Chapter
Jul 11, 2012

A Risk-Sensitive Markup Decision Model

Publication: Construction Research Congress 2012: Construction Challenges in a Flat World

Abstract

Construction risk can be associated with different factors such as the size and complexity of the project, the experience of the contractor with similar type of work, unexpected weather conditions, unexpected ground conditions, or even unanticipated market changes. Failure to estimate the uncertainties that accompany a specific project often leads to a delayed project with cost overruns and compromised quality. Therefore, when bidding on a certain project, a contractor has to consider the possibility and the magnitude of construction risks involved, and then decide on its optimum markup accordingly. Cost uncertainty is not only an issue at the conceptual phase of a project but continues even into the construction phase. In addition to the uncertainty in the final project cost, the attitude of the contractor towards risk taking is of equal or even more importance in choosing the optimum markup and the resulting bid price for a project. This paper uses established principles of decision analysis and utility theory to develop a risk-sensitive bidding model that aims at determining the contractor's optimal markup value for a project given his risk attitude and his uncertainty about the final project cost. A sensitivity analysis is then conducted through a numerical example to illustrate the effect of risk aversion and cost variance on the optimum markup for the competitive low bid method.

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Go to Construction Research Congress 2012
Construction Research Congress 2012: Construction Challenges in a Flat World
Pages: 199 - 208

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Published online: Jul 11, 2012

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Assistant Professor, Department of Civil Engineering, 308 Bassil Bldg., Lebanese American University, Byblos, Lebanon. E-mail: [email protected]
Photios Ioannou [email protected]
M.ASCE
Professor and Program Advisor for Construction Engineering and Management Program, Department of Civil and Environmental Engineering, 2350 G.G. Brown Bldg., University of Michigan, Ann Arbor, MI 48109-2125. E-mail: [email protected]

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