Abstract

Various delivery methods are used in the water industry for delivering treatment plant projects, which include the traditional design-bid-build (DBB) method as well as alternative project delivery methods (APDM), such as construction manager at risk (CMAR) and design-build (DB). Research has shown that APDM may improve water infrastructure project delivery performance when compared to DBB. However, utilizing an APDM does not guarantee a project’s successful delivery; other project variables also influence project delivery performance. The objective of this study is to develop exploratory mathematical models to investigate the impact of project-specific delivery factors and attributes on a water project’s success. The authors assess unit cost performance, which is a measure of a water treatment plant’s capacity in million gallons per day, over a project’s total cost. This study consisted of holding an industry expert workshop to review and develop a data collection questionnaire. Information on a total of 15 water treatment plant projects delivered in the US was collected and used to develop multiple linear regression models that explored project-specific key factors and attributes that impact unit cost performance. Results of the regression models revealed four critical variables: (1) use of GMP; (2) project team experience; (3) level of design completed before constructor engagement; and (4) project complexity, to have a statistically significant impact on the unit cost performance of water projects. The findings and contributions of this study can aid water stakeholders in understanding the unit cost performance impact of key project variables on their projects and support them in their project delivery method decisions.

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article.

Acknowledgments

This work builds on a project funded by the Water Research Foundation (WRF) under Project No. 4685 “Project Delivery Performance Evaluation and Decision Support Tool for Water and Wastewater Capital Projects.” The authors would also like to thank all industry collaborators who have contributed to this research effort.

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Go to Practice Periodical on Structural Design and Construction
Practice Periodical on Structural Design and Construction
Volume 28Issue 1February 2023

History

Received: Nov 16, 2021
Accepted: Aug 19, 2022
Published online: Nov 7, 2022
Published in print: Feb 1, 2023
Discussion open until: Apr 7, 2023

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Postdoctoral Research Scholar, Ira A. Fulton Schools of Engineering, Arizona State Univ., P.O. Box 873005, Tempe, AZ 85287-3005 (corresponding author). ORCID: https://orcid.org/0000-0002-1764-4844. Email: [email protected]
Mounir El Asmar, Ph.D., A.M.ASCE [email protected]
Associate Professor and Co-Director of the National Center of Excellence on SMART Innovations, School of Sustainable Engineering and the Built Environment, Ira A. Fulton Schools of Engineering, Arizona State Univ., Tempe, AZ 85287-3005. Email: [email protected]
Samuel T. Ariaratnam, Ph.D., F.ASCE https://orcid.org/0000-0001-5973-0655 [email protected]
P.E.
Fellowship in the Canadian Academy of Engineering, Professor and Construction Engineering Program Chair, Ira A. Fulton Schools of Engineering, Arizona State Univ., Tempe, AZ 85287-3005. ORCID: https://orcid.org/0000-0001-5973-0655. Email: [email protected]

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