Modeling and Assessment of Project Risk Dynamics: A Case of Addis-Djibouti Railway Project
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Date
2022-05
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Addis Ababa University
Abstract
Railway construction projects are characterized by large operations, long construction periods, complex processes, high financial intensity, dynamic environment, multiple stakeholder involvement, and exposure to the external environment. Due to their complexity and dynamic nature as well as the involvement of various stakeholders, the construction projects are exposed to the effects of numerous risk factors leading to delays and cost overruns. Several studies have been conducted on railway construction projects to analyze the impact of project risks. However, few attempts have been made to evaluate the overall dynamics, interrelationships, uncertainty, and feedback effects of risks on project objectives. The purpose of this research is to develop a dynamic risk assessment model that assesses the impact of project risks on delays and cost overruns of the Addis-Djibouti railway construction project.
This research has conducted an extensive literature review on construction project risk assessment and the techniques of risk analysis of railway construction projects. From the literature review and experts’ opinion, forty-two construction project risk factors were identified and categorized into design, construction, management, resource, contractual and external risks. A structured questionnaire survey and pairwise comparisons of factors were conducted to obtain the opinions of domain experts on likelihood, impact on delays and cost overruns and interrelationships between risks.
The model was developed using fuzzy synthetic evaluation, Bayesian belief network, fuzzy analytic network process, and system dynamics approach. Fuzzy synthetic evaluation and Bayesian belief network were employed to address uncertainty, subjective judgments, data unavailability, and interrelationships between risks and to determine the likelihood of project risks. A fuzzy analytic network process was also adopted to determine the impact of risks on project time and cost taking into account the interdependence and network of project risks. Then, the overall dynamics and feedback effects of the risks were analyzed using system dynamics. The dynamic risk analysis model was implemented on the case project and it was validated using different modeling tests.
The findings of the research showed that contractor's lack of experience, right-of-way, incomplete contract details, poor quality of construction, payment delays, design changes, lack of coordination, and client's financial difficulties were identified as the significant risks that have a higher impact on delays and cost overruns. Based on their categories, the results showed that design, construction, and management-related risks have a significant impact on project objectives. The result of dynamic risk analysis showed that design-related risks were the most critical risks that had a greater impact on project cost and time.
The proposed model is an effective tool for risk assessment to support project managers, clients, contractors, and stakeholders in decision-making and helps to forecast the impact of risks on delays and cost overruns. The model can be used as a project risk analysis tool for other construction projects to help managers identify significant risks and analyze the interdependence, dynamic, and feedback effects on project objectives. On this basis, it is recommended that design, construction, and management-related risks should be given due attention in managing railway construction projects. Moreover, it is also recommended that project managers should consider the interrelationship, dynamic, and feedback effects of risks to analyze their impact on project cost and time. Further research is needed to analyze the impact of risks on quality and other project objectives.
The research made an original contribution to the body of knowledge in project risk assessment in terms of analyzing project risks in a holistic way taking uncertainty, interdependency, and dynamic and feedback effects of risks into account.
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Keywords
Railway construction project; project risk assessment; Project risk modeling; Fuzzy synthetic evaluation; Fuzzy Bayesian belief network; Fuzzy analytic network process; System dynamics