We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a field experiment at a medical research symposium, where we exogenously varied opportunities for face‐to‐face encounters among 15,817 scientist‐pairs. Our data include direct observations of interaction patterns collected using sociometric badges, and detailed, longitudinal data of the scientists' postsymposium publication records over 6 years. We find that interacting scientists acquire more knowledge and coauthor 1.2 more papers when they share some overlapping interests, but cite each other's work between three and seven times less when they are from the same field. Our findings reveal both collaborative and competitive effects of knowledge similarity on knowledge production outcomes.
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InnoCentive.com, a firm connecting R&D labs of large organizations to diverse external solvers through innovation contests, has to decide if it will enable collaboration in its community. Case covers the basics of a distributed innovation system works and the advantages of having external R&D. Links how concepts of open source are applied to a non-software setting. Describes the rationale for participation by solvers in innovation contests and the benefits that accrue to firms. Raises the issue if a community can be shifted to collaboration when competition was the basis of prior interaction.
We investigate the factors driving workers’ decisions to generate public goods inside an organization through a randomized solicitation of workplace improvement proposals in a medical center with 1200 employees. We find that pecuniary incentives, such as winning a prize, generate a threefold increase in participation compared to non-pecuniary incentives alone, such as prestige or recognition. Participation is also increased by a solicitation appealing to improving the workplace. However, emphasizing the patient mission of the organization led to countervailing effects on participation. Overall, these results are consistent with workers having multiple underlying motivations to contribute to public goods inside the organization consisting of a combination of pecuniary and altruistic incentives associated with the mission of the organization.
In summary, we show that a prize-based contest on a commercial platform can effectively recruit skilled individuals to apply their knowledge to a big-data biomedical problem. Deconstruction and transformation of problems for a heterogeneous solver community coupled with adequate data to produce and validate results can support solution diversity and minimize the risk of sub-optimal solutions that may arise from limited searches. In addition to the benefits of generating new knowledge, this strategy may be particularly useful in situations where the computational or algorithmic problem, or potentially any science problem, represents a barrier to rapid progress but where finding the solution is not itself the major thrust of the investigator’s scientific effort. The America Competes Act passed by the US Congress provides funding agencies with the authority to administer their own prize-based contests and paves the way for establishing how grant recipients might access commercial prize platforms to accelerate their own research.