Multiple criteria analysis (MCA) for complex decision-makingMethodology courses and philosophy of science


Course information


ECTS: 1.5
Number of session: 2
Hours per session: 3
Entry level: Intermediate
Course fee:

  • free for PhD candidates of the Graduate School
  • €220 for non-members
  • consult our enrolment policy for more information

    Contact:

    Telephone: +31 (0)10 4082607


    Session 1
    November 27 (Monday) 2017
    13:30 - 16:30
    Mandeville building (directions) room T3-05

    Session 2
    December 18 (Monday) 2017
    13:30 - 16:30
    Mandeville building (directions) room T3-09 


    Introduction

    This course introduces the multiple criteria analysis (MCA) framework with particular focus and illustrations from environmental and public policy and decision-making. This approach has been widely used in a large variety of complex decision-making problems and fields regarding prioritisation of different policies, actions, projects and measures against multiple criteria or objectives.

    The main elements, characteristics, steps, strengths and weakness of MCA will be discussed during this course. In this two (half) days course different case studies will illustrate the applicability and contribution of MCA approach particularly in project prioritisation and decision making under uncertainty in public domain. Participants will have the opportunity to apply and understand this method through a workshop on prioritisation of alternative actions and the application of different software tool(s).


    Working method

    The course will include a mix of lectures, and an in-class group simulation workshop using MCA software tool(s). There will be two (afternoon) sessions consisting of one introductory lecture of 1.5 hours and three sessions (of 1.5 hours each) dedicated to a group simulation workshop.  

    Participants will work with data sets and background information supplied for the course, but can also use a data set of their own to work with. Data can be from any source: experiments, surveys, time series, panels, databases, etc. 


    Learning objectives

    After completion of this course, you will:

    • Understand the main elements, characteristics and steps of MCA process
    • Apply a MCA at a real complex decision making problem
    • Incorporate uncertainty in decision making analysis
    • Understand different weighting techniques that can be applied in MCA
    • Simulate a participatory decision making process based on MCA
    • Use a MCA software

    Session description

    Session 1
    Introduction to multiple criteria analysis for complex decision-making

    Session 2
    Group simulation workshop


    How to prepare

    • There are no preparatory assignments for this course. 
    • Participants will be given data sets and information they can use during the simulation exercise.
    • You will need to bring a laptop for which you have the necessary rights to install software.
    • In order to actively participate, you are required to read some literature in advance (will be provided later).

    About the instructor

    Stelios Grafakos holds a PhD from Erasmus University Rotterdam (EUR) on integrated sustainability assessment and multiple criteria decision-making of low carbon energy technologies. He currently works as a senior researcher and scientific advisor in the field of urban sustainability and climate change mitigation and adaptation.