Examples of research on appraising investments considering future uncertainty and management flexibility
| Infrastructure | Source | Future uncertainty modelled | Impacts considered | Simulation method used |
|---|---|---|---|---|
| Hospitals and clinics | (de Neufville et al., 2008) | Changes in demographics, changes in patterns, causes and effects of health and disease, changes in medical technology | Economic cost of intervention and net benefit for operation | Monte Carlo |
| (Esders et al., 2020) | Number of patients | Economic cost of intervention and net benefit for operation | Binomial trees | |
| Engineering systems for on-shore liquefied natural gas and petrol plants | (Cardin et al., 2015) | Demand of liquefied natural gas | Economic cost of intervention | Monte Carlo |
| (Santa-Cruz and Heredia-Zavoni, 2011) | Economic variables (hydrocarbon prices and maintenance costs) and the engineering variables (the probability of fatigue damage) | Economic cost of intervention | Monte Carlo | |
| Engineering systems for waste and energy | (Cardin and Hu, 2016) | Required capacity of waste disposal and energy supply | Economic cost of intervention and net benefit for operation | Monte Carlo |
| Bridges | (Ellingham and Fawcett, 2007) | Weight and spacing of the axles related to traffic demand | Economic cost of intervention and net benefit for operation | Monte Carlo |
| Highways | (Fawcett et al., 2014) | Traffic demand | Economic cost of intervention and net benefit for operation | Monte Carlo |
| Parking silos | (De Neufville and Scholtes, 2011; De Neufville et al., 2006) | Number of parking plots required | Economic cost of intervention and net benefit from rent | Monte Carlo |
| (Elvarsson et al., 2021) | Number of parking plots required due to the outbreak of autonomous vehicles | Economic cost of intervention and benefit from rent | Monte Carlo | |
| Office buildings’ façades | (Esders et al., 2016) | Operating costs | Economic cost of intervention and net benefit from operation | Binomial trees |
| Space sharing in general buildings space | (Fawcett and Chadwick, 2007; Fawcett and Rigby, 2009) | Demand of working space | Economic cost of intervention and net benefit from operation | Agent-based simulation model |
| Layout of buildings’ ground floor | (Ellingham and Fawcett, 2007) | Commercial rents | Economic cost of intervention and benefit from rent | Binomial trees |
| Vertical expansion of office buildings | (Guma and de Neufville, 2008) | Future cash flows (rents) and demand for office space | Economic cost of intervention and operation | Monte Carlo |
| Ground floor ceilings in general buildings | (Martani et al., 2018) | Use change rate | Economic cost of intervention and net benefit from operation | Monte Carlo |
| Energy retrofit in existing buildings | (Ashuri et al., 2011) | Energy price | Economic cost of intervention and net benefit from operation | Monte Carlo |
| Infrastructure | Source | Future uncertainty modelled | Impacts considered | Simulation method used |
|---|---|---|---|---|
| Hospitals and clinics | ( | Changes in demographics, changes in patterns, causes and effects of health and disease, changes in medical technology | Economic cost of intervention and net benefit for operation | Monte Carlo |
| ( | Number of patients | Economic cost of intervention and net benefit for operation | Binomial trees | |
| Engineering systems for on-shore liquefied natural gas and petrol plants | ( | Demand of liquefied natural gas | Economic cost of intervention | Monte Carlo |
| ( | Economic variables (hydrocarbon prices and maintenance costs) and the engineering variables (the probability of fatigue damage) | Economic cost of intervention | Monte Carlo | |
| Engineering systems for waste and energy | ( | Required capacity of waste disposal and energy supply | Economic cost of intervention and net benefit for operation | Monte Carlo |
| Bridges | ( | Weight and spacing of the axles related to traffic demand | Economic cost of intervention and net benefit for operation | Monte Carlo |
| Highways | ( | Traffic demand | Economic cost of intervention and net benefit for operation | Monte Carlo |
| Parking silos | ( | Number of parking plots required | Economic cost of intervention and net benefit from rent | Monte Carlo |
| ( | Number of parking plots required due to the outbreak of autonomous vehicles | Economic cost of intervention and benefit from rent | Monte Carlo | |
| Office buildings’ façades | ( | Operating costs | Economic cost of intervention and net benefit from operation | Binomial trees |
| Space sharing in general buildings space | ( | Demand of working space | Economic cost of intervention and net benefit from operation | Agent-based simulation model |
| Layout of buildings’ ground floor | ( | Commercial rents | Economic cost of intervention and benefit from rent | Binomial trees |
| Vertical expansion of office buildings | ( | Future cash flows (rents) and demand for office space | Economic cost of intervention and operation | Monte Carlo |
| Ground floor ceilings in general buildings | ( | Use change rate | Economic cost of intervention and net benefit from operation | Monte Carlo |
| Energy retrofit in existing buildings | ( | Energy price | Economic cost of intervention and net benefit from operation | Monte Carlo |
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