Bidding Strategy using Multiple Regression

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Abstract
Multiple regression analysis is applied to construction competitive bidding to give a contractor new insights that will help him compete more effectively. Data from 48 projects bid by a contractor are collected and analyzed. Two models are developed, one for use in deciding whether or not to estimate and bid a job and one to aid in his markup decision. Expected value criteria are applied to both decisions. The proposed two-phase bidding strategy is demonstrated on two jobs and problems in the contractor's competitive position are diagnosed using the model. Practicalities of model development for other contractors are considered.

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