Deep foundation pit (DFP) projects have been a high incidence area of safety accidents because of their own high danger and complexity. Therefore, it is necessary to study the resilience of their construction safety system. This paper systematically identifies the key factors affecting the resilience of deep foundation pit construction based on the analysis of the composition of the deep foundation pit construction safety system (DFPCTSS), the synergistic relationship of its subsystems in the face of the interference and impact of internal and external disaster-causing factors, and the causal mechanism of typical accidents in DFP accidents and the emergent process of system resilience. A resilience evaluation indicator system based on four capacity dimensions of prevention absorption, resistance, recovery, and learning adaptation was constructed by using the fuzzy Delphi method, which is characterized by the resilience emergence process. Then the correlation and weight of evaluation indexes were analyzed based on the DEMATEL–ANP method, the boundary cloud parameters of the resilience evaluation grade were set according to the normal extension cloud model, and the membership degree of the resilience evaluation level was calculated to complete the evaluation of the resilience level. Finally, taking a DFP project of a metro station as an example, the above model was used to evaluate the resilience level of its construction safety system, and suggestions for resilience enhancement were put forward. The results show that the evaluation results are consistent with the actual situation of the project, and the evaluation model is conducive to providing a systematic analysis method and improvement countermeasures for deep foundation pit construction safety management from the perspective of resilience.

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Construction and demolition waste (C&DW) during new district development shows the characteristics of large quantity, concentrated distribution, and long duration on both supply and demand sides. The construction of the new district has objective conditions to promote the scale development of recycling industries and achieve green development through local digestion, so the recycling indicators for the new district proposed by the government are generally higher than those of other regions. However, many new districts have yet to systematically identify key drivers (KDs) of recycling and form win-win governance mechanisms with multiple government and market subjects, resulting in uncontrolled accumulation or high-cost discard of C&DW. This paper identifies 29 recycling drivers and 8 governing subjects through literature research and a field study of five national new districts in China. Then, a 2-mode social network and two 1-mode social networks are constructed to analyze the complex interactions between drivers and governing subjects, taking Nanjing Jiangbei New District as an example. The results of the study show that most of the drivers need at least 2 governance subjects to promote together, which indicates that it is necessary to build a collaborative governance mechanism of multiple subjects. This study provides a structured framework to analyze the drivers of recycling in new district development and the collaborative governance of multiple subjects, which can provide a basis for promoting efficient recycling of new district development.