Open AccessDetecting unbalanced bids via an improved grading-based model
Author(s) -
Gül Polat,
Harun Turkoglu,
Atilla Damcı,
Firat Dogu Akin
Publication year - 2020
Publication title -
organization, technology and management in construction
Language(s) - English
Resource type - Journals
eISSN - 1847-6228
pISSN - 1847-5450
DOI - 10.2478/otmcj-2020-0004
Subject(s) - bidding , call for bids , grading (engineering) , business , microeconomics , order (exchange) , construction bidding , operations research , profit (economics) , real time bidding , computer science , actuarial science , economics , industrial organization , finance , marketing , procurement , project management , engineering , civil engineering , management , pre construction services , program management
Unbalanced bidding, also known as skewed bidding, is the process of increasing and/or decreasing the prices of various bid items without altering the total offered bid price. Bids can be unbalanced either mathematically (front-end loading) or materially (quantity error exploitation). Owners should be very careful when evaluating the tenders as awarding a contract to an unbalanced bid may result in severe cost overruns because the prices of those items do not reflect their true costs and markup allocations. Unbalanced bidding is still a contentious issue in the construction industry. While some researchers consider it as a legal bidding strategy in such a fierce competitive business environment, others view it as an unethical practice and claim that unbalanced bids should be disqualified. Studies regarding unbalanced bidding can be categorized into two groups: (1) the ones focusing on detecting or preventing this practice to help owners; and 2) the ones focusing on optimizing unbalanced bidding to help contractors. This study aims to develop a model, which consists of eight grading systems, to assist owners in detecting materially unbalanced bids. The proposed model is the improved version of the previous model, which was composed of five grading systems. In order to demonstrate how this grading-based model can be used by owners, an illustrative example is presented. It was found that owners can easily and successfully detect unbalanced bids via the proposed model.