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Mobility-as-a-Service (MaaS) is an emerging business model driven by theconcept of "Everything-as-a-Service" and enabled through mobile internettechnologies. In the context of economic deregulation, a MaaS system consistsof a typical two-sided market, where travelers and transportation serviceproviders (TSPs) are two groups of agents interacting with each other through aMaaS platform. In this study, we propose a modeling and optimization frameworkfor the regulation of two-sided MaaS markets. We consider a name-your-own-price(NYOP)-auction mechanism where travelers submit purchase-bids to accommodatetheir travel demand via MaaS platform, and TSPs submit sell-bids to supplymobility resources for the MaaS platform in exchange for payments. We cast thisproblem as a single-leader multi-follower game (SLMFG) where the leader is theMaaS regulator and two groups of follower problems represent the travelers andthe TSPs. The MaaS regulator aims to maximize its profits by optimizingoperations. In response to the MaaS regulator's decisions, travelers (resp.TSPs) adjust their participation level in the MaaS platform to minimize theirtravel costs (resp. maximize their profits). We analyze cross-group networkeffects in the MaaS market, and formulate SLMFGs without and with networkeffects leading to mixed-integer linear bilevel programming and mixed-integerquadratic bilevel programming problems, respectively. We propose customizedbranch-and-bound algorithms based on strong duality reformulations to solvethese SLMFGs. Extensive numerical experiments conducted on large scalesimulation instances generated from realistic mobility data highlight that theperformance of the proposed algorithms is significantly superior to abenchmarking approach, and provide meaningful managerial insights for theregulation of two-sided MaaS markets in practice.

Single-leader multi-follower games for the regulation of two-sided Mobility-as-a-Service markets