Stefan, Matthias Huber, Jürgen Kirchler, Michael Sutter, Matthias Walzl, Markus
Year of Publication:
Discussion Papers of the Max Planck Institute for Research on Collective Goods No. 2020/10
Rankings are prevalent information and incentive tools in labor markets with strong competition for talent. In a dynamic model of multi-tasking and an accompanying experiment with financial professionals, we identify hidden ranking costs when performance in one task is incentivized and ranked while another prosocial task is not: (i) a ranking influences behavior if individuals lag behind: they spend more total effort and substitute effort in the prosocial task with effort in the ranked task; (ii) those ahead in the ranking spend less total effort and lower relative effort in the ranked task. Implications for incentive schemes are discussed.
multi-tasking decision problem rank incentives framed field experiment finance professionals