Article ID: | iaor201526644 |
Volume: | 24 |
Issue: | 6 |
Start Page Number: | 947 |
End Page Number: | 960 |
Publication Date: | Jun 2015 |
Journal: | Production and Operations Management |
Authors: | Rapoport Amnon, Mak Vincent, Gisches Eyran J |
Keywords: | decision, programming: dynamic, game theory, networks, learning, markov processes |
We report the results of an experimental study of route choice in congestible networks with a common origin and common destination. In one condition, in each round of play network users independently committed themselves at the origin to a three‐segment route; in the other condition, they chose route segments sequentially at each network junction upon receiving en route information. At the end of each round, players received ex‐post complete information about the distribution of the route choices. Although the complexity of the network defies analysis by common users, traffic patterns in both conditions converged rapidly to the equilibrium solution. We account for the observed results by a Markov adaptive learning model postulating regret minimization and inertia. We find that subjects' learning behavior was similar across conditions, except that they exhibited more inertia in the condition with en route information.