Engineering, Construction and Architectural Management: Volume 28 Issue 5

Guest editorial

Obuks A. Ejohwomu, Paul W. Chan, Yujie Lu

Metrics development and modelling the mixed reality and digital twin adoption in the context of Industry 4.0

Samad M.E. Sepasgozar, Mohsen Ghobadi, Sara Shirowzhan, David J. Edwards, Elham Delzendeh

This paper aims to examine the current technology acceptance model (TAM) in the field of mixed reality and digital twin (MRDT) and identify key factors affecting users' intentions…

Developing effective 4IR leadership framework for construction organisations

Kehinde Alade, Abimbola Olukemi Windapo

Globally, the business organisations are experiencing a transformation due to the Fourth Industrial Revolution (4IR). The need for an effective 4IR leadership has placed new…

Actionable strategy framework for digital transformation in AECO industry

Sanjay Bhattacharya, K.S. Momaya

The Fourth Industrial Revolution (4IR) holds the potential to improve capabilities- and technology-based innovation, which will enable breakout for architectural, engineering…

Developing a construction business model transformation canvas

Priyadarshini Das, Srinath Perera, Sepani Senaratne, Robert Osei-Kyei

Industry 4.0 is driving an incremental shift in paradigms for the construction industry. Current research in the built environment is limited to exploring the exponential…

The effectiveness of interactive virtual reality for furniture, fixture and equipment design communication: an empirical study

Abhinesh Prabhakaran, Abdul-Majeed Mahamadu, Lamine Mahdjoubi, Patrick Manu, Che Khairil Izam Che Ibrahim, Clinton Ohis Aigbavboa

This study aims to propose a novel approach to developing an interactive and immersive virtual environment for design communication in the furniture, fixture and equipment (FFE…

Towards a BIM-based approach for improving maintenance performance in IBS building projects

Zul-Atfi Bin Ismail

The contemporary practice of conventional maintenance for industrialised building system (IBS) constructions suffers from poor service delivery and defect repetition. A key…

Application of machine learning in predicting construction project profit in Ghana using Support Vector Regression Algorithm (SVRA)

Emmanuel Adinyira, Emmanuel Akoi-Gyebi Adjei, Kofi Agyekum, Frank Desmond Kofi Fugar

Knowledge of the effect of various cash-flow factors on expected project profit is important to effectively manage productivity on construction projects. This study was conducted…