Abstract
The construction industry is one of the leading industries in the economy of any country. However, the industry is vulnerable to changes and uncertainties, either external or internal, due to its fragmented and dynamic nature. Coronavirus disease (COVID-19), which first emerged in Wuhan, China in 2019, is considered a pandemic by the World Health Organization (WHO). COVID-19 has quickly spread all over the world resulting in significant social and economic consequences. The main objective of the study is to determine the challenges and opportunities due to pandemic in the construction industry and to categorize them. Through a review of the existing literature and interviews with construction experts, the challenges and opportunities arising from the COVID-19 pandemic were listed. A questionnaire survey was designed to evaluate them. Principal Component Analysis (PCA) was utilized to group the identified challenges and opportunities. PCA was conducted with SPSS Version 25.0 software. The most critical challenges of the pandemic were determined as ‘the requirement of COVID-19 protocols’, ‘restriction on movement and travel’, ‘additional safety equipment use’, where the most important opportunities were found as ‘hygiene programs’, ‘use of technological tools effectively’, and ‘BIM-enabled construction’. The research contributes to the body of knowledge in terms of making construction practitioners beware of the main challenges and opportunities along with leading them to act towards change and uncertainty. This study further provides general guidelines and implications for practitioners and policymakers in case of similar outbreaks.
Original language | English |
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Journal | IEEE Transactions on Engineering Management |
Early online date | 18 Mar 2022 |
DOIs | |
Publication status | E-pub ahead of print - 18 Mar 2022 |
Bibliographical note
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- COVID-19
- Challenges
- Companies
- Construction industry
- Industries
- Interviews
- Pandemics
- Uncertainty
- construction
- oppor-tunities
- pandemic
- principal component analysis (PCA)