Identifying Successful Ideas in Crowdsourcing Contest: Effects of Idea Content and Competition Intensity

While crowdsourcing idea contests have the potential to harness widely distributed knowledge, the quantity and complexity involved in idea assessment induce a great effort and challenge for organizations. Drawing upon knowledge recombination and innovation literature, this study proposes a model that can assist organizations in efficiently processing crowdsourced ideas by exploring how two aspects of an idea: the idea content and the contest competition intensity. Using a rich dataset of 16,057 ideas submitted to 61 socio-economic crowdsourcing idea contests, we find that successful ideas are more likely to originate from more distinctive knowledge while ideas that combine diverse knowledge from a broad set of topics are less likely to be successful in the idea contest. Further, competition intensity plays an influencing role in weakening the positive relationship between idea distinctiveness and success. This study contributes to the growing crowdsourcing literature and provides practical guidance for crowdsourcing intermediaries and organizations.