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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.

  • Type: Journal Article
  • Keywords: Best management practices, construction methods, construction productivity, Australia
  • ISBN/ISSN: 2204-9029
  • URL: https://doi.org/10.5130/AJCEB.v16i3.4882
  • Abstract:
    This research investigates management practices that have the potential to enhance productivity in building projects by focusing on construction methods. In phase 1 of the study, face-to-face interviews with nineteen experts were conducted to identify the best management practices for construction methods. The qualitative data analysis reached saturation and resulted in a list of best practices for construction methods that are relevant to the local industry. The second phase used an industry-wide survey to prioritize the best practices. Accordingly, project start-up plan, traffic control plan, machinery positioning strategy, project completion plan, and dynamic site layout plan were shown to be the top five best practices for construction methods. The study also revealed that high levels of implementation of best practices are associated with low levels of project delays. The use of best practices also varied according to the project costs. There were no discernible differences between the top five best practices. The authors suggest that they should be implemented jointly to improve productivity in building projects. Contractors could use the logistic regression model developed, to predict the probability of exceeding a baseline productivity factor and, on that basis, implement corrective actions to achieve the desired level of productivity. 

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.