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Alasad, R and Motawa, I (2015) Dynamic demand risk assessment for toll road projects. Construction Management and Economics, 33(10), 799-817.

  • Type: Journal Article
  • Keywords: system dynamics; demand risk; monte carlo simulation; toll roads
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/01446193.2016.1143561
  • Abstract:
      To bridge the gap between supply of and increasing demand for roads, public-private partnership (PPP) concession contracts in which the investment cost is recovered via payments from the end users have been established. Although this mechanism has been seen as an efficient way for road projects to be completed on time and within budget, the demand risk faced during the operation stage has considerably limited this efficiency. Demand depends on a range of interrelated and dynamic factors such as the demographic and economic conditions. In addition, uncertainty is an inherent aspect of most demand-underlying factors which always make demand estimation inaccurate. However, this uncertainty is largely ignored by modellers where a single demand estimate is often used when evaluating the facility. The aim is to develop a system dynamics model to assess demand risk in road projects. The model captures the factors affecting demand and their relationships and simulates their change over time. By employing Monte Carlo simulation, the model assesses the likelihood and potential effect of an event on the outcome and provides a full picture of the various effects of potential risk. The model can help public, private, and financial stakeholders of PPP facilities make more informed decisions.;To bridge the gap between supply of and increasing demand for roads, public-private partnership (PPP) concession contracts in which the investment cost is recovered via payments from the end users have been established. Although this mechanism has been seen as an efficient way for road projects to be completed on time and within budget, the demand risk faced during the operation stage has considerably limited this efficiency. Demand depends on a range of interrelated and dynamic factors such as the demographic and economic conditions. In addition, uncertainty is an inherent aspect of most demand-underlying factors which always make demand estimation inaccurate. However, this uncertainty is largely ignored by modellers where a single demand estimate is often used when evaluating the facility. The aim is to develop a system dynamics model to assess demand risk in road projects. The model captures the factors affecting demand and their relationships and simulates their change over time. By employing Monte Carlo simulation, the model assesses the likelihood and potential effect of an event on the outcome and provides a full picture of the various effects of potential risk. The model can help public, private, and financial stakeholders of PPP facilities make more informed decisions.;