Accessibility navigation


Estimating the number of new and repeated bidders in construction auctions

Ballesteros-Pérez, P. and Skitmore, M. (2016) Estimating the number of new and repeated bidders in construction auctions. Construction Management and Economics, 34 (12). pp. 919-934. ISSN 0144-6193

[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

429kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1080/01446193.2016.1231408

Abstract/Summary

The number of new bidders – bidders from whom there is no previous registered participation – is an important variable in most bid tender forecasting models, since the unknown competitive profile of the former strongly limits the predictive accuracy of the latter. Analogously, when a bidder considers entering a bid or when an auctioneer is handling a procurement auction, assessing the likely proportion of experienced bidders is considered an important aspect, as some strategic decisions or even the awarding criteria might differ. However, estimating the number of bidders in a future auction that have not submitted a single bid yet is difficult, since there is no data at all linking their potential participation, an essential requirement for the implementation of any forecasting or estimation method. A practical approach is derived for determining the expected proportion of new bidders to frequent bidders as a function of the population of potential bidders. A multinomial model useful for selective and open tendering is proposed and its performance is validated with a dataset of actual construction auctions. Final remarks concern the valuable information provided by the model to an enduring unsolved bidding problem and the prospects for new research continuations.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of the Built Environment > Construction Management and Engineering > Business Innovation in Construction
ID Code:66559
Publisher:Taylor & Francis

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation