The purpose of this paper is to develop a framework for identifying the most promising user-generated ideas in user communities.
To develop the framework, each user-generated idea is first classified into a specific category depending on its source, such as market trend-, need-, solution- or mental ideation-based ideas. The degree of shared identity (shared agreement minus shared disagreement) based on user votes for each idea within the user community is then evaluated.
This study argues that unlike need-based user-generated ideas, trend-based ideas will not succeed in the marketplace even if they receive the highest ratings or the most votes from community members, and that hence such trend-based ideas should not be implemented. Moreover, solution- and mental ideation-based user ideas, even though they receive the lowest ratings or fewest votes from community members, are more likely to succeed in the marketplace, and thus, such ideas should not be discarded.
Community- and idea-level variables are combined to identify the most promising user-generated ideas for firms. This prevents overlooking the most promising ideas simply because their popularity is low within the user community. Moreover, this method prevents selecting the least promising ideas even though their popularity is high with the user community.
