How open is innovation research? – An empirical analysis of data sharing among innovation scholars

Pruschak, Gernot; Barczak, Gloria; Piller, Frank; Kaminski, Jermain (2021). How open is innovation research? – An empirical analysis of data sharing among innovation scholars Industry and Innovation Taylor & Francis https://doi.org/10.1080/13662716.2021.1967727

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We investigate what fosters or inhibits data sharing behaviour in a sample of 173 innovation management researchers. Theoretically, we integrate resource-based arguments with social exchange considerations to juxtapose the trade-off between data as a proprietary resource for researchers and the benefits that reciprocity in academic relations may provide. Our empirical analysis reveals that the stronger scholars perceive the comparative advantage of non-public datasets, the lower the likelihood of data sharing. Expected communal benefits may increase the likelihood of data sharing, while negative perceptions of increased data scrutiny are consequential in inhibiting data sharing. Only institutional pressure may help to solve this conundrum; most respondents would therefore like to see journal policies that foster data sharing.

Item Type:

Journal Article (Original Article)

Division/Institute:

Business School > Institute for Applied Data Science & Finance
Business School > Institute for Applied Data Science & Finance > Applied Data Science
Business School

Name:

Pruschak, Gernot;
Barczak, Gloria;
Piller, Frank and
Kaminski, Jermain

Subjects:

H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics

ISSN:

1366-2716

Publisher:

Taylor & Francis

Language:

English

Submitter:

Christian Hopp

Date Deposited:

01 Dec 2021 12:07

Last Modified:

08 Dec 2021 14:46

Publisher DOI:

https://doi.org/10.1080/13662716.2021.1967727

ARBOR DOI:

10.24451/arbor.15832

URI:

https://arbor.bfh.ch/id/eprint/15832

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