A Competitive-Bidding Strategy

Friedman, Lawrence

doi:10.1287/opre.4.1.104

Cited by 443 publications

(226 citation statements)

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“…One of the early, notable contributions to the field is by Friedman (1956) on competitive bidding strategy. It involves maximising the expected profit from a single tender where each competitor submits a closed bid by selecting a mark-up on cost that maximises expected value of the profit -which is the product of the mark-up and the probability of winning the contract (Runeson and Skitmore 1999).…”

Section: Theorymentioning

confidence: 99%

Winning the Bid – A Step-Wise Approach Using BIMto Reduce Uncertainty in Construction Bidding

Aslesen¹,

Kristensen²,

Schanche³

et al. 2018

26th Annual Conference of the International Group for Lean Construction

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This paper explains how to win a construction bid at the right costs. It suggests a structured, step-wise approach where at each step data analyses are carried out based on earlier bids, which are combined with assessments from an active risk management system, to come up with reliable estimates. To make sure all significant cost elements in the project are understood, linked together and communicated effectively, a building information model (BIM) is applied and worked on every step of the way from a preliminary, rough estimation to a final, complete bid.The paper derives from an ongoing development project to improve the bidding process in a Norwegian construction company. It intends to solve the following problem: How can we reduce the uncertainty in the bids we offer?The paper introduces a new way to organize the bidding process, including certain principles, to reduce uncertainty already in the project development, and attempts to increase our knowledge of the construction bidding process. The literature review is focused on theories of relevance to address the uncertainties inherent in construction bidding. The paper concludes that a project bid will always be burdened with uncertainty. Whereas traditional bidding theory gives support to the behaviour of economic agents who do the pricing to maximise profit, we find it relevant to introduce the concept of bounded rationality to explain why construction bidding is not a straightforward matter and how uncertainty management is fundamental to come up with the right costs.

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Section: Theorymentioning

confidence: 99%

Winning the Bid – A Step-Wise Approach Using BIMto Reduce Uncertainty in Construction Bidding

Aslesen¹,

Kristensen²,

Schanche³

et al. 2018

26th Annual Conference of the International Group for Lean Construction

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“…The first probability-based bidding model was proposed by Freidman (Friedman, 1956). Many researchers have discussed the validity and practicality of such probabilistic monetary value models (Gates, 1976;Benjamin and Meador, 1979;Ioannou, 1988).…”

Section: Previous Studiesmentioning

confidence: 99%

A Neural Network Mark-up Estimation Model for Syrian Contractors

Wanous¹,

Boussabaine²

2017

IJAEC

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. AbstractOne of the most important decisions that have to be made by construction contractors is how much to mark-up the estimated cost of a new project. The main objectives of this paper are to model the relationship between mark-up estimation and the key factors affecting it and to compare the application of regression analysis and neural network techniques on the mark-up decision making process in order to find which technique is more reliable in terms of accuracy and robustness. The most influential mark-up factors were identified through a formal questionnaire survey conducted among Syrian contractors. Subsequently, data on one hundred and eleven real-life bidding situations was collected from Syria. Ninety-six of these projects were used to develop linear, non-linear regression and neural network mark-up models. The remaining fifteen projects were randomly held-back for validating the developed models. The neural network model proved to be robust and more accurate than the regression models. Although this study was carried out in the context of the Syrian construction industry, the methodology and the findings have much broader geographical applicability.

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“…The first Ph.D. in operations research was granted for a dissertation that presented a model to help bidders decide how to bid in a sealed bid auction. (See Friedman 1956, 1957.) The model was a decision theory model.…”

Section: Operations Research/management Science and Engineeringmentioning

confidence: 99%