Evaluation of medical service quality based on a novel multi-criteria decision-making method with unknown weighted information

• Autorzy: Zhao Butian , Zhang Runtong , Xing Yuping

Identyfikatory

DOI

10.24425/acs.2021.138696

• Języki publikacji: EN

Abstrakty

EN

In modern society, people concern more about the evaluation of medical service quality. Evaluation of medical service quality is helpful for medical service providers to supervise and improve their service quality. Also, it will help the public to understand the situation of different medical providers. As a multi-criteria decision-making (MCDM) problem, evaluation of medical service quality can be effectively solved by aggregation operators in interval-valued q-rung dual hesitant fuzzy (IVq-RDHF) environment. Thus, this paper proposes interval-valued q-rung dual hesitant Maclaurin symmetric mean (IVq-RDHFMSM) operator and interval-valued q-rung dual hesitant weighted Maclaurin symmetric mean (IVq-RDHFWMSM) operator. Based on the proposed IVq-RDHFWMSM operator, this paper builds a novel approach to solve the evaluation problem of medical service quality including a criteria framework for the evaluation of medical service quality and a novel MCDM method. What’s more, aiming at eliminating the discordance between decision information and weight vector of criteria determined by decisionmakers (DMs), this paper proposes the concept of cross-entropy and knowledge measure in IVq-RDHF environment to extract weight vector from DMs’ decision information. Finally, this paper presents a numerical example of the evaluation of medical service for hospitals to illustrate the availability of the novel method and compares our method with other MCDM methods to demonstrate the superiority of our method. According to the comparison result, our method has more advantages than other methods.

Słowa kluczowe

EN

interval-valued q-rung dual hesitant fuzzy set; Maclaurin symmetric mean operator; multi-criteria decision-making; aggregation operators

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2021
• Tom: Vol. 31, No. 3
• Strony: 645--685
• Opis fizyczny: Bibliogr. 59 poz., rys., tab., wzory

Twórcy

autor

Zhao Butian

• School of Management and Economic, Beijing Jiaotong University, Beijing, 100044, China

autor

Zhang Runtong

• School of Management and Economic, Beijing Jiaotong University, Beijing, 100044, China

autor

Xing Yuping

• Glorious Sun School of Business and Management, DongHua University, Shanghai, 200051, China

