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Funding acknowledgement analysis: an enhanced tool to investigate research sponsorship impacts: the case of nanotechnology

Author

Listed:
  • Jue Wang

    () (Florida International University)

  • Philip Shapira

    () (University of Manchester
    Georgia Institute of Technology)

Abstract

Abstract There is increasing interest in assessing how sponsored research funding influences the development and trajectory of science and technology. Traditionally, linkages between research funding and subsequent results are hard to track, often requiring access to separate funding or performance reports released by researchers or sponsors. Tracing research sponsorship and output linkages is even more challenging when researchers receive multiple funding awards and collaborate with a variety of differentially-sponsored research colleagues. This article presents a novel bibliometric approach to undertaking funding acknowledgement analysis which links research outputs with their funding sources. Using this approach in the context of nanotechnology research, the article probes the funding patterns of leading countries and agencies including patterns of cross-border research sponsorship. We identify more than 91,500 nanotechnology articles published worldwide during a 12-month period in 2008–2009. About 67% of these publications include funding acknowledgements information. We compare articles reporting funding with those that do not (for reasons that may include reliance on internal core-funding rather than external awards as well as omissions in reporting). While we find some country and field differences, we judge that the level of reporting of funding sources is sufficiently high to provide a basis for analysis. The funding acknowledgement data is used to compare nanotechnology funding policies and programs in selected countries and to examine their impacts on scientific output. We also examine the internationalization of research funding through the interplay of various funding sources at national and organizational levels. We find that while most nanotechnology funding is nationally-oriented, internationalization and knowledge exchange does occur as researchers collaborate across borders. Our method offers a new approach not only in identifying the funding sources of publications but also in feasibly undertaking large-scale analyses across scientific fields, institutions and countries.

Suggested Citation

  • Jue Wang & Philip Shapira, 2011. "Funding acknowledgement analysis: an enhanced tool to investigate research sponsorship impacts: the case of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 563-586, June.
  • Handle: RePEc:spr:scient:v:87:y:2011:i:3:d:10.1007_s11192-011-0362-5
    DOI: 10.1007/s11192-011-0362-5
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Goio Etxebarria & Mikel Gomez-Uranga & Jon Barrutia, 2012. "Tendencies in scientific output on carbon nanotubes and graphene in global centers of excellence for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 253-268, April.
    2. Cristian Mejia & Yuya Kajikawa, 2018. "Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 883-904, March.
    3. Konstantin Fursov & Ian Miles, 2013. "Framing Emerging Nanotechnologies: Steps Towards A Forward-Looking Analysis Of Skills," HSE Working papers WP BRP 15/STI/2013, National Research University Higher School of Economics.
    4. Erjia Yan & Chaojiang Wu & Min Song, 2018. "The funding factor: a cross-disciplinary examination of the association between research funding and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 369-384, April.
    5. Sabatier, Mareva & Chollet, Barthélemy, 2017. "Is there a first mover advantage in science? Pioneering behavior and scientific production in nanotechnology," Research Policy, Elsevier, vol. 46(2), pages 522-533.
    6. Star X. Zhao & Wen Lou & Alice M. Tan & Shuang Yu, 2018. "Do funded papers attract more usage?," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 153-168, April.
    7. Xia Fan & Xiaowan Yang & Liming Chen, 2015. "Diversified resources and academic influence: patterns of university–industry collaboration in Chinese research-oriented universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(2), pages 489-509, August.
    8. Belén Álvarez-Bornstein & Fernanda Morillo & María Bordons, 2017. "Funding acknowledgments in the Web of Science: completeness and accuracy of collected data," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1793-1812, September.
    9. Xin Xu & Alice M. Tan & Star X. Zhao, 2015. "Funding ratios in social science: the perspective of countries/territories level and comparison with natural sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 673-684, September.
    10. Philip Shapira & Seokbeom Kwon & Jan Youtie, 2017. "Tracking the emergence of synthetic biology," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1439-1469, September.
    11. Fengqing Zhang & Erjia Yan & Xin Niu & Yongjun Zhu, 2018. "Joint modeling of the association between NIH funding and its three primary outcomes: patents, publications, and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 591-602, October.
    12. Fernanda Morillo & Belén Álvarez-Bornstein, 2018. "How to automatically identify major research sponsors selecting keywords from the WoS Funding Agency field," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1755-1770, December.
    13. Sabatier, Mareva & Chollet, Barthélemy, 2017. "Is there a first mover advantage in science? Pioneering behavior and scientific production in nanotechnology," Research Policy, Elsevier, vol. 46(2), pages 522-533.
    14. Liu, Weishu & Hu, Guangyuan & Tang, Li, 2018. "Missing author address information in Web of Science—An explorative study," Journal of Informetrics, Elsevier, vol. 12(3), pages 985-997.
    15. 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.
    16. Mu-Hsuan Huang & Mei-Jhen Huang, 2018. "An analysis of global research funding from subject field and funding agencies perspectives in the G9 countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 833-847, May.

    More about this item

    Keywords

    Funding acknowledgement analysis; Research funding; Research sponsorship; Nanotechnology; Research outputs; Publications; Bibliometrics;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • H59 - Public Economics - - National Government Expenditures and Related Policies - - - Other
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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