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Multi-Criteria Decision Analysis
Last Updated: 2026-06-01 11:33:19
Abstract
This introduction to "Multi-Criteria Decision Analysis" combines prescriptive Decision Theory (Multi-Attribute Value and Utility Theory) with practical application and computer-based decision support systems. Aspects of descriptive (behavioral) Decision Theory (psychology) are introduced. Participants apply the theory to an environmental decision problem (group work).
Objective
The main objective is to learn "Multi-Attribute Value Theory" (MAVT) and apply it step-by-step to an environmental decision problem. Multi-Attribute Utility Theory" (MAUT) is shortly introduced. At the end, participants should be able to carry out MCDA on their own, in research projects and in practice (e.g., working as consultant). The participants learn how to structure complex decision problems and break them down into manageable parts. An important aim is to integrate the objectives and preferences of different decision-makers or stakeholders. The participants will practice how to elicit subjective (personal) preferences from stakeholders with structured interviews. They will learn to include uncertainty in decision models and test assumptions with sensitivity analyses. Participants should have an understanding of people's limitations to decision-making, based on insights from descriptive Decision Theory. They will use formal computer-based tools to integrate "objective / scientific" data with "subjective / personal" preferences to find consensus solutions that are acceptable to different stakeholders.
Content
GENERAL DESCRIPTION Multi-Criteria Decision Analysis (MCDA) is an umbrella term for a set of methods to structure, formalize, and analyze complex decision problems involving multiple objectives (aims, criteria), many different alternatives (options, choices), and different stakeholders which may have conflicting preferences. Uncertainty (e.g., of environmental data) adds to the complexity of environmental decisions. MCDA helps to make decision problems more transparent and guides stakeholders into making rational choices. Today, MCDA-methods are being applied to many complex decision situations. This class is designed for participants interested in transdisciplinary approaches that help to better understand real-world decision problems and that contribute to finding sustainable solutions. The course focuses on "Multi-Attribute Value Theory" (MAVT). It gives a short introduction to "Multi-Attribute Utility Theory" (MAUT) and behavioral Decision Theory, the psychological field of Decision Analysis. STRUCTURE The course consists of a combination of lectures, exercises and discussion in the class, exercises in small groups, and reading. Some exercises are computer assisted, applying the ValueDecisions app, a browser-based MCDA software in a user-friendly R-shiny interface. For the analyses, participants need a laptop. The participants will choose an environmental case study to work on in small groups throughout the semester. They will summarize this work in a graded report. Additional reading of selected sections in the textbook Eisenführ et al. (2010) is required to understand the theory. Participants’ individual learning of MCDA will be tested in one mandatory quiz. GRADING The grade for the course is determined by one mandatory quiz at a fixed date that is individually completed during class (30%) and a semester-long group project with a final written group report to be delivered at the end of the semester (70%). There is no possibility to repeat the quiz! If participants miss the mandatory quiz, it is graded 1. Last cancellation / deregistration date for this graded semester performance: first Tuesday in March! Please note that after that date no deregistration will be accepted and the course will be considered as “fail” / unsatisfactory grade.
Resources
Lecture Notes
No script (see below)
Literature
Theory is supported by reading selected sections in: Eisenführ, Franz; Weber, Martin; and Langer, Thomas (2010) Rational Decision Making. 1st edition, 447 p., Springer Verlag, ISBN 978-3-642-02850-2. Additional reading material will be recommended during the course. Lecture slides will be made available for download.
Learning Materials (Links)
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 33
- Signup End
- 25.02.2025
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Multi-Criteria Decision Analysis |
|
2 h weekly |
Offered In
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Doktorat Umweltsystemwissenschaften (Mehr Informationen unter: )
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