In recent years, the population growth rate has been gradually declining in China. As the population problem becomes increasingly significant, the accurate prediction of population development trends has become a top priority, used to facilitate national scientific planning and effective decision making. Based on historical data spanning a period of 20 years (1999–2018), this article presents predictions of the populations of 210 prefecture-level cities using the Malthusian model, Unary linear regression model, Logistic model, and Gray prediction model. Furthermore, because the gray prediction model exhibited the highest degree of accuracy in formulating predictions, this study uses the model to predict and analyze future population development trends. The results reveal that the population gap between cities is gradually widening, and the total urban population shows a pattern of rising in middle-tier cities (second-tier cities and third-tier cities) and declining in high-tier cities (first-tier cities and new first-tier cities) and low-tier cities (fourth-tier cities and fifth-tier cities). From the viewpoint of geographical distribution, the population growth rate is basically balanced between the northern part and the southern part of China. In addition, the population growth of the high-tier cities is gradually slowing while the low-tier cities are experiencing a negative growth of population, but middle-tier cities are experiencing skyrocketing population growth. From the viewpoint of regional development, although the development of regional integration has been strengthened over the years, the radiative driving effect of large urban agglomerations and metropolitan areas is relatively limited.

With technology and finance becoming increasingly integrated, it is imperative to use fintech to improve the capability to forestall and defuse major financial risks. As an area prone to financial risks, the real estate industry deserves in-depth research on the dynamics between risks and technological capability (TC). In this paper, a simulation model was constructed with system dynamics to examine whether an improvement in TC can effectively improve risk management capability (RMC), and to explore the specific interaction between RMC and TC under six policy scenarios. We present the following findings: (1) TC has a significant supporting role in risk management; (2) increasing R&D financial input is more effective than increasing personnel input when it comes to improving TC; (3) whether it is a single input or multiple inputs of different types, increasing R&D financial input is also more effective than increasing personnel input when it comes to improving risk management; (4) overall, improvements in TC and RMC have a positive effect on social and economic development. This study not only makes clear the interconnection between TC and RMC and enriches the research content in this field, but also provide a reference for preventing and resolving major financial risks and promoting stable social and economic development.

Currently, China’s economy is gradually shifting from “high-speed” development to “high-quality” development. The development of cultural industry which serves as a new engine of China’s economic development plays an important strategic role in building a cultural power and promoting economic transformation and upgrading. Based on the analysis of the current cultural development in China, this paper clarifies development periods of the cultural industry from the perspective of the WSR methodology, carries out a visual study on its policy texts, and actively explores the influencing factors and realization paths of cultural development. According to the study findings, WSR methodology provides theoretical and methodological support for the high-quality development of the cultural industry in China. The comprehensive and coordinated development of Wuli (technology), Shili (policy) and Renli (environment) is the only for China to improve its cultural development and promote the prosperity of its cultural market.