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Trend monitoring for linking science and strategy

Author

Listed:
  • Pavel Bakhtin

    (National Research University Higher School of Economics)

  • Ozcan Saritas

    (National Research University Higher School of Economics)

  • Alexander Chulok

    (National Research University Higher School of Economics)

  • Ilya Kuzminov

    (National Research University Higher School of Economics)

  • Anton Timofeev

    (National Research University Higher School of Economics)

Abstract

Rapid changes in Science & Technology (S&T) along with breakthroughs in products and services concern a great deal of policy and strategy makers and lead to an ever increasing number of Foresight and other types of forward-looking work. At the outset, the purpose of these efforts is to investigate emerging S&T areas, set priorities and inform policies and strategies. However, there is still no clear evidence on the mutual linkage between science and strategy, which may be attributed to Foresight and S&T policy making activities. The present paper attempts to test the hypothesis that both science and strategy affect each other and this linkage can be investigated quantitatively. The evidence for the mutual attribution of science and strategy is built on a quantitative trend monitoring process drawing on semantic analysis of large amount of textual data and text mining tools. Based on the proposed methodology the similarities between science and strategy documents along with the overlaps between them across a certain period of time are calculated using the case of the Agriculture and Food sector, and thus the linkages between science and strategy are investigated.

Suggested Citation

  • Pavel Bakhtin & Ozcan Saritas & Alexander Chulok & Ilya Kuzminov & Anton Timofeev, 2017. "Trend monitoring for linking science and strategy," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 2059-2075, June.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2347-5
    DOI: 10.1007/s11192-017-2347-5
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    References listed on IDEAS

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    Cited by:

    1. Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Irina V. Loginova, 2018. "Detecting and Validating Global Technology Trends Using Quantitative and Expert-Based Foresight Techniques," HSE Working papers WP BRP 82/STI/2018, National Research University Higher School of Economics.
    2. Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Maxim Kotsemir & Alina Lavrynenko, 2018. "Mapping the Radical Innovations in Food Industry: A Text Mining Study," HSE Working papers WP BRP 80/STI/2018, National Research University Higher School of Economics.
    3. Sokolov, Alexander & Shashnov, Sergey & Kotsemir, Maxim & Grebenyuk, Anna, 2019. "Quantitative analysis for a better-focused international STI collaboration policy: A case of BRICS," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 221-242.
    4. Ozcan Saritas & Pavel Bakhtin & Ilya Kuzminov & Elena Khabirova, 2021. "Big data augmentated business trend identification: the case of mobile commerce," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1553-1579, February.
    5. Leonid Gokhberg & Dirk Meissner & Ilya Kuzminov, 2023. "What semantic analysis can tell us about long term trends in the global STI policy agenda," The Journal of Technology Transfer, Springer, vol. 48(6), pages 2249-2277, December.
    6. Cui Huang & Chao Yang & Jun Su, 2018. "Policy change analysis based on “policy target–policy instrument” patterns: a case study of China’s nuclear energy policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1081-1114, November.
    7. Ilya Kuzminov & Irina Loginova & Elena Khabirova, 2018. "Stress Scenario Development: Global Challenges For The Russian Agricultural Sector," HSE Working papers WP BRP 88/STI/2018, National Research University Higher School of Economics.

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