Bibliografia

• [1] C. Teng, C. Ing, H. Chang, and K. Chung: Development of service quality scale for surgical hospitalization. Journal of the Formosan Medical Association, 106(6), (2007), 475-484, DOI: 10.1016/S0929-6646(09)60297-7.
• [2] I. Otay, B. Öztayşi, S. Çevik, and C. Kahraman: Multi-expert performance evaluation of healthcare institutions using an integrated intuitionistic fuzzy AHP&DEA methodology. Knowledge-Based Systems, 33 (2017), 90-106, DOI: 10.1016/j.knosys.2017.06.028.
• [3] J. Shieh, H. Wu, and K. Huang: A DEMATEL method in identifying key success factors of hospital service quality. Knowledge Based Systems, 23(3), (2010), 277-282, DOI: 10.1016/j.knosys.2010.01.013.
• [4] M.L. Mccarthy, R. Ding, and S.L. Zeger: A randomized controlled trial of the effect of service delivery information on patient satisfaction in an emergency department fast track. Academic Emergency Medicine, 18(7), (2011), 674-685, DOI: 10.1111/j.1553-2712.2011.01119.x.
• [5] L. Fei, J. Lu, and Y. Feng: An extended best-worst multi-criteria decision-making method by belief functions and its applications in hospital service evaluation. Computers & Industrial Engineering, 142, (2020), 106355, DOI: 10.1016/j.cie.2020.106355.
• [6] E.K. Zavadskas, Z. Turskis, and S. Kildiene˙: State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), (2014), 165-179, DOI: 10.3846/20294913.2014.892037.
• [7] Y. Xing, R. Zhang, M. Xia,and J. Wang: Generalized point aggregation operators for dual hesitant fuzzy information. Journal of Intelligent and Fuzzy Systems, 33(1), (2017), 515-527, DOI: 10.3233/JIFS-161922.
• [8] F. Zhang, S.Wang, J. Sun, J. Ye, and G.K. Liew: Novel parameterized score functions on interval-valued intuitionistic fuzzy sets with three fuzziness measure indexes and their application. IEEE Access, 7, (2018), 8172-8180, DOI: 10.1109/ACCESS.2018.2885794.
• [9] H. Zhang, R. Zhang, and H. Huang: Some picture fuzzy dombi heronian mean operators with their application to multi-attribute decision-making. Symmetry, 10(11), (2018), 593, DOI: 10.3390/sym10110593.
• [10] K.T. Atanassov: Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), (1986), 87-96, DOI: 10.1016/S0165-0114(86)80034-3.
• [11] R.R. Yager: Pythagorean membership grades in multicriteria decision making. IEEE Transactions on Fuzzy Systems, 22(4), (2014), 958-965, DOI: 10.1109/TFUZZ.2013.2278989.
• [12] J. Wang, R. Zhang, X. Zhu, Z. Zhou, X. Shang, and W. Li: Some q-rung orthopair fuzzy Muirhead means with their application to multi-attribute group decision making. Journal of Intelligent and Fuzzy Systems, 36(2), (2019), 1599-1614, DOI: 10.3233/JIFS-18607.
• [13] R.R. Yager: Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25(5), (2017), 1222-1230, DOI: 10.1109/TFUZZ.2016.2604005.
• [14] P. Liu and P. Wang: Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision making. International Journal of Intelligent Systems, 33(4), (2017), 259-280, DOI: 10.1002/int.21927.
• [15] C. Bonferroni: Sulle medie multiple di potenze. Bollettino dell’Unione Matematica Italiana, 5(3-4), (1950), 267-270.
• [16] S. Sykora: Mathematical means and averages: Generalized Heronian means. Stan’s Library, Ed. S. Sykora, 3, (2009), DOI: 10.3247/SL3Math 09.002.
• [17] C. Maclaurin: A second letter to Martin Folkes, Esq.: concerning the roots of equations, with the demonstration of other rules in algebra. Phil, Transaction (1683-1775), 394, (1729), 59-96.
• [18] R.F. Muirhead: Some methods applicable to identities and inequalities of symmetric algebraic functions of n letters. Proceedings of the Edinburgh Mathematical Societ., 21, (1902), 144-162, DOI: 10.1017/S001309150003460X.
• [19] P. Liu and J. Liu: Some q-rung orthopair fuzzy Bonferroni mean operators and their application to multi-attribute group decision making. International Journal of Intelligent Systems, 33(2), (2018), 315-347, DOI: 10.1002/int.21933.
• [20] G. Wei, H. Gao, and Y. Wei: Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision making. International Journal of Intelligent Systems, 33(7), (2017), 1426-1458, DOI: 10.1002/int.21985.
• [21] P. Liu and D. Li: Some Muirhead mean operators for intuitionistic fuzzy numbers and their applications to group decision making. PloS ONE, 12(1), (2017), 423-431, DOI: 10.1371/journal.pone.0168767.
