Effects sparked by shining stars: Consequences earned and posed by high performers at work

Abstract

Organizations tend to follow two common practices. First, they seek out and recruit the best and the brightest, with the assumption that these high performers create value and drive success within the organization. Second, they increasingly rely upon workgroups and teams to accomplish organizational goals. Though each practice alone has merit, their interaction seems problematic. Organizational leaders invest substantial resources to recruit standouts, yet also want high performers to seamlessly embed within, and contribute to, workgroups and teams. I am intrigued to consider several puzzles that seem to exist where these trends intersect. How are high performers received by peers their workgroup? How do high performers influence the motivation of their teammates? What impact will high performers have on team collaboration and coordination? This dissertation seeks to address these and related questions. In three essays, I develop a theory of consequences of outperformance, focusing on implications for the high performer, his or her peers, and the team as a whole. In Essay 1, I offer a theoretical and empirical account of how high performers are socially treated by their peers. I identify prosocial (i.e., other-oriented) characteristics of the high performer and of the social environment that can mitigate unfavorable social behaviors from peers. In Essay 2, I examine how the presence of a high performer affects the proactive motivation and performance of lower-performing teammates. I also explore individual characteristics that make teammate motivation more or less susceptible to the presence of a high performer. In Essay 3, I explore how the composition of members' past performance impacts team processes. I argue that steeper differences in performance histories galvanize social order, which can facilitate coordination among members yet reduce dynamic collaboration--both of which are critical to team innovation. Using a multi-method approach, I examine these hypotheses using field studies, individual experiments, and team simulations.