Service design for shared micromobility

Abstract

Service design for shared micromobility services, such as e-mopeds, involves decisions on service location, fleet size, pricing, and resource allocation, which are typically based on potential demand estimates. In practice, however, potential users adopt the service gradually, leading to market penetration over time. Ignoring this gradual penetration can lead to suboptimal decisions and service failures. We propose a phased optimization model to maximize profitability over a planning horizon divided into discrete periods. The model jointly determines service locations, fleet size, and spatio-temporal resource allocation while ensuring a targeted service level. To model gradual adoption, we apply an extended Bass diffusion framework in which adoption depends on service quality, defined by accessibility and availability, and social influence, reflecting the impact of current users on others’ adoption. The phased deployment strategy aligns service expansion and investment decisions with adoption growth (market penetration) over multiple periods. Applied to a bike-sharing case in Manhattan, the proposed approach improves resource allocation and increases profitability by up to 47% compared with an upfront strategy under parameter misestimation. Furthermore, ignoring service quality in the adoption model leads to a profit loss of up to 54% when user expectations are high The results shed light on the value of synchronizing service design decisions with user adoption dynamics.