As an effective measure to reduce energy and material consumption, green building has drawn much attention all over the world. Under the background of ecological city construction, the development speed of green building is extremely high in China. However, it is unclear about the overview of regional green building development. This study puts forward an evaluation model to scientifically measure the regional development of green building. The rough set theory and the catastrophe progression method optimized by entropy method are utilized in the model. A case study is conducted to clarify the application of the evaluation model, and the spatial distribution of regional green building development in 2015 is shown in the end. The result shows that the evaluation model is scientific and applicable. The spatial distribution of green building development in China was uneven. Green building development concentrated on the Beijing-Tianjin-Hebei area, Jiangsu-Zhejiang-Shanghai Area, Guangdong and Chongqing. Tibet was almost the bottom in every aspect, but it performed the best in economic efficiency. This study not only contributes to the research area of green building development, but also helps to promote green buildings in practice.

The construction industry suffers from poor safety performance caused by the joint effect of insufficient safety investment by contractors and inefficient safety supervision by the government because of the information gap between the two sides. The present study aims to put forward a new pathway to improve safety investment supervision efficiency and analyze the decision-making interactions of stakeholders under this new pathway. For this purpose, this study establishes a safety investment information system to eliminate the information gap between the government and contractors for construction projects in China and further develops a dynamic safety investment supervision mechanism based on this. Evolutionary game theory is used to describe the decision-making interactions among stakeholders under the current static supervision mechanism and the dynamic supervision mechanism proposed in this research. Moreover, system dynamics is adopted to simulate the evolutionary game process and analyze the supervision effect and equilibrium state of different supervision mechanisms. The results reveal that the proposed safety investment information system could facilitate the transition of the supervision mode from static to dynamic; the evolutionarily stable strategy does not exist in the current static penalty scenario; and the dynamic supervision mechanism that correlates penalties with contractors’ unlawful behavior probability can restrain the fluctuation of the evolutionary game model effectively and the players’ strategy choices gradually stabilize in the equilibrium state. The results validate the effectiveness of the proposed dynamic supervision mechanism in improving supervision efficiency. This study not only contributes to the literature on safety supervision policy-making but also helps to improve supervision efficiency in practice.

This study aims to examine the national risk governance mechanism of critical infrastructure in China from a cross-section perspective. The first research objective is to identify whether horizontal collaboration exists in the risk governance of critical infrastructure. Building on this, the second research objective is to investigate the extent of cross-section collaboration in the transportation and energy domains. The third research objective is to identify the pathways of horizontal collaboration at various levels. The data for this research consists of policy documents retrieved from the official websites of the Ministry of Transport of the People’s Republic of China, the National Energy Administration, and the Peking University Legal Information Website. A total of 127 documents were collected using specific search keywords. To analyze data, content analysis is adopted to generate a co-word matrix so that semantic network centrality can be explored. The result indicates that in the transportation domain “engineering” and “road” feature in the top 10 for both standardized degree and degree proportion, while “administration” ranks third highest in share proportion. In the energy infrastructure risk governance keyword network, the fourth highest closeness centrality value is 54.762, associated with keywords such as “administration” and “engineering”. These findings suggest that horizontal collaboration is evident at both institutional and personal levels. Moreover, the results imply that the inner collaboration within national risk governance is intricate and interdependent. The study reveals interconnections between different industries and administration levels, contributing a fresh perspective to urban risk governance theory exploration.