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Machine learning methods for the market segmentation of the performing arts audiences

Author

Listed:
  • Maria M. Abad-Grau
  • Maria Tajtakova
  • Daniel Arias-Aranda

Abstract

The interaction of human experts with machine learning and data mining tools leads to improved results in decision-making support systems. In marketing decisions related to market segmentation, the use of only one technique does not guarantee an optimal solution, as such a solution may not even be achievable. In this paper, we analyse the market segmentation decisions in the performing arts through a combination of expert opinions and machine learning algorithms in order to obtain a consensual model that allows a better understanding of market preferences together with a deep knowledge about reliability in the obtained results. The results and data were applied to build a model of market segmentation of students based on their attendance in, attitudes towards, and intentions in attending opera and ballet performances.

Suggested Citation

  • Maria M. Abad-Grau & Maria Tajtakova & Daniel Arias-Aranda, 2009. "Machine learning methods for the market segmentation of the performing arts audiences," International Journal of Business Environment, Inderscience Enterprises Ltd, vol. 2(3), pages 356-375.
    • Handle: RePEc:ids:ijbenv:v:2:y:2009:i:3:p:356-375
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