Determining the probability distributions of cost and time overrun arising from different contractor selection strategies in construction projects

Student thesis: Doctoral ThesisDoctor of Philosophy

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Abstract

Failing to adequately select the winning contractor can lead to problems in the project delivery phase such as bad quality and project delay; which ultimately results in cost overruns. There are two strategies involved with selecting contractors: one is the lowest tender, the other is called best value.Selecting the lowest tender is straightforward; the latter strategy would involve scoring the contractors' tenders on price and quality and ranking them.The aim of this research is to provide a model of determining the probability distributions of cost and time arising from choosing different contractor selection strategies: lowest tender or best value tender.The research presents an approach by which a what-if scenario can be analyzed using educational facilities projects in the UK. A Monte Carlo Simulation model was developed to allow the evaluation of the probability distributions of cost, and duration arising from the different strategies; these a represented as probability curves.The results show that the lowest tenderer would likely overrun in cost but the cost will be below the price of the best value tenderer. However, there is a higher probability that the lowest tender will exceed the clients’ expected duration, perhaps by a significant amount.The first contribution of the thesis is the development of a novel model of determining the probability distributions of cost and time involved with the different contractor selection strategies by using Monte Carlo simulation. The second contribution is a fresh way of looking at cost overruns. It is proposed that contractors’ cost overrun for a project should be compared to the price of the next highest tender to gauge its real impact.

Details

Original languageEnglish
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Supervisors/Advisors
Award date2017

    Keywords

  • Contractor selection, lowest price, best value tender, Monte Carlo simulations

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