Pay-for-Performance and Emerging Search...

Prior research suggests that the fit between task complexity and incentive schemes like pay-for-performance positively affects organizational performance. This study goes a step further and seeks to investigate how different types of pay-for-performance affect subordinates’ search behavior for novel solutions to complex decision problems. Based on NK fitness landscapes, the study employs an agent-based simulation with subordinate decision-makers individually adapting their search behavior via reinforcement learning. The results suggest that the emerging search strategy is subtly shaped by the (mis-)fit between task complexity and incentive structure. In particular, the results indicate that search behavior may arise for different “reasons” ranging from fostering new solutions to even preventing alterations.