IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i11d10.1007_s11192-022-04358-x.html
   My bibliography  Save this article

Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection

Author

Listed:
  • Arash Hajikhani

    (VTT Technical Research Centre of Finland)

  • Arho Suominen

    (VTT Technical Research Centre of Finland
    Tampere University)

Abstract

The sustainable development goals (SDGs) are a blueprint for achieving a better and more sustainable future for all by defining priorities and aspirations for 2030. This paper attempts to expand on the United Nations SDGs definition by leveraging the interrelationship between science and technology. We utilize SDG classification of scientific publications to compile a machine learning (ML) model to classify the SDG relevancy in patent documents, used as a proxy of technology development. The ML model was used to classify a sample of patent families registered in the European Patent Office (EPO). The analysis revealed the extent to which SDGs were addressed in patents. We also performed a case study to identify the offered extension of ML model detection regarding the SDG orientation of patents. In response to global goals and sustainable development initiatives, the findings can advance the identification challenges of science and technology artefacts. Furthermore, we offer input towards the alignment of R&D efforts and patenting strategies as well as measurement and management of their contribution to the realization of SDGs.

Suggested Citation

  • Arash Hajikhani & Arho Suominen, 2022. "Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6661-6693, November.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:11:d:10.1007_s11192-022-04358-x
    DOI: 10.1007/s11192-022-04358-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04358-x
    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/s11192-022-04358-x?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Maarten Hajer & Måns Nilsson & Kate Raworth & Peter Bakker & Frans Berkhout & Yvo De Boer & Johan Rockström & Kathrin Ludwig & Marcel Kok, 2015. "Beyond Cockpit-ism: Four Insights to Enhance the Transformative Potential of the Sustainable Development Goals," Sustainability, MDPI, vol. 7(2), pages 1-10, February.
    2. Anders Hayden, 2021. "From Fantasy to Transformation: Steps in the Policy Use of “Beyond-GDP” Indicators," Springer Books, in: Éloi Laurent (ed.), The Well-being Transition, chapter 0, pages 119-139, Springer.
    3. Tobias Mistele & Tom Price & Sabine Hossenfelder, 2019. "Predicting authors’ citation counts and h-indices with a neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 87-104, July.
    4. Florian Kreuchauff & Vladimir Korzinov, 2017. "A patent search strategy based on machine learning for the emerging field of service robotics," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 743-772, May.
    5. Patrick Kenekayoro & Kevan Buckley & Mike Thelwall, 2015. "Clustering research group website homepages," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2023-2039, March.
    6. Olivier E. Malay, 2021. "How to Articulate Beyond GDP and Businesses’ Social and Environmental Indicators?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 1-25, May.
    7. Changyong Lee & Gyumin Lee, 2019. "Technology opportunity analysis based on recombinant search: patent landscape analysis for idea generation," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 603-632, November.
    8. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    9. Yonghe Lu & Xin Xiong & Weiting Zhang & Jiaxin Liu & Ruijie Zhao, 2020. "Research on classification and similarity of patent citation based on deep learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 813-839, May.
    10. Samira Ranaei & Arho Suominen & Alan Porter & Stephen Carley, 2020. "Evaluating technological emergence using text analytics: two case technologies and three approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 215-247, January.
    11. Byungun Yoon & Sungjoo Lee & Gwanghee Lee, 2010. "Development and application of a keyword-based knowledge map for effective R&D planning," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 803-820, December.
    12. Malay, Olivier E., 2019. "Do Beyond GDP indicators initiated by powerful stakeholders have a transformative potential?," Ecological Economics, Elsevier, vol. 162(C), pages 100-107.
