This paper divides government policy according to policy quantity, policy effectiveness and policy executive force so that the government policy can be quantified in more detail. Green patent data is used to represent green technological innovation, and the fixed effect model and panel data analysis from 2010 to 2019 are employed. The empirical results show that government policy has a significant direct promoting effect on green technology innovation. And the positive impact of policy quantity and policy effectiveness on green technology innovation is greater than that of policy executive force. In addition, the government policy will weaken the positive effect of enterprise innovation vitality on green technology innovation. Research conclusions also show that the direct and indirect effects of government policies on green technology innovation are heterogeneous. The government still needs appropriately policies adapted to the local situation, coordinated in policy quantity, policy effectiveness, and executive force, and accelerate the establishment of market-oriented green technology innovation environment. Different regions also should find the right green technology innovation policy scheme for their own regions.

The relationship among cities is getting closer, so are housing prices. Based on the sale price of stocking houses in thirty-five large and medium-sized cities in China from 2010 to 2021, this study established the modified gravity model and used the method of social network analysis to explore the spatial linkage of urban housing prices. The results show that: (1) from the overall network structure, the integration degree of housing price network in China is still at a low stage, and the influence of housing price is polarized; (2) from the individual network structure, Beijing, Shanghai, Shenzhen, Nanjing, Hangzhou, and Hefei have a higher degree of centrality. Chengdu, Xining, Kunming, Urumqi, and Lanzhou stay in an isolation position every year; (3) from the results of cohesive subgroup analysis, different cities play different roles in the block each year and have different influences on other cities. (4) Emergencies, such as outbreaks of COVID-19, also have an impact on the housing price network. Structural divergence among urban housing prices has become more pronounced, and the diversity of house price network has been somewhat reduced. Based on the above findings, this paper puts forward some recommendations for the healthy development of housing market from the perspective of housing price network.

Urban–rural transformation development is the key to resolving the imbalance in the dual structure of urban and rural areas. However, the transformation of the urban–rural relationship will also affect the structure and spatial distribution of land use. This paper measured the spatial–temporal characteristics of land–use transition in the Yangtze River Delta from 1990 to 2018 by using a geo–information Tupu method and explored the driving mechanism of land–use transition under the background of urban–rural transformation development by using a spatial regression analysis method. The results showed the following: (1) The transition from cultivated land to urban construction land, from rural residential land to cultivated land, and from rural residential land to urban construction land were the three main types of land–use transition in the Yangtze River Delta during urban–rural transformation development. (2) The transition from cultivated land to urban construction land was always the most important type of land–use transition. It expanded from the central area to the surrounding cities. The transition of rural residential land to cultivated land and urban construction land began to increase significantly after the year 2010, which was the urban–rural integration development period. (3) The urban–rural land–use transition was driven by government policies, industrial restructuring, population urbanization and migration. During the urban–rural integration development period, secondary industry and tertiary industry were the main driving factors of the transition from cultivated land to urban construction land. The number of policies, the primary industry, the total population, and the urbanization rate were the main driving factors of the transition from rural residential land to cultivated land. Primary industry, secondary industry, and tertiary industry were the main driving factors of the transition from rural residential land to urban construction land. Finally, the study provided some suggestions for policy, industry, and population driving forces.

Boosting green technology innovation of enterprise is the key to achieving a win-win situation for both environmental performance and economic performance. However, some Chinese enterprises still have hesitations and misgivings as to whether they should adopt green technology. Considering the uncertainty of the innovation and the irrational psychological factors of decision makers, the purpose of this paper is to analyse the driving mechanisms and the long-term behaviour of enterprises green technology innovation, as well as to explore what preconditions are required for enterprises to adopt green technology innovation. The methods are prospect theory and evolutionary games. This paper first calculates the equilibrium stability and evolutionary stability strategies of the enterprise green technology innovation system and then simulates the effect of subjective gains and losses values and other psychological parameters in the prospect editing and evaluation stage. Results show that increase in subjective gain and decrease in reference points and subjective spill benefit will motivate enterprises to adopt green technology innovation in the prospect editing stage; higher risk preference and lower loss aversion will increase enterprises’ motivation for green technology innovation in the prospect evaluation stage. Besides, we find that enterprise decisions are influenced by risk perception and loss aversion rather than just the magnitude of the benefits and cost. Small- and medium-sized enterprises are more likely to turn to green technology innovation than large enterprises under the same level of risk preference and loss aversion. Finally, some suggestions are put forward for the government to encourage enterprises to adopt green technology innovation. This paper can provide a reference for theoretical and practical research on evolutionary game and prospect theory on green technology innovation of enterprises.

Home-purchase limit is a unique administrative housing policy of China and has non-negligible influences on the housing price. The objective of this study is to analyze the spillover effect of home-purchase limit policy on housing prices in 35 large and medium-sized cities. The panel data of these cities and the spatial Durbin model are employed in this study. The results indicate that the spillover effect of home-purchase limit policy is positive and significant in all of 35 cities. However, when we categorize these cities into high-risk, medium-risk, and low-risk based on housing price characteristics, the spillover effect of home-purchase limit policy is different. It is not significant in high-risk cities, is negatively significant in medium-risk cities, and is positively significant in low-risk cities. This paper suggests that local governments can pay more attention to the precise design and implementation of home-purchase limit policy, and maintain policy continuity to avoid further spillover fluctuations in housing prices.