IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0234172.html
   My bibliography  Save this article

When are researchers willing to share their data? – Impacts of values and uncertainty on open data in academia

Author

Listed:
  • Stefan Stieglitz
  • Konstantin Wilms
  • Milad Mirbabaie
  • Lennart Hofeditz
  • Bela Brenger
  • Ania López
  • Stephanie Rehwald

Abstract

Background: E-science technologies have significantly increased the availability of data. Research grant providers such as the European Union increasingly require open access publishing of research results and data. However, despite its significance to research, the adoption rate of open data technology remains low across all disciplines, especially in Europe where research has primarily focused on technical solutions (such as Zenodo or the Open Science Framework) or considered only parts of the issue. Methods and findings: In this study, we emphasized the non-technical factors perceived value and uncertainty factors in the context of academia, which impact researchers’ acceptance of open data–the idea that researchers should not only publish their findings in the form of articles or reports, but also share the corresponding raw data sets. We present the results of a broad quantitative analysis including N = 995 researchers from 13 large to medium-sized universities in Germany. In order to test 11 hypotheses regarding researchers’ intentions to share their data, as well as detect any hierarchical or disciplinary differences, we employed a structured equation model (SEM) following the partial least squares (PLS) modeling approach. Conclusions: Grounded in the value-based theory, this article proclaims that most individuals in academia embrace open data when the perceived advantages outweigh the disadvantages. Furthermore, uncertainty factors impact the perceived value (consisting of the perceived advantages and disadvantages) of sharing research data. We found that researchers’ assumptions about effort required during the data preparation process were diminished by awareness of e-science technologies (such as Zenodo or the Open Science Framework), which also increased their tendency to perceive personal benefits via data exchange. Uncertainty factors seem to influence the intention to share data. Effects differ between disciplines and hierarchical levels.

Suggested Citation

  • Stefan Stieglitz & Konstantin Wilms & Milad Mirbabaie & Lennart Hofeditz & Bela Brenger & Ania López & Stephanie Rehwald, 2020. "When are researchers willing to share their data? – Impacts of values and uncertainty on open data in academia," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-20, July.
  • Handle: RePEc:plo:pone00:0234172
    DOI: 10.1371/journal.pone.0234172
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0234172
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0234172&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0234172?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
    ---><---

    References listed on IDEAS

    as
    1. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    2. Benedikt Fecher & Sascha Friesike & Marcel Hebing, 2015. "What Drives Academic Data Sharing?," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-25, February.
    3. Vicente-Saez, Ruben & Martinez-Fuentes, Clara, 2018. "Open Science now: A systematic literature review for an integrated definition," Journal of Business Research, Elsevier, vol. 88(C), pages 428-436.
    4. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    5. Heather A Piwowar & Roger S Day & Douglas B Fridsma, 2007. "Sharing Detailed Research Data Is Associated with Increased Citation Rate," PLOS ONE, Public Library of Science, vol. 2(3), pages 1-5, March.
    6. A. Willem & M. Buelens, 2005. "Knowledge Sharing in Public Sector Organizations: The Effect of Organizational Characteristics on Interdepartmental Knowledge Sharing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/344, Ghent University, Faculty of Economics and Business Administration.
    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. Isabel Steinhardt & Mareike Bauer & Hannes Wünsche & Sonja Schimmler, 2023. "The connection of open science practices and the methodological approach of researchers," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3621-3636, August.
    2. Christian Vidal-Cabo & Enrique Alfonso Sánchez-Pérez & Antonia Ferrer-Sapena, 2024. "Perception and Reuse of Open Data in the Spanish University Teaching and Research Community," Data, MDPI, vol. 9(10), pages 1-21, October.

