Abstract

In the construction industry, reducing the quantities of engineered materials provides a significant opportunity of mitigating the environmental impacts caused by material production and processing. Although the efficient use of materials has been receiving considerable attention in the building industry, there has been little research aimed at measuring the material use efficiency (MUE) of a project. The goal of this study is to fulfill this gap by using data envelopment analysis (DEA) as a benchmarking technique to measure the overall MUE performance of a building project and to further compare the performance against peer projects in order to promote enhanced efficiency through target setting. In this study, the efficiency is measured by adopting the quantities of a variety of materials consumed during construction as inputs and the floor area of a built facility as an output. To generate a more reliable efficiency score, a stepwise variable selection scheme is first applied and then the MUE scores of projects are ranked based on their cross-efficiency. In addition, clustering analysis and DEA are fused to enable a more realistic target to be set for each input, thereby determining practical, yet challenging targets for each underperforming project. A sample of 12 healthcare projects is used as a case study to demonstrate how the proposed MUE benchmarking model can be used to measure and improve the MUE. The results reveal that the model enables projects to evaluate their MUE performance, recognize the gap with the best-performing projects, and help them determine the targets to become efficient.

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Data Availability Statement

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

Acknowledgments

We thank the CII and CII’s NHFBP participants for their contribution to this research by supporting project data. The conclusions herein are those of the authors and do not necessarily reflect the views of CII. This research was supported by National R&D Program through the National Research Foundation of Korea (NRF) funded by Ministry of Science and ICT (NRF-2020R1F1A1070612) and was also supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0008475).

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Go to Journal of Management in Engineering
Journal of Management in Engineering
Volume 39Issue 6November 2023

History

Received: Apr 2, 2023
Accepted: Jul 18, 2023
Published online: Sep 12, 2023
Published in print: Nov 1, 2023
Discussion open until: Feb 12, 2024

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Assistant Professor, Dept. of Manufacturing and Construction Management, Central Connecticut State Univ., 1615 Stanley St., New Britain, CT 06050-4010. ORCID: https://orcid.org/0000-0003-1413-6593. Email: [email protected]
Assistant Professor of Instruction, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 Yates St., Arlington, TX 76010. ORCID: https://orcid.org/0000-0001-8255-2295. Email: [email protected]
Myungjin Chae [email protected]
Associate Professor, Dept. of Manufacturing and Construction Management, Central Connecticut State Univ., 1615 Stanley St., New Britain, CT 06050-4010. Email: [email protected]
Associate Professor, Dept. of Civil Engineering, Yeungnam Univ., Gyeongsan 38541, Korea (corresponding author). ORCID: https://orcid.org/0000-0002-7396-5917. Email: [email protected]

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