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A two-sided matching decision-making approach based on prospect theory under the probabilistic linguistic environment

  • Soft computing in decision making and in modeling in economics
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Abstract

This paper aims to propose a two-sided matching decision-making approach with the probabilistic linguistic evaluations. Existing two-sided matching decision-making methods rarely consider the psychological behaviors of the subjects, which makes the matching result deviate from the reality. To overcome this drawback, we introduce the prospect theory to describe the perception of the subjects. At first, the probabilistic linguistic evaluations are normalized. Then, the evaluations under the cost criteria are transformed into their benefit types to guarantee the consistency of the computation process. Thereafter, calculate the prospect values for the subjects based on the defined relative normalized Lance distance of the probabilistic linguistic term sets. Afterwards, aggregate the prospect values into the satisfaction degrees. On the basis of this, build the multi-objective two-sided matching decision-making model and further transform it into the single-objective model. To solve the latter is to obtain the optimal matching result. An illustrative example of intelligent technology transfer is presented to validate the proposed approach, and the optimal matching result is obtained for the demanders and the providers. Finally, we demonstrate the advantages of the proposed approach comparing with the existing methods.

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Funding

This work was supported by the National Natural Science Foundation of China under Grant 61773123, 71801090, the Humanities and Social Science Foundation of the Ministry of Education of China under Grant 19YJA630071, and the Key Project of the Philosophy and Social Science Foundation of Hunan Province of China under Grant 18ZDB009.

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Authors and Affiliations

  1. School of Economics and Management, Fuzhou University, Fuzhou, 350108, Fujian, China

    Xiang Jia

  2. School of Science, Hunan University of Technology, Zhuzhou, 412007, China

    Xin-Fan Wang & Lang Zhou

  3. Decision Science Institute, Fuzhou University, Fuzhou, 350108, Fujian, China

    Ying-Ming Wang

  4. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, 350108, Fujian, China

    Ying-Ming Wang

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  1. Xiang Jia
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  2. Xin-Fan Wang
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  3. Ying-Ming Wang
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  4. Lang Zhou
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Correspondence to Ying-Ming Wang.

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Jia, X., Wang, XF., Wang, YM. et al. A two-sided matching decision-making approach based on prospect theory under the probabilistic linguistic environment. Soft Comput 26, 3921–3938 (2022). https://doi.org/10.1007/s00500-022-06737-1

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