Calyber: A Ridesharing Game

This case introduces Calyber, a simulation-based game designed to provide a hands-on and engaging experience in developing real-time pricing and matching decisions for shared ride services, where multiple riders are pooled into a single vehicle. Students design and implement dynamic pricing and matching policies using a rich historical ridesharing data set, competing for top performance on a holdout test set. Through this case, students gain practical insight into stochastic dynamic decision making within a modern, relevant, and data-driven context. Results from previous class implementations provide strong evidence of enhanced learning and engagement. Funding: This work was supported by the National Science Foundation [Grant 2517861] and the Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2022-03524]. Supplemental Material: The Calyber Teaching Note and supplemental files are available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .