The Open Innovation in Science research field: a collaborative conceptualisation approach

Openness and collaboration in scientific research are attracting increasing attention from scholars and practitioners alike. However, a common understanding of these phenomena is hindered by disciplinary boundaries and disconnected research streams. We link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. This framework captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. Moreover, it elucidates individual-, team-, organisation-, field-, and society‐level factors shaping OIS practices. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners

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

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