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Ke, Y, Davis, P and Jefferies, M (2016) A conceptual model of psychological contracts in construction projects . Construction Economics and Building, 16(03), 20-37.

Coggins, J, Teng, B and Rameezdeen, R (2016) Construction insolvency in Australia: reining in the beast . Construction Economics and Building, 16(03), 38-56.

Davis, P, Gajendran, T, Vaughan, J and Owi, T (2016) Assessing construction innovation: theoretical and practical perspectives . Construction Economics and Building, 16(03), 104-115.

Gurmu, A, T, Aibinu, A, A and Chan, T, K (2016) A study of best management practices for enhancing productivity in building projects: construction methods perspectives . Construction Economics and Building, 16(03), 1-19.

Hardie, M (2016) Vectors of technical innovation delivery by small and medium Australian construction firms. Construction Economics and Building, 16(03), 59-70.

Hosseini, M, R, Banihashemi, S, Chileshe, N, Namzadi, M. O, Udaeja, C, Rameezdeen, R and McCuen, T (2016) BIM adoption within Australian Small and Medium-sized Enterprises (SMEs): an innovation diffusion model . Construction Economics and Building, 16(03), 71-86.

Ishak, S, S, M and Newton, S (2016) An innovation resistance factor model . Construction Economics and Building, 16(03), 87-103.

  • Type: Journal Article
  • Keywords: User resistance, technology innovation, diffusion of innovation, technology acceptance model, social network
  • ISBN/ISSN: 2204-9029
  • URL: https://doi.org/10.5130/AJCEB.v16i3.5164
  • Abstract:
    The process and implementation strategy of information technology in construction is generally considered through the limiting prism of theoretical contexts generated from innovation diffusion and acceptance. This research argues that more attention should be given to understanding the positive effects of resistance. The study develops a theoretical framing for the Integrated Resistance Factor Model (IRFM). The framing uses a combination of diffusion of innovation theory, technology acceptance model and social network perspective. The model is tested to identify the most significant resistance factors using Partial Least Square (PLS) technique. All constructs proposed in the model are found to be significant, valid and consistent with the theoretical framework. IRFM is shown to be an effective and appropriate model of user resistance factors. The most critical factors to influence technology resistance in the online project information management system (OPIMS) context are: support from leaders and peers, complexity of the technology, compatibility with key work practices; and pre-trial of the technology before it is actually deployed. The study provides a new model for further research in technology innovation specific to the construction industry.