IDEAS home Printed from https://ideas.repec.org/a/gam/jecomi/v11y2023i8p207-d1209106.html
   My bibliography  Save this article

Invention in Times of Global Challenges: A Text-Based Study of Remote Sensing and Global Public Goods

Author

Listed:
  • Ingrid Ott

    (Chair of Economic Policy, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

  • Simone Vannuccini

    (Groupe de Recherche en Droit, Économie et Gestion (GREDEG) Université Côte d’Azur, Sophia Antipolis Cedex, 06410 Biot, France)

Abstract

We study whether remote sensing (RS), a set of technologies with global reach and a variety of applications, can be considered instrumental to the provision of global public goods (GPG). We exploit text information from patent data and apply structural topic modeling to identify topics related (or relevant) to GPG provision, and trace their participation in the evolution of remote sensing technology over time. We develop a new indicator of affinity to GPG (and other themes) using meta information from our dataset. We find that, first, RS displays features of a general-purpose technology. Second, while peripheral, GPG-relevant topics are present in the RS topic space, and in some cases overlap with topics with high affinity in AI and participation of public sector actors in invention. With our analysis, we contribute to a better understanding of the interplay between the dynamics of technology and (global) political economy, a field of research yet under-explored.

Suggested Citation

  • Ingrid Ott & Simone Vannuccini, 2023. "Invention in Times of Global Challenges: A Text-Based Study of Remote Sensing and Global Public Goods," Economies, MDPI, vol. 11(8), pages 1-24, August.
    • Handle: RePEc:gam:jecomi:v:11:y:2023:i:8:p:207-:d:1209106
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7099/11/8/207/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7099/11/8/207/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grid Thoma, 2009. "Striving for a large market: evidence from a general purpose technology in action," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 18(1), pages 107-138, February.
    2. Nelson, Richard R., 2003. "On the uneven evolution of human know-how," Research Policy, Elsevier, vol. 32(6), pages 909-922, June.
    3. Margaret E. Roberts & Brandon M. Stewart & Edoardo M. Airoldi, 2016. "A Model of Text for Experimentation in the Social Sciences," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 988-1003, July.
    4. Clifford Bekar & Kenneth Carlaw & Richard Lipsey, 2018. "General purpose technologies in theory, application and controversy: a review," Journal of Evolutionary Economics, Springer, vol. 28(5), pages 1005-1033, December.
    5. Inge Kaul, 2012. "Global Public Goods: Explaining their Underprovision," Journal of International Economic Law, Oxford University Press, vol. 15(3), pages 729-750, September.
    6. Edoardo M. Airoldi & Jonathan M. Bischof, 2016. "Improving and Evaluating Topic Models and Other Models of Text," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1381-1403, October.
    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. Camilla Salvatore & Silvia Biffignandi & Annamaria Bianchi, 2022. "Corporate Social Responsibility Activities Through Twitter: From Topic Model Analysis to Indexes Measuring Communication Characteristics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1217-1248, December.
    2. Dehler-Holland, Joris & Okoh, Marvin & Keles, Dogan, 2022. "Assessing technology legitimacy with topic models and sentiment analysis – The case of wind power in Germany," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    3. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    4. Simone Vannuccini & Ekaterina Prytkova, 2021. "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series 2021-02, SPRU - Science Policy Research Unit, University of Sussex Business School.
    5. Dehler-Holland, Joris & Schumacher, Kira & Fichtner, Wolf, 2021. "Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1).
    6. Carlos Mendez & Fernando Mendez & Vasiliki Triga & Juan Miguel Carrascosa, 2020. "EU Cohesion Policy under the Media Spotlight: Exploring Territorial and Temporal Patterns in News Coverage and Tone," Journal of Common Market Studies, Wiley Blackwell, vol. 58(4), pages 1034-1055, July.
    7. Valerio Astuti & Marta Crispino & Marco Langiulli & Juri Marcucci, 2022. "Textual analysis of a Twitter corpus during the COVID-19 pandemics," Questioni di Economia e Finanza (Occasional Papers) 692, Bank of Italy, Economic Research and International Relations Area.
    8. Nobuyuki Hanaki & Ali I. Ozkes, 2023. "Strategic environment effect and communication," Experimental Economics, Springer;Economic Science Association, vol. 26(3), pages 588-621, July.
    9. Davide Consoli & Pier Paolo Patrucco, 2011. "Complexity and the Coordination of Technological Knowledge: The Case of Innovation Platforms," Chapters, in: Handbook on the Economic Complexity of Technological Change, chapter 8 Edward Elgar Publishing.
    10. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.
    11. Battke, Benedikt & Schmidt, Tobias S. & Stollenwerk, Stephan & Hoffmann, Volker H., 2016. "Internal or external spillovers—Which kind of knowledge is more likely to flow within or across technologies," Research Policy, Elsevier, vol. 45(1), pages 27-41.
    12. Gambardella, Alfonso & Conti, Raffaele & Novelli, Elena, 2018. "Specializing in Generality: Firm Strategies When Intermediate Markets Work," CEPR Discussion Papers 12782, C.E.P.R. Discussion Papers.
    13. Marcel Fratzscher & Tobias Heidland & Lukas Menkhoff & Lucio Sarno & Maik Schmeling, 2023. "Foreign Exchange Intervention: A New Database," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(4), pages 852-884, December.
    14. Arthur Dyevre & Nicolas Lampach, 2021. "Issue attention on international courts: Evidence from the European Court of Justice," The Review of International Organizations, Springer, vol. 16(4), pages 793-815, October.
    15. Li Tang & Jennifer Kuzma & Xi Zhang & Xinyu Song & Yin Li & Hongxu Liu & Guangyuan Hu, 2023. "Synthetic biology and governance research in China: a 40-year evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5293-5310, September.
    16. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    17. Symitsi, Efthymia & Stamolampros, Panagiotis & Daskalakis, George & Korfiatis, Nikolaos, 2021. "The informational value of employee online reviews," European Journal of Operational Research, Elsevier, vol. 288(2), pages 605-619.
    18. Ramlogan, Ronnie & Consoli, Davide, 2007. "Knowledge, Understanding and the Dynamics of Medical Innovation," European Journal of Economic and Social Systems, Lavoisier, vol. 20(2), pages 231-249.
    19. Nelson, John P., 2023. "Differential “progressibility” in human know-how: A conceptual overview," Research Policy, Elsevier, vol. 52(2).
    20. Lehrer, Mark & Banerjee, Preeta M. & Wang, I. Kim, 2017. "When the sky is the limit on scale: From temporal to multiplicative scaling in process-based technologies," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 151-159.

    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:gam:jecomi:v:11:y:2023:i:8:p:207-:d:1209106. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.