Sustainable dynamic pricing for rural shared mobility-on-demand systems

Shared mobility-on-demand (SMOD) systems allow customers to request customized rides that the provider bundles through ridepooling. Owing to their flexibility and efficiency in low-demand settings, SMOD systems are expected to become a cornerstone of rural public transport. Operationally, dynamic pricing can influence which rides customers order, thereby enhancing system performance. In the literature, dynamic pricing is exclusively applied to maximize profit. However, rural SMOD services primarily provide basic mobility as a public service and should contribute to reducing the greenhouse gas emissions of passenger transportation. With this work, we present the first multi-objective, sustainable dynamic pricing approach that considers all three dimensions of sustainability, i.e., social, environmental, and economic objectives. The core idea is to set prices that maximize served demand while adhering to a dynamic lower price bound ensuring that the price of each ride at least covers its marginal cost. Thereby, our approach carefully balances the partially conflicting sustainability objectives. To accurately evaluate demand displacement and marginal cost of rides, which is crucial for making dynamic pricing decisions, we propose a post-decision rollout algorithm that anticipates the future evolution of the booking process. We comprehensively evaluate our approach based on a real-world data set of a rural SMOD provider and derive managerial insights regarding the practical impact of sustainable dynamic pricing. Our findings show that sustainable dynamic pricing achieves substantially better performance than static pricing while preventing monopoly markups, which would result from profit-based dynamic pricing.