Title:
Analyzing uncertainty in the price of materials and financial risk management strategies

dc.contributor.advisor Castro-Lacouture, Daniel
dc.contributor.author Ilbeigi, Mohammad
dc.contributor.committeeMember Song, Xinyi
dc.contributor.committeeMember Dilkina, Bistra
dc.contributor.committeeMember Jared, David
dc.contributor.committeeMember Welch, Timothy
dc.contributor.department Building Construction
dc.date.accessioned 2018-07-11T18:49:05Z
dc.date.available 2018-08-01T11:00:30Z
dc.date.created 2017-08
dc.date.issued 2017-05-11
dc.date.submitted August 2017
dc.date.updated 2018-07-11T18:49:05Z
dc.description.abstract Significant volatility and unprecedented uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs with regards to proper cost estimating and budgeting of transportation projects. Previous studies indicate that owner organizations often overpay for projects under fixed-price contracts that transfer the material price risk to contractors due to increased risk premiums and hidden contingencies in contractors’ submitted bid prices. A common method widely used by state DOTs for handling the issue of extra risk premiums in submitted bid prices and avoiding overpayment to contractors is to offer price adjustment clauses (PACs) in contracts. A PAC is a risk sharing contractual mechanism that guarantees an adjustment in payment to contractors based on the size and direction of the material price change. Although uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs and many transportation agencies utilize PACs to control consequences of material price volatility, there is little knowledge about analyzing uncertainties in the price of asphalt cement and actual performance of PACs. This dissertation aims to analyze uncertainty in the price of asphalt cement and examine performance of PACs in highway construction projects. After a comprehensive review of the existing body of knowledge about uncertainties in the price of critical materials in transportation projects and PACs, time series analysis is conducted and four univariate time series forecasting models are created to forecast future price of asphalt cement. The results of the time series forecasting show that all four time series models can predict the future values of asphalt cement price with proper accuracy but among the four models, the ARIMA and Holt Exponential Smoothing models are the most accurate prediction models with less than 2% error. Then, ARCH/GARCH time series analysis is conducted to quantify and forecast level of uncertainties in the price of asphalt cement. The results of this step can help transportation agencies systematically measure, analyze and forecast the uncertainties in the price of asphalt cement and implement their risk management strategies at the right time. In next step, impacts of offering PACs on submitted bid prices for major asphalt line items are analyzed using multivariate regression analysis. Finally, effects of offering PACs on dispersion of submitted bid prices and number of bidders are analyzed using system monitoring processes.
dc.description.degree Ph.D.
dc.embargo.terms 2018-08-01
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/60051
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Uncertainty
dc.subject Price adjustment clauses
dc.subject Asphalt cement
dc.subject Forecasting
dc.title Analyzing uncertainty in the price of materials and financial risk management strategies
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Castro-Lacouture, Daniel
local.contributor.corporatename College of Design
local.contributor.corporatename School of Building Construction
local.relation.ispartofseries Doctor of Philosophy with a Major in Building Construction
relation.isAdvisorOfPublication 6d614946-815e-49ef-b07a-ccf3260a0846
relation.isOrgUnitOfPublication c997b6a0-7e87-4a6f-b6fc-932d776ba8d0
relation.isOrgUnitOfPublication 45be5867-cf11-4a7f-b0de-7cd1fc348427
relation.isSeriesOfPublication 1ae3308a-2b56-4c89-8669-a4c987e93f4c
thesis.degree.level Doctoral
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