IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v67y2016i4p776-799.html
   My bibliography  Save this article

Institutional and individual factors affecting scientists' data-sharing behaviors: A multilevel analysis

Author

Listed:
  • Youngseek Kim
  • Jeffrey M. Stanton

Abstract

No abstract is available for this item.

Suggested Citation

  • Youngseek Kim & Jeffrey M. Stanton, 2016. "Institutional and individual factors affecting scientists' data-sharing behaviors: A multilevel analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 776-799, April.
    • Handle: RePEc:bla:jinfst:v:67:y:2016:i:4:p:776-799
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/asi.23424
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Charles Ayoubi & Boris Thurm, 2023. "Knowledge diffusion and morality: Why do we freely share valuable information with Strangers?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 75-99, January.
    2. Joshua Borycz & Robert Olendorf & Alison Specht & Bruce Grant & Kevin Crowston & Carol Tenopir & Suzie Allard & Natalie M. Rice & Rachael Hu & Robert J. Sandusky, 2023. "Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    3. Keiko Kurata & Mamiko Matsubayashi & Shinji Mine, 2017. "Identifying the Complex Position of Research Data and Data Sharing Among Researchers in Natural Science," SAGE Open, , vol. 7(3), pages 21582440177, July.
    4. Anne E Thessen & Paul Bogdan & David J Patterson & Theresa M Casey & César Hinojo-Hinojo & Orlando de Lange & Melissa A Haendel, 2021. "From Reductionism to Reintegration: Solving society’s most pressing problems requires building bridges between data types across the life sciences," PLOS Biology, Public Library of Science, vol. 19(3), pages 1-12, March.
    5. Federica Cugnata & Chiara Brombin & Chiara Maria Poli & Roberto Buccione & Clelia Serio, 2024. "Modelling perception and resilience factors to data sharing in clinical and basic research: an observational study," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3169-3192, June.
    6. Carol Tenopir & Natalie M Rice & Suzie Allard & Lynn Baird & Josh Borycz & Lisa Christian & Bruce Grant & Robert Olendorf & Robert J Sandusky, 2020. "Data sharing, management, use, and reuse: Practices and perceptions of scientists worldwide," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-26, March.
    7. Libby Hemphill & Margaret L. Hedstrom & Susan Hautaniemi Leonard, 2021. "Saving social media data: Understanding data management practices among social media researchers and their implications for archives," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 97-109, January.
    8. Jinya Liu & Kunhua Zhao & Liping Gu & Huichuan Xia, 2024. "To share or not to share, that is the question: a qualitative study of Chinese astronomers’ perceptions, practices, and hesitations about open data sharing," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    9. Claire M Mason & Paul J Box & Shanae M Burns, 2020. "Research data sharing in the Australian national science agency: Understanding the relative importance of organisational, disciplinary and domain-specific influences," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.
    10. Pablo Dorta-González & Sara M. González-Betancor & María Isabel Dorta-González, 2021. "To what extent is researchers' data-sharing motivated by formal mechanisms of recognition and credit?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2209-2225, March.
    11. Youngseek Kim & Ayoung Yoon, 2017. "Scientists' data reuse behaviors: A multilevel analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2709-2719, December.
    12. Harper, Lindsey M. & Kim, Youngseek, 2018. "Attitudinal, normative, and resource factors affecting psychologists’ intentions to adopt an open data badge: An empirical analysis," International Journal of Information Management, Elsevier, vol. 41(C), pages 23-32.

    More about this item

    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:bla:jinfst:v:67:y:2016:i:4:p:776-799. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    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.