Journal of Intelligent Information Systems

, Volume 50, Issue 2, pp 341–362 | Cite as

Case-based decision model matches ideal point model:

Application to marketing decision support system


This paper studies the relationship between a case-based decision theory (CBDT) and an ideal point model (IPM). We show that a case-based decision model (CBDM) can be transformed into an IPM under some assumptions. This transformation can allow us to visualize the relationship among data and simplify the calculations of distance between one current datum and the ideal point, rather than the distances between data. Our results will assist researchers with their product design analysis and positioning of goods through CBDT, by revealing past dependences or providing a reference point. Furthermore, to check whether the similarity function, presented in the theoretical part, is valid for empirical analysis, we use data on the viewing behavior of audiences of TV dramas in Japan and compare the estimation results under the CBDM that corresponds to a standard decision model with similarities and other various similarity functions and without a similarity function. Our empirical analysis shows that the CBDM with a similarity function, presented in this study, best fits the data.


Case-based decision theory Ideal point model Visualization Similarity function Marketing strategy Decision support system 


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Faculty of EconomicsOkinawa International UniversityGinowan CityJapan
  2. 2.Institute of Social Sciences, College of Humanities and Social Sciences, Academic AssemblyShinshu UniversityNaganoJapan

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