Green technology innovation of heavily polluting enterprises is a critical way to alleviate environmental pressure and promote sustainable development. However, the ways in which the interaction of influencing factors affects heavily polluting enterprises in green technology innovation in China have not been fully addressed and need to be investigated in this field. This paper explored the impact of government environmental regulation, corporate social responsibility (CSR), and public attention on promoting green technology innovation of heavily polluting enterprises based on S-O-R (stimulus–organism–response) and stakeholder theories. The panel data of A-share listed companies in China’s heavily polluting industries from 2008 to 2020 was used to investigate their interactions by adopting POLS (Pooled Ordinary Least Square) method. The main results show that (1) environmental regulation has a significant positive effect on green technology innovation; it especially has a great impact on state-owned heavily polluting enterprises; (2) CSR plays a mediating role between environmental regulation and green technology innovation; (3) public attention has a moderating effect between CSR and green technology innovation and also moderates the indirect effect of environmental regulation on green technology innovation through CSR. The results illustrate that green technology innovation should be not only guided by governmental regulation, but also supplemented by enterprises’ internal driven force and public supervision, which can give implications for promoting the development of green technology innovation and optimizing environmental policy tools.

With the convergence of China’s “entrepreneurial society” and the “digital age,” part-time entrepreneurial behavior (PEB) has received widespread attention as a new form of labor relations and entrepreneurial paths. Entrepreneurial self-efficacy (ESE) is an important indicator of entrepreneurs’ confidence in their skills and in coping with uncertain entrepreneurial challenges. However, studies on how ESE affects different types of PEB have not been thoroughly carried out. To fill the existing research gap, the primary objective of this paper is to thoroughly investigate the individual impact of three key factors, namely organizational management self-efficacy (OMSE), opportunity development self-efficacy (ODSE), and risk-taking self-efficacy (RTSE), on economic profit-driven part-time entrepreneurial behavior (EPEB) and self-value-driven part-time entrepreneurial behavior (SPEB), respectively. Based on the “cognition-environment-behavior” logic of triadic reciprocal determinism, this study also aims to examine the moderating effect of entrepreneurial resources (ERs) and attempt to understand how external factors regulate internal factors (OMSE, ODSE, and RTSE) to form the results of EPEB and SPEB. This study adopted a quantitative research approach with a questionnaire survey, taking 457 part-time entrepreneurs in 11 major cities as subjects. The main results show that (1) OMSE and ODSE have a positive effect on EPEB, while RTSE has an inverted U-shaped effect on it; (2) ODSE and RTSE have a positive effect on SPEB, and OMSE has an inverted U-shaped effect on it; and (3) ERs play a positive moderating role in the above processes. The results can not only effectively guide part-time entrepreneurs in PEB but also provide a reference for the government to improve part-time entrepreneurship policies.

The Chinese economy is transitioning from high-speed development to high-quality development, and water environmental governance is a key factor promoting economic transformation. Due to low returns and high investment in China’s water environmental governance, the PPP (public–private-partnership) model is often adopted. However, the PPP model has historically faced challenges adapting to local conditions in China, leading to social risks in the PPP projects of water environmental governance. To reduce these risks, this paper takes a vulnerability perspective, employing the system dynamics simulation method to explore the dynamic evolution process of social risks in the PPP projects of water environmental governance. The main results show the following: (1) the external manifestations of social risks during the construction and operation periods vary significantly, exhibiting notable fluctuations; (2) during the construction period, there is a surge in social risks followed by a returns to lower than normal levels, then a gradual upward trend; during the operation period, social risks initially decrease to a lower level before gradually increasing; and (3) city class, relevant legal systems, and resource reserves emerge as critical factors influencing vulnerability and social risks. The higher the city class, the lower the project vulnerability; the soundness of the legal system for PPP projects can effectively reduce vulnerability and social risks; sufficient resource reserves can reduce social risks. Based on the above findings, this paper proposes several suggestions aiming to reduce the vulnerability and social risks in PPP projects, optimize the process of water environmental governance, and further promote the sustainable development of water environmental governance and the high-quality economy of China.

