Sea Ice
- About
- Imprint
- Scenarios
- Arctic Marine Transportation by 2030
- Introduction
- Aim of this Study
- Key Factor Classification
- Definitions of Key Factors and Future Projections
- 1. Climate
- 2. Legal framework
- 3. Global Trade Dynamics – Global economic growth
- 4. Safety of other Routes
- 5. Socio-economic impact of global climate change
- 6. Oil Price
- 7. Major Arctic Shipping Disasters
- 8. Windows of Operation
- 9. Maritime Insurance Industry
- 10. Collaboration in resource extraction by China, Japan and Russia
- 11. Transit fees
- 12. Conflict between indigenous and commercial use
- 13. Arctic Enforcers
- 14. Energy sources for propulsion
- 15. New resource discovery
- 16. World Trade Patterns
- 17. Regulation in the Arctic
- Consistency matrix
- Scenarios
- Suggest Wild Cards
- Suggest Key Factors
- References
- Glossary
- Yakutat Community Energy Scenarios
- Introduction to Scenario-Management
- The Consistency and Robustness Analysis
- 1. Key Factors and their Future Projections
- 2. Assigning plausibility values to future projections
- 3. Projection Bundles
- 4. Assigning consistency values
- 5. Obtaining overall consistency values for the projection bundles
- 6. The combinatorial problem of the consistency analysis
- 7. The Robustness of a projection bundle
- Disruptive event analysis – Wild Cards
- ScenLab v1.7 Client download
- Arctic Marine Transportation by 2030
2. Assigning plausibility values to future projections
It is possible to assign plausibility values to the future projections of a key factor,
i.e. to state that one of the future projections is expected to be much more likely
to occur than the others.
Example 1
The key factor ‘Foreign Policy’ has the future projections ‘Containment’, ‘Preemptive
Strikes’ and ‘Isolation’. One might consider ‘Containment’ to be the most
likely future foreign policy and therefore assign it a plausibility value of 0.65, while
‘Isolation’ is very unlikely with just 0.1. Since plausibility values need to add up
to 1 that leaves ‘Preemptive Strikes’ with 0.25.
Keep in mind that these occurrence plausibilities are ad-hoc plausibilities, i.e.
they are based on assumptions of one future development without considering
dependencies between two or more future developments. Plausibility values are
merely a tool to identify futures that are regarded more likely than others; they
are not capable of giving an absolute occurrence probability for a future projection.
Not assigning plausibility values is equivalent to assuming an equal distribution
of plausibility values among the future projections of a key factor. This is the
default setting in ScenLab.
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