Abstract

The construction industry consists of various sectors that have different needs and functions. Those sector-specific differences create different risks that construction professionals empirically know. However, there is no documented and unbiased assessment to validate the empirical knowledge. Identifying the varying spectrum of risks present in different construction sectors in a systematic manner can facilitate more effective and efficient sharing, learning, and adoption of proven construction project management methods across these sectors. Ultimately, this can lead to significant improvements in construction productivity as a whole. This research analyzed risks in different construction sectors, including the commercial building, industrial, and civil infrastructure sectors in a comparative and quantitative manner. Project risk registers from the three construction sectors were analyzed using fuzzy set qualitative comparative analysis and coincidence analysis. The study identified various risk configurations in each sector, as well as their similarities and dissimilarities. Based on the findings, an ideal path to the utilization and dissemination of advanced construction management strategies and methods across the construction sectors was developed. These results are expected to assist project participants and stakeholders in adopting and implementing advanced project planning, delivery, and management strategies derived from other construction sectors while taking into account different risks.

Practical Applications

The construction industry possesses a wealth of effective and proven construction project management knowledge and know-how that holds the potential to enhance productivity. Despite these resources, the industry still faces productivity challenges. One contributing factor is the industry’s isolated nature, which makes it difficult to share and disseminate knowledge and know-how across construction sectors and the industry as a whole. Identifying similarities and differences across the construction sectors is one prerequisite for promoting seamless knowledge sharing and dissemination. These factors influence the level of modifications and adjustments for successful implementation in different construction sectors. In this background, this study identified similarities and dissimilarities in project risk spectrums across construction sectors in a comparative manner. Ideal pathways for sharing and disseminating knowledge and know-how were proposed based on the observed risk spectrums. The findings aim to streamline the sharing and dissemination of construction management expertise by offering direction for evaluating and selecting appropriate project planning, delivery, and management strategies. Such insights, which take into account different project risk spectrums in different construction sectors, will contribute significantly to improving productivity throughout the construction industry.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors would like to sincerely thank the funding support from the Construction Industry Institute (RT-383), as well as its member companies and all the professional industry partners who aided in supplying information to complete this study.

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 150Issue 6June 2024

History

Received: Apr 24, 2023
Accepted: Dec 11, 2023
Published online: Mar 18, 2024
Published in print: Jun 1, 2024
Discussion open until: Aug 18, 2024

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Suryeon Kim [email protected]
Ph.D. Candidate, Dept. of Construction Science, Texas A&M Univ., College Station, TX 77840. Email: [email protected]
Ph.D. Student, Durham School of Architectural Engineering and Construction, Univ. of Nebraska, Lincoln, NE 68588. ORCID: https://orcid.org/0009-0000-2689-9905. Email: [email protected]
James C. Smith CIAC Endowed Professor, Dept. of Construction Science, Texas A&M Univ., College Station, TX 77840 (corresponding author). ORCID: https://orcid.org/0000-0003-4074-1869. Email: [email protected]
Philip Barutha [email protected]
Associate Teaching Professor, Dept. of Civil and Environmental Engineering, Univ. of Notre Dame, Notre Dame, IN 46556. Email: [email protected]

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