| Project/Area Number |
18K12881
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 07090:Commerce-related
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| Research Institution | Hosei University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 分位点回帰 / マーケティング / マーケティング・リサーチ |
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| Outline of Final Research Achievements |
The purpose of this study is to understand consumers more deeply and to obtain suggestions for marketing strategies by applying quantile regression to marketing data. In the analysis using actual data, quantile regression was applied to the measurement of advertising effectiveness, the selection of effective marketing variables, and the causal model of customer satisfaction. In the application to the measurement of advertising effectiveness, there were cases in which advertisements that were judged to be ineffective in the ordinary regression analysis were found to be effective in the upper quartile. In the application to variable selection, it was shown that the variables selected as explanatory variables for the model differed depending on the quantile. In the application to the customer satisfaction model, the coefficients differed depending on the quantile, indicating that factors affecting customer satisfaction may differ between customers with high and low satisfaction levels.
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| Academic Significance and Societal Importance of the Research Achievements |
分位点回帰は経済学で広く応用されている分析方法で，目的変数の条件付き分位点を推定することができる。その有用性にもかかわらず，マーケティングではほとんど利用されていない。本研究では分位点回帰をマーケティングデータに適用することで対象を通常の回帰分析よりも詳細に理解した。同じマーケティング変数を受けていても購入数量が多い優良顧客を理解するはマーケティング施策の改善につながる。
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