Abstract
There are usually multiple stakeholders involved in a group decision-making (GDM) problem. The probabilistic linguistic preference relation (PLPR) is an effective tool to describe the preference of each stakeholder. The probability distribution of linguistic preference can be available from statistics analysis on the questionnaires. In GDM process, the essential step is to execute the consensus reaching process (CRP) that is a dynamic iterative process by utilizing the feedback mechanism to update the preference of identified stakeholders. However, the existing feedback mechanisms with the fixed boundary parameter neglect the individual psychological behavior, leading to false CRP. For which, the personalized feedback mechanism based on self-confidence and leadership is developed to generate recommendation advice for the identified stakeholders, which is the three-step procedure: (1) construct trust relationship network and obtain trust degree among stakeholders; (2) assess individual self-confidence level from professional ability and sociability that are captured by entropy and trust degree, respectively, and (3) identify the opinion leader as reference preference. Furthermore, we analyze the convergence and consistency of identified stakeholders after adopting the feedback recommendation. Then, an example of hydropower development project assessments is illustrated to show the feasibility of the proposed method. Finally, by comparison and analysis with other consensus models, it demonstrates the advantages of the proposed feedback mechanism.
Published Version
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