4.6 Article

Impact of COVID-19 on the US Construction Industry as Revealed in the Purdue Index for Construction

Journal

JOURNAL OF MANAGEMENT IN ENGINEERING
Volume 38, Issue 1, Pages -

Publisher

ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)ME.1943-5479.0000995

Keywords

Coronavirus disease 2019 (COVID-19); Purdue index for construction (Pi-C); Granger causality test; Structural equation modeling (SEM); Long short-term memory (LSTM); Multivariable prediction; Data analytics

Ask authors/readers for more resources

The COVID-19 pandemic has had unprecedented impacts on the US construction industry, causing labor shortages, project suspensions and cancellations, and disruptions in supply chains and logistics. Understanding these effects and future changes is crucial for the industry. This study utilizes the Purdue Index for Construction (Pi-C), which measures the health status of the construction industry based on five dimensions and corresponding metrics, to assess the impact of the pandemic. The study identifies the relationship between COVID-19 and Pi-C metrics, develops prediction models using deep learning algorithms, and forecasts the trends in the construction industry. The results show significant impacts in the economy and stability dimensions, while the social dimension remains unaffected. The Pi-C predicts no significant adverse impacts on the US construction industry from the pandemic until the end of 2022.
The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented impacts (e.g., labor shortage, suspension and cancellation of projects, and disrupted supply and logistics) on the US construction industry. To address challenges caused by the pandemic, it is critical for the construction industry to develop a clear understanding of how the pandemic has affected the industry and how it will change in the future. However, assessing the impacts of COVID-19 on the construction industry is challenging due to the broad influence of the pandemic and the dynamic nature of the industry. The Purdue Index for Construction (Pi-C), which was developed as an indicator based on five dimensions and corresponding metrics to measure the health status of the construction industry, offers an opportunity to understand the impact of the pandemic. In this context, this paper presents a study to reveal the relationship between COVID-19 and the health status of the industry as measured through Pi-C and predict the future trend of the construction industry. This study achieves the objective via the three steps. First, the relationship between the pandemic and Pi-C metrics is identified using the Granger causality test and structural equation modeling (SEM) analysis. Second, multivariable prediction models are developed based on a long short-term memory (LSTM) network-a deep learning algorithm-to predict Pi-C metrics in the future. Third, forecasted Pi-C metrics are integrated into the existing Pi-C structure to analyze the impacts of the COVID-19 pandemic and predict its trends in 2021-2022. The results revealed that the impacts of the pandemic were conspicuous in two Pi-C dimensions (economy and stability), whereas no significant impacts were observed in the remaining Pi-C dimension (social). In addition, the Pi-C forecasted that there would be no significant adverse impacts on the US construction industry caused by the pandemic until the end of 2022.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available