Share:


Pension service institution selection by a personalized quantifier-based MACONT method

    Zhi Wen Affiliation
    ; Huchang Liao   Affiliation

Abstract

With the emergence of a variety of pension service institutions, how to choose a suitable institution has become a strategic decision-making problem faced by pension service demanders. To solve this problem, this study identifies key evaluation criteria of pension service institutions through the analysis of the relevant literature. Then, this study proposes a mixed aggregation by comprehensive normalization technique (MACONT) with a personalized quantifier to select pension service institutions, where the personalized qualifier with cubic spline interpolation is used to derive the position weights of criteria, and the MACONT is improved to determine the ranking of alternatives. A case study about the selection of pension service institutions is provided to verify the feasibility of the proposed model. It is found that the proposed method is effective in dealing with heterogeneous evaluation information, and the personalized quantifiers can be combined with MACONT methods to obtain an optimal solution associated with the attitude of pension service demanders. The identified key evaluation criteria are not only significant for pension service demanders, but also conducive to the further improvement of property management related to pension services.

Keyword : multi-criteria decision making, pension service evaluation, personalized quantifier, cubic spline interpolation, MACONT method, probabilistic linguistic term set

How to Cite
Wen, Z., & Liao, H. (2021). Pension service institution selection by a personalized quantifier-based MACONT method. International Journal of Strategic Property Management, 25(6), 446–458. https://doi.org/10.3846/ijspm.2021.15651
Published in Issue
Sep 27, 2021
Abstract Views
813
PDF Downloads
543
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Bai, C. Z., Zhang, R., Qian, L. X., & Wu, Y. N. (2017). Comparisons of probabilistic linguistic term sets for multi-criteria decision making. Knowledge-Based Systems, 119, 284–291. https://doi.org/10.1016/j.knosys.2016.12.020

Brauers, W. K. M., & Zavadskas, E. K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5–24. https://doi.org/10.3846/tede.2010.01

Gorzalczany, M. B. (1987). A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Systems, 21(1), 1–17. https://doi.org/10.1016/0165-0114(87)90148-5

Guo, K. H. (2014). Quantifier induced by subjective expected value of sample information. IEEE Transactions on Cybernetics, 44(10), 1784–1794.
https://doi.org/10.1109/TCYB.2013.2295316

Guo, K. H. (2016). Quantifier induced by subjective expected value of sample information with Bernstein polynomials. European Journal of Operational Research, 254, 226–235. https://doi.org/10.1016/j.ejor.2016.03.015

Guo, K. H., & Xu, H. (2018). Personalized quantifier by Bernstein polynomials combined with interpolation spline. International Journal of Intelligent Systems, 33, 1507–1533.
https://doi.org/10.1002/int.21991

Ji, L., Fan, W. F., & Liu, H. G. (2020). Research on performance evaluation of government purchase of pension services from social forces based on the investigation in the Yangtze River delta. Yuejiang Academic Journal, 4, 79–123. https://doi.org/10.13878/j.cnki.yjxk.2020.04.009

Juan, Y. K., Hsus, Y. C., & Chang, Y. P. (2021). Site selection assessment of vacant campus space transforming into daily care centers for the aged. International Journal of Strategic Property Management, 25(1), 34–49.
https://doi.org/10.3846/ijspm.2020.13800

Kane, A. R., & Kane, L. R. (1988). Long-term care: variations on a quality assurance theme. Inquiry, 25(1), 132–146.

Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26, 435–451.
https://doi.org/10.15388/Informatica.2015.57

Liang, J. J., & Wang, Y. M. (2020). Study on the performance evaluation of community home endowment service institutions: a case study of Shanghai. Engineering Economy, 30(1), 74–77.
https://doi.org/10.19298/j.cnki.1672-2442.202001074

Li, G. D., Yamaguchi, D., & Nagai, M. (2007). A grey-based decision-making approach to the supplier selection problem. Mathematical and Computer Modelling, 46(3–4), 573–581. https://doi.org/10.1016/j.mcm.2006.11.021

Lin, M. W., Chen, Z. Y., Liao, H. C., & Xu, Z. S. (2019). ELECTRE II method to deal with probabilistic linguistic term sets and its application to edge computing. Nonlinear Dynamics, 96, 2125–2143.
https://doi.org/10.1007/s11071-019-04910-0

