Under the background of “dual-carbon” target construction, the low-carbon environmental protection and ecological construction of Huzhou city in China have received high attention. To scientifically measure the low-carbon construction effect of the city, this study constructs a reasonable comprehensive evaluation system of low-carbon city competitiveness from four aspects, including low-carbon economic foundation, low-carbon lifestyle, low-carbon environmental construction, and low-carbon technology development. An integrated weight model of attributes consisting of the analytic hierarchy process (AHP) and entropy weight method is then established, and on this basis, an integrated TOPSIS model is constructed to assess the development of low-carbon competitiveness in Huzhou City. A horizontal comparative analysis of five cities around Huzhou is also conducted, and the current level of low-carbon competitiveness of cities in the central region of the Yangtze River Delta is further explored. Finally, several relevant reference suggestions for Huzhou city are provided to build an ecological model city and a green low-carbon national model and help the government to accelerate the pace of building a low-carbon city in the whole region.

It is of great significance to build an efficient and cooperative innovation system and support system under the background of China persisting in leading the development with innovation and speeding up the construction of an innovation-oriented country. The collaborative relationship and profit distribution of each innovation subject will be analyzed through the study of the innovation activity in the innovation chain. With consideration of the characteristics of the innovation chain such as high risk, financing difficulty, cooperative partnership and so on and using the internal financing mode of supply chain for reference, the game model of internal financing between members of the innovation chain will be established. The game equilibriums will be solved and analyzed, and the optimal equilibriums will be achieved by designing the contracts to establish the internal financing mechanisms in the innovative chain. For the risk asymmetry at each stage of the innovation chain, the contracts will be optimized to construct the risk sharing mechanism to control the risk of the internal financing in the innovation chain. In order to make innovations, this paper creates the financial support mode of the innovation chain, improves the innovation support system and increases the efficiency of the innovation chain.

The green transition of polluting firms is critical for achieving sustainable economic development. While previous research has explored the relationship between environmental policy and corporate pollution, it has often neglected the sustainability challenges faced by firms. Drawing on data from listed companies in China from 2008 to 2022, this paper empirically examines the impact of environmental policy on the risk-taking behavior of polluting firms. Building on this analysis, we assess the ecological impact, characteristics, and underlying mechanisms of a specific policy, while proposing solutions to promote sustainability in polluting firms. The findings indicate that, although environmental policy reduces the risk-taking levels of polluting firms, it has not been effective in curbing pollution emissions. This effect is particularly pronounced in firms exhibiting characteristics such as low-quality environmental information disclosure, industry resource crowding, and stringent regional assessments. The policy heightens financing constraints and investment costs for polluting firms and diminishes their expectations for future growth, ultimately suppressing both their capacity and willingness to take risks. Further analysis suggests that environmental coordination regulations and green transition guidance can encourage risk-taking behavior among polluting firms. These findings offer empirical evidence from the perspective of polluting firms, providing valuable insights into addressing the sustainability dilemma.

This study investigates risk contagion and dependence structures between U.S. and Chinese technology-related stock markets, focusing on the electronics and semiconductor sectors. We employ DCC-GARCH models to capture time-varying correlations and copula models to analyze nonlinear and tail dependencies. To highlight extreme risk dynamics, we extend the analysis to Value-at-Risk (VaR) series derived from a GARCH(1,1)-Skewed-t model. Empirical results reveal three major findings. First, volatility clustering and negative skewness are evident across markets, with extreme downside risks concentrated during the 2015 Chinese stock market crash and the 2020 COVID-19 pandemic. Second, copula results show stronger upper-tail dependence in cross-border broad markets and more symmetric dependence within domestic Chinese markets, while U.S. sectoral linkages exhibit the highest vulnerability during downturns. Third, dynamic copula analysis indicates that downside contagion is episodic and crisis-driven, whereas rebound co-movements are structurally persistent. These findings contribute to understanding systemic vulnerability in global technology markets. They provide insights for investors, regulators, and policymakers on monitoring cross-market contagion and managing systemic risk under stress scenarios.

Firms can purchase innovation results to improve their technology. In this context, the key to transfer success is reasonably priced innovation results. Considering the match between innovation results and firm technology, this study analyzes the nonlinear improvement effect of innovation results on technology. The pricing decision is then assessed by a game model of the innovation results transfer and pricing that is based on the entire innovation process, including research and development (R&D) and transfer. Then the method for transfer pricing of innovation results is obtained from the equilibrium of game. The results show that firms tend to evaluate innovation results by matching them with their own technologies, and then make bids based on the R&D costs. Here, innovation results are obtained by firms with high-level matching. After considering the matching, the transfer pricing of innovative results will prosper the transfer market and improve the success rate of transfer. Several factors affect the possibility of transfer of innovation results and their price, including the R&D ability of the institution, the technology levels of firms, and the technological competition between firms. These conclusions were validated using a numerical example. Keyword : transfer of innovation result, match between innovation and technology, transfer price, influencing factor, bidding game, pricing decision