Water resources are the foundation for human survival and development, yet intensified human activities have increased the risks of water quality deterioration. Existing water quality early warning studies predominantly emphasize prediction performance while often under-addressing anomaly determination, which contributes to frequent false alarms in operational monitoring. From a dual-driven perspective of knowledge and data, this study develops an integrated framework for water quality monitoring and abnormal early warning. On the knowledge-driven side, abnormal water quality observations are systematically categorized into pseudo anomalies induced by accidental disturbances and true anomalies characterized by sustained structural deviations such as violent fluctuations or upward/downward leaps. Accordingly, reproducible identification strategies are designed, including rolling-statistics-based detection for isolated false data points, rolling-variance screening for variance-shrinkage sequences, and difference-threshold rules for rapid-change segments, enabling the exclusion of pseudo anomalies from model learning and improving alert credibility. On the data-driven side, a Stacking ensemble learning model is constructed by integrating multiple base learners to capture nonlinear temporal patterns and enhance multi-step prediction performance. The proposed framework is validated using high-frequency water quality, water level, and rainfall data from three monitoring stations in the Phase II of the Eastern Route of China’s South-to-North Water Diversion Project. Results show that the ensemble model demonstrates good tracking ability, while the knowledge–data coupling mechanism effectively distinguishes pseudo anomalies from true anomalies, thereby reducing false alarms and improving the practical feasibility of water quality monitoring and early warning.

Water environment governance of large rivers is an essential measurement of ecological protection in China. The effectiveness of governance depends highly on the fulfillment of strategic CSR (corporate social responsibility) of Chinese leading enterprises. However, the fulfillment of strategic CSR often brings economic burden to the leading enterprises and needs government compensation support. Therefore, this paper explores the impact of government compensation on the fulfillment of strategic CSR of Chinese leading enterprises by constructing a multi-stage portfolio model. The main results show that (1) the prerequisite for leading enterprises to fulfill strategic CSR is sufficient profits; (2) the increase in government compensation can significantly affect the proportion of strategic CSR fulfillment of leading enterprises; (3) only when the portfolio considers both strategic CSR and project benefits, can the leading enterprises obtain the highest economic returns and better fulfill strategic CSR. The results can provide policy reference for the government to stimulate the fulfillment of leading enterprises’ strategic CSR and also give suggestions for the leading enterprises to alleviate the economic pressure brought by fulfilling strategic CSR.

The engineering general contracting mode is an advanced engineering transaction mode, and design optimization is one of the important driving forces for vigorously promoting the general contracting mode. The application proportion of the general contracting mode in infrastructure projects is not high, the number of successful projects is not large, and the implementation effect is not ideal. One of the main reasons is that the design optimization theory and practice of international standard general contracting projects cannot adapt to the general contracting projects in the Chinese context, making local general contracting projects face huge challenges such as low enthusiasm for design optimization from all parties and unsatisfactory design optimization effects. Therefore, under the premise of bounded rationality, when the owner adopts control methods of different intensities, an evolutionary game study on the selection of design optimization strategies between the design and construction parties is carried out, and stability control strategies are proposed through case experiments and simulations. The research results indicate the following: firstly, the design optimization of general contracting projects in the Chinese context is feasible, but it depends on the distribution ratio of benefits obtained from the design optimization. Compared with general civil construction general contracting projects, the design optimization allocation ratio of industrial construction general contracting projects is more significant; secondly, the mixed control method of strong control and weak control is the optimal choice for the owner of the general contracting project; and thirdly, there are multiple evolutionary stable points, and mechanism design or incentive measures should be used to guide owners to choose weak control strategies, while design and construction parties should choose their design optimization strategies. The research results provide a reference for owners to determine the proportion and scheme of design optimization allocation, and for construction parties to determine design optimization strategies.