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Clarke, L and Herrmann, G (2004) Cost vs. production: disparities in social housing construction in Britain and Germany. Construction Management and Economics, 22(05), 521-32.

Gil, N, Tommelein, I D and Ballard, G (2004) Theoretical comparison of alternative delivery systems for projects in unpredictable environments. Construction Management and Economics, 22(05), 495-508.

Lewis, T M (2004) The construction industry in the economy of Trinidad & Tobago. Construction Management and Economics, 22(05), 541-9.

Miller, C J M, Packham, G A, Pickernell, D G and Mcgovern, M (2004) Building for the future: the potential importance of the construction industry in Welsh economic development policy. Construction Management and Economics, 22(05), 533-40.

Ng, F P and Björnsson, H C (2004) Using real option and decision analysis to evaluate investments in the architecture, construction and engineering industry. Construction Management and Economics, 22(05), 471-82.

Ng, S T, Cheung, S-O, Skitmore, M and Wong, T C Y (2004) An integrated regression analysis and time series model for construction tender price index forecasting. Construction Management and Economics, 22(05), 483-93.

  • Type: Journal Article
  • Keywords: Cost estimate; integrated forecasting model; tender price index forecast; time series modelling; regression analysis
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/0144619042000202799
  • Abstract:

    Clients need to be informed in advance of their likely future financial commitments and cost implications as the design evolves. This requires the estimation of building cost based on historic cost data that is updated by a forecasted Tender Price Index (TPI), with the reliability of the estimates depending significantly on accurate projections being obtained of the TPI for the forthcoming quarters. In practice, the prediction of construction tender price index movement entails a judgemental projection of future market conditions, including inflation. Statistical techniques such as Regression Analysis (RA) and Time Series (TS) modelling provide a powerful means of improving predictive accuracy when used individually. An integrated RA-TS model is developed and its predictive power compared with the individual RA or TS models. The accuracy of the RA-TS model is shown to outperform the individual RA and TS models in both one and two-period forecasts, with the integrated RA-TS model accurately predicting (95% confidence level) one-quarter forecasts for all the 34 holdout periods involved, with only one period not meeting the confidence limit for two-quarter forecasts

Phua, F T T (2004) Modelling the determinants of multi-firm project success: a grounded exploration of differing participant perspectives. Construction Management and Economics, 22(05), 451-9.

Poon, C S, Yu, A T W and Jaillon, L (2004) Reducing building waste at construction sites in Hong Kong. Construction Management and Economics, 22(05), 461-70.

Wu, C-H, Hsieh, T-Y, Cheng, W-L and Lu, S-T (2004) Grey relation analysis of causes for change orders in highway construction. Construction Management and Economics, 22(05), 509-20.