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Modeling bidding competitiveness and position performance in multi-attribute construction auctions

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posted on 30.04.2018 by Pablo Ballesteros-Perez, Maria Luisa del Campo-Hitschfeld, Daniel Mora-Melia, David Dominguez
© 2015 The Authors. Currently, multi-attribute auctions are becoming widespread awarding mechanisms for contracts in construction, and in these auctions, criteria other than price are taken into account for ranking bidder proposals. Therefore, being the lowest-price bidder is no longer a guarantee of being awarded, thus increasing the importance of measuring any bidder's performance when not only the first position (lowest price) matters.Modeling position performance allows a tender manager to calculate the probability curves related to the more likely positions to be occupied by any bidder who enters a competitive auction irrespective of the actual number of future participating bidders.This paper details a practical methodology based on simple statistical calculations for modeling the performance of a single bidder or a group of bidders, constituting a useful resource for analyzing one's own success while benchmarking potential bidding competitors.

Funding

This research study was funded in Chile by CONICYT under the Programs Initiation into research 2013 (project number 11130666) and 2014 (project number 11140128).

History

School

  • Architecture, Building and Civil Engineering

Published in

Operations Research Perspectives

Volume

2

Pages

24 - 35

Citation

BALLESTEROS-PEREZ, P. ...et al., 2015. Modeling bidding competitiveness and position performance in multi-attribute construction auctions. Operations Research Perspectives, 2, pp. 24-35.

Publisher

© The Authors. Published by Elsevier

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Publication date

2015

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

ISSN

2214-7160

Language

en

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