Game Analysis of Dynamic Planning Evolution for the Optimization of Community Governance Structure in Smart Cities

Abstract

In this paper, we study the structural optimization of community governance in smart cities and optimize the structure based on the game analysis of dynamic planning evolution. Theoretically, the connotation and extension of the concept of “self‐organization” are cleared, and the environment and conditions of community self‐organization formation, the formation process of community self‐organization, and the types of community self‐organization are discussed. The so‐called “self‐organization” is a process of spontaneously moving from disorder to order, and the environment and conditions of community self‐organization are mainly the openness, nonequilibrium state, and nonlinearity of the system. The key parameters of the contract with the change of the values of each factor make up for the inability to collect data for the empirical study in this paper; then, it presents four linear stages along with the cause such as self‐creation, self‐expansion, self‐maintenance, and self‐degeneration, respectively. The types of community self‐organization mainly include community self‐organization with random aggregation, socialized community self‐organization, and stable community self‐organization with autonomy orientation. By systematically sorting out the relationship between community self‐organization and government, while confirming the positive significance of community self‐organization to community cultural governance, various complex conflicts and game relationships will deeply affect the actual effectiveness of cultural governance and provide useful knowledge reference for future community cultural governance.