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The purpose of this paper is to develop a novel integrated risk assessment method from the system perspective to evaluate the risk of the cross-regional mega construction project (CMCP). Furthermore, this paper aims to confirm the core risk source factors and refine the risk management strategies of CMCPs through a case study.

Based on the analysis of the risk system of CMCPs, the concept model and risk assessment principles of integrated risk assessment were confirmed. The risk source factors and project objectives of the CMCP were identified from a literature review, export interview and case analysis. According to the vulnerability theory, the integrated risk assessment model was developed by involving vulnerabilities, threats, objectives and interaction of those factors synthetically. Then, ZW high-speed railway from China was analyzed to verify the feasibility and effectiveness of the proposed method.

As a result, 12 threat factors and 12 vulnerability factors were identified. Based on the case study, the main external threat comes from T13 (conflicts of interest between local governments) and T23 (harsh natural environment); the most easily exploited internal vulnerabilities were V11 (complexity of technology), V13 (lack of experience in technical application), V21 (inadequate experience) and V23 (lack of interest coordination mechanism). Moreover, the economic objective was most affected.

It is essential to develop an interest coordination mechanism for CMCPs. The harsh natural environment is a critical factor, but it also promotes technological innovation and iteration. Public opinions in different regions are critical for CMCPs, and more emphasis should be placed on public opinion surveys of CMCPs. Moreover, diverse and flexible environmental protection strategies should apply in CMCPs.

This research has the following three contributions. First, based on vulnerability theory, an integrated risk assessment approach of CMCPs is developed, which enriches the risk measurement method system and provides inspiration for future research on risk in the construction industry. Second, the risk sources of CMCPs are identified from the perspective of vulnerability and threat to provide clear guidance for the risk management of CMCPs. Third, the core risk source factors and management strategies confirmed by the case study will be beneficial for various governments in different regions and project managers to optimize the project management scheme, as they are transferable management experiences.

Consequence prediction is an emerging topic in safety management concerning the severity outcome of accidents. In practical applications, it is usually implemented through supervised learning methods; however, the evaluation of classification results remains a challenge. The previous studies mostly adopted simplex evaluation based on empirical and quantitative assessment strategies. This paper aims to shed new light on the comprehensive evaluation and comparison of diverse classification methods through visualization, clustering and ranking techniques.

An empirical study is conducted using 9 state-of-the-art classification methods on a real-world data set of 653 construction accidents in China for predicting the consequence with respect to 39 carefully featured factors and accident type. The proposed comprehensive evaluation enriches the interpretation of classification results from different perspectives. Furthermore, the critical factors leading to severe construction accidents are identified by analyzing the coefficients of a logistic regression model.

This paper identifies the critical factors that significantly influence the consequence of construction accidents, which include accident type (particularly collapse), improper accident reporting and handling (E21), inadequate supervision engineers (O41), no special safety department (O11), delayed or low-quality drawings (T11), unqualified contractor (C21), schedule pressure (C11), multi-level subcontracting (C22), lacking safety examination (S22), improper operation of mechanical equipment (R11) and improper construction procedure arrangement (T21). The prediction models and findings of critical factors help make safety intervention measures in a targeted way and enhance the experience of safety professionals in the construction industry.

The empirical study using some well-known classification methods for forecasting the consequences of construction accidents provides some evidence for the comprehensive evaluation of multiple classifiers. These techniques can be used jointly with other evaluation approaches for a comprehensive understanding of the classification algorithms. Despite the limitation of specific methods used in the study, the presented methodology can be configured with other classification methods and performance metrics and even applied to other decision-making problems such as clustering.

This study sheds new light on the comprehensive comparison and evaluation of classification results through visualization, clustering and ranking techniques using an empirical study of consequence prediction of construction accidents. The relevance of construction accident type is discussed with the severity of accidents. The critical factors influencing the accident consequence are identified for the sake of taking prevention measures for risk reduction. The proposed method can be applied to other decision-making tasks where the evaluation is involved as an important component.