    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. Mike Thelwall & Marcus Munafò & Amalia Mas-Bleda & Emma Stuart & Meiko Makita & Verena Weigert & Chris Keene & Nushrat Khan & Katie Drax & Kayvan Kousha, 2020. "Is useful research data usually shared? An investigation of genome-wide association study summary statistics," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-11, February.
    2. Eirini Delikoura & Dimitrios Kouis, 2021. "Open Research Data and Open Peer Review: Perceptions of a Medical and Health Sciences Community in Greece," Publications, MDPI, vol. 9(2), pages 1-19, March.
    3. Stefan Reichmann & Thomas Klebel & Ilire Hasani‐Mavriqi & Tony Ross‐Hellauer, 2021. "Between administration and research: Understanding data management practices in an institutional context," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(11), pages 1415-1431, November.
    4. Côrte-Real, Nadine & Ruivo, Pedro & Oliveira, Tiago & Popovič, Aleš, 2019. "Unlocking the drivers of big data analytics value in firms," Journal of Business Research, Elsevier, vol. 97(C), pages 160-173.
    5. Mohammed Akhmaaj, Asmaeil Ali & Sharif, Mohamed Omar, 2024. "The effects of planned behavior model constructs and technology acceptance model constructs on online purchasing behavior: An empirical study on internet users in the Libya city of Tripoli," Technology in Society, Elsevier, vol. 79(C).
    6. Aziz Barhmi & Omar Hajaji, 2023. "Multidisciplinary Approach to Supply Chain Resilience: Conceptualization and Scale Development," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 43-69.
    7. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    8. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    9. Severin Oesterle & Arne Buchwald & Nils Urbach, 2022. "Investigating the co-creation of IT consulting service value: empirical findings of a matched pair analysis," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 571-597, June.
    10. repec:plo:pone00:0037552 is not listed on IDEAS
    11. Zhang, Qingyu & Vonderembse, Mark A. & Cao, Mei, 2009. "Product concept and prototype flexibility in manufacturing: Implications for customer satisfaction," European Journal of Operational Research, Elsevier, vol. 194(1), pages 143-154, April.
    12. Hajiheydari, Nastaran & Delgosha, Mohammad Soltani & Olya, Hossein, 2021. "Scepticism and resistance to IoMT in healthcare: Application of behavioural reasoning theory with configurational perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    13. Sara Moussawi & Marios Koufaris & Raquel Benbunan-Fich, 2021. "How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 343-364, June.
    14. Turcan Nelly & Rusu Andrei & Cujba Rodica, 2019. "Study on the Mapping of Research Data in the Republic of Moldova in the Context of Open Science," International Journal of Advanced Statistics and IT&C for Economics and Life Sciences, Sciendo, vol. 9(1), pages 11-22, June.
    15. Wanda J. Orlikowski & C. Suzanne Iacono, 2001. "Research Commentary: Desperately Seeking the “IT” in IT Research—A Call to Theorizing the IT Artifact," Information Systems Research, INFORMS, vol. 12(2), pages 121-134, June.
    16. Petschnig, Martin & Heidenreich, Sven & Spieth, Patrick, 2014. "Innovative alternatives take action – Investigating determinants of alternative fuel vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 68-83.
    17. Yan, Ruihe & Gong, Xiang, 2022. "Peer-to-peer accommodation platform affordance: Scale development and empirical investigation," Journal of Business Research, Elsevier, vol. 144(C), pages 922-938.
    18. Monideepa Tarafdar & Sufian Qrunfleh, 2017. "Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 925-938, February.
    19. Kuldeep Baishya & Harsh Vardhan Samalia, 2020. "Factors Influencing Smartphone Adoption: A Study in the Indian Bottom of the Pyramid Context," Global Business Review, International Management Institute, vol. 21(6), pages 1387-1405, December.
    20. Dehghani, Milad & William Kennedy, Ryan & Mashatan, Atefeh & Rese, Alexandra & Karavidas, Dionysios, 2022. "High interest, low adoption. A mixed-method investigation into the factors influencing organisational adoption of blockchain technology," Journal of Business Research, Elsevier, vol. 149(C), pages 393-411.
    21. Siti Salwa Mohd Ishak & Sidney Newton, 2018. "Testing a Model of User Resistance Towards Technology Adoption in Construction Organizations," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-27, December.

    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:plo:pone00:0234172. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.