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Trend monitoring for linking science and strategy

Scientometrics volume 111, pages 2059–2075 (2017)Cite this article

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.

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Acknowledgements

The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5-100’.

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Authors and Affiliations

  1. Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics, Moscow, Russian Federation

    Pavel Bakhtin, Ozcan Saritas, Alexander Chulok, Ilya Kuzminov & Anton Timofeev

Authors
  1. Pavel Bakhtin
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  2. Ozcan Saritas
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  3. Alexander Chulok
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  4. Ilya Kuzminov
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  5. Anton Timofeev
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Correspondence to Ozcan Saritas.

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Bakhtin, P., Saritas, O., Chulok, A. et al. Trend monitoring for linking science and strategy. Scientometrics 111, 2059–2075 (2017). https://doi.org/10.1007/s11192-017-2347-5

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  • DOI: https://doi.org/10.1007/s11192-017-2347-5

Keywords

  • Science and strategy
  • Science push
  • Strategy pull
  • Text mining
  • Tech mining
  • Trend analysis
  • Semantic similarity
  • Foresight
  • Agriculture and food sector