IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v129y2024i9d10.1007_s11192-024-05126-9.html
   My bibliography  Save this article

Does science disrupt technology? Examining science intensity, novelty, and recency through patent-paper citations in the pharmaceutical field

Author

Listed:
  • Keye Wu

    (Nanjing University
    Nanjing University)

  • Ziyue Xie

    (Nanjing University
    Charles Sturt University)

  • Jia Tina Du

    (Charles Sturt University
    University of South Australia)

Abstract

The role of scientific knowledge in advancing technology is widely recognized, but its impact in generating disruptive ideas and catalyzing technological change is less well known. To fill this gap, this study addresses a new research question about whether and how prior scientific knowledge contributes to technological disruptiveness. Specifically, our study focused on the pharmaceutical field, which has a frequent interaction between science and technology, and employed the patent-paper citations to explore the disruptive impact of science on technology. Drawing on the 1,883,593 granted patents in pharmaceuticals and their 1,546,960 cited papers prior to 2018, we found patents with scientific references appear to be more disruptive than those without scientific citations and such effect has gradually pronounced in recent decades, even though technological disruptiveness is generally declining over time. For each granted patent, we further developed three scientific characteristics including science intensity, science novelty and science recency and estimated their effects on technological disruptiveness. The regression analysis showed science intensity and science novelty both have an inverted U-shaped relationship with technological disruptiveness, suggesting intermediate-level novel scientific knowledge input can inspire the generation of disruptive ideas for pharmaceutical technological innovation. While science recency presents a negative association, underlying that recent scientific knowledge could offer advanced theoretical insights that may destabilize the existing technological trajectory. Moreover, collaboration is another important factor in enhancing the disruptive impact of science on technology. Our study contributes to the existing literature by introducing the disruptive impact of science on technology.

