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A patent analysis method to trace technology evolutionary pathways

Author

Listed:
  • Xiao Zhou

    (School of Management and Economics, Beijing Institute of Technology)

  • Yi Zhang

    (School of Management and Economics, Beijing Institute of Technology)

  • Alan L. Porter

    (School of Public Policy, Georgia Institute of Technology)

  • Ying Guo

    (School of Management and Economics, Beijing Institute of Technology)

  • Donghua Zhu

    (School of Management and Economics, Beijing Institute of Technology)

Abstract

Increased competition due to rapid technological development pushes all participants in the market to focus on the prospect of New and Emerging Science & Technologies (NESTs). One promising NEST, dye-sensitized solar cells (DSSCs), has attracted attention in recent years. We focus on three research questions: how can we estimate DSSCs research activity trends; how can we identify DSSCs market expansion patterns; and, seeking to identify potential subsystems, what are the likely evolutionary paths of DSSCs development? In this paper, patent analysis is applied to help determine the developmental stage of a particular technology and trace its potential evolutionary pathways. In addition, since patent information can reflect commercial degree, we use patent transfer patterns to help evaluate market shift prospects.

Suggested Citation

  • Xiao Zhou & Yi Zhang & Alan L. Porter & Ying Guo & Donghua Zhu, 2014. "A patent analysis method to trace technology evolutionary pathways," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 705-721, September.
    • Handle: RePEc:spr:scient:v:100:y:2014:i:3:d:10.1007_s11192-014-1317-4
    DOI: 10.1007/s11192-014-1317-4
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    3. Junmo Kim & Juneseuk Shin, 2018. "Mapping extended technological trajectories: integration of main path, derivative paths, and technology junctures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1439-1459, September.
    4. Ting Zhang & Juan Chen & Xiaofeng Jia, 2015. "Identification of the Key Fields and Their Key Technical Points of Oncology by Patent Analysis," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-18, November.
    5. Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
    6. Zhang, Yi & Wu, Mengjia & Miao, Wen & Huang, Lu & Lu, Jie, 2021. "Bi-layer network analytics: A methodology for characterizing emerging general-purpose technologies," Journal of Informetrics, Elsevier, vol. 15(4).
    7. Zhang, Yi & Robinson, Douglas K.R. & Porter, Alan L. & Zhu, Donghua & Zhang, Guangquan & Lu, Jie, 2016. "Technology roadmapping for competitive technical intelligence," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 175-186.
    8. Wang, Xiaoli & Daim, Tugrul & Huang, Lucheng & Li, Zhiqiang & Shaikh, Ruqia & Kassi, Diby Francois, 2022. "Monitoring the development trend and competition status of high technologies using patent analysis and bibliographic coupling: The case of electronic design automation technology," Technology in Society, Elsevier, vol. 71(C).
    9. Munan Li, 2015. "A novel three-dimension perspective to explore technology evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1679-1697, December.
    10. Xuan Shi & Lingfei Cai & Hongfang Song, 2019. "Discovering Potential Technology Opportunities for Fuel Cell Vehicle Firms: A Multi-Level Patent Portfolio-Based Approach," Sustainability, MDPI, vol. 11(22), pages 1-22, November.
    11. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
    12. Huang, Ying & Porter, Alan L. & Zhang, Yi & Lian, Xiangpeng & Guo, Ying, 2019. "An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 831-843.

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