Department   Undergraduate School  , School of Commerce
   Position   Professor
Language English
Publication Date 2021/12
Type Academic Journal
Peer Review Peer reviewed
Title "Applying the peak-end rule to decision-making regarding similar products: A case-based decision approach", Expert Systems
Contribution Type Co-authored (other than first author)
Journal Expert Systems
Journal TypeAnother Country
Publisher Wiley
Volume, Issue, Page 38(8),pp.e12763
Authorship Last author
Author and coauthor Keita Kinjo and Takeshi Ebina
Details This study proposes a marketing decision support system (DSS) for firms using case-based and peak-end approaches to model consumers. The proposed DSS is composed of model and estimation methods. We employ a similarity function used in case-based decision theory to examine the degree of similarity between the past and current products offered to a consumer. First, by extension, the proposed model could be utilized to analyse not only the same product but also multiple similar products. The DSS could be applied to a broad range of decision problems. Second, by extending the case-based decision model, our DSS considerably reduces the number of computational operations needed. Third, the model demonstrated the best fit among the compared models and possessed high prediction accuracy when analysing the viewing data for Japanese television dramas. The DSS could increase the future purchase probability of a product.
URL for researchmap https://researchmap.jp/ebinatakeshi2010