Search results

Due to the close connection between urban cluster and carbon emissions (CEs) but a lack of study on it of the construction industry, this paper aims to explore the relationship between the polycentric spatial structure (PSS) of the urban clusters and CEs of the construction industry (CECI).

This research uses panel data of 10 Chinese urban clusters from 2006–2021, calculates their PSSs in the aspects of economy and employment and adopts a panel regression model to explore the effect of the spatiotemporal characteristics of the PSSs on the CECI.

First, the CECI in 10 Chinese urban clusters showed a rising trend in general, and the CECI in the Yangtze River Delta (YRD) was much higher than those in the rest of urban clusters. Second, both Shandong Peninsula (SP) and Guangdong-Fujian-Zhejiang (GFZ) exhibited high degrees of polycentric characteristics, while Beijing-Tianjin-Hebei (BTH) showed weaker degrees. Third, the results demonstrated that the polycentric development of urban clusters did not help reduce the CECI but rather promote the CE. The polycentric index, considering the linear distance from the main center to sub center, had a more significant impact on the CECI.

Previous studies have investigated the impact of urban spatial structure (USS) on CEs; however, few of them have studied in the field of construction industry. Moreover, most research of CEs have concentrated at the national and provincial levels, with fewer studies on urban clusters. This paper contributes to this knowledge by investigating how the PSS of urban cluster influence the CECI.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.

In China, engineering insurance has been questioned as not being beneficial as expected. This paper seeks to further understand how China's engineering insurance industry functions and to provide a macro perspective explanation for engineering insurance's underdevelopment.

Three industrial organization hypotheses were extended to the engineering insurance context: structure conduct performance (SCP), relative market power (RMP) and efficiency structure (ES) hypotheses. This paper employed the Generalized Method of Moments (GMM) and Data Envelopment Analysis (DEA) bootstrap to test the hypotheses using panel data from 2008 to 2017.

The results suggest that the SCP paradigm is validated in China's engineering insurance market, indicating a concentrated market where the welfare of consumers (e.g. owners, contractors and designers) may be eroded. Several factors are identified to have significant impacts on engineering insurers' performance, such as the investment return, percentage of engineering business, the ratio of outstanding claims, the number of large contractors, market rivalry and entry barriers.

Despite the sheer size of China's construction industry and the urgent need to improve risk management, the insurance industry that serves construction firms engineering insurance is underdeveloped. Engineering insurance is yet to be understood from a macro perspective, which may reveal the underlying reasons for engineering insurance's underdevelopment. The industrial organization theories provided a theoretical framework to test the functioning of this specific industry. The disaggregated data (engineering line specific) is employed to ensure effective regulation and policymaking.