Exploring heterogeneity in preferences for Mobility as a Service: An airport ground access case in Qingdao, China

Abstract

Mobility as a Service (MaaS) presents a promising solution to alleviate road congestion in airport-urban corridors by integrating multimodal transportation services. This study investigates heterogeneity in user preferences for MaaS through a case study of Qingdao Jiaodong International Airport in China. A Latent Class Choice Model (LCCM) framework was employed to analyze stated preference data collected via choice experiments, focusing on MaaS bundling, pricing, and individual attributes. Three distinct user segments were identified: Strong Supporters, primarily young, low-income, non-local travelers favoring public transport-based MaaS; Conditional Supporters, high-income frequent flyers open to MaaS if it matches taxi-like convenience; and Non-Supporters, older, car-owning residents resistant to MaaS. Results reveal significant heterogeneity in preferences, driven by age, income, car ownership, and travel frequency. The study highlights the importance of tailored MaaS packages: cost-effective public transport bundles with discounts for Strong Supporters, on-demand services for Conditional Supporters, and car-sharing incentives for Non-Supporters. Findings underscore the need for differentiated marketing strategies and equitable service design to enhance MaaS adoption in airport access scenarios. This research provides actionable insights for policymakers and operators to optimize MaaS implementation in suburban airport contexts, addressing challenges such as travel time reliability, multimodal integration, and user-specific needs.