Managing Construction Projects through Dynamic Modeling: Reviewing the Existing Body of Knowledge and Deriving Future Research Directions

• Published in: Journal of management in engineering 2018-11, Vol.34 (6), p.21-38
• Main Authors: Abotaleb, Ibrahim S, El-adaway, Islam H
• Format: Article
• Language: English
• Subjects: Dynamic models; Technical Papers
• ISSN: 0742-597X; 1943-5479
• DOI: 10.1061/(ASCE)ME.1943-5479.0000633

AbstractTo improve decision making in construction projects, dynamic models have been developed to grasp the complex project dynamics that traditional scheduling and decision-making techniques miss. However, each of the existing dynamic models focuses only on limited parameters impacting the project management cycle and thus are unable to capture the full picture. Accordingly, this paper reviews the existing literature related to utilizing dynamic modeling for construction management applications with the objective of grasping in a holistic manner the direct and indirect impacts of different project parameters. To this effect, the authors: (1) conducted a meta-analysis of previous studies of dynamic modeling in construction management; (2) identified and defined interrelated dynamic parameters that impact project performance; and (3) used social network analysis (SNA) to quantitatively pinpoint the strengths and gaps in the literature and provide a roadmap toward the areas that should be further addressed. For example, one of the important findings is the need to further investigate the dynamics of out-of-sequence work and its impact on project performance, since such dynamics were found to be rarely examined. Another important finding is the absence of models incorporating simultaneously all dynamic parameters. The paper concludes by presenting guidelines—including a conceptual framework—to proactively derive future research directions toward more effective and efficient management of today’s complex construction projects. Ultimately, the comprehensive analytic approach suggested by this research could result in better decision-making processes, reduced cost and schedule overruns, and timely and less costly resolution of claims and disputes.