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Information learning-driven consensus reaching process in group decision-making with bounded rationality and imperfect information: China’s urban renewal negotiation

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Abstract

Since the preferences of DMs with bounded rationality are heterogeneous and cannot be directly observed in most cases, GDM with bounded rationality under imperfect information is ubiquitous. To solve these problems, the paper proposes consensus models that minimize cost and maximize utility with prospect theory value function and imperfect information based on stochastic programming. The proposed consensus models are incorporated with a new information learning strategy that combines prior information learning based on existing information observed before negotiation and feedback obtained during negotiation to achieve group consensus. Moreover, the paper applies the proposed consensus models to the demolition negotiation problem in China’s urban renewal projects, and the effectiveness of the proposed information learning strategy is tested with comparative experiments. We further analyze the effects of the accuracy of the prior information, the moderator’s confidence in the prior information, the number of rounds of feedback, and the number of residents on GDM, which can provide practical suggestions for the government’s negotiation strategies for demolition and rebuilding projects.

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Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 72001031, No. 71804018), the China Postdoctoral Research Foundation (Grant No. 2020 M673146), the Fundamental Research Funds for the Central Universities (No. 2021CDJSKJC16), and the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 18YJC630039).

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Authors and Affiliations

  1. School of Management Science and Real Estate, Chongqing University, Chongqing, China

    Quanbo Zha, Jinfan Cai, Jianping Gu & Guiwen Liu

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  1. Quanbo Zha
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  2. Jinfan Cai
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  3. Jianping Gu
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Contributions

Quanbo Zha: Methodology, Supervision, Conceptualization, Writing - review & editing, Funding acquisition, Validation.

Jinfan Cai: Data curation, Software, Formal analysis, Validation, Writing - original draft, Writing - review & editing.

Jianping Gu: Conceptualization, Resources, Investigation, Methodology, Writing - review & editing, Funding acquisition, Validation.

Guiwen Liu: Supervision, Validation, Resources, Formal analysis, Writing - review & editing.

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Correspondence to Jianping Gu.

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Zha, Q., Cai, J., Gu, J. et al. Information learning-driven consensus reaching process in group decision-making with bounded rationality and imperfect information: China’s urban renewal negotiation. Appl Intell 53, 10444–10458 (2023). https://doi.org/10.1007/s10489-022-04019-9

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