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Graphical method for identifying high outliers in construction contract auctions

Skitmore, Martin (2001) Graphical method for identifying high outliers in construction contract auctions. Journal of the Operational Research Society, 52(7), pp. 800-809.

Abstract

Construction contract auctions are characterised by (1) a heavy emphasis on the lowest bid as that is which usually determines the winner of the auction, (2) anticipated high outliers due to the presence of uncompetitive bids, (3) very small samples, and (4) uncertainty of the appropriate underlying density function model of the bids. This paper describes a graphical method for simultaneously identifying outliers and density function by first removing candidate (high) outliers and then examining the goodness-of-fit of the resulting reduced samples by comparing the reduced sample predictability (by the expected value of the lowest order statistic) of the lowest bid with that of the equivalent predictability by Monte Carlo simulations of one of the common density functions. When applied to a set of 1073 auctions, the results indicate the appropriateness of censored and reduced sample lognormal models for a wide range of cut-off values. These are compared with cut-off values used in practice and to identify potential improvements.

Impact and interest:

9 citations in Scopus
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4 citations in Web of Science®

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ID Code: 4138
Item Type: Journal Article
Additional URLs:
Keywords: Construction, contract, auctions, outliers, goodness, of, fit, censored samples, small samples
ISSN: 1476-9360
Subjects: Australian and New Zealand Standard Research Classification > TECHNOLOGY (100000)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2001 Palgrave Macmillan
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 16 May 2006
Last Modified: 09 Jun 2010 22:32

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