01553493

Component

Volatility and uncertainty in the price of asphalt cement increases the risk of contractors in fixed- price contracts and can lead to price speculation and bid inflation. One of the most common strategies used to address inflated bid prices and encourage the submission of lower bids is price adjustment clauses (PACs) which guarantee an adjustment in payments to contractors based on the size and direction of material price changes. Currently, many state DOTs exclude some transportation projects from their PAC programs based on material quantity or project dollar value. However, there is little knowledge about the effects of offering PAC on bid prices of transportation projects within different ranges of asphalt quantity and project dollar value. The research objective of this paper is to empirically analyze the effects of offering PAC on submitted bid prices in different projects within various ranges of asphalt quantity and dollar value. Data on 981 transportation projects was collected. The projects were clustered based on their total asphalt quantity and project dollar value using K-means clustering method. In each cluster, multivariate regression analysis was conducted to model the variations in submitted bid prices for asphalt line items. Finally, clusters where offering PAC was a statistically significant explanatory variable in the regression model were identified. The results indicate that the described framework can systematically identify the ranges of asphalt quantity and project dollar values in which offering PAC has reduced submitted bid prices. This study can help state DOTs to design and evaluate their PAC programs accurately.

This paper was sponsored by TRB committee AFH10 Construction Management. Alternate title: Data Mining Approach for Analyzing Effects of Price Adjustment Clauses on Bid Prices Considering Material Quantity and Project Size.

01550057

15-5489

English

13p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Asphalt cement; Bids; Cluster analysis; Construction projects; Contract administration; Cost estimating; Data mining; Prices; Regression analysis; State departments of transportation

Georgia

Administration and Management; Construction; Data and Information Technology; Highways; I10: Economics and Administration

Transportation Research Board Annual Meeting 2015 Paper #15-5489

PRP, TRIS, TRB, ATRI

Dec 30 2014 1:51PM