Zhou, X (2011) Managing commodity risks in highway contracts: Quantifying premiums, accounting for correlations among risk factors, and designing optimal price-adjustment contracts. PhD thesis, Texas A&M University, USA.
Abstract
It is a well-known fact that macro-economic conditions, such as prices of commodities (e.g.oil, cement and steel) affect the cost of construction projects. In a volatile market environment, highway agencies often pass such risk to contractors using fixed-price contracts. In turn, the contractors respond by adding premiums in bid prices. If the contractors overprice the risk, the price of fixed-price contract could exceed the price of the contract with adjustment clauses. Consequently, highway agencies have the opportunity to design a contract that not only reduces the future risk of exposure, but also reduces the initial contract price. The main goal of this dissertation is to investigate the impact of commodity price risk on construction cost and the optimal risk hedging of such risks using price adjustment clauses. More specifically, the objective of the dissertation is to develop models that can help highway agencies manage commodity price risks. In this dissertation, a weighted least square regression model is used to estimate the risk premium; both univariate and vector time series models are estimated and applied to simulate changes in commodity prices over time, including the effect of correlation; while the genetic algorithm is used as a solution approach to a multi-objective optimization formulation. The data set used in this dissertation consists of TxDOT bidding data, market-based data including New York Mercantile Exchange (NYMEX) future options data, and Engineering News-Record (ENR) material cost index data. The results of this dissertation suggest that the optimal risk mitigation actions are conditional on owners‘ risk preferences, correlation among the prices of commodities, and volatility of the market.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Damnjanovic, I |
| Uncontrolled Keywords: | market; optimization; construction cost; construction project; highway; bidding; owner; cost index; time series |
| Index terms: | cost index, construction cost, owner, economic condition, regression model, option, dissertation, estimate, risk factor, multi-objective optimization, New York, genetic algorithm, time series, risk premium, bidding, agency, exposure, risk mitigation, accounting, preference, construction project |
| Subjects: | environmental hazards, algorithms, decision-making and reasoning, financial risk, Geography, production management, economic analysis, bidding, research dissemination and communication, decision analysis, sociology, statistical analysis, public and environmental health, financial and cost management, data science |
| Topics: | Project Management, Geographical Context, Health and Safety, Sustainability, Procurement, Risk Management, Digital Applications, Research Practice, Business Strategy, Cost Management, Stakeholder Management |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here