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Chen, Z, Li, H, Shen, Q and Xu, W (2004) An empirical model for decision-making on ISO 14000 acceptance in the Shanghai construction industry. Construction Management and Economics, 22(01), 55-73.

Dunn, B (2004) The regionalization of international contracting and its implications for models of construction spending. Construction Management and Economics, 22(01), 93-100.

Lavy, S and Shohet, I M (2004) Integrated maintenance management of hospital buildings: a case study. Construction Management and Economics, 22(01), 25-34.

Manavazhi, M R (2004) Assessment of the propensity for revisions in design projects through the dichotomous characterization of designer effort. Construction Management and Economics, 22(01), 47-54.

Moselhi, O, Li, J and Alkass, S (2004) Web-based integrated project control system. Construction Management and Economics, 22(01), 35-46.

Pan, Z (2004) Commercial housing ownership predictors in urban China: an analysis of a national survey. Construction Management and Economics, 22(01), 85-91.

Pries, F, Dorée, A G, Veen, B V d and Vrijhoef, R (2004) Note: The role of leaders' paradigm in construction industry change. Construction Management and Economics, 22(01), 7-10.

Skitmore, R M (2004) Predicting the probability of winning sealed bid auctions: the effects of outliers on bidding models. Construction Management and Economics, 22(01), 101-9.

  • Type: Journal Article
  • Keywords: Bidding models; bidding theory; construction contracts; empirical tests; predicted probability; probability of lowest bid; sealed bid auctions; tendering theory; logscore test; outliers
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/0144619042000186103
  • Abstract:

    This paper is concerned with the effect of outliers on predictions of the probability of tendering the lowest bid in sealed bid auctions. Four of the leading models are tested relative to the equal probability model by an empirical analysis of three large samples of real construction contract bidding data via all-in (in-sample), one-out and one-on (out-of-sample) frames. Outliers are removed in a sequence of cut-off values proportional to the standard deviation of bids for each auction. A form of logscore is used to measure the ability to predict the probability of each bidder being the lowest. The results show that, although statistically significant in some conditions, all the models produce rather poor predictions in both one-out and one-on mode, with the effects of outliers being generally small.

Sohail, M and Baldwin, A N (2004) Performance indicators for 'micro-projects' in developing countries. Construction Management and Economics, 22(01), 11-23.

Turner, J R (2004) Farsighted project contract management: incomplete in its entirety. Construction Management and Economics, 22(01), 75-83.