Forecasting the number and distribution of new bidders for an upcoming construction auction
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Description
Estimating the number of new bidders in construction auctions is relevant for both private companies and contracting authorities. For private companies, it allows the total number of competing bidders to be estimated, which may lead to better adjustments of future bids. For contracting authorities, it allows the population size of all potential bidders to be estimated and thus to implement better awarding criteria. Mathematical models for forecasting the number of new bidders and the population size of all potential bidders are, however, very scarce in the construction management literature. In this paper, we propose an exponential model for predicting the average number of new bidders based on an urn analogy. The model allows the number of new bidders to be estimated as a function of new versus total participating bidders observed in previous auctions. The parameter estimates obtained from the model also allow the statistical distribution of the number of potential new bidders to be modeled using a sum of binomial distributions. We validate the exponential model on three published construction auction data sets, showing that the proposed model significantly outperforms the multinomial model - the most advanced model for performing similar tasks found in the literature.
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ID Code: | 131782 | ||||
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Item Type: | Contribution to Journal (Journal Article) | ||||
Refereed: | Yes | ||||
ORCID iD: |
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Measurements or Duration: | 10 pages | ||||
Keywords: | auction, bidders, binomial, competitiveness, exponential model, forecasting | ||||
DOI: | 10.1061/(ASCE)CO.1943-7862.0001694 | ||||
ISSN: | 1943-7862 | ||||
Pure ID: | 33487974 | ||||
Divisions: | Past > QUT Faculties & Divisions > QUT Business School Past > Institutes > Institute for Future Environments Past > QUT Faculties & Divisions > Science & Engineering Faculty Current > Schools > School of Economics & Finance |
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Copyright Owner: | Consult author(s) regarding copyright matters | ||||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
Deposited On: | 31 Jul 2019 22:33 | ||||
Last Modified: | 03 Mar 2024 05:57 |
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