Abstract In this paper, we evaluate a lottery-based revenue-neutral incentive mechanism to reduce the congestion in urban transportation systems. Specifically, we test the use of random lottery-based reward schemes to promote public transit usage during off‐peak periods. We derive the theoretical equilibrium for this decision-making game and test the validity of the proposed mechanism through monetized laboratory experiments. We use methods from experimental economics to investigate the behavioral assumptions within such an incentive-based mechanism. We find counterintuitive results where a Pure Nash Equilibrium explains behavior in one regime and Quantal Response Equilibrium explains behavior in another regime. Specifically, there is no shift to off-peak periods when the expected value of traveling in the off-peak is less than that at peak, which is explained by a Pure Nash Equilibrium. However, there is a substantial shift to the off-peak period when the expected value of traveling in the off-peak is larger than that of the peak, but much less than that predicted by a Pure Nash Equilibrium. The Quantal Response Equilibrium performs reasonably well in this condition, and we conclude that risk attitudes play a significant role in explaining behavior in lottery-based incentive mechanisms. This study, which relies on the gamification of travel behavior, finds that the proposed mechanism can provide a sustainable shift in users’ choices.
Highlights Developed a lottery-based incentive revenue-neutral mechanism to promote off-peak periods. The proposed mechanism relies on the gamification of travel behavior in transit. The incentive mechanism was tested using monetized experiments. Results show that the observed outcomes differ from the predicted equilibrium. Users' risk attitudes play a significant role in lottery-based incentive schemes.
An endogenous lottery-based incentive mechanism to promote off-peak usage in congested transit systems
Transport Policy ; 46 ; 46-55
2015-11-13
10 pages
Article (Journal)
Electronic Resource
English
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