https://doi.org/10.1080/00207721.2018.1442513
  • Zhang, H., Kou, G., & Peng, Y. (2019). Soft consensus cost models for group decision making and economic interpretations. European Journal of Operational Research, 277(3), 964–980. https://doi.org/10.1016/j.ejor.2019.03.009
  • Zhou, X., Wang, L., Liao, H., Wang, S., Lev, B., & Fujita, H. (2019). A prospect theory-based group decision approach considering consensus for portfolio selection with hesitant fuzzy information. Knowledge-Based Systems, 168, 28–38. https://doi.org/10.1016/j.knosys.2018.12.029

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