The effect of partial and full relative performance information in problem-solving

• In Event: Relative Performance Information

Abstract

We examine how variations in the completeness of public relative performance information (RPI) affect individual performance in problem-solving. Using experiments, we contrast the effects of full and partial RPI on well-defined and ill-defined problems. Full RPI is akin to a public scoreboard on which employees’ performances are ranked, whereas partial RPI means that only the top-ranking employees are public. Consistent with prior RPI research (e.g., Takfov 2013), we find that full RPI increases performance in the well-defined problem space more than partial RPI. However, we find the opposite effect in the ill-defined problem space, where partial RPI increases performance more than full RPI.

Authors

• Kun Huo, Western University

• Leslie Berger, Wilfrid Laurier University