Disaggregate Attribution Analysis on Web Advertising
| Project/Area Number |
16K03972
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Commerce
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| Research Institution | Gunma University (2018)
Nagasaki University (2016-2017) |
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Principal Investigator |
Takahashi Kei 群馬大学, 数理データ科学教育研究センター, 准教授 (70595280)
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| Research Collaborator |
Hirai Hirohide
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 広告効果 / 心理的効果 / ベイズ推定 / Web広告 / 逐次推定 / ベイジアンモデル / MCMC / 隠れマルコフモデル / 商学 / マーケティング / 広告 / ベイズ統計 |
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| Outline of Final Research Achievements |
This study develops a hidden Markov model that has hidden and discrete states of consumers' attitude for advertisement. In this model, we consider three psychological effects on advertisement, forgetting, wear-in and wear-out effects. We apply this model for data at the EC site. As a result of analysis, sign conditions on parameters in psychological effects. Additionally, we reveal that there exists little wear-in effects in this EC site data. Secondly, we conduct attribution analysis based on our model. Consequently, we get different attribute allocation from that without considering psychological effects.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，Webサイト等へのアクセス履歴データにより，従来集計的な把握に留まっていた心理的効果，具体的には忘却効果，刷込み効果，擦切れ効果について非集計的に存在を把握することができた．また，Web広告において多用されていたアフィリエイトやリターゲティング広告について，その広告を"踏んだ"ことによる離脱を考慮すると，最終目標への貢献度が低いことが分かった．
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Report
(4 results)
Research Products
(19 results)
