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Decision Analysis for Environmental Management


Admission requirements

Required course(s):



Systemic transitions are necessary to move humanity towards a sustainable future. Just to name a few, the ways we produce energy and chemicals, provide transport and health services, need to be rethought if we want to secure a fair and enduring society. Each of these transitions comes with several environmental challenges, due to the use of resources and release of pollutants of different nature. It is thus imperative that we assess these sustainability implications as accurately and as comprehensively as possible. In addition, preferences from multiple stakeholders (e.g., government, industry, civil society) need to be accounted for as well.

In this context, decisions are more needed than ever, and they need to be taken quickly. How can we make sense of all this information to provide (strategy/policy) recommendations for Decision Makers (DMs)? This course will answer this question by introducing students to Multiple Criteria Decision Analysis (MCDA). MCDA is a discipline that has been specifically developed to help DMs make better decisions. It allows to comprehensively evaluate alternatives by integrating conflicting objectives and preferences of the DMs.

The students will learn the key concepts of decision quality in the context of sustainability and resilience-driven environmental management. This will include the understanding of how sustainability and resilience frameworks can be applied to environmental management at different scales, from a micro (e.g., technologies) to a macro (e.g., countries) scale.

Key potentials of MCDA will be discussed, including the capability of conveying a wealth of information that describes each alternative (e.g., a policy, a technology, an investment strategy) in a synthetic fashion, like a ranking from the best to the worst, a sorting in good, medium, and bad classes, or the choice of a subset of the most preferred alternatives.

Throughout the Block, we will explore practical MCDA-based case studies which include, among others, sustainability evaluation of different mixes of energy technologies, resilience assessment of countries’ electricity supply, resources criticality, remediation of contaminated sites.

Course Objectives


  • Outline how sustainability and resilience frameworks are used to support environmental management

  • Describe the Multiple Criteria Decision Analysis (MCDA) process and distinguish the role of the stakeholders in each of its steps

  • Explain MCDA methods of different type, tailored to the most common decision-making problems (i.e., ranking and classification) in environmental management and beyond


  • Develop a decision support model to assess a set of alternatives using sustainability and/or resilience frameworks

  • Tailor solutions proposed to tackle challenging steps in decision-making to different contexts


Timetables for courses offered at Leiden University College in 2023-2024 will be published on this page of the e-Prospectus.

Mode of instruction

This course delivers a stepwise introduction to the tools needed to support complex decision-making, using a mix of lectures, class discussions, workshops, and small group meetings with the instructor to shape critical thinking and decision support expertise. The classes will be interactive and develop the students’ analytical skills for tackling pressing decision-making challenges, primarily in the area of energy systems analysis.

This course is (mostly) project-based, meaning that each student will be part of a specific group that will work on a project of interest(*) throughout the whole block. Each group will develop an understanding of the sustainability and/or resilience-related impacts of their project. After that, each group will tailor their decision support model to provide a comprehensive score for the alternatives under evaluation in order to rank them and identify the best performing one(s).

(*) Examples of previous projects include the choice of electricity storage technologies, location of a geothermal power plant, development of energy transition policies for a country, and renovation strategies for the Hortus Botanicus of Leiden University.

Assessment Method

  • Course participation (10%, ongoing week 1-7)

  • Group project part 1 (13%, week 3): Initial proposal for the case study to be modelled and analysed by means of MCDA

  • Group project part 2 (17%, week 6): Final presentation of the case study to be modelled and analysed by means of MCDA

  • Individual assignment (30%, week 7): Personal proposal of a research strategy to improve at least one step of the group project

  • Final exam (30%, week 8): Open and close-ended questions on course material

Reading list

Several readings will be made available throughout the course. These will include journal publications and chapters, including from these key books about MCDA:

  • Greco S, Ehrgott M, Figueira J. (Eds.) Multiple Criteria Decision Analysis: State of the Art Surveys. New York: Springer-Verlag; 2016. (A recent survey of the main families of MCDA methods presented by some of the main researchers in the area)

  • Belton V, Stewart TJ. (Eds.) Multiple criteria decision analysis - An integrated approach: Kluwer Academic Publisher; 2002. (A very approachable book as an introduction to MCDA and some of its methods)

  • Ren, J. (Ed.) Energy Systems Evaluation (Volume 2). Multi-Criteria Decision Analysis: Springer, Cham; 2021(A good compendium of MCDA applications in the areas of energy systems analysis)


Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator,


Dr. Marco Cinelli,


Who should attend this course?

Students with a main desire of learning how to shape and integrate different types of information/data and preferences to aid decision-makers making sound decisions.