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The sensitivity and fragility of the construction industry’s economic system make the economic resilience of the construction industry (ERCI) a key concern for stakeholders and decision-makers. This study aims to measure the ERCI, identify the heterogeneity and spatial differences in ERCI, and provide scientific guidance and improvement paths for the industry. It provides a foundation for the implementation of resilience policies in the construction industry of developing countries in the future.

The comprehensive index method, Theil index method, standard deviation ellipse method and geographic detector model are used to investigate the spatial differences, spatiotemporal evolution characteristics and the influencing factors of the ERCI from 2005 to 2020 in China.

The ERCI was “high in the east and low in the west”, and Jiangsu has the highest value with 0.64. The Theil index of ERCI shows a wave downward pattern, with significant spatial heterogeneity. The overall difference in ERCI is mainly caused by regional differences, with the contribution rates being higher by more than 70%. Besides, the difference between different regions is increasing. The ERCI was centered in Henan Province, showing a clustering trend in the “northeast-southwest” direction, with weakened spatial polarization and a shrinking distribution range. The market size, input level of construction industry factors, industrial scale and economic scale are the main factors influencing economic resilience. The interaction between each influencing factor exhibits an enhanced relationship, including non-linear enhancement and dual-factor enhancement, with no weakening or independent relationship.

Exploring the spatial differences and driving factors of the ERCI in China, which can provide crucial insights and references for stakeholders, authorities and decision-makers in similar construction economic growth leading to the economic growth of the national economy context areas and countries.

The construction industry development is the main engine for the national economy growth of most developing countries. This study establishes a comprehensive evaluation index on the resilience measurement and analyzes the spatial effects, regional heterogeneity and driving factors on ERCI in the largest developing country from a dynamic perspective. Moreover, it explores the multi-factor interaction mechanism in the formation process of ERCI, provides a theoretical basis and empirical support for promoting the healthy development of the construction industry economy and optimizes ways to enhance and improve the level of ERCI.

Reducing construction waste generation and carbon emission in the construction industry is crucial for the “dual carbon” goal. Evaluating the efficiency of reducing construction waste generation and carbon emission in the construction industry at the regional level is an important evaluation basis for the sustainable development of the construction industry. It provides a basis for formulating construction waste and carbon reduction policies tailored to local conditions and comprehensively promote the sustainable development of the construction industry.

A three stage SBM-DEA model based on non-expected outputs is proposed by combining the SBM-DEA model with the SFA method. The proposed model is used to evaluate the efficiency of construction waste and carbon reduction in the construction industry in 30 regions of China from 2010 to 2020. Moreover, the study explores the impact of environmental variables such as urbanization level, proportion of construction industry employees, resident consumption level, and technological progress.

From 2010 to 2020, the efficiency of construction waste and carbon reduction in China’s construction industry has been increasing year by year. Provinces with higher efficiency of construction waste and carbon reduction in the construction industry are mainly concentrated in the eastern coastal areas, showing an overall pattern of “East>West>Northeast>Middle”. There is a clear correlation between the level of urbanization, the proportion of construction industry employees, residents’ consumption level, technological progress, labor input, machinery input, and capital investment. The construction waste and carbon emission efficiency of the construction industry in various provinces is greatly influenced by environmental factors.

The research results provide policy makers and business managers with effective policies for reducing construction waste generation and carbon emission in the construction industry, especially circular economy policies. To provide empirical support for further understanding the connotation of construction waste and carbon reduction in the construction industry, to create innovative models for construction waste and carbon reduction, and to promote the multiple benefits of construction waste and carbon reduction in the construction industry, and to provide empirical support for countries and enterprises with similar development backgrounds in China to formulate relevant policies and decision-making.

The construction industry is a high investment, high energy consumption, and high pollution industry. This study uses the three stage SBM-DEA model to explore the efficiency of construction waste and carbon reduction in the construction industry, providing a new perspective for the evaluation of sustainable development in the construction industry, enriching and improving the theory of sustainable development.

The growth of the Chinese economy has resulted in a significant increase in construction and demolition waste (CDW), and regional differences in CDW generation are gradually increasing. The purpose of this study is to investigate the regional differences in CDW generation and the driving factors that influence CDW generation in different areas of China. To provide a systematic advisement for local governments to select the appropriate policy, reduce CDW generation.

The generation of CDW was calculated by region, based on the area estimation method, from 2005 to 2018. The relationship between CDW generation and economic development, and the driving factors of CDW generation in different regions of China, was investigated using the environmental Kuznets curve (EKC) model and the STIRPAT theoretical model.

CDW generation of China increased at the average annual growth rate of 10.86% from 2005 to 2018. The main areas of CDW generation were concentrated in the eastern and central regions, while the proportion of CDW generation in the northeast region decreased gradually, and the changes varied significantly across different regions. The EKC between CDW generation and economic development was established for the whole country, North China, Northeast China, East China, Central South China, Southwest China and Northwest China. Three main factors based on the STIRPAT theoretical model were identified and explained into a framework to reduce CDW generation. The results provided a useful theoretical basis and data support guide for devising effective policies and regulations for the Chinese context.

The findings from this study can ultimately support policymakers and waste managers in formulating effective policies for waste management strategies and CDW-specific legislation. Additionally, it can help the coordinated reduction of CDW generation across regions in China and can support construction enterprises (in their development strategies), similar developing economies and foreign firms planning to operate in China.

This study contributes to the field through the STIRPAT model on driving factors of CDW generation in the Chinese context, in different regions.

Public-private partnership (PPP) projects for construction waste recycling have become the main approach to construction waste treatment in China. Risk sharing and income distribution of PPP projects play a vital role in achieving project success. This paper is aimed at building a practical and effective risk sharing and income distribution model to achieve win–win situation among different stakeholders, thereby providing a systematic framework for governments to promote construction waste recycling.

Stakeholders of construction waste recycling PPP projects were reclassified according to the stakeholder theory. Best-worst multi–criteria decision-making method and comprehensive fuzzy evaluation method (BWM–FCE) risk assessment model was constructed to optimize the risk assessment of core stakeholders in construction waste recycling PPP projects. Based on the proposed risk evaluation model for construction waste recycling PPP projects, the Shapley value income distribution model was modified in combination with capital investment, contribution and project participation to obtain a more equitable and reasonable income distribution system.

The income distribution model showed that PPP Project Companies gained more transaction benefits, which proved that PPP Project Companies played an important role in the actual operation of PPP projects. The policy change risk, investment and financing risk and income risk were the most important risks and key factors for project success. Therefore, it is of great significance to strengthen the management of PPP Project Companies, and in the process of PPP implementation, the government should focus on preventing the risk of policy changes, investment and financing risks and income risks.

The findings from this study have advanced the application methods of risk sharing and income distribution for PPP projects and further improved PPP project-related theories. It helps to promote and rationalize fairness in construction waste recycling PPP projects and to achieve mutual benefits and win–win situation in risk sharing. It has also provided a reference for resource management of construction waste and laid a solid foundation for long-term development of construction waste resources.

PPP mode is an effective tool for construction waste recycling. How to allocate risks and distribute benefits has become the most important issue of waste recycling PPP projects, and also the key to project success. The originality of this study resides in its provision of a holistic approach of risk allocation and benefit distribution on construction waste PPP projects in China as a developing country. Accordingly, this study adds its value by promoting resource development of construction waste, extending an innovative risk allocation and benefit distribution method in PPP projects, and providing a valuable reference for policymakers and private investors who are planning to invest in PPP projects in China.