EBINA TAKESHI
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 Type | Another 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 |