Construction cost overrun chronically plagues contractors. To address the issue, numerous studies have explored cost overrun risks (CORs). Nevertheless, their methods of identifying risk relationship are susceptible to experts’ experience. In addition, they fail to unearth the relationship structure information and analyze the risk propagation effect. To fill these gaps, this paper intends to propose a methodology that integrates the engineering case analysis and complex network theory, so as to obtain a stable relationship structure and reveal its inherent property. First, 52 CORs and 158 risk paths are extracted from 156 engineering cases, followed by the establishment of a cost overrun risk propagation network (CORPN). Finally, the statistical properties of CORPN are explored. The results indicate that CORPN presents the topological property of heterogeneity. A large number of risk paths can be blocked through preventing the CORs with large total degree, like delay in construction period and engineering quantity increase. Meanwhile, CORPN shows the small-world property. The efficiency of risk propagation can be reduced through preventing the CORs with high betweenness centrality, such as lack of technical skill and experience. These findings contribute to the formulation of beforehand strategies that promote the cost management.

The improvement of the macro-level accident situation in the Chinese construction industry is currently an urgent task for the government due to the high accident rate. This study intends to use improved principal component analysis to explore the accident situations in the Chinese construction industry from a multi-dimensional perspective, aiming at providing targeted direction on the improvement of the accident situation for the government. Six composite indicators that can quantify the accident situation are firstly selected based on a wide review of the literature and interviews with safety experts, with the original data collected from China institutions. The classical principal component analysis is then improved to examine the correlations between indicators, and further to evaluate accident situations in China provinces. Finally, the features of accident situations are explored and analyzed from a multi-dimensional perspective. The findings show that the improved principal component analysis can retain more dispersion degree information of the original data. Meanwhile, three principal components including the accident frequency, trend, and severity were extracted to quantify the accident situation, and a hierarchical indicator system for the comprehensive evaluation of the accident situation was constructed to deeper understand multi-dimensional characteristics of China’s accident situations. Furthermore, there exist great regional differences of accident situations in Chinese provinces. From the overall perspective, the accident situation shows a declining trend from the western backward region to the highly developed eastern coastal region. This study provides a multi-dimensional perspective for the government to formulate safety regulations and improve the accident situation.

The multi-attribute and group-decision problem in the selection of a construction diversion scheme for large hydropower projects often involves multi-decision subjects and schemes. Each scheme includes multiple attributes, and the attribute values and weights are multi-attribute group decision-making problems with interval numbers. In this study, a new method for solving the multi-attribute group-decision problem is proposed by integrating regret theory, negotiation gathering theory, and the Monte Carlo simulation technique. Firstly, decision-makers’ comprehensive perception utility for each scheme is calculated based on the regret theory. Then, non-uniform and fuzzy opinion of different decision subjects are negotiated and gathered, and negotiation intervals of the attribute weights are calculated through group negotiation gathering theory. Moreover, fuzzy complementary judgment matrixes describing an excellent degree of the diversion schemes are obtained by conducting Monte Carlo simulations. Finally, the alternative diversion schemes are sorted in terms of their priorities, and the reliability of the sorting procedure is confirmed. The multi-attribute group-decision problem in the selection of a construction diversion scheme for Jinping I Hydropower Station is effectively solved by the proposed method. The proposed method is reliable and may significantly contribute to engineering decision-making.

As one of the most high-risk sections, the construction industry has traditionally been the research hotspot. Yet little attention has been paid to macro-level accident situations of the entire industry. Therefore, this study develops a comprehensive assessment model on accident situations of Chinese building industry, aiming at assisting the government to better understand and improve accident situations of the entire industry. Based on China conditions, six indicators related to accident situations are firstly selected to establish an indicator system; then structure entropy weight method is proposed to determine indicator weighs, with dynamic classification method to explore the characteristics of accident situations. The results demonstrate that the provinces with poor accident situations account for 53% of all provinces, and they are mainly distributed in the central and western regions of China where there exist the underdeveloped economy. Meanwhile, some provinces experience poor accident situations that could be out-of-control, especially for Hebei. Provinces in the southeastern and northeastern regions of China perform relatively well, but they still have much improvement room for accident situations. The findings validate the rationality of the developed model and can provide valuable insights of safety regulation strategies for the government from the macro-level perspective.

Large hydropower project involves numerous stakeholders in the construction phase. The risk of delayed payment may escalate into an event of catastrophic economic loss through complex stakeholders’ relationships. This paper builds a complex stakeholder network by collecting all contract prices in large hydropower project construction (LHPC) and proposes a novel mathematical model based on Cellular Automata Susceptible-Infected-Susceptible (CA-SIS) framework to analyze the risk propagation of delayed payment (RPDP). In the model, to approximate actual loss diffusion, risk-resisting and risk-mitigating abilities of stakeholders are combined, and relevance between risk mitigation and time is taken into account. The rationality and feasibility of the novel model are illustrated through its application to an actual LHPC. The simulation results include the following: RPDP presents three phases: risk first slightly propagates, risk then exponentially breaks out, and at last propagation consequence will reach a stable state related to stakeholders’ risk-resisting ability closely; in respect of stakeholders’ risk-mitigating ability and property of the network, RPDP range decreases with the increase of number of partners and homogeneity of contract price distribution; in respect of stakeholders’ risk-resisting ability, RPDP range decreases with the decrease of number of partners. This research can serve as a powerful complement to analyze and control the delayed payment in LHPC.