A Gaussian mixture model evaluation of construction companies' business acceptance capabilities in performing construction and maintenance activities during COVID-19 pandemic. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Shehadeh, Ali; Alshboul, Odey; Hamedat, Ola
• Is Part Of: International journal of management science and engineering management. Volume 17:Issue 2(2022)
• Page Start: 112
• Page End: 122
• Publication Date: 2022-04-03
• Subjects: COVID-19 -- construction industry -- business capability -- Gaussian mixture model; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2021.1991851
• Languages: English
• ISSNs: 1750-9661

Abstract

ABSTRACT: COVID-19 pandemic is a big challenge to the construction industry. Thus, governmental support for construction companies is required. However, it is challenging to accurately quantify the necessary support via traditional data collection and analysis methods. Therefore, a Gaussian mixture model is developed to empirically estimate the construction companies' capabilities in performing construction and maintenance activities during the pandemic. The proposed model evaluates the construction sector's business acceptance capacity in performing construction and maintenance activities during pandemics. The model was developed after data collection, processing, and analysis processes. The model's efficiency was validated via a case study, where the analysis results showed acceptable accuracy and offered a comprehensive view of the relationship between the pandemic scale and the recovery cost. Thus, decision-makers can utilize the proposed model to optimally distribute governmental support among construction companies during pandemics, where adequate measures can be taken to maintain sustainable and resilient business capacity for the construction industry.