"Distant Search, Narrow Attention: How Crowding Alters Organizations' Filtering of User Suggestions"

In their search for innovation, organizations often invite external contributors to make suggestions. Soliciting suggestions is a form of distant search, since it allows organizations to tap knowledge that may not reside inside the firm. Organizations engaging in distant search often face a large pool of suggestions, an outcome we refer to as crowding. When crowding occurs, organizations, whose attention is limited, can only pay attention to a subset of suggestions. Our core argument is that crowding narrows organizations’ attention; that is, despite the organizations’ efforts to reach out to external contributors to access novel suggestions, they are more likely to pay attention to suggestions that are familiar, not distant. We test our theory with a unique longitudinal dataset that captures how 922 organizations responded to 105,127 crowdsourced suggestions from external contributors. After distinguishing between three different dimensions of distance (content, structural and personal), we find that (1) all three types of distance have independent negative effects on the likelihood of attention; (2) crowding amplifies these negative effects; and (3) there are differences among their magnitudes. We elaborate on the broader implications of these findings for the literature on attention, search, and crowdsourcing.