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Acceptance of contemporary technologies for cost management of construction projects

Auteur(s):




Médium: article de revue
Langue(s): anglais
Publié dans: Journal of Information Technology in Construction, , v. 27
Page(s): 864-883
DOI: 10.36680/j.itcon.2022.042
Abstrait:

The construction industry has become more digital and the traditional methods of construction activities are gradually becoming outdated. In this era of digital construction, various information and communication technologies have been developed and deployed to the site for the management and control of construction activities including cost management. Irrespective of the benefits of adopting these technologies, most of them are still not readily accepted for use for construction management. This study articulated Seven (7) recent technologies driving the industry and evaluated their acceptance for cost management of construction projects. The technologies include mobile technology, Augmented/Virtual Reality (AR/VR), Building Information Modeling (BIM), Internet of Things (IoT), Autonomous Equipment (Drones and Robotics), Artificial Intelligence (AI), and Predictive Analytics (PA). Data was gathered using a restructured questionnaire and technology acceptance model analysis was performed to identify which of the technologies have higher acceptance for cost management based on the criteria of availability, affordability, frequency of use, usefulness for cost management, and acceptance in the industry. Test statistics using Spearman’s correlations and Kendall’s correlations for each of the technologies and Spearman’s Correlations of Technology acceptance with other variables in the TAM Model were performed. The results showed that mobile technology has higher correlation values than other technologies, and therefore has a higher acceptance for cost management. Kendall’s coefficient of concordance values and Spearman’s correlation values for Mobile technology were all above 0.6 which indicates a high level of agreement among the raters and strong relationships between the compared TAM variables.

Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.36680/j.itcon.2022.042.
  • Informations
    sur cette fiche
  • Reference-ID
    10702804
  • Publié(e) le:
    11.12.2022
  • Modifié(e) le:
    16.12.2022
 
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