Crowdsourcing for innovation: Effects of idea content and competition intensity on idea success

Abstract

While crowdsourcing idea contests have the potential to harness widely distributed knowledge, the quantity of ideas and the complexity involved in idea assessment create a great effort and challenge for organizations. Drawing on tournament theory and the knowledge recombination perspective, this study proposes a model that can assist organizations in efficiently processing crowdsourced ideas by exploring two aspects: the idea content and the contest competition intensity. Analyzing a rich dataset of 16,057 ideas submitted in 61 socio-economic crowdsourcing idea contests, we find that successful ideas are more likely to stem 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. Furthermore, competition intensity weakens the positive relationship between idea distinctiveness and success, while it does not influence idea diversity. This study contributes to the growing crowdsourcing literature and offers practical guidance for crowdsourcing intermediaries and organizations.