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Investigating U.S. Industry Practitioners' Perspectives towards the Adoption of Emerging Technologies in Industrialized Construction

Author(s):





Medium: journal article
Language(s): en 
Published in: Buildings, , n. 5, v. 10
Page(s): 85
DOI: 10.3390/buildings10050085
Abstract:

In recent years, a growing amount of research has focused on improving the performance of industrialized construction using emerging technologies. It is still necessary to have an in-depth understanding of the industry practitioners’ perspectives on the application of emerging technologies. Thus, a well-designed survey was distributed to industry practitioners who have been involved in industrialized construction projects. Then, a set of data analysis methods were utilized on the collected data to address the proposed four specific research questions. Results indicate that 3D and nD models, sensing techniques, and business information models are the technologies with the highest current utilization level. Extended reality, additive manufacturing, and advanced data analytics are the technologies with the highest development potential. Project inputs (e.g., cost, time, and labor), as well as implementation cost and software constraints (e.g., capital costs, software upgrading, and compatibility), are the main factors that affect practitioners’ decisions to adopt emerging technologies in industrialized projects. Inter-group comparison results indicate that company background has little significant influence on practitioners’ perspectives, while personal career profiles can significantly affect practitioners’ perspectives. Significantly, by uncovering the suggestions and viewpoints of practitioners, this paper aligns academic research with industry needs, ultimately providing guidance on future research directions and applications.

Copyright: © 2020 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10421462
  • Published on:
    06/05/2020
  • Last updated on:
    07/01/2021