The Factors Influencing the Idea Recognition of Open Innovation Platforms: Take LEGO Ideas as an Example

Fudong Wang, Wei Gao, Fengtao Liu


With the influx of users posting their ideas to Open Innovation Platforms (OIPs), there has been widespread interest in how companies screen high-quality ideas. Most of the existing literature on idea quality focuses on the adoption of ideas by companies, while ignoring the recognition among users. Based on the ideas posted by users of LEGO Ideas, this study first analyzes the influence of users’ social learning and social network on their innovation ability, and then further investigates the influence of idea authors’ innovation ability and idea content’s characteristics on idea recognition based on signal theory. The findings suggest that more challenging social learning as well as weighted indegree and betweenness centrality of social network positively affect users’ innovation ability and weighted outdegree of social network negatively affects users’ innovation ability. Meanwhile, idea authors’ innovation ability and the number of pictures, text length, richness, popularity, and emotional polarity of idea content positively affect idea recognition. Distinct from the existing literature, this paper focuses on idea recognition among users, delves into the influence of social learning and social network on users’ innovation ability, and integrates the study of factors influencing users’ innovation ability into the study of factors influencing idea recognition.

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