MCDA — Multi-Criteria Decision Making in e-commerce

  • Hans -J. Lenz
  • Alexandr Ablovatski
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 482)


The growing markets of e-commerce created renewed interest in methodologies that were developed more than thirty years ago and found broad usage in various fields like Operations Research, Decision Theory, Artificial Intelligence, Micro-Economic Theory, etc. One such methodology is multi-criteria decision-making or analysis (MCDA). It can be used for making decisions about options like goods and services, and plays an import role in e- as well as m-commerce markets. We review the main techniques of MCDA like SCORING (SAW), TOPSIS, AHP, PROMETHEE, DEA and apply them to one particular decision example using a software program specifically developed for this purpose, available online at We carefully compare the methods presented, and propose a hybrid technique called “GiUnTa” to reconcile the differing rankings obtained with each procedure. A similar approach and software solution can be used in real life decision situations that require fast consideration of multiple criteria over a large number of alternatives.


Data Envelopment Analysis Data Envelopment Analysis Model Efficiency Frontier Screen Shot Simple Additive Weighting 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Bamberg, G. and Coenenberg, A.G., Betriebswirtschaftliche Entscheidungslehre, 11. Auflage, Verlag Vahlen, München, 2002Google Scholar
  2. J.P. Brans, P. Vincke, B. Mareschal, How to select and how to rank projects: The Promethee method, EJOR 24, 1984Google Scholar
  3. Charnes, A., Cooper, W., Rhodes, E., Measuring the efficiency of decison making units, EJOR, 1978Google Scholar
  4. Charnes, A., Cooper, W., Lewin, A.Y., Seiford, M, Data Envelopment Analysis: Theory, Methdology and Applications, Kluwer, Boston, 1994Google Scholar
  5. J. Chomicki, Optimization of Preference Queries,, 2003Google Scholar
  6. Y. Dimopoulos, P. Moraitis, A. Tsoukias: Decision Analysis of Actions in Hierarchical Decomposition, Intelligent Agents: Decision-Support and Planning, G. Delia Riccia et al. (eds.), CISM series, Springer, Wien, New York, 2005.Google Scholar
  7. Emrouznejad, A., Data Envelopment Analysis (DEA) page, access 26.02.04.Google Scholar
  8. Emrouznejad, A., An Extension to SAS/OR for Decision System Support, access 26.02.04Google Scholar
  9. Fandel, G. and Gal, T. (eds.), Multiple criteria decision making, Springer, Berlin etc., 1997zbMATHGoogle Scholar
  10. S. French, Decision Theory — An Introduction to the Mathematics of Rationality, Springer, New York, 1988zbMATHGoogle Scholar
  11. Hwang C. L., Yoon K., Multiple Attribute Decision Making: Methods and Applications, Berlin etc., Springer Verlag, 1981zbMATHGoogle Scholar
  12. R. Keeney, H. Raiffa: Decisions with Multiple Objectives: Preferences and value tradeoffs, Springer, New York etc., 1976Google Scholar
  13. Naumann, F., Quality-driven Query Answering for integrated information systems, LNCS, Springer, Berlin etc., 2001Google Scholar
  14. Saaty, T.L., The Analytic Hierarchy Process, Springer, New York, 1980zbMATHGoogle Scholar
  15. Schneeweiß, Ch., Planung 1, Springer, Berlin usw., 1991Google Scholar

Copyright information

© CISM, Udine 2006

Authors and Affiliations

  • Hans -J. Lenz
    • 1
  • Alexandr Ablovatski
    • 2
  1. 1.Institute of Production, Information Systems and Operations ResearchFree UniversityBerlinGermany
  2. 2.Library and Information ServicesKenyon CollegeGambierUSA

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