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Evidencing the Productive Value of the 4IR in the AEC Sector.

By: Contributor(s): Material type: TextTextSeries: Engineering, Construction and Architectural Management SeriesPublisher: Bradford, West Yorkshire : Emerald Publishing Limited, 2021Copyright date: ©2021Edition: 1st edDescription: 1 online resource (171 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781802623444
Subject(s): Genre/Form: Additional physical formats: Print version:: Evidencing the Productive Value of the 4IR in the AEC SectorDDC classification:
  • 658
LOC classification:
  • HF5351 .E953 2021
Online resources:
Contents:
Cover -- Guest editorial -- Metrics development and modelling the mixed reality and digital twin adoption in the context of Industry 4.0 -- Developing effective 4IR leadership framework for construction organisations -- Actionable strategy framework for digital transformation in AECO industry -- Developing a construction business model transformation canvas -- The effectiveness of interactive virtual reality for furniture, fixture, and equipment design communication: an empirical study -- Towards a BIM-based approach for improving maintenance performance in IBS building projects -- Application of machine learning in predicting construction project profit in Ghana using Support Vector Regression Algorithm (SVRA).
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Cover -- Guest editorial -- Metrics development and modelling the mixed reality and digital twin adoption in the context of Industry 4.0 -- Developing effective 4IR leadership framework for construction organisations -- Actionable strategy framework for digital transformation in AECO industry -- Developing a construction business model transformation canvas -- The effectiveness of interactive virtual reality for furniture, fixture, and equipment design communication: an empirical study -- Towards a BIM-based approach for improving maintenance performance in IBS building projects -- Application of machine learning in predicting construction project profit in Ghana using Support Vector Regression Algorithm (SVRA).

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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