Abstract

The selection of novel ideas is vital to the development of truly innovative products. Firms often turn to idea crowdsourcing challenges, in which both ideators and the seeker firms participate in the idea selection process. Yet prior research cautions that ideators and seeker firms may not select novel ideas. To address the links between idea novelty and selection, this study proposes a bi-faceted notion of idea novelty and probes the role of task structure. Novelty may be local or global, in line with information processing literature. Using semantic analyses of data on 12,079 ideas shared on OpenIDEO during 47 contests held between 2010–2017, the authors find that the selection of novel ideas differs according to the selector, the form of novelty, and the challenge task structure. The results help explain some paradoxical findings in previous studies, with key implications for both ideators and seeker firms. In particular, this research uses measures of local and global novelty, along with additional linguistic measures, to produce a predictive model that seeker firms can leverage when ideator selection metrics such as likes are unavailable.

Note: Research papers posted on SSRN, including any findings, may differ from the final version chosen for publication in academic journals.

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• Keyword(s):
• data project 74
• decision making 19

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