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Estimating the number of new and repeated bidders in construction auctions

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journal contribution
posted on 2018-04-27, 10:31 authored by Pablo Ballesteros-Perez, Martin Skitmore
© 2016 Informa UK Limited, trading as Taylor & Francis Group. 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.

History

School

  • Architecture, Building and Civil Engineering

Published in

Construction Management and Economics

Volume

34

Issue

12

Pages

919 - 934

Citation

BALLESTEROS-PEREZ, 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.

Publisher

© Taylor and Francis

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2016-08-25

Publication date

2016-09-27

Notes

This is an Accepted Manuscript of an article published by Taylor & Francis in Construction Management and Economics on 27 Sep 2016, available online: https://doi.org/10.1080/01446193.2016.1231408

ISSN

0144-6193

eISSN

1466-433X

Language

  • en