• [22] G. Wu, H. Garg, H. Gao, and C. Wei: Interval-valued Pythagorean fuzzy maclaurin symmetric mean operators in multiple attribute decision making. IEEE Access, 99(1), (2018), 67866-67884, DOI: 10.1109/ACCESS.2018.2877725.
• [23] K. Bai, X. Zhu, J. Wang, and R. Zhang: Some partitioned Maclaurin symmetric mean based on q-rung orthopair fuzzy information for dealing with multi-attribute group decision making. Symmetry, 10(9), (2018), 383, DOI: 10.3390/sym10090383.
• [24] G. Wei and M. Lu: Pythagorean fuzzy Maclaurin symmetric mean operators in multiple attribute decision making. International Journal of Intelligent Systems, 33(6), (2017), 1043-1070, DOI: 10.1002/int.21911.
• [25] J. Qin: Generalized Pythagorean fuzzy Maclaurin symmetric means and its application to multiple attribute SIR group decision model. Journal of Intelligent and Fuzzy Systems, 20(1), (2017), 943-957, DOI: 10.1007/s40815-017-0439-2.
• [26] P. Liu, and X. Qin: Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decisionmaking. Journal of Experimental & Theoretical Artificial Intelligence, 29(6), (2017), 1-30, DOI: 10.1080/0952813X.2017.1310309.
• [27] H. Wang, P. Liu, and Z. Liu: Trapezoidal interval type-2 fuzzy Maclaurin symmetric mean operators and their applications to multiple attribute group decision making. International Journal for Uncertainty Quantification, 8(44), (2018), 343-360, DOI: 10.1615/Int.J.UncertaintyQuantification.2018020768.
• [28] H. Garg: Hesitant Pythagorean fuzzy Maclaurin symmetric mean operators and its applications to multiattribute decision-making process. International Journal of Intelligent Systems, 34(4), (2019), 601-626, DOI: 10.1002/int.22067.
• [29] K.T. Atanassov and G. Gargov: Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 31, (1989), 343-349, DOI: 10.1016/0165-0114(89)90205-4.
• [30] H. Garg: A novel accuracy function under interval-valued Pythagorean fuzzy environment for solving multicriteria decision making problem. Journal of Intelligent and Fuzzy Systems, 31(1), (2016), 529-540, DOI: 10.3233/IFS-162165.
• [31] B.P. Joshi, A. Singh, P.K. Bhatt, and K.S. Vaisla: Interval valued q-rung orthopair fuzzy sets and their properties. Journal of Intelligent and Fuzzy Systems, 35(5), (2018), 5225-5230, DOI: 10.3233/JIFS-169806.
• [32] H. Kalani, M. Akbarzadeh, A. Akbarzadeh, and I. Kardan: Intervalvalued fuzzy derivatives and solution to interval-valued fuzzy differential equations. Journal of Intelligent and Fuzzy Systems, 30(6), (2016), 3373-3384, DOI: 10.3233/IFS-162085.
• [33] T. Chen: An interval-valued Pythagorean fuzzy outranking method with a closeness-based assignment model for multiple criteria decision making. International Journal of Intelligent Systems, 33(2), (2017), 126-168, DOI: 10.1002/int.21943.
• [34] Z. Li, G. Wei, and H. Gao: Methods for multiple attribute decision making with interval-valued Pythagorean fuzzy information. Mathematics, 6, (2018), 228, DOI: 10.3390/math6110228.
• [35] N. Jan, T. Mahmood, L. Zedam, K.Ullah, J.C. Alcantud, and B. Davvaz: Analysis of social networks, communication networks and shortest path problems in the environment of interval valued q-rung orthopair fuzzy information. Journal of Intelligent and Fuzzy Systems, 21, (2019), 1687-1708, DOI: 10.1007/s40815-019-00643-9.
• [36] H. Gao, Y. Ju, W. Zhang, and D. Ju: Multi-attribute decision-making method based on interval-valued q-rung orthopair fuzzy archimedean Muirhead mean operators. IEEE Access, 99(1), (2019), 74300-74315, DOI: 10.1109/ACCESS.2019.2918779.
• [37] V. Torra: Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), (2010), 529-539, DOI: 10.1002/int.20418.
• [38] B. Zhu, Z. Xu, and M. Xia: Dual hesitant fuzzy sets. Journal of Applied Mathematics, 2012, (2012), 1-13, DOI: 10.1155/2012/879629.
• [39] D. Yu, W. Zhang, and G.Q. Huang: Dual hesitant fuzzy aggregation operators. Textit Technological and Economic Development of Economy, 22(2), (2015), 1-16, DOI: 10.3846/20294913.2015.1012657.
• [40] Y. Xing, R. Zhang, M. Xia, and J. Wang: Generalized point aggregation operators for dual hesitant fuzzy information. Journal of Intelligent and Fuzzy Systems, 33(1), (2017), 515-527, DOI: 10.3233/JIFS-161922.
• [41] Z. Su, Z. Xu, H. Zhao, and S. Liu: Distribution-based approaches to deriving weights from dual hesitant fuzzy information. Symmetry, 11(1), (2019), 85, DOI: 10.3390/sym11010085.
