Abstract
In this work, we develop a set of tools able to analyse different options in a generic case of critical infrastructure development with the consideration of climate change adaptation needs. As an example that will guide us through the process, we refer to a decision problem related to the hydraulic regulation of a strategic infrastructure (e.g. an airport, a power plant, a train station or a logistic centre) exposed to uncertain future climatic extremes.
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Notes
- 1.
See also http://www.netsymod.eu/.
- 2.
The principle of Pareto dominance (Pareto optimality) is extremely useful in investment decisions and even more in the field of multi-criteria analysis as it allows to isolate those alternatives of choice with contrasting rankings in their criteria and thus identifies real conflicts (trade-offs) in the decision-making process.
- 3.
Download available at http://www.netsymod.eu/DSSwelcome.html.
- 4.
We listed these four options for the sake of concreteness and to add realism to our case study. However, any project alternative with evident or potential trade-offs in their performances could be considered an option.
- 5.
To add additional variability to the simulation database, Likert scales could also be fuzzy (Fourali 1997), i.e. it could be made possible to choose more than one value, creating in this way a range instead of a spot value.
- 6.
Definition of deep uncertainty from the Society for Decision Making Under Deep Uncertainty (www.deepuncertainty.org).
- 7.
There are several techniques to reach group consensus, most notably the Delphi method and the nominal group technique (Delbecq et al. 1975).
- 8.
CART simulation for risk takers available upon request.
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Bernhofer, J., Giupponi, C., Mojtahed, V. (2019). A Decision-Making Model for Critical Infrastructures in Conditions of Deep Uncertainty. In: Cecconi, F., Campennì, M. (eds) Information and Communication Technologies (ICT) in Economic Modeling. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-22605-3_9
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