Suggested Citation

  • Keye Wu & Ziyue Xie & Jia Tina Du, 2024. "Does science disrupt technology? Examining science intensity, novelty, and recency through patent-paper citations in the pharmaceutical field," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5469-5491, September.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:9:d:10.1007_s11192-024-05126-9
    DOI: 10.1007/s11192-024-05126-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-024-05126-9
    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/s11192-024-05126-9?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. Michael J. Stringer & Marta Sales‐Pardo & Luís A. Nunes Amaral, 2010. "Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(7), pages 1377-1385, July.
    2. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
    3. Rodrigo Costas & Thed N. Leeuwen & María Bordons, 2012. "Referencing patterns of individual researchers: Do top scientists rely on more extensive information sources?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2433-2450, December.
    4. Ebadi, Ashkan & Auger, Alain & Gauthier, Yvan, 2022. "Detecting emerging technologies and their evolution using deep learning and weak signal analysis," Journal of Informetrics, Elsevier, vol. 16(4).
    5. Robert J. W. Tijssen & Jos Winnink, 2016. "Twenty-first century macro-trends in the institutional fabric of science: bibliometric monitoring and analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2181-2194, December.
    6. Messeni Petruzzelli, Antonio & Ardito, Lorenzo & Savino, Tommaso, 2018. "Maturity of knowledge inputs and innovation value: The moderating effect of firm age and size," Journal of Business Research, Elsevier, vol. 86(C), pages 190-201.
    7. Wang, Jian & Veugelers, Reinhilde & Stephan, Paula, 2017. "Bias against novelty in science: A cautionary tale for users of bibliometric indicators," Research Policy, Elsevier, vol. 46(8), pages 1416-1436.
    8. Rodrigo Costas & Thed N. van Leeuwen & Anthony F.J. van Raan, 2010. "Is scientific literature subject to a ‘Sell-By-Date’? A general methodology to analyze the ‘durability’ of scientific documents," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(2), pages 329-339, February.
    9. Bruno Cassiman & Reinhilde Veugelers & Pluvia Zuniga, 2008. "In search of performance effects of (in)direct industry science links," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 17(4), pages 611-646, August.
    10. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    11. Michael Park & Erin Leahey & Russell J. Funk, 2023. "Papers and patents are becoming less disruptive over time," Nature, Nature, vol. 613(7942), pages 138-144, January.
    12. Lutz Bornmann & Sitaram Devarakonda & Alexander Tekles & George Chacko, 2020. "Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019)," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1149-1155, May.
    13. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2012. "Referencing patterns of individual researchers: Do top scientists rely on more extensive information sources?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2433-2450, December.
    14. Veugelers, Reinhilde & Wang, Jian, 2019. "Scientific novelty and technological impact," Research Policy, Elsevier, vol. 48(6), pages 1362-1372.
    15. Schoenmakers, Wilfred & Duysters, Geert, 2010. "The technological origins of radical inventions," Research Policy, Elsevier, vol. 39(8), pages 1051-1059, October.
    16. Hohberger, Jan, 2016. "Diffusion of science-based inventions," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 66-77.
    17. John-Paul Ferguson & Gianluca Carnabuci, 2017. "Risky Recombinations: Institutional Gatekeeping in the Innovation Process," Organization Science, INFORMS, vol. 28(1), pages 133-151, February.
    18. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    19. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    20. Lee Fleming & Olav Sorenson, 2004. "Science as a map in technological search," Strategic Management Journal, Wiley Blackwell, vol. 25(8‐9), pages 909-928, August.
    21. Ke, Qing, 2020. "Technological impact of biomedical research: The role of basicness and novelty," Research Policy, Elsevier, vol. 49(7).
    22. Michael J. Stringer & Marta Sales-Pardo & Luís A. Nunes Amaral, 2010. "Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1377-1385, July.
    23. Pezzoni, Michele & Veugelers, Reinhilde & Visentin, Fabiana, 2022. "How fast is this novel technology going to be a hit? Antecedents predicting follow-on inventions," Research Policy, Elsevier, vol. 51(3).
    24. Arthur, W. Brian, 2007. "The structure of invention," Research Policy, Elsevier, vol. 36(2), pages 274-287, March.
    25. Ugo Finardi, 2011. "Time relations between scientific production and patenting of knowledge: the case of nanotechnologies," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 37-50, October.
    26. Atul Nerkar, 2003. "Old Is Gold? The Value of Temporal Exploration in the Creation of New Knowledge," Management Science, INFORMS, vol. 49(2), pages 211-229, February.
