Document Type : Original Article

Authors

1 Ph.D. Candidate, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Professor, Department of Project and Construction Management, School of Architecture, University of Tehran, Tehran, Iran

3 Associate professor, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Abstract

Research has shown that complexity may be a significant factor in a project's failure to meet cost, time, and quality goals. Although important indicators of project complexity have been identified in many studies, their weight effect has yet to be investigated. This article reviewed the project complexity literature to develop a simple and dynamic framework, and 40 complexity indicators were identified and classified into nine factors. Then, they were provided to 30 industrial experts and two research consultants for evaluation to determine the role of each indicator in Evaluating the complexity of industrial projects. These indicators were validated, weighted, and ranked during the three stages of implementing the Delphi method. The results showed that the indicators related to the complexity factors of the project's context, content, and dependency have the highest accumulated weight. Also, the presence of uncertainty and ambiguity in increasing the weight of each indicator showed an influential role. The presented framework was used to measure the level of complexity in 14 industrial projects. The results showed a high level of complexity in international projects being implemented by Iranian companies. Despite the difference in complexity management approach in these projects, commonalities were identified for which the proposed solutions can help other project managers achieve positive results for complexity management. With the help of the results of this research, project managers can have a framework for measuring complexity management and allow industry experts to prioritize and efficiently allocate their limited resources in complex projects.

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