EBINA TAKESHI    Department   Undergraduate School  , School of Commerce    Position   Professor
Language	English
Publication Date	2018/04
Type	Academic Journal
Peer Review	Peer reviewed
Title	"Case-Based Decision Model Matches Ideal Point Model: Application to Marketing Decision Support System", Journal of Intelligent Information Systems
Contribution Type	Co-authored (other than first author)
Journal	Journal of Intelligent Information Systems
Journal Type	Another Country
Publisher	Springer
Volume, Issue, Page	50(2),pp.341-362
Author and coauthor	Keita Kinjo and Takeshi Ebina
Details	This paper studies the relationship between a case-based decision theory (CBDT) and an ideal point model (IPM). We show 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, 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 the CBDM with a similarity function, presented in this study, best fits the data.