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In this study, we draw on signalling theory to examine the organization‐level relationship between reputation and employee movement in and out of organizations. Focusing on organizations’ media reputations relative to their peers, we map all employee flows between organizational dyads in a population of English hospitals. We find support for our main argument that an organization's relative reputation predicts employee mobility above and beyond what can be explained by its absolute level of reputation. In particular, our findings suggest that the number of employees moving between two organizations is highest when both organizations have a high reputation. We refer to this as the elites’ mutual attraction effect (EMA‐effect). We also find that the motives of voluntary leavers and geographical distance between two organizations influence the strength of this EMA‐effect. Overall, this study shows that developing and testing dyadic theory can extend research on organizational reputation and collective turnover in meaningful ways.

OVERVIEW: When crowdsourcing intermediaries lose crowd members, they lose potential high-quality solutions in the future. As the number of contests and intermediaries grows, it is increasingly critical for crowdsourcers to meet the needs of solvers and avoid seeing them migrate to the competition. Besides winning contests, intensive communication and customized feedback are solvers' most central needs. For this study, we surveyed 202 solvers about the importance of communication in crowdsourcing contests. Based on our quantitative and qualitative insights, we derive key principles that can help crowdsourcers maintain and grow their solver base. KEYWORDS: Crowdsourcing contests, Solvers, Problem solving, Crowdsourcing contests are becoming mainstream (Boudreau and Lakhani 2013) as an increasing number of firms and other organizations recognize the vast potential of sourcing ideas and solutions from crowds of [...]

Objective. To identify factors associated with methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections at the level of the hospital organization. Data Sources. Data from all 173 acute trusts in the English [...]

The Internet of Things (IoT) is permeating all areas of life. However, connected devices are associated with substantial risks to users’ privacy, as they rely on the collection and exploitation of personal data. The case of connected cars demonstrates that these risks may be more profound in the IoT than in extant contexts, as both a user's informational and physical space are intruded. We leverage this unique setting to collect rich context-immersive interview (n = 33) and large-scale survey data (n = 791). Our work extends prior theory by providing a better understanding of the formation of users’ privacy risk perceptions, the effect such perceptions have on users’ willingness to share data, and how these relationships in turn are affected by inter-individual differences in individuals’ regulatory focus, thinking style, and institutional trust.