• [42] G. Maity, D. Mardanya, S.K. Roy, and G.W. Weber: A new approach for solving dual-hesitant fuzzy transportation problem with restrictions, Sadhana, 44(75), (2019), DOI: 10.1007/s12046-018-1045-1.
• [43] G. Qu, Q. An, W. Qu, F. Deng, and T. Li: Multiple attribute decision making based on bidirectional projection measures of dual hesitant fuzzy set. Journal of Intelligent and Fuzzy Systems, 7(5), (2019), 7087-7102, DOI: 10.3233/JIFS-181970.
• [44] Y. Xu, X. Shang, J. Wang, H. Zhao, R. Zhang, and K. Bai: Some intervalvalued q-rung dual hesitant fuzzy Muirhead mean operators with their application to multi-attribute decision-making. IEEE Access, 99(1), (2019), 54724-54745, DOI: 10.1109/ACCESS.2019.2912814.
• [45] T. Zhu, L. Luo, H. Liao, X. Zhang, and W. Shen: A hybrid multicriteria decision making model for elective admission control in a Chinese public hospital. Knowledge-Based Systems, 173, (2019), 37-51, DOI: 10.1016/j.knosys.2019.02.020.
• [46] X. Gou, Z. Xu, H. Liao, and F. Herrera: Multiple criteria decision making based on distance and similarity measures under double hierarchy hesitant fuzzy linguistic environment. Computers & Industrial Engineering, 126, (2018), 516-530, DOI: 10.1016/j.cie.2018.10.020.
• [47] Y. Xu, X. Shang, J. Wang, W. Wu, and H. Huang: Some q-rung dual hesitant fuzzy Heronian mean operators with their application to multiple attribute group decision-making. Symmetry, 10(10), (2018), 472, DOI: 10.3390/sym10100472
• [48] Y. Ju, X. Liu, and S. Yang: Interval-valued dual hesitant fuzzy aggregation operators and their applications to multiple attribute decision making. Journal of Intelligent and Fuzzy Systems, 27(3), (2014), 1203-1218, DOI: 10.3233/IFS-131085.
• [49] W. Yang and Y. Pang: Hesitant interval-valued Pythagorean fuzzy VIKOR method. International Journal of Intelligent Systems, 34(5), (2018), 754-789, DOI: 10.1002/int.22075.
• [50] H. Hiidenhovi, P. Laippala, and K. Nojonen: Development of a patientorientated instrument to measure service quality in outpatient departments. Journal of Advanced Nursing, 34(5), (2001), 696-705, DOI: 10.1046/j.1365-2648.2001.01799.x.
• [51] L. Li and W. Benton: Hospital capacity management decisions: Emphasis on cost control and quality enhancement. European Journal of Operational Research, 146(3), (2003), 596-614, DOI: 10.1016/S0377-2217(02) 00225-4.
• [52] C. Tian, Y. Tian, and L. Zhang: An evaluation scale of medical services quality based on “patients’ experience”. Journal of Huazhong University of Science and Technology [Medical Sciences], 34, (2014), 289-297, DOI: 10.1007/s11596-014-1273-5.
• [53] S. Das, B. Dutta, and De. Guha: Weight computation of criteria in a decision-making problem by knowledge measure with intuitionistic fuzzy set and interval-valued intuitionistic fuzzy set. Soft Computing, 20(9), (2016), 3421-3442, DOI: 10.1007/s00500-015-1813-3.
• [54] W. Zhang, X. Li, and Y. Ju: Some aggregation operators based on Einstein operations under interval-valued dual hesitant fuzzy setting and their application. Mathematical Problems in Engineering, 1, (2014), DOI: 10.1155/2014/958927.
• [55] K. Rahman, S. Abdullah, M. Shakeel, M.S. Khan, and M. Ullah: Interval-valued Pythagorean fuzzy geometric aggregation operators and their application to group decision making problem. Cogent Mathematics, 4, (2017), DOI: 10.1080/23311835.2017.1338638.
• [56] Y. Zang, X. Zhao, and S. Li: Interval-valued dual hesitant fuzzy Heronian mean aggregation operators and their application to multi-attribute decision making, International Journal of Computational Intelligence and Applications, 17(4), (2018), DOI: 10.1142/S1469026818500050.
• [57] J. Wang, X. Shang, X. Feng, and M. Sun: A novel multiple attribute decision making method based on q-rung dual hesitant uncertain linguistic sets and Muirhead mean. Archives of Control Sciences, 30(2), (2020), 233-272, DOI: 10.24425/acs.2020.133499.
• [58] L. Li, R. Zhang, J. Wang, and X. Shang: Some q-orthopair linguistic Heronian mean operators with their application to multi-attribute group decision making. Archives of Control Sciences, 28(4), (2018), 551-583, DOI: 10.24425/acs.2018.125483.
• [59] A. Biswas and A. Sarkar: Development of dual hesitant fuzzy prioritized operators based on Einstein operations with their application to multicriteria group decision making. Archives of Control Sciences, 28(4), (2018), 527-549, DOI: 10.24425/acs.2018.125482.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).