Incentive or disincentive for research data disclosure? A large-scale empirical analysis and implications for open science policy

Seokbeom Kwon and Kazuyuki Motohashi

International Journal of Information Management, 2021, vol. 60, issue C

Abstract: When researchers disclose their original data, they can enhance the visibility of their research works and gain more academic credits (credit effect). By contrast, doing so may accelerate the knowledge replacement process, which dissipates the academic credit that their research works may have received (competition effect). In this study, we examine whether and the extent to which scientists gain academic credit for their research works by publicly disclosing their data. Our review of various literature hypothesizes that data-disclosing research gains more academic credit than non-data-disclosing research in the short term. However, this difference gradually disappears and reverses as the competition effect emerges. This pattern is expected to systematically differ depending on the academic reputation of the journals where the data-disclosing research is published. We empirically test the derived hypotheses by analyzing the metadata of over 310,000 Web of Science Core Collection (WoS CC)-indexed journal articles published in 2010. Our analysis supports both hypotheses. The present study contributes to the on-going policy discussion about the need for institutional measures to promote disclosure of research data by scientists.

Keywords: Data sharing; Open science; Data disclosure; Open data Policy (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:60:y:2021:i:c:s0268401221000645

DOI: 10.1016/j.ijinfomgt.2021.102371

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