    13. Yu-Shan Chen & Ke-Chiun Chang, 2010. "Analyzing the nonlinear effects of firm size, profitability, and employee productivity on patent citations of the US pharmaceutical companies by using artificial neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 75-82, January.
    14. Paul Schreyer, 2021. "Framing Measurement Beyond GDP," CEPA Working Papers Series WP172021, School of Economics, University of Queensland, Australia.
    15. Campbell, Richard S., 1983. "Patent trends as a technological forecasting tool," World Patent Information, Elsevier, vol. 5(3), pages 137-143.
    16. Chyi-Kwei Yau & Alan Porter & Nils Newman & Arho Suominen, 2014. "Clustering scientific documents with topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 767-786, September.
    17. Sinha, Avik & Sengupta, Tuhin & Alvarado, Rafael, 2020. "Interplay between Technological Innovation and Environmental Quality: Formulating the SDG Policies for Next 11 Economies," MPRA Paper 104247, University Library of Munich, Germany, revised 2020.
    18. Fukuda, Kayano, 2020. "Science, technology and innovation ecosystem transformation toward society 5.0," International Journal of Production Economics, Elsevier, vol. 220(C).
    19. Nora Altgilbers & Lothar Walter & Martin G. Moehrle, 2020. "Frugal Invention Candidates As Antecedents Of Frugal Patents — The Role Of Frugal Attributes Analysed In The Medical Engineering Technology," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(06), pages 1-23, August.
    20. United Nations UN, 2015. "Transforming our World: the 2030 Agenda for Sustainable Development," Working Papers id:7559, eSocialSciences.
    21. Hartmann, Jochen & Huppertz, Juliana & Schamp, Christina & Heitmann, Mark, 2019. "Comparing automated text classification methods," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 20-38.
    22. Ronald Vatananan-Thesenvitz & Amaury-Alexandre Schaller & Randall Shannon, 2019. "A Bibliometric Review of the Knowledge Base for Innovation in Sustainable Development," Sustainability, MDPI, vol. 11(20), pages 1-22, October.
    23. Ivan Haščič & Mauro Migotto, 2015. "Measuring environmental innovation using patent data," OECD Environment Working Papers 89, OECD Publishing.
    24. Kahn, Kenneth B., 2018. "Understanding innovation," Business Horizons, Elsevier, vol. 61(3), pages 453-460.
    25. Pavitt, Keith, 1991. "What makes basic research economically useful?," Research Policy, Elsevier, vol. 20(2), pages 109-119, April.
    26. Schot, Johan & Steinmueller, W. Edward, 2018. "Three frames for innovation policy: R&D, systems of innovation and transformative change," Research Policy, Elsevier, vol. 47(9), pages 1554-1567.
    27. C. Freeman, 2004. "Technological infrastructure and international competitiveness," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(3), pages 541-569, June.
    28. Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
    29. Nicholas A. Ashford & Ralph P. Hall, 2011. "The Importance of Regulation-Induced Innovation for Sustainable Development," Sustainability, MDPI, vol. 3(1), pages 1-23, January.
    30. Dosi, Giovanni & Llerena, Patrick & Labini, Mauro Sylos, 2006. "The relationships between science, technologies and their industrial exploitation: An illustration through the myths and realities of the so-called `European Paradox'," Research Policy, Elsevier, vol. 35(10), pages 1450-1464, December.
    31. Patrick Kenekayoro, 2018. "Identifying named entities in academic biographies with supervised learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 751-765, August.
    32. Luuk Klomp & George Van Leeuwen, 2001. "Linking Innovation and Firm Performance: A New Approach," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 8(3), pages 343-364.
    33. Mingyang Wang & Zhenyu Wang & Guangsheng Chen, 2019. "Which can better predict the future success of articles? Bibliometric indices or alternative metrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1575-1595, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yi Zhang & Chengzhi Zhang & Philipp Mayr & Arho Suominen, 2022. "An editorial of “AI + informetrics”: multi-disciplinary interactions in the era of big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6503-6507, November.
    2. Percia David, Dimitri & Maréchal, Loïc & Lacube, William & Gillard, Sébastien & Tsesmelis, Michael & Maillart, Thomas & Mermoud, Alain, 2023. "Measuring security development in information technologies: A scientometric framework using arXiv e-prints," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

