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Journal Article

Distant search, narrow attention: How crowding alters organizations' filtering of suggestions in crowdsourcing

Academy of Management Journal 58 (3): 856–880
2016 Highly cited paper (Web of Knowledge) , 2015 Darmstadt Innovation Research Best Paper Award
Henning Piezunka, Linus Dahlander (2015)
Technology, R&D management
Selection, evaluation, user-based innovation, crowd sourcing
When organizations reach out to their users for ideas, users take on a considerable role in the innovation process. Including users expands the number of participants and potential ideas from which an organization can select. But how do organizations select some user suggestions while rejecting or ignoring others? We analyze the selection processes at 24,067 organizations that collectively received 702,729 suggestions. Our findings suggest that organizations filter the suggestions they receive by focusing on suggestions that inspire feedback from the user community. Despite receiving contributions from a diverse pool of users, organizations quickly settle into a pattern of attending to only a few. To our surprise, collective user preferences only matter as a filter mechanism when crowding is high. In contrast, the debate among users about a suggestion strongly increases the likelihood of it being selected by the organization. Our illustration of the screening criteria organizations use to winnow suggestions has broad implications for the selection literature. We also bring insight to the literature on user-driven innovation processes by studying all suggestions that were considered, rather than only those organizations select and implement.
With permission of the Academy of Management
As of May/June 2016, this highly cited paper received enough citations to place it in the top 1% of the academic field of Economics & Business based on a highly cited threshold for the field and publication year. – Data from Essential Science Indicators℠
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