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Monitoring patterns of open innovation using the patent-based brokerage analysis

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  • Suh, Yongyoon
  • Jeon, Jeonghwan

Abstract

As the paradigm of open innovation continues to proliferate in both academia and practice especially for the last decade, many studies have attempted to investigate patterns of open innovation. However, empirical and quantitative approaches to monitoring the patterns of open innovation are less conducted because of the difficulty in data collection and the lack of effective methods. Also, it is difficult to identify the patterns of open innovation when there are many cases of open innovation in a wide range of technology areas. In this respect, this paper aims to quantitatively monitor the patterns of open innovation using the patent-based brokerage analysis in the case of mobile communications technology. Using patent citation information, the knowledge flow between technology fields and firms is identified, especially for structuring the open innovation network of 5G technology. Then, the patent-based brokerage analysis based on the open innovation network is conducted to extract brokerage patents that present the patterns of open innovation: inbound and outbound innovation. Furthermore, the brokerage firms are explored to recommend the partnerships in the open innovation network. According to the results, it is expected that “strategy for open innovation dynamics” is systematically formulated based on the brokerage patents and partners in various technology areas.

Suggested Citation

  • Suh, Yongyoon & Jeon, Jeonghwan, 2019. "Monitoring patterns of open innovation using the patent-based brokerage analysis," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 595-605.
    • Handle: RePEc:eee:tefoso:v:146:y:2019:i:c:p:595-605
    DOI: 10.1016/j.techfore.2018.01.037
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    References listed on IDEAS

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    1. Lee, Sungjoo & Park, Gwangman & Yoon, Byungun & Park, Jinwoo, 2010. "Open innovation in SMEs--An intermediated network model," Research Policy, Elsevier, vol. 39(2), pages 290-300, March.
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    4. Yun, JinHyo Joseph & Won, DongKyu & Jeong, EuiSeob & Park, KyungBae & Yang, JeongHo & Park, JiYoung, 2016. "The relationship between technology, business model, and market in autonomous car and intelligent robot industries," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 142-155.
    5. Martin Meyer, 2000. "Patent Citations in a Novel Field of Technology — What Can They Tell about Interactions between Emerging Communities of Science and Technology?," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(2), pages 151-178, September.
    6. Lee, Kyungpyo & Lee, Sungjoo, 2013. "Patterns of technological innovation and evolution in the energy sector: A patent-based approach," Energy Policy, Elsevier, vol. 59(C), pages 415-432.
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    Cited by:

    1. Zhang, Jingjing & Groen, Aard, 2021. "Informal and formal open activities: Innovation protection methods as antecedents and innovation outputs as consequences," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    2. Jugend, Daniel & Fiorini, Paula De Camargo & Armellini, Fabiano & Ferrari, Aline Gabriela, 2020. "Public support for innovation: A systematic review of the literature and implications for open innovation," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    3. SUN, Yu-tao & ZHANG, Chen & WANG, Jin-min, 2022. "How to Benefit from Balancing External Knowledge Acquisition? A Chinese EIT Industry Case," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
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    5. Jinhyo Joseph Yun & Zheng Liu & Euiseob Jeong & Sangwoo Kim & Kyunghun Kim, 2022. "The Difference in Open Innovation between Open Access and Closed Access, According to the Change of Collective Intelligence and Knowledge Amount," Sustainability, MDPI, vol. 14(5), pages 1-19, February.
    6. Alessandro Comai, 2020. "A new approach for detecting open innovation in patents: the designation of inventor," The Journal of Technology Transfer, Springer, vol. 45(6), pages 1797-1822, December.

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