Spatial Distribution And Regulation Strategy Of Smart Elderly Care Industry In Guizhou Provinc

Smart elderly care industry is an emerging industrial form that takes intelligent products and information platforms as its carrier,faces market demand and deeply integrates new generation information technology.With the increasing demand for smart elderly care in Guizhou province,the problem of insufficient supply of smart elderly care resources is gradually deepening.Based on this,the spatial distribution characteristics of the smart elderly care industry in Guizhou province are visualized and analyzed by using hierarchical map,equilibrium degree,nuclear density and locational entropy.A system dynamics model of the spatial distribution of the smart elderly care industry in Guizhou province is also constructed based on system dynamics theory.Then the mechanism of the spatial distribution of the smart elderly care industry in Guizhou province is systematically studied through computer simulation,providing a strong support for the spatial distribution of the smart elderly care industry in Guizhou province.The result can strongly support the regulation of the spatial distribution for the smart elderly care industry in Guizhou province.Firstly,based on the theory of industrial economics and the academic research on the spatial distribution of the smart elderly care industry by domestic and foreign scholars,this paper analyzes the development status and distribution characteristics of the smart elderly care industry in Guizhou province by using descriptive analysis and metric geographic distribution method.The analysis finds that:(1)The scale of the smart elderly industry in Guizhou province has begun to take shape,while it still faces problems such as insufficient technical application and slow development of scale,with much room for development.(2)The overall distribution of the smart elderly industry in Guizhou province shows the characteristics of central clustering from north to south and edge clustering from west to east,with uneven distribution and significant industrial clustering.Secondly,based on the location theory,this paper uses qualitative analysis to study various factors affecting the spatial distribution of the smart elderly care industry in Guizhou province,and constructs the index system of factors affecting the spatial distribution of the smart elderly care industry in Guizhou province.It is found that the factors influencing the spatial distribution of the smart elderly care industry in Guizhou province mainly involve four aspects: nature,market,society and technology,and the index system of factors influencing the spatial distribution of the smart elderly care industry in Guizhou province is established on this basis.Thirdly,based on the system dynamics theory,system dynamics method is used to analyze the cause-effect relationship of the variables in the spatial distribution system of the smart elderly care industry in Guizhou province.Moreover,this paper constructs the causal circuit and flow diagram of the spatial distribution system of the smart elderly care industry in Guizhou province,and determines the system dynamics model.Based on the construction of the system dynamics model,simulation is used to simulate and analyze the regulation strategy of the factors influencing the spatial distribution of the smart elderly industry in Guizhou Province.The simulation finds that among the influencing factors of the spatial distribution of the smart elderly care industry in Guizhou province:(1)Technology factor is the key factor and should be improved.(2)Natural factor and social factor are the robust factors and should be enhanced.(3)Market factor is the reserved factor and should be maintained.Finally,this paper proposes countermeasures for regulating the spatial distribution for the smart elderly care industry in Guizhou province:(1)Focus on promoting the development of core key factors;(2)Consolidate and strengthen the development of core robust factors;(3)Stabilize and improve the development of core retention factors.