Information Disclosure for Increasing User Satisfaction From a Shared Ride

Abstract

On-demand ridesharing services play a crucial part in the development of modern smart cities. Unfortunately, despite their advantages, not many people opt to use them. We believe that increasing the user satisfaction from the services will cause more people to utilize them. Sometimes, it is possible to increase user satisfaction by providing accurate information related to the alternative modes of transportation, such as a private taxi ride and public transportation. For example, a passenger may be more satisfied with a shared-ride if she is told that a private taxi ride would have cost her 50% more. The challenge is thus to decide which information should be revealed to the user in order to increase the user satisfaction. To address this problem, we model our environment as a signaling game and analyze the perfect Bayesian equilibria for three agents’ classes: (1) the honest agent model, in which the agent must only provide truthful information, (2) a no utility for lying model, in which the agent receives no utility if it elects to provide false information, and (3) a penalized false information model, in which the agent is penalized for providing false information. We show that in the honest agent model and in the no utility for lying model, the agent must reveal all the information regarding the possible alternatives to the passenger. However, in the penalized false information model, there are two types of equilibria, one in which she is truthful (but must keep silent sometimes), and the other, in which the agent provides false information. The latter equilibrium type includes equilibria that seem unreasonable. Therefore, we propose a novel criterion to filter out such equilibria, and demonstrate its usefulness in another game.