Efficacy of Incentive Structures for Boundedly Rational Dispatchers in Large-Scale Queueing Networks

This paper employs computational approaches to model and explore the efficacy of different incentive structures on the decision making behavior of dispatchers in complex queueing networks, and the subsequent effects of these decisions on teams working within the network and on network performance itself. Computational models that express network structure and function, as well as the decision making process of dispatchers operating within the network and the effect these decisions have on team performance, are presented. Performance of the network under status quo and other incentive structures and decision making processes is illustrated via simulation, validated against data from a large-scale debris removal mission that followed a series of tornadoes in the U.S. state of Alabama in 2011. Results of the simulation experiments suggest that the optimal incentive structure assuming a rational decision maker remains optimal under lower levels of rationality. Furthermore, a simple uniform reward structure is likely to produce performance improvements over the status quo incentive structure under most scenarios.