Abstract:

To identify the key mechanisms underlying behavioral transitions， a multi-path structural model was developed encompassing user expectations， perceived service quality， overall satisfaction， complaint behavior， and continued usage intention. Empirical data were used to estimate the relationships among these variables. Building on this foundation， an agent-based simulation model was constructed， dividing users into four behavioral states “non-adoption， initial contact， active use， and regular adoption”. The model simulates the evolution of user behavior throughout the service process. Simulation results indicate that the transition rate from “active use to regular adoption” is only 36.36%， while the downgrade risk for regular adopters reaches 53.81%， representing a structural bottleneck for platform operations. Under strategy intervention scenarios， improving service reliability increases the proportion of regular adopters from 28.7% to 32.4% and reduces their downgrade rate to 50.15%. In contrast， a complaint mitigation strategy mainly targets the negative feedback pathway； although it can temporarily increase the proportion of regular adopters to 31.5%， it fails to effectively curb subsequent attrition， with the downgrade rate rising to 55.73%. This suggests that its capacity to stabilize user behavior is limited and insufficient for sustaining long-term usage relationships. The findings provide strategic support for optimizing platform service processes and managing user structure.

Key words: engineering of communications and transportation system, user behavioral evolution, satisfaction structural model, agent-based simulation, service reliability, complaint management