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Obtaining advantages from technology revolution: A patent roadmap for competition analysis and strategy planning

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  • Yu, Xiang
  • Zhang, Ben

Abstract

This paper aims to propose a new kind of patent roadmaps, including a roadmapping method and application directions. The patent roadmap is used to analyze patent competition and develop a patent strategy. In the patent roadmap, patent analysis, patent maps and a generic technology roadmap are used. By using these three methods in combination, two concepts, patent information and patent strategies, are linked. Further, the patent roadmap provides theoretical and informational support for companies, allowing them to learn about the current patent competition situation, and perform corresponding patent layout planning. Compared to previous research on technology and patent roadmaps, this study illustrates the patent competition situation in some industries, and provides a new method for patent strategy planning and its applications. In a case study, this paper presents the patent roadmap of the high-speed railway track (HSRT) industry, specifying the whole roadmapping process and an application in patent planning. Finally, conclusions are drawn that, in applications, the proposed patent roadmap not only plays an important role in helping companies to find new technology opportunities, avoiding duplicate R&D investments, preventing patent infringement risks, and so on, but also has important significance for guiding the overall industry development.

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  • Yu, Xiang & Zhang, Ben, 2019. "Obtaining advantages from technology revolution: A patent roadmap for competition analysis and strategy planning," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 273-283.
    • Handle: RePEc:eee:tefoso:v:145:y:2019:i:c:p:273-283
    DOI: 10.1016/j.techfore.2017.10.008
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    Cited by:

    1. Kim, Junhan & Geum, Youngjung, 2021. "How to develop data-driven technology roadmaps:The integration of topic modeling and link prediction," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    2. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    3. Hu, Gang-Gao, 2021. "Is knowledge spillover from human capital investment a catalyst for technological innovation? The curious case of fourth industrial revolution in BRICS economies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    4. Chih-Yi, Su & Bou-Wen, Lin, 2021. "Attack and defense in patent-based competition: A new paradigm of strategic decision-making in the era of the fourth industrial revolution," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    5. Nazarenko, Anastasia & Vishnevskiy, Konstantin & Meissner, Dirk & Daim, Tugrul, 2022. "Applying digital technologies in technology roadmapping to overcome individual biased assessments," Technovation, Elsevier, vol. 110(C).
    6. Wang, Chang & Geng, Hongjun & Sun, Rui & Song, Huiling, 2022. "Technological potential analysis and vacant technology forecasting in the graphene field based on the patent data mining," Resources Policy, Elsevier, vol. 77(C).
    7. Tikas, Gaurav Dilip, 2023. "Team innovation capability: Scale development and validation," Technovation, Elsevier, vol. 126(C).
    8. Puccetti, Giovanni & Giordano, Vito & Spada, Irene & Chiarello, Filippo & Fantoni, Gualtiero, 2023. "Technology identification from patent texts: A novel named entity recognition method," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

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