| Project/Area Number |
17K03659
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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 |
Economic statistics
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| Research Institution | Kobe University |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 技術分析 / 情報検索 / Data Science / 特許分析 / 検索技術 / 計量経済学 / データサイエンス |
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| Outline of Final Research Achievements |
In this research, 1) We developed a novel technological analysis framework by constructing the technological competitor retrieval system by aggregating over 100 million patents and about 50 million corresponding patenters, which enable to perform various technological analysis systematically, effectively, and efficiently, 2) Based on the technological competitor retrieval system, we developed a novel and the most comprehensive technological competitor analysis by searching for the most likely technological competitors, 3) we developed a novel approach of measuring technological competition based on the ranking results of competitors searched by technological competitor retrieval system.
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| Academic Significance and Societal Importance of the Research Achievements |
経済分析の分野ではあまり取り入れられていない、Data Science手法の１つである検索技術を、新たな応用経済学の技術・経済分析手法として紹介することで、学術的な貢献を行うことができた。
本研究で構築した類似技術企業検索システムやSystematicかつScalableな技術分析手法は、R&D戦略、M&A戦略、イノヴェーション伝播などのさまざまな分析に応用可能で、企業のみならず国家単位での技術分析への応用が期待できる。技術は経済と密接につながっているため、今後の技術と経済の関係を読み解くうえで包括的かつ客観的な分析手法として貢献できることが期待できる。
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