IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v59y2025i1d10.1007_s11135-024-01982-y.html
   My bibliography  Save this article

Cross-country analysis of science, technology and innovation policies: non-covid-19 related and Covid-19 specific STI policies in OECD countries

Author

Listed:
  • Margherita Russo

    (Università di Modena e Reggio Emilia)

  • Pasquale Pavone

    (Università di Modena e Reggio Emilia)

  • Dirk Meissner

    (National Research University Higher School of Economics, Russian Federation)

  • Fabrizio Alboni

    (Università di Bologna)

Abstract

In OECD countries, Science, Technology and Innovation (STI) policies were seen as key aspects of coping with the Covid-19 pandemic. Now that the pandemic is over, identifying which policy mix portfolios characterised countries in terms of their non-Covid-19 related and Covid-19 specific STI policies fills a knowledge gap on changes in STI policies induced by exogenous shocks. The descriptive nature of this exercise sheds light on the emergency phase, which was addressed in different ways by countries with similar STI policy portfolios in the last decade before the pandemic. Using information on STI policy initiatives in OECD countries, this paper proposes a multidimensional analysis to classify policy initiatives based on both codes (of innovation policy themes, policy instruments and target beneficiaries) and free text policies’ descriptions. Based on text mining and clustering techniques, the multidimensional analysis highlights semantic similarities between the combinations of codes and terms, making it possible to identify policy mixes that characterise non-Covid-19 related and Covid-19 specific STI policies. The cross-country comparison draws attention to the specific policy mix portfolios implemented by countries during the pandemic. The paper contributes to the literature on innovation policy mix in terms of research methods and results in identifying STI policy portfolios and groups of countries with similar structural composition of their innovation policy portfolios, implementing a range of STI strategies in tackling the pandemic. Policy implications of the findings are discussed, with a forward-looking perspective for the analysis of post-pandemic STI policies.

