Product positioning using principles from the self-organizing map

Chris Charalambous, George C. Hadjinicola, Eitan Muller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper presents a methodology that identifies the position of a new product in the attribute space. The methodology uses principles from Kohonen’s self-organizing feature map. The algorithm presented is robust and can be used for a number of objective functions commonly used in the product positioning problem. The method can also be used in competitive environments where other competing products are already present in the market. Furthermore, the algorithm can accommodate single-choice models (the consumer purchases the product “closest” to his/her preferences) and probabilistic-choice models (the consumer assigns to each product a probability for purchasing it).

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2001 - International Conference, Proceedings
EditorsKurt Hornik, Georg Dorffner, Horst Bischof
PublisherSpringer Verlag
Number of pages7
ISBN (Print)3540424865, 9783540446682
StatePublished - 2001
EventInternational Conference on Artificial Neural Networks, ICANN 2001 - Vienna, Austria
Duration: 21 Aug 200125 Aug 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Artificial Neural Networks, ICANN 2001


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