    27. Toole, Andrew A., 2012. "The impact of public basic research on industrial innovation: Evidence from the pharmaceutical industry," Research Policy, Elsevier, vol. 41(1), pages 1-12.
    28. Anthony F. J. Raan & Jos J. Winnink, 2018. "Do younger Sleeping Beauties prefer a technological prince?," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 701-717, February.
    29. Lutz Bornmann & Alexander Tekles, 2019. "Disruptive papers published in Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 331-336, July.
    30. Breschi, Stefano & Catalini, Christian, 2010. "Tracing the links between science and technology: An exploratory analysis of scientists' and inventors' networks," Research Policy, Elsevier, vol. 39(1), pages 14-26, February.
    31. Ugo Rizzo & Nicolò Barbieri & Laura Ramaciotti & Demian Iannantuono, 2020. "The division of labour between academia and industry for the generation of radical inventions," The Journal of Technology Transfer, Springer, vol. 45(2), pages 393-413, April.
    32. R. J. W. Tussen & R. K. Buter & Th. N. van Leeuwen, 2000. "Technological Relevance of Science: An Assessment of Citation Linkages between Patents and Research Papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 389-412, February.
    33. Jiang Li & Dongbo Shi, 2016. "Sleeping beauties in genius work: When were they awakened?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(2), pages 432-440, February.
    34. Antoine Dechezleprêtre & Yann Ménière & Myra Mohnen, 2017. "International patent families: from application strategies to statistical indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 793-828, May.
    35. Scott Shane, 2001. "Technological Opportunities and New Firm Creation," Management Science, INFORMS, vol. 47(2), pages 205-220, February.
    36. Du, Jian & Li, Peixin & Guo, Qianying & Tang, Xiaoli, 2019. "Measuring the knowledge translation and convergence in pharmaceutical innovation by funding-science-technology-innovation linkages analysis," Journal of Informetrics, Elsevier, vol. 13(1), pages 132-148.
    37. Xiangjie Kong & Huizhen Jiang & Wei Wang & Teshome Megersa Bekele & Zhenzhen Xu & Meng Wang, 2017. "Exploring dynamic research interest and academic influence for scientific collaborator recommendation," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 369-385, October.
    38. Michelle Gittelman & Bruce Kogut, 2003. "Does Good Science Lead to Valuable Knowledge? Biotechnology Firms and the Evolutionary Logic of Citation Patterns," Management Science, INFORMS, vol. 49(4), pages 366-382, April.
    39. Antonio Malva & Stijn Kelchtermans & Bart Leten & Reinhilde Veugelers, 2015. "Basic science as a prescription for breakthrough inventions in the pharmaceutical industry," The Journal of Technology Transfer, Springer, vol. 40(4), pages 670-695, August.
    40. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    41. Chen, Jiyao & Shao, Diana & Fan, Shaokun, 2021. "Destabilization and consolidation: Conceptualizing, measuring, and validating the dual characteristics of technology," Research Policy, Elsevier, vol. 50(1).
    42. Chul Lee & Gunno Park & Jina Kang, 2018. "The impact of convergence between science and technology on innovation," The Journal of Technology Transfer, Springer, vol. 43(2), pages 522-544, April.
    43. Julie Callaert & Maikel Pellens & Bart Looy, 2014. "Sources of inspiration? Making sense of scientific references in patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1617-1629, March.
    44. Russell J. Funk & Jason Owen-Smith, 2017. "A Dynamic Network Measure of Technological Change," Management Science, INFORMS, vol. 63(3), pages 791-817, March.
    45. Antje Klitkou & Magnus Gulbrandsen, 2010. "The relationship between academic patenting and scientific publishing in Norway," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 93-108, January.
    46. Paul Almeida & Jan Hohberger & Pedro Parada, 2011. "Individual scientific collaborations and firm-level innovation," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(6), pages 1571-1599, December.
    47. Zhou, Yuan & Dong, Fang & Kong, Dejing & Liu, Yufei, 2019. "Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 205-220.
    48. Staša Milojević, 2012. "How Are Academic Age, Productivity and Collaboration Related to Citing Behavior of Researchers?," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-13, November.
    49. Ming-Fu Wu & Keng-Wei Chang & Wei Zhou & Juan Hao & Chien-Chung Yuan & Ke-Chiun Chang, 2015. "Patent Deployment Strategies and Patent Value in LED Industry," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
    50. Colavizza, Giovanni & Franceschet, Massimo, 2016. "Clustering citation histories in the Physical Review," Journal of Informetrics, Elsevier, vol. 10(4), pages 1037-1051.
    51. Paula Stephan & Reinhilde Veugelers & Jian Wang, 2017. "Reviewers are blinkered by bibliometrics," Nature, Nature, vol. 544(7651), pages 411-412, April.
    52. Michael Roach & Wesley M. Cohen, 2013. "Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research," Management Science, INFORMS, vol. 59(2), pages 504-525, October.
    53. Francois P. Kabore & Walter G. Park, 2019. "Can patent family size and composition signal patent value?," Applied Economics, Taylor & Francis Journals, vol. 51(60), pages 6476-6496, December.
