Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 7 results ...

Elhag, T M S and Boussabaine, A H (2001) Tender price estimation using artificial neural networks. Journal of Financial Management of Property and Construction, 6(03), 193–208.

Fortune, C (2001) Exploring the model selection process in the formulation of building project advice. Journal of Financial Management of Property and Construction, 6(03), 167–77.

Kaka, A P (2001) Turnover forecasting for contracting companies based on published information. Journal of Financial Management of Property and Construction, 6(03), 217–29.

Kenley, R (2001) In-project end-date forecasting: an idiographic, deterministic approach, using cash-flow modelling. Journal of Financial Management of Property and Construction, 6(03), 209–16.

Lo, H P and Lam, M-L (2001) A bidding strategy using multivariate distribution. Journal of Financial Management of Property and Construction, 6(03), 155–65.

Ogunlana, S O, Bhokha, S and Pinnemitr, N (2001) Application of artifical neural network (ANN) to forecast construction cost of buildings at the pre-design stage. Journal of Financial Management of Property and Construction, 6(03), 179–92.

Skitmore, M (2001) Raftery curves for tender price forecasting: Empirical probabilities and pooling. Journal of Financial Management of Property and Construction, 6(03), 141–54.

  • Type: Journal Article
  • Keywords: Raftery Curves; tender price forecasts; empirical probabilities; data pooling; Hong Kong construction contracts
  • ISBN/ISSN: 1366-4387
  • URL: http://www.emeraldinsight.com/journals.htm?issn=1366-4387
  • Abstract:
    A method is proposed for the empirical derivation of Raftery Curve probabilities from forecasted/actual value ratios. The method is applied to a set of Hong Kong construction contract data. Using the error of predicted ratios as the measure of opportunity cost, it is then shown how the method may be used to identify the best data poolings amongst subsets