On being balanced in an unbalanced world
Skitmore, R.M. and Cattell, D.W. (2010). On being balanced in an unbalanced world. Submitted to the Journal of the operational research society (Accepted).
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© Copyright R.M. Skitmore & D.W. Cattell, 2010
Unbalanced bidding, or bid skewing, involves the uneven distribution of mark-up among a contract project’s component items in such a way as to attempt to derive increased benefit to the unbalancer but without involving any change in the total tender price. Those who issue such contracts have reason to protect themselves from the ‘hidden’ costs of unbalancing. They typically reserve the right to reject any unacceptably unbalanced bid, but in order to do so, they have need to detect this. Models have been developed to increase both the systemised execution and detection of unbalancing but, although unbalancing is thought to be widespread in general, virtually nothing is known of its use, success or otherwise. This is of particular concern for the detection methods as, without testing, there is no way of knowing the extent to which unbalanced bids are remaining undetected or balanced bids are being falsely detected as unbalanced.
This paper reports on a simulation study aimed at demonstrating the likely effects of unbalanced bid detection models in a deterministic environment involving front-loading (FL) unbalancing. A proportion of bids are automatically and maximally unbalanced over a long series of simulated contract projects and the profits and detection rates of both the balancers and unbalancers are compared.
The results show that, as expected, the balanced bids are often incorrectly detected as unbalanced, with the rate of (mis)detection increasing with the proportion of FL bidders in the auction. It is also shown that, while the profit for balanced bidders remains the same irrespective of the number of FL bidders involved, the FL bidder’s profit increases with the greater proportion of FL bidders present in the auction. Sensitivity tests show the results to be generally robust, with (mis)detection rates increasing further when there are fewer bidders in the auction and when more data is averaged to determine the baseline value, but being smaller or larger with increased cut-off values and increased cost and estimate variability depending on the number of FL bidders involved. The FL bidder’s expected benefit from unbalancing, on the other hand, increases when there are fewer bidders in the auction. It also increases when the cut-off rate and discount rate is increased, and when there is less variability in the costs and their estimates, and when less data is used in setting the baseline values.
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