An integrated construction schedule risk analysis approach for infrastructure projects under uncertainty

Abstract

The construction industry, especially the infrastructure sector, has often been challenged by the enormous losses and damages resulted from construction schedule delay. In order to manage schedule appropriately, many efforts in both academia and practice have been made to identify construction schedule risks, analyze the risk effects on construction schedule, and develop schedule risk mitigation strategies. A variety of theoretical methods have been developed, such as program evaluation and review technique (PERT), correlated schedule risk analysis model (CSRAM) and system dynamics (SD) approach. However, few of such efforts have investigated the complexity and uncertainty of the construction schedule risks in a systematic manner. These risks have usually regarded as independent rather than interdependent in the past research, which is convenient for the analysis but is not in line with the practice. There thus remain knowledge gaps between the functions of the developed theoretical methods and the actual requirements for addressing the construction schedule delay issues in practice. Therefore, this research aims to develop an integrated construction schedule risk analysis approach, IRISK, for infrastructure projects under uncertainty, which explores how the construction schedule risks of infrastructure projects could be managed appropriately from the contractor’s perspective. This integrated approach IRISK was developed in four interrelated steps. Firstly, construction schedule risks at the industry-level were identified via a comprehensive literature review based on the dialectical systems theory, and verified through expert interviews with 15 selected stakeholders. The levels of significance of the identified risks were measured through a questionnaire survey with 81 relevant stakeholders in the wider community. Secondly, the key risks with network structure at the project-level were distinguished and examined through focus group discussion with five key stakeholders from case project management team using the network theory. Thirdly, the probability of the examined risks was verified through another focus group discussion with the same five participants and then quantified based on the Bayesian Belief Network (BBN) method using real-time information collected from a case infrastructure project. Finally, the construction schedule of infrastructure projects with the effects of risks incorporated was predicted and analyzed using the Monte Carlo Simulation (MCS) technique. This developed integrated approach was contextualized and validated using a real-life infrastructure project of underground railway construction in Southern China (in Greater Bay of China). Totally 32 risks have been identified as the significant construction schedule risks for the case project, while the key risk network has been constructed for the case project consisting of 21 risks and 39 correlations. Among these key risks, six risks have been further distinguished as sensitive risks to the construction schedule of the case project. The predicted construction schedule from IRISK provided an accurate result, only 12.081% longer than the actual duration with delay occurred. Furthermore, in order to address sensitive risks and prevent the occurrence of serious construction delay in the future works, five kinds of potential strategies have been developed and re-assessed within the context of case project, and two strategies (i.e., sufficient funding preparation strategy and improved strategy) have been selected as the most effective risk mitigation strategy (single and multiple kinds of risks respectively), reducing the uncertainty value from 0.067 to 0.058 and 0.043 respectively. The results showed that the complex correlations between the identified risks and between the yielded activity durations were appropriately considered and addressed through this developed approach, IRISK. This research should be valuable in providing insights into the complexity and uncertainty of construction schedule risks that exist in infrastructure projects. The developed integrated approach and its supporting analytical methods should support researchers in construction project management to better understand the complexity and uncertainty of construction schedule risks in a systematic logic. The approach should also provide practitioners with a reliable tool to more effectively manage construction schedule delay risks in infrastructure projects.