Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Rankings are intended as incentive tools on labor markets. Yet, when agents perform multiple tasks, rankings might have unintended side-effects, especially if not all tasks can be ranked with respect to performance. We analyze the dynamics of multi-tasking and present an experiment with 286 finance professionals in which we identify hidden ranking costs when performance in one task is ranked while in another prosocial task it is not. We find that subjects lagging behind (leading) in the ranked task devote less (more) effort to the prosocial task. We discuss implications for optimal incentive schemes in organizations with multi-tasking.