Investigation of Bid Price Competition Measured through Prebid Project Estimates, Actual Bid Prices, and Number of Bidders

Carr, Paul G.

doi:10.1061/(asce)0733-9364(2005)131:11(1165)

Cited by 64 publications

(29 citation statements)

References 4 publications

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“…Such research can be divided into the study of model development to support bid decision making [4,5,[10][11][12][13][14] and study to determine bid cost and contingencies in consideration of bidding risks [8,15,16].…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting Project’s Uncertainty Risk in the Bidding Process by Integrating Unstructured Text Data and Structured Numerical Data Using Text Mining

Lee

2017

Applied Sciences

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Abstract:The construction bidding process takes place in the early stages of a construction project. The bidding process involves many uncertainties since the construction risk factors are predicted and reflected in the bid price before construction commences. Therefore, bidders should thoroughly understand the uncertainty factors of the project before make bidding decisions. The uncertainty risk of construction projects is determined by the content that is contained in the bidding document. If the information provided in the bidding document is not accurate and is unclear, the uncertainty of the projects increases. Thus, this study is performed to predict risks in the bidding process of construction projects by analyzing the uncertainty of the bidding document and using it as factors to predict a project's bidding risk. To achieve this, bidding risk prediction modeling was conducted using the pre-bid clarification information of each project. In addition, text mining on pre-bid RFI documents, which are in an unstructured text data format, was performed and the results of text mining were used as major influencing factors for the risk prediction models. As a result, the accuracy of the risk prediction model including text data was improved (72.92%) when compared to the prediction model using only numeric data (52.08%). The results of this study are expected to strengthen the possibility of further similar studies in the future since it enhances the predictive accuracy by incorporating the uncertainty of the bidding document, which is rarely considered in previous studies.

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Section: Literature Reviewmentioning

confidence: 99%

Predicting Project’s Uncertainty Risk in the Bidding Process by Integrating Unstructured Text Data and Structured Numerical Data Using Text Mining

Lee

2017

Applied Sciences

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“…Indeed, an extensive literature has focused on the study of the potential number of bidders (Banki et al 2008;Carr 2005;Ngai et al 2002); nonetheless, no variable has yet been proven to be reliable enough to forecast the number of bidders that will take part in a future tender.…”

Section: Complementing the Smartbid Bid Tender Forecasting Modelmentioning

confidence: 99%

Estimating Future Bidding Performance of Competitor Bidders in Capped Tenders

Ballesteros‐Pérez

González-Cruz

Fernández-Diego

et al. 2014

Journal of Civil Engineering and Management

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"Estimating future bidding performance of competitor bidders in capped tenders." Journal of Civil Engineering and Management. In press. 1-12.http://dx.doi.org/10. 3846/13923730.2014.914096 The authors recommend going to the publisher's website in order to access the full paper.If this paper helped you somehow in your research, feel free to cite it. This author's version of the manuscript was downloaded totally free from: Abstract. Research in Bid Tender Forecasting Models (BTFM) has been in progress since the 1950s. None of the developed models were easy-to-use tools for effective use by bidding practitioners because the advanced mathematical apparatus and massive data inputs required. This scenario began to change in 2012 with the development of the Smartbid BTFM, a quite simple model that presents a series of graphs that enables any project manager to study competitors using a relatively short historical tender dataset. However, despite the advantages of this new model, so far, it is still necessary to study all the auction participants as an indivisible group; that is, the original BTFM was not devised for analyzing the behavior of a single bidding competitor or a subgroup of them. The present paper tries to solve that flaw and presents a stand-alone methodology useful for estimating future competitors' bidding behaviors separately.Keywords: bid, tender, auction, construction, score, forecast.Reference to this paper should be made as follows: Ballesteros-Pérez, P.; González-Cruz, M. C.; Fernández-Diego, M.; Pellicer, E. 2014. Estimating future bidding performance of competitor bidders in capped tenders, Journal of Civil Engineering and Management

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“…From [10], increasing the number of advertisers leads to small bid prices and slow convergent speed. However, several advertisers compete for one slot will not reduce the convergent speed in the NDSSA.…”

Section: Consider Ad I Has the Maximum Abp δ I And Ad I And Ad X Hamentioning

confidence: 99%

Bid Increment Adjusting Strategies in English Auction-based Sponsored Search

Tsung¹,

Ho²,

Lee³

2014

Appl. Math. Inf. Sci.

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Abstract:English auctions are applied in many current e-commerce applications because of the easy implementation. Some sponsored search advertising (SSA) services consider the ascending bidding rules of English auctions to determine winners. However, the high computation cost of determining winners is the major drawback of the English auction-based SSAs. Because the SSA is an online service, Internet users do not wait for a long time to receive the search result pages. In this paper, we provide a mechanism to reduce the overhead of computing winners and maximize the revenue obtained by the search engine provider (SEP). Our proposed mechanism adopts the minimum increase price (MIP), which is similar to the central price in the English auction, to indicate how much should be raised for the bids with updated prices. We design a uniform MIP adjusting strategy and an adaptive MIP adjusting strategy to determine the MIP setting in each round. We analyze the convergent speed of two proposed MIP adjusting strategies. According to our simulation results, we conclude the following properties. For all the SEP revenue considerations, the adaptive MIP adjusting strategy is outstanding in popular keywords, and rare keywords for the uniform MIP adjusting strategy. Opposite results are obtained for the convergent speed.

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Investigation of Bid Price Competition Measured through Prebid Project Estimates, Actual Bid Prices, and Number of Bidders

Cited by 64 publications

References 4 publications

Predicting Project’s Uncertainty Risk in the Bidding Process by Integrating Unstructured Text Data and Structured Numerical Data Using Text Mining

Predicting Project’s Uncertainty Risk in the Bidding Process by Integrating Unstructured Text Data and Structured Numerical Data Using Text Mining

Estimating Future Bidding Performance of Competitor Bidders in Capped Tenders

Bid Increment Adjusting Strategies in English Auction-based Sponsored Search

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