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Discovering shifts in competitive strategies in probiotics, accelerated with TechMining

Author

Listed:
  • Jose M. Vicente-Gomila

    (Universitat Politècnica de València)

  • Anna Palli

    (IRTA Institut de Recerca Agroalimentária)

  • Begoña Calle

    (IRTA Institut de Recerca Agroalimentária)

  • Miguel A. Artacho

    (Universitat Politècnica de València)

  • Sara Jimenez

    (IRTA Institut de Recerca Agroalimentária)

Abstract

Profiling the technological strategy of different competitors is a key element for the companies in a given industry, as well to technology planners and R&D strategists. The analysis of the patent portfolio of a company as well as its evolution in the time line is of interest for technology analysts and decision makers. However, the need for the participation of experts in the field of a company as well as patent specialists, slows down the process. Bibliometrics and text mining techniques contribute to the interpretation of specialists. The present paper tries to offer a step by step procedure to analyze the technology strategy of several companies through the analysis of their portfolio claims, combined with the use of TechMining with the help of a text mining tool. The procedure, complemented with a semantic TRIZ analysis provides key insights in disclosing the technological analysis of some competitors in the field of probiotics for livestock health. The results show interesting shifts in the key probiotic and prebiotic ingredients for which companies claim protection and therefore offers clues about their technology intention in the life sciences industry in a more dynamic, convenient and simple way.

Suggested Citation

  • Jose M. Vicente-Gomila & Anna Palli & Begoña Calle & Miguel A. Artacho & Sara Jimenez, 2017. "Discovering shifts in competitive strategies in probiotics, accelerated with TechMining," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1907-1923, June.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2339-5
    DOI: 10.1007/s11192-017-2339-5
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    References listed on IDEAS

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    Cited by:

    1. Yang, Chao & Huang, Cui & Su, Jun, 2018. "An improved SAO network-based method for technology trend analysis: A case study of graphene," Journal of Informetrics, Elsevier, vol. 12(1), pages 271-286.
    2. 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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    More about this item

    Keywords

    Technology strategy; Bibliometrics; Animal health; Tech mining; Semantic TRIZ;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights

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