    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. Švarc, Jadranka & Dabić, Marina, 2021. "Transformative innovation policy or how to escape peripheral policy paradox in European research peripheral countries," Technology in Society, Elsevier, vol. 67(C).
    2. Hans Pohl, 2021. "Internationalisation, innovation, and academic–corporate co-publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1329-1358, February.
    3. Jaros³aw Brodny & Magdalena Tutak, 2023. "The level of implementing sustainable development goal "Industry, innovation and infrastructure" of Agenda 2030 in the European Union countries: Application of MCDM methods," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 47-102, March.
    4. Chiara Mio & Silvia Panfilo & Benedetta Blundo, 2020. "Sustainable development goals and the strategic role of business: A systematic literature review," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3220-3245, December.
    5. Castellacci, Fulvio & Natera, Jose Miguel, 2013. "The dynamics of national innovation systems: A panel cointegration analysis of the coevolution between innovative capability and absorptive capacity," Research Policy, Elsevier, vol. 42(3), pages 579-594.
    6. Li, Yanfei & Ji, Qiang & Zhang, Dayong, 2020. "Technological catching up and innovation policies in China: What is behind this largely successful story?," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    7. Filiou, Despoina & Kesidou, Effie & Wu, Lichao, 2023. "Are smart cities green? The role of environmental and digital policies for Eco-innovation in China," World Development, Elsevier, vol. 165(C).
    8. Oier Imaz & Andoni Eizagirre, 2020. "Responsible Innovation for Sustainable Development Goals in Business: An Agenda for Cooperative Firms," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    9. Lukas D. Filser & Fábio Francisco Silva & Otávio José Oliveira, 2017. "State of research and future research tendencies in lean healthcare: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 799-816, August.
    10. Jan Anton van Zanten & Rob van Tulder, 2020. "Beyond COVID-19: Applying “SDG logics” for resilient transformations," Journal of International Business Policy, Palgrave Macmillan, vol. 3(4), pages 451-464, December.
    11. Olivier E. Malay, 2021. "How to Articulate Beyond GDP and Businesses’ Social and Environmental Indicators?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 1-25, May.
    12. Tobias Wendler, 2019. "About the Relationship Between Green Technology and Material Usage," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 1383-1423, November.
    13. Most Asikha Aktar & Mukaramah Binti & Md. Mahmudul Alam, 2020. "Science, Technology and Innovation (STI) Policy for Sustainable Development," Post-Print hal-03519872, HAL.
    14. Friedrich, Christoph & Feser, Daniel, 2021. "Combining knowledge bases for system innovation in regions: Insights from an East German case study," University of Göttingen Working Papers in Economics 430, University of Goettingen, Department of Economics.
    15. Emilio Abad-Segura & Ana Batlles-delaFuente & Mariana-Daniela González-Zamar & Luis Jesús Belmonte-Ureña, 2021. "Implications for Sustainability of the Joint Application of Bioeconomy and Circular Economy: A Worldwide Trend Study," Sustainability, MDPI, vol. 13(13), pages 1-24, June.
    16. Béné, Christophe, 2022. "Why the Great Food Transformation may not happen – A deep-dive into our food systems’ political economy, controversies and politics of evidence," World Development, Elsevier, vol. 154(C).
    17. Simon Gwara & Edilegnaw Wale & Alfred Odindo & Chris Buckley, 2021. "Attitudes and Perceptions on the Agricultural Use of Human Excreta and Human Excreta Derived Materials: A Scoping Review," Agriculture, MDPI, vol. 11(2), pages 1-30, February.
    18. Iris Wanzenböck & Joeri H Wesseling & Koen Frenken & Marko P Hekkert & K Matthias Weber, 0. "A framework for mission-oriented innovation policy: Alternative pathways through the problem–solution space," Science and Public Policy, Oxford University Press, vol. 47(4), pages 474-489.
    19. Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
    20. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.

    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:scient:v:127:y:2022:i:11:d:10.1007_s11192-022-04358-x. 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.