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Innovation Trend and Case Studies Using Big Data Analysis (Japanese)

Listed author(s):
  • KINUKAWA Shinnya
  • TANAKA Tatsuo
  • NISHIO Koji
  • MOTOHASHI Kazuyuki

In this paper, we construct a conceptual framework to understand innovations using big data analysis. Using this framework, some quantitative trend analysis by applying the cases listed in "The Big Data Report" (Nikkei BP) was conducted. In addition, we selected representative cases from the list—Komatsu, Nihon-Chozai, and Lawson Innovation Laboratory—to conduct detailed case studies. We find that increasingly more firms use external datasets for their innovation, while the "open innovation" type— innovation by collaborating with external firms—does not increase over time. In addition, three-quarters of all cases are for increasing existing business efficiency, instead of creating new services. In order to facilitate big data innovation, the commitment of top management at firms is important. In addition, some policy implications are found in the areas of privacy and standardization of data transactions.

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Paper provided by Research Institute of Economy, Trade and Industry (RIETI) in its series Policy Discussion Papers (Japanese) with number 15015.

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Length: 25 pages
Date of creation: Oct 2015
Handle: RePEc:eti:rpdpjp:15015
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