TY - JOUR
T1 - Predicting construction schedule overruns during COVID-19 using ordinal logistic regression
AU - Adepu, Nikhitha
AU - Kermanshachi, Sharareh
AU - Pamidimukkala, Apurva
AU - Nwakpuda, Emily
N1 - Publisher Copyright:
© 2024, Emerald Publishing Limited.
PY - 2024
Y1 - 2024
N2 - Purpose: The effects of the COVID-19 outbreak on the construction industry were formidable and far-reaching, as the construction sector is a major contributor to the gross domestic product (GDP), which balances various sectors of the global economy, and to infrastructure growth, which is a primary gauge of a nation’s advancement. The outbreak led to workforce disruptions, worker deficits, dwindling efficiency, elongated project durations, and scarce opportunities for training and mentorship, and despite endeavors to mitigate these challenges, construction timelines experienced significant interruptions. Various researchers have pinpointed contributing elements, but few have constructed a predictive model to gauge the degree of impact. Design/methodology/approach: Therefore, this research intends to fill by introducing an ordinal logistic regression method to forecast the impacts of a pandemic or other similar type of crisis. To achieve this, an online survey was developed and distributed to collect the perceptions of the construction engineers and managers about the diverse contributors to the exceeding project timelines during the COVID-19 pandemic outbreak. Findings: Findings from this study indicate that financial liquidity, modifications to original plans, delays in securing governmental clearances, and a shortage of competent labor have medium-to-high levels of impact on project schedules. Originality/value: This study will furnish decision-makers with crucial knowledge that will give them the tools to refine their strategies and judiciously allocate resources to overcome the unique hurdles encountered by various construction segments and will enhance the industry's capability to respond more effectively to challenges inherent in this type of crisis.
AB - Purpose: The effects of the COVID-19 outbreak on the construction industry were formidable and far-reaching, as the construction sector is a major contributor to the gross domestic product (GDP), which balances various sectors of the global economy, and to infrastructure growth, which is a primary gauge of a nation’s advancement. The outbreak led to workforce disruptions, worker deficits, dwindling efficiency, elongated project durations, and scarce opportunities for training and mentorship, and despite endeavors to mitigate these challenges, construction timelines experienced significant interruptions. Various researchers have pinpointed contributing elements, but few have constructed a predictive model to gauge the degree of impact. Design/methodology/approach: Therefore, this research intends to fill by introducing an ordinal logistic regression method to forecast the impacts of a pandemic or other similar type of crisis. To achieve this, an online survey was developed and distributed to collect the perceptions of the construction engineers and managers about the diverse contributors to the exceeding project timelines during the COVID-19 pandemic outbreak. Findings: Findings from this study indicate that financial liquidity, modifications to original plans, delays in securing governmental clearances, and a shortage of competent labor have medium-to-high levels of impact on project schedules. Originality/value: This study will furnish decision-makers with crucial knowledge that will give them the tools to refine their strategies and judiciously allocate resources to overcome the unique hurdles encountered by various construction segments and will enhance the industry's capability to respond more effectively to challenges inherent in this type of crisis.
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U2 - 10.1108/IJBPA-11-2023-0161
DO - 10.1108/IJBPA-11-2023-0161
M3 - Article
AN - SCOPUS:85200356721
SN - 2398-4708
JO - International Journal of Building Pathology and Adaptation
JF - International Journal of Building Pathology and Adaptation
ER -