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Adafin, J, Wilkinson, S, Rotimi, J O B, MacGregor, C, Tookey, J and Potangaroa, R (2022) Creating a case for innovation acceleration in the New Zealand building industry. Construction Innovation, 22(1), 185-204.

Chen, Q, Adey, B T, Haas, C T and Hall, D M (2022) Exploiting digitalization for the coordination of required changes to improve engineer-to-order materials flow management. Construction Innovation, 22(1), 76-100.

Ginigaddara, B, Perera, S, Feng, Y and Rahnamayiezekavat, P (2022) Offsite construction skills evolution: an Australian case study. Construction Innovation, 22(1), 41-56.

Habibi, S (2022) Role of BIM and energy simulation tools in designing zero-net energy homes. Construction Innovation, 22(1), 101-19.

Liu, C, M.E. Sepasgozar, S, Shirowzhan, S and Mohammadi, G (2022) Applications of object detection in modular construction based on a comparative evaluation of deep learning algorithms. Construction Innovation, 22(1), 141-59.

Malaeb, Z and Hamzeh, F R (2022) IPD-inspired framework for measuring stakeholder integration in public-private partnerships. Construction Innovation, 22(1), 160-84.

Mock, B and O'Connor, J (2022) Taxonomic categories for commissioning and startup hot spot strategies. Construction Innovation, 22(1), 120-40.

Okpala, I, Nnaji, C and Awolusi, I (2022) Wearable sensing devices acceptance behavior in construction safety and health: assessing existing models and developing a hybrid conceptual model. Construction Innovation, 22(1), 57-75.

  • Type: Journal Article
  • Keywords: construction safety monitoring; construction technology; innovation management; predictive modeling; safety management; technology acceptance; technology adoption; wearable sensing devices
  • ISBN/ISSN:
  • URL: https://doi.org/10.1108/CI-04-2020-0056
  • Abstract:
    This study aims to examine relationships between several key technology acceptance variables that predict workers' wearable sensing devices (WSDs) acceptance in the construction industry by using technology acceptance model, theory of planned behavior and unified theory of acceptance and use of technology (UTAUT) model. The study proposes a hybrid conceptual model to measure construction field workers' intentions to use WSDs and their usage behaviors. The study introduces variables that are instrumental in understanding and improving WSD acceptance in construction. The study was carried out using a structured literature review, online survey and structural equation modeling. A total of 195 field workers across the USA, with experience in using WSDs, participated in the study. Results indicate that all three theories predict WSD acceptance with variables explaining at least 89% of the variance in actual use, with the UTAUT outperforming other models (91%). However, the differences between the predictive power of these models were not statistically significant. A hybrid conceptual model is proposed using findings from the present study. Practical implications: The study contributes to knowledge and practice by highlighting key variables that influence WSD acceptance. Findings from this study should provide stakeholders with critical insights needed to successfully drive WSD acceptance in the construction industry. To the best of the authors' knowledge, this is the first study that evaluates the predictive strength of multiple technology acceptance theories and models within the construction worker safety technology domain. Additionally, the study proposes a hybrid conceptual model which could provide practitioners and researchers with information pertinent to enhancing WSD acceptance.

Poirier, E, Staub-French, S, Pilon, A, Fallahi, A, Teshnizi, Z, Tannert, T and Froese, T (2022) Design process innovation on brock commons tallwood house. Construction Innovation, 22(1), 23-40.

Staub-French, S, Pilon, A, Poirier, E, Fallahi, A, Kasbar, M, Calderon, F, Teshnizi, Z and Froese, T (2022) Construction process innovation on Brock Commons Tallwood House. Construction Innovation, 22(1), 1-22.