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An online reviews information fusion method and its application to public property service quality evaluation

    Shanshan Lin   Affiliation
    ; Wenjin Zuo   Affiliation
    ; Hualin Lin   Affiliation
    ; Qiang Hu   Affiliation

Abstract

With the rapid development of computer networking technology, people pay more and more attention to the role of online reviews in management decision making. The existing methods of online reviews fusion are limited to rational decision-making behavior, which does not accord with the characteristics of evaluators’ behavior characteristics in the real environment. In order to solve the online reviews fusion problem based on bounded rational behavior which is closer to the reality of property service quality evaluation, the multi-index and multi-scale (MIMS) method is extended into the generalized form, the online reviews are quantified by using the adverb structure scaling method, and an online reviews fusion method based on the improved TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) model is proposed. The feasibility and effectiveness of the proposed method are verified by an example analysis of property service quality evaluation. The research results are as follows: the adverb structure scaling method is suitable for a large number of online reviews processing, the proposed method improves the efficiency of online reviews information fusion, and it is feasible and effective to evaluate property service quality based on the bounded rationality of evaluator’s behavior.


First published online 14 January 2022

Keyword : generalized MIMS method, adverb structure scaling method, improved TODIM method, online reviews information fusion, public property service quality evaluation

How to Cite
Lin, S., Zuo, W., Lin, H., & Hu, Q. (2022). An online reviews information fusion method and its application to public property service quality evaluation. International Journal of Strategic Property Management, 26(1), 1-10. https://doi.org/10.3846/ijspm.2022.16172
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Jan 28, 2022
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