    54. Narin, Francis & Hamilton, Kimberly S. & Olivastro, Dominic, 1997. "The increasing linkage between U.S. technology and public science," Research Policy, Elsevier, vol. 26(3), pages 317-330, October.
    55. Liang, Guoqiang & Hou, Haiyan & Ding, Ying & Hu, Zhigang, 2020. "Knowledge recency to the birth of Nobel Prize-winning articles: Gender, career stage, and country," Journal of Informetrics, Elsevier, vol. 14(3).
    56. Zihanxin Li & Guilong Zhu, 2021. "Knowledge Transfer Performance of Industry-University-Research Institute Collaboration in China: The Moderating Effect of Partner Difference," Sustainability, MDPI, vol. 13(23), pages 1-22, November.
    57. Na Liu & Jianqi Mao & Jiancheng Guan, 2020. "Knowledge convergence and organization innovation: the moderating role of relational embeddedness," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1899-1921, December.
    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. Libo Sheng & Dongqing Lyu & Xuanmin Ruan & Hongquan Shen & Ying Cheng, 2023. "The association between prior knowledge and the disruption of an article," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4731-4751, August.
    2. Wang, Fang, 2024. "Does the recombination of distant scientific knowledge generate valuable inventions? An analysis of pharmaceutical patents," Technovation, Elsevier, vol. 130(C).
    3. Veugelers, Reinhilde & Wang, Jian, 2019. "Scientific novelty and technological impact," Research Policy, Elsevier, vol. 48(6), pages 1362-1372.
    4. Liang, Guoqiang & Hou, Haiyan & Ding, Ying & Hu, Zhigang, 2020. "Knowledge recency to the birth of Nobel Prize-winning articles: Gender, career stage, and country," Journal of Informetrics, Elsevier, vol. 14(3).
    5. Ke, Qing, 2020. "Technological impact of biomedical research: The role of basicness and novelty," Research Policy, Elsevier, vol. 49(7).
    6. Ugo Rizzo & Nicolò Barbieri & Laura Ramaciotti & Demian Iannantuono, 2020. "The division of labour between academia and industry for the generation of radical inventions," The Journal of Technology Transfer, Springer, vol. 45(2), pages 393-413, April.
    7. Basse Mama, Houdou, 2018. "Nonlinear capital market payoffs to science-led innovation," Research Policy, Elsevier, vol. 47(6), pages 1084-1095.
    8. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    9. Barbieri, Nicolò & Marzucchi, Alberto & Rizzo, Ugo, 2020. "Knowledge sources and impacts on subsequent inventions: Do green technologies differ from non-green ones?," Research Policy, Elsevier, vol. 49(2).
    10. Sun, Bixuan & Kolesnikov, Sergey & Goldstein, Anna & Chan, Gabriel, 2021. "A dynamic approach for identifying technological breakthroughs with an application in solar photovoltaics," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    11. Sam Arts & Nicola Melluso & Reinhilde Veugelers, 2023. "Beyond Citations: Measuring Novel Scientific Ideas and their Impact in Publication Text," Papers 2309.16437, arXiv.org, revised Oct 2024.
    12. Kenneth Zahringer & Christos Kolympiris & Nicholas Kalaitzandonakes, 2017. "Academic knowledge quality differentials and the quality of firm innovation," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(5), pages 821-844.
    13. Zhao, Shengchao & Zeng, Deming & Li, Jian & Feng, Ke & Wang, Yao, 2023. "Quantity or quality: The roles of technology and science convergence on firm innovation performance," Technovation, Elsevier, vol. 126(C).
    14. René Belderbos & Nazareno Braito & Jian Wang, 2024. "Heterogeneous university research and firm R&D location decisions: research orientation, academic quality, and investment type," The Journal of Technology Transfer, Springer, vol. 49(5), pages 1959-1989, October.
    15. Chen, Xi & Mao, Jin & Ma, Yaxue & Li, Gang, 2024. "The knowledge linkage between science and technology influences corporate technological innovation: Evidence from scientific publications and patents," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    16. William Arant & Dirk Fornahl & Nils Grashof & Kolja Hesse & Cathrin Söllner, 2019. "University-industry collaborations—The key to radical innovations? [Universität-Industrie-Kooperationen – Der Schlüssel zu radikalen Innovationen?]," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 39(2), pages 119-141, October.
    17. Nils Grashof & Holger Graf, 2023. "Universities that matter for regional knowledge base renewal - the role of multilevel embeddedness," Jena Economics Research Papers 2023-009, Friedrich-Schiller-University Jena.
    18. Hohberger, Jan, 2016. "Diffusion of science-based inventions," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 66-77.
    19. Yang, Alex J., 2024. "Unveiling the impact and dual innovation of funded research," Journal of Informetrics, Elsevier, vol. 18(1).
    20. Ke, Qing, 2020. "An analysis of the evolution of science-technology linkage in biomedicine," Journal of Informetrics, Elsevier, vol. 14(4).

    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:129:y:2024:i:9:d:10.1007_s11192-024-05126-9. 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.