Distant Search, Narrow Attention: How Crowding Alters Organizations’ Filtering of Suggestions in Crowdsourcing

Abstract

In their search for innovation, organizations often invite suggestions from external contributors. Soliciting suggestions is a form of distant search, since it allows organizations to tap into knowledge that may not reside within their organizational boundaries. Organizations engaging in distant search often face a large pool of suggestions, an outcome we refer to as crowding. When crowding occurs, organizations, given a limited attention span, can attend to only a subset of suggestions. Our core argument is that crowding narrows the attention of organizations; that is, despite organizations’ efforts to reach out to external contributors and access suggestions that capture distant knowledge, 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 (a) all three types of distance have independent negative effects on the likelihood of attention, (b) crowding amplifies these negative effects, and (c) there are differences among the effects’ magnitudes. We elaborate on the broader implications of these findings for the literatures on attention, search, and crowdsourcing.