Construction projects are associated with risks, which influence projects’ performance and quality. To ensure the on-time completion of construction projects, project managers often use risk assessment and management methods to reduce risks in the project life cycle. Identifying risk factors and the relationship between major risk factors and the quality of construction projects facilitates construction management. In this study, 948 project records of construction inspection from 1993 to 2020 were collected from the Public Construction Management Information System (PCMIS) of the Taiwan central government to conduct an expert survey to identify five risk dimensions and 19 major risk factors associated with Taiwanese construction projects. The hybrid analytic hierarchy process (AHP) and an artificial neural network (ANN) were employed to develop a model for predicting major risk factors and construction quality. The AHP was used to calculate the weight of major risk factors to verify their influence on construction. The ANN was adopted to extract the features of major risk factors to predict the quality of a construction project. The accuracy of the prediction model was 85%. The project managers can reference the prediction results obtained with the proposed method to perform effective risk management and devise decision-making strategies for construction management.

Risks inevitably exist in all stages of a project. In a construction project, which is highly dynamic and complex, risk factors affect the expected achievement rates of the three main performance goals, namely schedule, cost, and quality. A comprehensive risk management procedure requires three crucial steps: risk confirmation, analysis, and treatment. Risk analysis is the core of risk management. Through structural equation modeling, this study developed a risk analysis model that takes a different perspective and considered the occurrence probability of risk events and the extent to which these events affect a project. The contractor dimension was discovered to exert the strongest influence on an overall project, followed by the subcontractor and design dimensions. This paper proposes a novel construction project risk analysis model, which considers the entire project. The proposed model can be used as a reference for risk managers to make decisions about project risks, so as to achieve the ultimate goal of saving resources and the sustainable operation of the construction project.