Liao, H. C., Mi, X. M., & Xu, Z. S. (2020). A survey of decisionmaking methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions. Fuzzy Optimization Decision Making, 19, 81–134. https://doi.org/10.1007/s10700‐019‐09309‐5

Liao, H. C., Xu, Z. S., Zeng, X. J., & Merigó, J. M. (2015). Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets. Knowledge-Based Systems, 76, 127–138. https://doi.org/10.1016/j.knosys.2014.12.009

Mi, X. M., Liao, H. C., Wu, X. L., & Xu, Z. S. (2020). Probabilistic linguistic information fusion: a survey on aggregation operators in terms of principles, definitions, classifications, applications, and challenges. International Journal of Intelligent Systems, 35(3), 529–556. https://doi.org/10.1002/int.22216

Pang, Q., Wang, H., & Xu, Z. S. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Science, 369, 128–143.
https://doi.org/10.1016/j.ins.2016.06.021

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

Shao, Q. H., Yuan, J. F., Lin, J., Huang, W., Ma, J. W., & Ding, H. X. (2021). An SBM-DEA based performance evaluation and optimization for social organizations participating in community and home-based elderly care services. PLOS ONE, 16(3), 1–25. https://doi.org/10.1371/journal.pone.0248474

Shao, Q. H., Yuan, J. F., Zheng, C. L., & Lin, J. (2020). Performance evaluation of social organizations participating in home care services. China Real Estate, 58–66.
https://doi.org/10.13562/j.china.real.estate.2020.02.016

Turskis, Z., Morkunaite, Z., & Kutut, V. (2017). A hybrid multiple criteria evaluation method of ranking of cultural heritage structures for renovation projects. International Journal of Strategic Property Management, 21(3), 318–329.
https://doi.org/10.3846/1648715X.2017.1325782

Wang, K. (2020). Quality of home-based service: concept, assessment and policy response. Social Policy Research, 89–102. https://doi.org/10.19506/j.cnki.cn10-1428/d.2020.03.009

Wen, Z., Liao, H. C., & Emrouznejad, A. (2021). Information representation of blockchain technology: risk evaluation of investment by personalized quantifier with cubic spline interpolation. Information Processing & Management, 58(4), 102571. https://doi.org/10.1016/j.ipm.2021.102571

Wen, Z., Liao, H. C., & Zavadskas, E. K. (2020). MACONT: mixed aggregation by comprehensive normalization technique for multi-criteria analysis. Informatica, 31(4), 857–880. https://doi.org/10.15388/20-INFOR417

Wu, X. L., & Liao, H. C. (2018). An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Information Fusion, 43, 13–26. https://doi.org/10.1016/j.inffus.2017.11.008

Wu, X. L., & Liao, H. C. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272, 1017–1027.
https://doi.org/10.1016/j.ejor.2018.07.044

Xu, Q., & Zhou, Y. (2019). Performance evaluation and influencing factors analysis of community home care service quality. Journal of Guangdong Institute of Public Administration, 31(5), 77–86. https://doi.org/10.13975/j.cnki.gdxz.2019.05.010

Yager, R. R. (1988). On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 18(1), 183–190. https://doi.org/10.1109/21.87068

Yuan, J., Li, L., Wang, E., & Skibniewski, M. J. (2019). Examining sustainability indicators of space management in elderly facilities – a case study in China. Journal of Cleaner Production, 208, 144–159. https://doi.org/10.1016/j.jclepro.2018.10.065

Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Electronics and Electrical Engineering, 122(6), 3–6. https://doi.org/10.5755/j01.eee.122.6.1810

Zhang, Y. X., Xu, Z. S., Wang, H., & Liao, H. C. (2016). Consistency-based risk assessment with probabilistic linguistic preference relation. Applied Soft Computing, 49, 817–833.
https://doi.org/10.1016/j.asoc.2016.08.045

Zhao, N., & Fang, W. H. (2016, August 18–20). Research on the service quality evaluation model of institutional pension – a case study of Beijing city. In International Conference on Management Science and Engineering – Annual Conference Proceedings (pp. 802–809), Olten, Switzerland.