Multi-criteria Decision Analysis

  • Jean-Michel Josselin
  • Benoît Le Maux


Multiple criteria decision analysis is devoted to the development of decision support tools to address complex decisions, especially where other methods fail to consider more than one outcome of interest. The approach is very flexible as outcomes can be quantifiable in non-monetary terms and be expressed in ordinal or numerical terms (Sect. 11.1). Basically speaking, it starts with the construction of a value tree and the identification of relevant criteria (Sect. 11.2). The approach then proceeds with gathering information about the performance of each assessed alternative against the whole set of criteria. Values are generally normalized from 0 to 1, thereby constituting what is termed a score matrix (Sect. 11.3). Numerical weights are also assigned to criteria to better reflect their relative importance (Sect. 11.4). Weights and scores are then combined to arrive at a ranking or sorting of alternatives. Should a compensatory analysis be implemented, the approach would rely on aggregation methods to build a composite indicator (Sect. 11.5). Should a non-compensatory analysis be carried out, the approach would instead examine each dimension individually (Sect. 11.6). Furthermore, a sensitivity analysis of the weights and scores can be used to explore how changes in assumptions influence the results (Sect. 11.7).


Value tree Scores Weights Composite indicator Non-compensatory analysis Sensitivity analysis 


  1. Beinat, E. (1997). Value functions for environmental management. Berlin: Springer.CrossRefGoogle Scholar
  2. Beroggi, G. (1991). Decision modeling in policy management: An introduction to the analytic concepts. Heidelberg: Springer.Google Scholar
  3. de Borda, J. C. (1784). Mémoire sur les Elections au Scrutin. In Histoire de L’Academie Royale des Sciences.Google Scholar
  4. de Condorcet, M. (1785). Essai sur l’application de l’analyse à la probabilité des décisions rendues à la probabilité des voix. Paris: De l’imprimerie royale.Google Scholar
  5. Department for Communities and Local Government. (2009). Multi-criteria analysis: A manual.Google Scholar
  6. French, S., Maule, J., & Papamichail, N. (2009). Decision behaviour, analysis and support. University of Manchester, Cambridge University Press.Google Scholar
  7. Hobbs, B. F., & Meier, P. (2000). Energy decisions and the environment: A guide to the use of multicriteria methods. International Series in Operations Research & Management Science.Google Scholar
  8. Ishizaka, A., & Nemery, P. (2013). Multi-criteria decision analysis: Methods and software. New York: Wiley.CrossRefGoogle Scholar
  9. Melese, F., Richter A. and Solomon B. (2015). Military cost-benefit analysis: Theory and practice. In Studies in defence and peace economics. Routledge.Google Scholar
  10. Nardo, M., Saisana, M., Saltelli, A., & Tarantola, S. (2005). Tools for composite indicators building. Prepared for the EU Commission.Google Scholar
  11. New South Wales Government. (2013). Principles and guidelines for economic appraisal of transport investment and initiatives.Google Scholar
  12. OECD. (2008). The handbook on constructing composite indicators: Methodology and user guide.Google Scholar
  13. Pomerol, J.-C., & Barba-Romero, S. (2000). Multicriterion decision in management principles and practice. Heidelberg: Springer.CrossRefGoogle Scholar
  14. Roy, B. (1968). Classement et choix en présence de points de vue multiples (la méthode Electre). Revue française d’automatique, d‘informatique et de recherche opérationnelle 8.Google Scholar
  15. Roy, B., & Berthier, P. (1973). La méthode ELECRE II. Rapport technique. Note de travail, l42. METRA, Direction Scientifique.Google Scholar
  16. Roy, B., & Bouyssou, D. (1993). Aide multicritère à la décision: méthodes et cas. Paris: Économica.Google Scholar
  17. Roy, B., & Hugonnard, J. C. (1982). Ranking of suburban line extension projects on the Paris Metro System by a multicriteria method. Transportation Research A16.Google Scholar
  18. Saaty, T. (1980). The analytical hierarchy process. New York: Wiley.Google Scholar
  19. Thokala, P., Devlin, N., Marsh, K., Baltussen, R., Boysen, M., Kalo, Z., et al. (2016). Multiple criteria decision analysis for health care decision making—An introduction: Report 1 of the ISPOR MCDA emerging good practices task force. Value in Health, 19, 1–13.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jean-Michel Josselin
    • 1
  • Benoît Le Maux
    • 1
  1. 1.Faculty of EconomicsUniversity of Rennes 1RennesFrance

Personalised recommendations