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Identifying new business opportunities from competitor intelligence: An integrated use of patent and trademark databases

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  • Lee, Mingook
  • Lee, Sungjoo

Abstract

This study aims to analyze the position of technology-centered companies in complex market dynamics and discover new business opportunities from competitor intelligence. For this, we consider both technology and market characteristics in providing competitor intelligence by utilizing patent data as a representative proxy for a firm's technology, and trademark data as an information source for the firm's target goods and services. To analyze the two types of data, a collaborative filtering approach together with portfolio analyses and association mining techniques were adopted. Theoretically, this is one of the earliest attempts to combine patent data and trademark data to investigate corporate strategies. In practice, the research results are expected to be used as a decision criterion to diagnose the economic value that companies can obtain by entering the market, as well as the technological value to be passed onto their customers. Thus, the proposed approach can be useful to support effective technology and business strategies in a firm.

Suggested Citation

  • Lee, Mingook & Lee, Sungjoo, 2017. "Identifying new business opportunities from competitor intelligence: An integrated use of patent and trademark databases," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 170-183.
    • Handle: RePEc:eee:tefoso:v:119:y:2017:i:c:p:170-183
    DOI: 10.1016/j.techfore.2017.03.026
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    Citations

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    Cited by:

    1. Jungpyo Lee & So Young Sohn, 2021. "Recommendation system for technology convergence opportunities based on self-supervised representation learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 1-25, January.
    2. Teng, Fei & Sun, Yuling & Chen, Fang & Qin, Aning & Zhang, Qi, 2021. "Technology opportunity discovery of proton exchange membrane fuel cells based on generative topographic mapping," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Anisur R. Faroque & Farhad Uddin Ahmed & Mahabubur Rahman & Mohammad Osman Gani & Sina Mortazavi, 2023. "Exploring the individual and joint effects of founders' and managers' experiential knowledge on international opportunity identification," Asian Business & Management, Palgrave Macmillan, vol. 22(4), pages 1274-1300, September.
    4. Motohashi, Kazuyuki & Zhu, Chen, 2023. "Identifying technology opportunity using dual-attention model and technology-market concordance matrix," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    5. Yougen Cao & Shengce Ren & Mei Du, 2022. "Strategic trademark management: a systematic literature review and prospects for future research," Journal of Brand Management, Palgrave Macmillan, vol. 29(5), pages 435-453, September.
    6. Yun, Siyeong & Song, Kisik & Kim, Chulhyun & Lee, Sungjoo, 2021. "From stones to jewellery: Investigating technology opportunities from expired patents," Technovation, Elsevier, vol. 103(C).
    7. Andersson, David E. & Ekman, Anton & Huila, Anton & Tell, Fredrik, 2023. "Industrial design rights and the market value of firms," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    8. Ioannis Anagnostopoulos & Anas Rizeq, 2021. "Conventional and neural network target‐matching methods dynamics: The information technology mergers and acquisitions market in the USA," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(2), pages 97-118, April.
    9. Kyungtae Kim & Sungjoo Lee, 2018. "How Can Big Data Complement Expert Analysis? A Value Chain Case Study," Sustainability, MDPI, vol. 10(3), pages 1-21, March.
    10. Ardito, Lorenzo & Ernst, Holger & Messeni Petruzzelli, Antonio, 2020. "The interplay between technology characteristics, R&D internationalisation, and new product introduction: Empirical evidence from the energy conservation sector," Technovation, Elsevier, vol. 96.
    11. Aaldering, Lukas Jan & Leker, Jens & Song, Chie Hoon, 2019. "Uncovering the dynamics of market convergence through M&A," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 95-114.
    12. Younghoon Lee, 2022. "Identifying Competitive Attributes Based on an Ensemble of Explainable Artificial Intelligence," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(4), pages 407-419, August.
    13. Wu, Yingwen & Ji, Yangjian, 2023. "Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining," Journal of Informetrics, Elsevier, vol. 17(2).
    14. Changyong Lee & Gyumin Lee, 2019. "Technology opportunity analysis based on recombinant search: patent landscape analysis for idea generation," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 603-632, November.
    15. Han, Xiaotong & Zhu, Donghua & Lei, Ming & Daim, Tugrul, 2021. "R&D trend analysis based on patent mining: An integrated use of patent applications and invalidation data," Technological Forecasting and Social Change, Elsevier, vol. 167(C).

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