Aged Care Projects Evaluation Research Based on the Self-Adaptive Consensus Emergence Model Driven by the Social Learning Mechanism

In recent years, the accelerated aging process in China has brought enormous pressure on the traditional aged care system. The private family-based aged care mode cannot resolve the contradiction between the insufficient labor force and a large elderly population. The public community-based aged care mode could effectively integrate various social resources such as housing, healthcare, land, education, etc., which may better meet diverse elderly care demands. The senior residents' evaluation of public aged care services is essential for local pension policy making, determining the local government's investment direction to some extent. Therefore, this research organizes a decision group to conduct the evaluation of alternative aged care service projects with Maslow's hierarchy-based evaluation framework. The decision group consists of senior citizens from the Xiaolingwei community in Nanjing, which is a deeply aging metropolis with the flourishing aged care service market and demand. Considering the aged residents' inherent preference differences rooted in living habits, cultural background, and risk attitude, it is essential to introduce an effective consensus model into the group evaluation to control opinion conflict and reach consensus. The current consensus models still have the following limitations: consensus models depend on the preset empirical consensus threshold, hardly reflecting the spontaneous consensus emergence; the inconsistency of group consensus opinion harms the reliability and effectiveness of group decision; the existing methods generally identify the non-cooperative behavior passively, lacking the adaptive and active management. Therefore, this paper develops the consensus emergence model driven by the social learning mechanism based on the BA scale-free network and the Bayesian learning rule, guiding the selfadaptive opinion evolution and the spontaneous consensus convergence. The novel consensus model includes three crucial parts: the environment network construction, the private cognition formation, and the individual preference modification. The proposed consensus emergence model has outstanding advantages in consensus consistency through spontaneous opinion evolution, the adaptive consensus emergence with greater consensus efficiency, and the consensus robustness under non-cooperators disturbance.