Idea Selection in Suggestion Systems: A Thematic Similarity Perspective

The literature on the fuzzy front-end of innovation, and in particular on suggestion systems, has focused mainly on organizational aspects and individual characteristics of submitters. We take a different approach and focus on the idea itself. To differentiate different ideas, we build on recent research in cognition that distinguishes two types of similarities: feature-based, taxonomic similarity, and context-based, thematic similarity. We operationalize the type of similarity in terms of idea character (‘thematicness’) and idea presentation (scenario and experiential proximity) with idea evaluation. Data were obtained from the suggestion system of the research and development department of a multinational manufacturer of consumer goods. We identify significant, positive relationships for all characteristics with idea evaluations. We discuss our findings in the context of bounded creativity approaches, derive theoretical and practical implications, and recommend avenues for future research.