Research on the Design of High-Speed Rail Waiting Service System Based on the Fogg Behavior Model

With the rapid expansion of China's high-speed rail network, the service efficiency bottleneck in large hub stations is becoming increasingly prominent, particularly during the waiting process. Traditional service systems lack human-centric thinking, leading to poor passenger experience and low operational efficiency. This study innovatively introduces the theoretical framework of the Fogg Behavior Model (FBM) to construct a user-behavior-driven high-speed rail waiting service system. FBM posits that a behavior (B) occurs only when three elements converge simultaneously at a moment: Motivation (M), Ability (A), and a Trigger (T) (B=MAT). Taking Dalian North Station as a case study, this research employs a multi-method approach including environmental surveys, user interviews, behavioral observations, and questionnaires (N=432) to systematically diagnose pain points in the waiting service. Analysis reveals a "bimodal distribution" of pain points: first, "High Motivation-Low Ability" (HM-LA) bottlenecks, where passengers have strong intentions but face execution barriers; second, "Low Motivation-High Ability" (LM-HA) missed opportunities, where passengers have the ability but lack immediate motivation to act. In response, this study proposes a "Dual-Track Driving" design strategy: optimizing physical service touchpoints on one hand, and developing digital service carriers on the other, integrating them into a synergistic system via a service blueprint. The core innovation lies in constructing a "Fogg-Service" dual-dimensional design framework that systematically translates behavioral intervention strategies into concrete service processes and interaction designs. A prototype comprising service robot hardware and an APP interactive system was developed and evaluated through usability testing and A/B testing. Test results show a 42% improvement in key task completion efficiency and an 89% user satisfaction rate. This research confirms the significant translational value of behavioral science models in complex public service scenarios and provides a methodology with both theoretical foundation and practical reference for service innovation in high-speed rail hubs.