  Finding innovative solutions to complex problems is often about finding
people who have access to novel information and alternative viewpoints.
Research has found that most people are connected to each other through just a
few degrees of separation, but successful social search is often difficult
because it depends on people using their weak ties to make connections to
distant social networks. Recursive incentive schemes have shown promise for
social search by motivating people to use their weak ties to find distant
targets, such as specific people or even weather balloons placed at undisclosed
locations. Here, we report on a case study of a similar recursive incentive
scheme for finding innovative ideas. Specifically, we implemented a competition
to reward individuals(s) who helped refer Grand Prize winner(s) in MIT's
Climate CoLab, an open innovation platform for addressing global climate
change. Using data on over 78,000 CoLab members and over 36,000 people from
over 100 countries who engaged with the referral contest, we find that people
who are referred using this method are more likely than others to submit
proposals and to submit high quality proposals. Furthermore, we find suggestive
evidence that among the contributors referred via the contest, those who had
more than one degree of separation from a pre-existing CoLab member were more
likely to submit high quality proposals. Thus, the results from this case study
are consistent the theory that people from distant networks are more likely to
provide innovative solutions to complex problems. More broadly, the results
suggest that rewarding indirect intermediaries in addition to final finders may
promote effective social network recruitment.
