Green buildings are an important initiative to address energy and environmental issues in the construction field. The high-quality development of green buildings is affected by many factors, and it is necessary to identify the critical factors affecting the high-quality development of green buildings and analyze them systematically. The adopted literature analysis method and expert consultation method, the DIM (DEMATEL-ISM-MICMAC) model was established to explore critical factors influencing green buildings’ high-quality development and their internal hierarchical structure, interrelationships, and mechanisms. Then, targeted suggestions were put forward to promote green buildings’ high-quality development. The results showed that: (1) The critical factors influencing green buildings’ high-quality development could be divided into five levels, three groups, and four areas. The economic development level, living standard of residents, education level, incentive policies, and compulsory laws and regulations were in the deep factor group, fundamentally affecting green buildings’ high-quality development. (2) In terms of drive and centrality, the economic development level, living standard of residents, education level, and incentive policies were at the forefront, playing a vital role in the high-quality development of green buildings.
The impact of collusion during the bidding processes of Chinese government investment projects is a major concern in academic and policy circles, as collusion breeds corruption and destroys the credibility of governments. Furthermore, it negatively impacts successful project completion, leading to cost overruns and the illegitimate enrichment of colluding agents, regardless of the intended social benefits. Using data from 166 selected regional policy implementations as the research sample, this paper uses the fuzzy set qualitative comparative analysis method to conduct a group analysis of typical cases. The purpose of this study is to identify and better understand the cooperative regional policy implementation environments in China and to identify effective methods to improve the governance quality of collusion controls in construction investment project bidding processes. Five key control paths are identified, covering 94% of the cases. It is also found that in lower social collusion situations, reasonable market competition regulations can directly reduce collusive behavior. The research results will help the government to formulate more adaptive control policies and promote high-quality development of government investment projects.
To effectively diagnose and monitor the vertical collusion in construction project bidding, this paper developed a comprehensive evaluation model with deep neural network and transfer learning. By this model, the collusion characteristics of bidders, tenderers, and bid evaluation experts were mined from limited data set hidden and collusion tendency was evaluated. Firstly, 18 evaluation indicators were established from literature review, court file summarization, typical case analysis, and expert consultation. Then, a comprehensive evaluation model was developed with the deep neural network and transfer learning. Finally, the model was trained and tested with the collected data set. The test results showed that the developed model achieved 87.3% identification accuracy in collusion tendency evaluation of different subjects.
This paper explores the spatiotemporal evolution characteristics and spatial correlation patterns of green building development differences in 41 cities in the Yangtze River Delta region from 2012 to 2020 by means of the gravity center analysis model and spatial autocorrelation analysis. In addition, it further clarifies the impact factors of the spatial differentiation pattern of green building development in combination with GeoDetector based on four dimensional factors of population and economy, market environment, policy, and other factors. The results showed that: (1) According to the analysis of the number of green buildings in each city from 2012 to 2020 and the natural discontinuity method, the development pattern of green buildings in the Yangtze River Delta region city clusters shows an imbalance, being highly concentrated in the eastern coastal areas with Suzhou (1) and Shanghai as the core. The overall trajectory of the center of gravity shows the development from southeast to northwest. (2) The global Moran’s I of green buildings in the Yangtze River Delta region city clusters is greater than 0, and all passed the significance test (Z > 1.96, p < 0.01), indicating that the green buildings in the Yangtze River Delta region city clusters show typical spatial aggregation characteristics. By using the local LISA index, it is found that in the H-H spatial autocorrelation distribution pattern with Suzhou (1) and Shanghai as the core, the core city has a strong attraction ability and relatively low radiation ability. (3) Based on the explanatory power mean, the main driving factors of the spatial differentiation pattern of green building development in the Yangtze River Delta region city clusters are education level (0.6656), technical level (0.6269), and the gross domestic product (0.6091). The factor interaction shows a two-factor enhancement and nonlinear enhancement effect, and there is neither a weakening nor an independent relationship.
The classification of collusion behaviors of government-invested project tenderers is one of the important methods to describe the characteristics and laws of collusion behaviors and strengthen the governance of collusion. Firstly, the variables that affect the type of collusion behavior are selected and cluster analysis is carried out on the cases of collusion in government investment project bidding. Then use the social network to mine the types and characteristics of the collusion behavior of the tenderee. Finally, a BP neural network automatic identification model is established to quickly discriminate the types of collusion, which can effectively overcome the subjectivity of traditional methods. As a result, three typical types of collusion of tenderees can be obtained: intervention type, opportunity type, and cooperation type. The study found that the three types of collusion behavior have their own characteristics and laws, and the relationship between the variables that affect the type of collusion behavior is complex and affects each other.
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