State-of-the-Art Reviews
Mar 25, 2023

Systematic Review of the Literature on Construction Productivity

Publication: Journal of Construction Engineering and Management
Volume 149, Issue 6

Abstract

Productivity, defined as output per input, is a key performance indicator. Construction is one of the least productive industries, and in this paper we explore how productivity measurement can be improved. The findings are based on a review of more than 100 studies. First, we summarize the indicators and data sources used to measure productivity at the macro (economic) and micro (more detailed) levels. Then we explore industry-level productivity trends. Contrary to popular belief, US construction productivity has not declined or stagnated over time. Also, the US has consistently outperformed the UK, Germany, and France. Next, we identify the most critical factors affecting construction productivity. These are related to labor, equipment and technology, construction site, schedule, supervisors, and materials. We also discuss new technologies that can help improve productivity: off-site construction, building information modeling, material tracking technologies, and automated productivity monitoring. Finally, we discuss challenges in this area: the unsuitability of labor productivity as an indicator, issues with activity-level productivity analysis, the disconnect between macro and micro levels, and the lack of micro-level productivity databases.

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Data Availability Statement

All data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

We would like to thank Dr. Danny Murguia from our research group for his valuable comments. Also, we extend our gratitude to Mr. Nathan Modica from the US Bureau of Labor Statistics for his clarifications on the data published by the bureau. Moreover, we are grateful to Mrs. Nicola Cavaleri from the Centre for Languages and Inter-Communication at the University of Cambridge for her comments on an earlier draft of this paper.

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Journal of Construction Engineering and Management
Volume 149Issue 6June 2023

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Published online: Mar 25, 2023
Published in print: Jun 1, 2023
Discussion open until: Aug 25, 2023

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Ph.D. Candidate, Dept. of Engineering, Univ. of Cambridge, Trumpington St., Cambridge CB2 1PZ, UK (corresponding author). ORCID: https://orcid.org/0000-0002-1389-7801. Email: [email protected]
Campbell Middleton, Ph.D. [email protected]
Professor, Dept. of Engineering, Univ. of Cambridge, Trumpington St., Cambridge CB2 1PZ, UK. Email: [email protected]

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Cited by

  • Measuring Activity-Level Construction Productivity, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-14602, 150, 8, (2024).
  • Measuring BIM Implementation: A Mathematical Modeling and Artificial Neural Network Approach, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-14262, 150, 5, (2024).
  • Measurement of Construction Productivity: State of the Practice in the UK, Construction Research Congress 2024, 10.1061/9780784485286.045, (445-454), (2024).

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