Detecting Information Bottlenecks in Architecture Engineering Construction Projects for Integrative Project Management
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 12
Abstract
Information bottlenecks are a central issue in architecture, engineering, and construction (AEC) projects. It is crucial to detect their occurrence to mitigate their impacts. Existing approaches to detect information bottlenecks use metrics that require estimating the quantity of information published, which is a challenging task in practice. In this paper, building on the literature and recent developments in automation, we introduce a revised model that uses unresolved activities during project delivery and frequency of information publication actions to detect information bottlenecks. We validated our model by applying it to a case study. We compared bottlenecks detected by our model to ground truth obtained in the case study independently using observational data and external verification. We further study how project activities requiring different levels of interactions among project participants with different roles (e.g., designer, contractor) affect our model’s performance. Results support our model and show that it is possible to attain comparable performance by considering only high-interdependency activities. Our research enables teams and project managers to keep a focus on issues that require intense communication among different experts and organizations to avoid bottleneck. Our contribution to the body of knowledge includes a revised model that detects information bottlenecks during project delivery and insights into integrative project management where the focus is on both project activities and collaboration needs across roles to streamline the whole process.
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Data Availability Statement
Part of the data, models, and codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was supported by the National Science Foundation (NSF) through Grants CMMI-1825678 and IIS-1928278. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the researchers and do not necessarily reflect the views of the NSF.
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Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 12 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Aug 23, 2022
Accepted: Jul 26, 2023
Published online: Oct 10, 2023
Published in print: Dec 1, 2023
Discussion open until: Mar 10, 2024
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