Abstracts – Browse Results
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Aghimien, D, Aigbavboa, C, Meno, T and Ikuabe, M (2021) Unravelling the risks of construction digitalisation in developing countries. Construction Innovation, 21(3), 456-75.
Akintola, A A, Venkatachalam, S, Root, D and Oti, A H (2021) Distilling agency in BIM-induced change in work practices. Construction Innovation, 21(3), 490-522.
El Sawalhi, N I and Yazgi, A N (2021) House of quality: a method to identify landscape design requirements. Construction Innovation, 21(3), 441-55.
Hwang, S, Ahn, S and Lee, S H (2021) Agent-embedded system dynamics (aeSD) modeling approach for analyzing worker policies: a research case on construction worker absenteeism. Construction Innovation, 21(3), 379-97.
M.E. Sepasgozar, S (2020) Digital technology utilisation decisions for facilitating the implementation of Industry 4.0 technologies. Construction Innovation, 21(3), 476-89.
- Type: Journal Article
- Keywords: construction industry 4.0; construction technology; customer; decision process; digital construction; digital technology; building information modelling; technology adoption; vendor
- ISBN/ISSN:
- URL: https://doi.org/10.1108/CI-02-2020-0020
- Abstract:
Emerging Construction Industry 4.0 technologies raise serious questions for construction companies when deciding whether to adopt or reject emerging technologies. Vendors seek to understand what factors are involved in how construction companies make these decisions and how they might vary across different companies. This paper aims to present a systematic, technology adoption decision-making framework for the construction industry which includes the key steps required for the final decision being made by companies up to the commencement of the operation of the technology. A total of 123 experienced practitioners were interviewed to identify a broad range of tasks relevant to decision-making. Participants known as customers or vendors were chosen to validate the findings of each group by using data triangulation methods. A systematic thematic analysis method was applied in the NVivo environment to analyse the data. This study identifies the active role of vendors who need to understand how their customers arrive at decisions to increase the rate of technology adoption. This paper also provides insights to new companies and late adopters (reported greater than 50%) about how others arrived at their decisions. Unlike other technology adoption models, this paper investigates vendors' corresponding interactions during the decision-making process. This paper also goes beyond previous studies, which focussed on the individual customer's intention to use a specific technology at a single-stage by developing a multi-stage framework to enable understanding the details of the decision process at the organisational level.
Moharrami, S, Taghaddos, M, RazaviAlavi, S R and AbouRizk, S (2021) A hybrid simulation approach for microtunneling construction planning. Construction Innovation, 21(3), 363-78.
Raoufi, M and Fayek, A R (2021) Hybrid fuzzy Monte Carlo agent-based modeling of workforce motivation and performance in construction. Construction Innovation, 21(3), 398-416.
Taghaddos, H, Heydari, M H and Asgari, A H (2021) A hybrid simulation approach for site layout planning in construction projects. Construction Innovation, 21(3), 417-40.