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Multi-criteria Decision Problems

  • Annika Kangas
  • Mikko Kurttila
  • Teppo Hujala
  • Kyle Eyvindson
  • Jyrki Kangas
Chapter
Part of the Managing Forest Ecosystems book series (MAFE, volume 30)

Abstract

The essential part of multi-criteria decision analysis is structuring a value tree (or a decision hierarchy). Important in this phase is to find the relevant set of criteria and their potential sub-criteria. In this chapter, a definition for such a good set of criteria is provided. It is also important to design good decision alternatives. Therefore, hints on how to produce these alternatives are given. Another important aspect in multi-criteria analyses is the trade-offs between the criteria. These trade-offs can be inferred from the choices the decision-maker makes, either from actual or stated choices. We present different multi-attribute utility models and the interpretations of trade-offs these approaches imply. We present different approaches such as MAUT-related methods and the analytic hierarchy process (AHP)-related methods for estimating the trade-offs (or parameters of the utility functions) from stated choices. We present how the methods are applied for selecting the best alternative or ranking the alternatives in multi-criteria problems. We discuss the differences between the approaches and between the interpretations of the results.

Keywords

Decision criteria Decision attribute Decision alternative Value tree Decision hierarchy Trade-off Multi-attribute utility model Analytic hierarchy process 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Annika Kangas
    • 1
  • Mikko Kurttila
    • 2
  • Teppo Hujala
    • 3
  • Kyle Eyvindson
    • 4
  • Jyrki Kangas
    • 5
  1. 1.Economics and SocietyNatural Resources Institute Finland (Luke)JoensuuFinland
  2. 2.Bio-based Business and IndustryNatural Resources Institute Finland (Luke)JoensuuFinland
  3. 3.Bio-based Business and IndustryNatural Resources Institute Finland (Luke)HelsinkiFinland
  4. 4.Department of Forest SciencesUniversity of HelsinkiHelsinkiFinland
  5. 5.School of Forest SciencesUniversity of Eastern FinlandJoensuuFinland

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