Suggested Citation

  • Margherita Russo & Pasquale Pavone & Dirk Meissner & Fabrizio Alboni, 2025. "Cross-country analysis of science, technology and innovation policies: non-covid-19 related and Covid-19 specific STI policies in OECD countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 343-367, February.
  • Handle: RePEc:spr:qualqt:v:59:y:2025:i:1:d:10.1007_s11135-024-01982-y
    DOI: 10.1007/s11135-024-01982-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-024-01982-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11135-024-01982-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Howoldt, David, 2024. "Characterising innovation policy mixes in innovation systems," Research Policy, Elsevier, vol. 53(2).
    2. Dirk Meissner & Sandrine Kergroach, 2021. "Correction to: Innovation policy mix: mapping and measurement," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1705-1705, October.
    3. Barry Bozeman, 2022. "Use of science in public policy: Lessons from the COVID-19 pandemic efforts to ‘Follow the Science’ [Health-protective Behaviour, Social Media Usage and Conspiracy Belief during the COVID-19 Public," Science and Public Policy, Oxford University Press, vol. 49(5), pages 806-817.
    4. Fabrizio Alboni & Pasquale Pavone & Margherita Russo, 2023. "The search for topics related to electric mobility: a comparative analysis of some of the most widely used methods in the literature," METRON, Springer;Sapienza Università di Roma, vol. 81(3), pages 367-391, December.
    5. Russo, Margherita & Pavone, Pasquale, 2021. "Evidence-based portfolios of innovation policy mixes: A cross-country analysis," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    6. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bolívar, Fernando & Duran, Miguel A. & Lozano-Vivas, Ana, 2023. "Bank business models, size, and profitability," Finance Research Letters, Elsevier, vol. 53(C).
    2. Reder, Maik & Yürüşen, Nurseda Y. & Melero, Julio J., 2018. "Data-driven learning framework for associating weather conditions and wind turbine failures," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 554-569.
    3. Marcin Gąsior, 2021. "Environmental Attitudes and Willingness to Purchase Online—Classification Approach," Sustainability, MDPI, vol. 13(15), pages 1-17, August.
    4. Dirk Czarnitzki & Malte Prüfer, 2024. "The Interplay between Public Procurement of Innovation and R&D Grants: Empirical Evidence from Belgium," Working Papers of ECOOM - Centre for Research and Development Monitoring 746875, KU Leuven, Faculty of Economics and Business (FEB), ECOOM - Centre for Research and Development Monitoring.
    5. Roopam Shukla & Ankit Agarwal & Kamna Sachdeva & Juergen Kurths & P. K. Joshi, 2019. "Climate change perception: an analysis of climate change and risk perceptions among farmer types of Indian Western Himalayas," Climatic Change, Springer, vol. 152(1), pages 103-119, January.
    6. Saemi Shin & Won Suck Yoon & Sang-Hoon Byeon, 2022. "Trends in Occupational Infectious Diseases in South Korea and Classification of Industries According to the Risk of Biological Hazards Using K-Means Clustering," IJERPH, MDPI, vol. 19(19), pages 1-19, September.
    7. Igor Kravchuk & Viktoriia Stoika, 2021. "Business Μodels of Βanks for the Financial Markets in the EU," European Research Studies Journal, European Research Studies Journal, vol. 0(2 - Part ), pages 371-382.
    8. Tea Petrin & Dragana Radicic, 2023. "Instrument policy mix and firm size: is there complementarity between R&D subsidies and R&D tax credits?," The Journal of Technology Transfer, Springer, vol. 48(1), pages 181-215, February.
    9. Song He & Xinyu Song & Xiaoxi Yang & Jijun Yu & Yuqi Wen & Lianlian Wu & Bowei Yan & Jiannan Feng & Xiaochen Bo, 2021. "COMSUC: A web server for the identification of consensus molecular subtypes of cancer based on multiple methods and multi-omics data," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-10, March.
    10. repec:osf:socarx:nftv3_v1 is not listed on IDEAS
    11. Jihane El Ouadi & Hanae Errousso & Nicolas Malhene & Siham Benhadou & Hicham Medromi, 2022. "A machine-learning based hybrid algorithm for strategic location of urban bundling hubs to support shared public transport," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3215-3258, October.
    12. Cyril Atkinson-Clement & Eléonore Pigalle, 2021. "What can we learn from Covid-19 pandemic’s impact on human behaviour? The case of France’s lockdown," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    13. Chuyuan Lin & Ying Yu & Lucas Y. Wu & Jiguo Cao, 2023. "Unsupervised learning on U.S. weather forecast performance," Computational Statistics, Springer, vol. 38(3), pages 1193-1213, September.
    14. Kreitmair, Ursula & Bower-Bir, Jacob, 2021. "Too different to solve climate change? Experimental evidence on the effects of production and benefit heterogeneity on collective action," Ecological Economics, Elsevier, vol. 184(C).
    15. Getaneh Addis Tessema & Jan van der Borg & Anton Van Rompaey & Steven Van Passel & Enyew Adgo & Amare Sewnet Minale & Kerebih Asrese & Amaury Frankl & Jean Poesen, 2022. "Benefit Segmentation of Tourists to Geosites and Its Implications for Sustainable Development of Geotourism in the Southern Lake Tana Region, Ethiopia," Sustainability, MDPI, vol. 14(6), pages 1-25, March.
    16. Wu, Tong & Rocha, Juan C. & Berry, Kevin & Chaigneau, Tomas & Hamann, Maike & Lindkvist, Emilie & Qiu, Jiangxiao & Schill, Caroline & Shepon, Alon & Crépin, Anne-Sophie & Folke, Carl, 2024. "Triple Bottom Line or Trilemma? Global Tradeoffs Between Prosperity, Inequality, and the Environment," World Development, Elsevier, vol. 178(C).
    17. Bita Mashayekhi & Kaveh Asiaei & Zabihollah Rezaee & Amin Jahangard & Milad Samavat & Saeid Homayoun, 2024. "The relative importance of ESG pillars: A two‐step machine learning and analytical framework," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(5), pages 5404-5420, October.
    18. Petricli, Gulcan & Inkaya, Tulin & Gokay Emel, Gul, 2024. "Identifying green citizen typologies by mining household-level survey data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    19. Young Hyun Kim & Kug Jin Jeon & Chena Lee & Yoon Joo Choi & Hoi-In Jung & Sang-Sun Han, 2021. "Analysis of the mandibular canal course using unsupervised machine learning algorithm," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-13, November.
    20. Stephanie Nguyen & Daisy Bertrand & Sylvie Llosa & Mathieu Alemany Oliver, 2025. "Exploring Bypass Practices on Sharing Platforms: A Typology of Users Who Bypass and Those Who Don’t," Journal of Business Ethics, Springer, vol. 199(2), pages 453-479, June.
    21. Turati, Pietro & Pedroni, Nicola & Zio, Enrico, 2017. "Simulation-based exploration of high-dimensional system models for identifying unexpected events," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 317-330.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:59:y:2025:i:1:d:10.1007_s11135-024-01982-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.