Abstract

The construction industry is one of the most significant contributors to the growth of the US economy as well as the global market. The Purdue Index for Construction (Pi-C) was developed in the form of a composite index consisting of five dimensions (Economy, Stability, Social, Development, and Quality) to monitor the health status of the construction industry and facilitate data-driven decision making. Despite its great potential, metrics under the Development and Quality dimensions are still missing, which limits our understanding of the health status of the construction industry. A promising approach to identify the missing metrics is to apply the latent Dirichlet allocation (LDA), which supports the discovery of latent topics from a large set of textual data. In this regard, this work introduces an LDA-based method to identify new metrics for the Development and Quality dimensions of the Pi-C. A total of 10,466 abstracts of research papers relevant to Development and Quality were collected from academic search engines using a web crawler. The LDA analysis was conducted to identify metrics and corresponding variables. As a result, two new metrics—Technology and Education—in the Development dimension and one new metric—Sustainability—in the Quality dimension were identified for Pi-C. Results revealed that the updated Pi-C improves our understanding of the construction industry in terms of technology, education, and sustainability. The updated Pi-C is expected to assist decision makers in data-driven decision-making and strategy development in the construction industry.

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Data Availability Statement

Some or all data, models, or code generated or used during the study are available from the corresponding author by request:
1.
Pi-C data, including dimensions, metrics, and variables.
2.
Extracted abstracts data.
3.
Code for the LDA analysis in Python.
4.
Results of LDA analysis.

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Journal of Management in Engineering
Volume 37Issue 6November 2021

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Received: Mar 10, 2021
Accepted: Jul 2, 2021
Published online: Sep 7, 2021
Published in print: Nov 1, 2021
Discussion open until: Feb 7, 2022

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Ph.D. Student, Lyles School of Civil Engineering, Purdue Univ., 550 Stadium Mall Dr., West Lafayette, IN 47907. ORCID: https://orcid.org/0000-0001-6816-0092. Email: [email protected]
Suyash Padhye [email protected]
Master’s Student, Lyles School of Civil Engineering, Purdue Univ., 550 Stadium Mall Dr., West Lafayette, IN 47907. Email: [email protected]
Soojin Yoon, M.ASCE [email protected]
Assistant Professor, Div. of Engineering Technology, Oklahoma State Univ., 511 Engineering North, Stillwater, OK 74078 (corresponding author). Email: [email protected]
Professor, Lyles School of Civil Engineering, Purdue Univ., 550 Stadium Mall Dr., West Lafayette, IN 47907. ORCID: https://orcid.org/0000-0003-4527-1974. Email: [email protected]
Makarand Hastak, M.ASCE [email protected]
Professor, Lyles School of Civil Engineering, Purdue Univ., 550 Stadium Mall Dr., West Lafayette, IN 47907. Email: [email protected]

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