Estimating Future Bidding Performance of Competitor Bidders in Capped Tenders

Abstract

"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

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

“…First, the current method is valid for virtually any type of auction (capped and uncapped); second, it provides more robust statistical measures concerning the bidding performance and a series of new probability distributions that improve the fitness with construction tendering data; and third, it proposes closed mathematical expressions to calculate the position probability curves of any bidder. Nevertheless, it goes without saying that the first work by Ballesteros-Pérez et al [18] actually paved the path for this study and even proposed a first expression to calculate group bidding performance, which will also be used here later.…”

“…In the literature, very few examples of performance parameters can be found, examples being the following four displayed at the top of Table 1, and nearly the only exceptions: P ik [30], P ′ ik [18], P ′′ ik [42] and P ′′′ ik [43]. In addition, in the upper table, a numerical example for N k = 5 bidders is given to illustrate how each of these position performance coefficients calculates the values for a range of different positions j ik from 1 to 5.…”

“…Finally, Ballesteros-Pérez et al [18] devised a methodology for measuring bidding performance applicable for capped tenders (tenders with a maximum price threshold set by the auctioneer). This attempt is the most similar to the model proposed here, but it includes several improvements.…”

“…The importance of using the method suggested above lies in the fact that any bidder who needs to know how effective he or she is when competing against others will always need a framework with which to compare performances with those of rivals [18], and this can only be effectively achieved by using a quantitative and objective approach that, to the best of our knowledge, has not been proposed within the bidding literature to date. This paper is organized as follows: Section 2 reviews the short literature on bidding performance, and then it presents the actual construction tender dataset that will be used as an example.…”

Optimal Pavement Maintenance Programs Based on a Hybrid Greedy Randomized Adaptive Search Procedure Algorithm

“…Previous studies have developed performance indicators for different types of infrastructure: pavements (Chamorro and Tighe, 2009;Chamorro et al, 2010;Sivilevičius and Vansauskas, 2013), bridges (Neves and Frangopol, 2005), etc. ; as well as other aspects in the construction management field (Ballesteros-Pérez et al, 2014). This study considers a performance indicator developed by Osorio et al (2014) to assess urban pavement conditions based on objective measures of surface distresses and evaluations by an expert panel.…”