701-1522-00L  Multi-Criteria Decision Analysis

Courses

Catalogue data

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).
Learning 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 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-making. 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: second Tuesday in March! Please note that after that date no deregistration will be accepted and the course will be considered as “fail” / unsatisfactory grade.
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.
Prerequisites / Notice	The course requires some understanding of (basic) mathematics. The "formal" parts are not too complicated and we will guide students through the mathematical applications and use of the ValueDecisions app (software). Participants should bring their own laptop (let us know if this is not possible). The course is limited to 30 participants (first come, first served).
Competencies	Subject-specific Competencies Concepts and Theories assessed Method-specific Competencies Analytical Competencies fostered Decision-making assessed Media and Digital Technologies fostered Problem-solving assessed Social Competencies Communication fostered Cooperation and Teamwork fostered Negotiation fostered Personal Competencies Creative Thinking assessed Critical Thinking assessed Self-direction and Self-management fostered

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits	3 credits
Examiners	J. Lienert
Type	graded semester performance
Language of examination	English
Repetition	Repetition only possible after re-enrolling for the course unit.
Additional information on mode of examination	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: second Tuesday in March! Please note that after that date no deregistration will be accepted and the course will be considered as “fail” / unsatisfactory grade.

Learning materials

Groups

Restrictions

Offered in

Programme	Section	Type
Doctorate Environmental Systems Sciences	Environmental Systems Policy	W
Geomatics Master	Major in Planning	W
MAS in Sustainable Water Resources	Elective Courses	W
Spatial Development and Infrastructure Systems Master	Major Courses for all Majors	W
Environmental Sciences Master	Modeling and Statistical Analysis	W