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Auteur(s):
ORCID
ORCID
ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 5, v. 13
Page(s): 1127
DOI: 10.3390/buildings13051127
Abstrait:

At the beginning of 2020, the COVID-19 contagious virus swept, which caused a lot of disturbances in all countries worldwide. The Egyptian government declared an emergency and placed the country under lockdown. Preventive measures such as social distancing, sterilization, mask wear, frequent temperature checks, offering COVID-19-related training, and encouraging work-from-home initiatives, among other precautions, have been implemented. Such precautionary measures affected the construction production rate. This research used a questionnaire and face-to-face interviews to solicit the opinion of construction industry professionals and experts on tier-one construction companies on the impact of this pandemic on construction production rate. A quantitative analysis has been done in this study using IBM SPSS Statistics 26© to determine the most important effective factors of the production rate of the construction industry, mainly in Egypt. Also, this study illustrates an Artificial Neural Networks (ANNs) model to predict the project’s cost and production rate at construction for the actual status in Egypt at the peak of COVID-19. The model does not only present the actual case but can also predict the most important and influential factors of the construction industry mainly in Egypt, at the peak of the virus, and can be used in other similar crises as a lesson learned which no study covered this area at the previous works. Finally, the results and the validation study of the proposed ANN model in the research show and present the actual status of production rate in the construction sector, mainly in Egypt (case study), and also predict the production rates of the construction sector at the future crisis.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10728050
  • Publié(e) le:
    30.05.2023
  • Modifié(e) le:
    01.06.2023
 
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