2004 Fiscal Year Final Research Report Summary
Marketing Models Utilizing Large Scale Data
| Project/Area Number |
14380191
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
社会システム工学
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| Research Institution | Keio University |
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Principal Investigator |
MORI Masao Keio University, Faculty of Science and Technology, Professor, 理工学部, 教授 (80016568)
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| Co-Investigator(Kenkyū-buntansha) |
OZAWA Masanori Keio University, Faculty of Science and Technology, Lecturer, 理工学部, 講師 (50152484)
YAJIMA Yasutoshi Tokyo Institute of Technology, Graduate School of Decision Science and Technology, Associate Professor, 大学院・社会理工学研究科, 助教授 (80231645)
IIDA Tetsuo Komazawa University, Faculty of Management, Associate Professor, 経営学部, 助教授 (20262305)
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| Project Period (FY) |
2002 – 2004
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| Keywords | Marketing Models / Sales Promotions / Multidimensional Unfolding Procedure / Basket Analysis / Latent Familiarities / Support Vector Machines / POS data / Huff Model |
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| Research Abstract |
Summing up our researches, we studied the following matters ;
1.Evaluation of Sales Promotion Activities :
Many retail stores and manufacturers are eager to know store-level price promotion effects and non-price promotion effects because each store has to decide store-specific marketing events.
First we propose a model to estimate the non-price promotion was generated by using scanner data. Second we study the price promotion of which item category produce largely effect on sales of each store.
2.Analysis of attractiveness of stores and/or goods through customers buying behavior.
3.Developments of tools for analyzing marketing models.
We obtain a new algorithm to solve large scale SVM problems and also study a validity checking procedure to utilize MDU (Multidimensional Unfolding Procedure) for scanner data over multi-categorical items.
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