Dr. Jan Reerink

We studied the conflict between two mechanisms influencing impact of scientific articles using an extensive dataset derived by methodological innovations of proven methods. This study covers contributions published in journals, indexed by the web of science database resulting in 15,598 individual articles. Making use of document co-citation analysis, we identify 35 major research streams of entrepreneurship science. The four most important research streams are (1) International entrepreneurship, (2) University-industry relations and entrepreneurship, (3) Venture capital policies and financing, and (4) Macroeconomic/global and regional impact of entrepreneurship. Furthermore, regression results show that the popularity of a research stream may attract undue attention from researchers via an inflationary effect. Furthermore, a research stream’s diversity represents a self correction mechanism in that it decreases expected publication impact. However, the inflationary effect seems to outweigh the self correction effect necessitating a strong research framework as a policy tool.

Open innovation is exemplified in crowdsourcing platforms that allow firms to broadcast R&D problems, which they are unable to solve by their own means, to a wide range of potential solvers. A few studies so far indicate that especially solvers from distant fields have higher chances to make the winning contributions in crowdsourcing contests. It is not fully understood, however, what generally attracts potential solvers to crowdsourcing in the first place and how solvers’ knowledge distance towards the broadcasted innovation problem in particular affect their initial interest and adoption. To investigate this question, we situate our study in the field of nanoscience and technology. By the means of topic modeling with over 900,000 scientific papers and 35 real requests for proposals (RfPs), we are able to locate solvers and problems within a knowledge space and measure the distance between them. In a field experiment, we invite scientists to inspect randomly assigned RfPs of high and low distance. In a subsequent discrete choice analysis, we measure their willingness to engage in solving the assigned R&D problem conditional on contractual arrangements. Our findings lend support to the conjecture that knowledge distance reduces scientists’ attention paid towards broadcasted innovation problems and their willingness to solve them. Contractual arrangements can only partially mitigate this effect. Solvers that are more closely linked to the problem are also more responsive to contract attributes. More distant solvers can best be incentivized by higher award money and by the right to license the invention also to third parties. Overall, we shed light on managing an important trade-off in innovation crowdsourcing: while more distant solvers could make valuable contributions, they are more difficult to contract.

Based on prior research on academic patenting and self-determination theory, we highlight the importance of scientist’ self-determined motivation to engage in academic patenting, a “taste for patents”. In a large scale empirical study, we can show that this self-determined taste for patenting arises among scientists that publish less, but more extensively engage with industry and work in faculties with patenting peers. Rather than crowding out external incentives can actually boost self-determined motivation. In conclusion, universities which want to become more entrepreneurial should either recruit scientists based on an inherent motivation to patent.