The Impact of Dynamic Pricing on Customer Satisfaction and Continuous Usage Behavior in Ride-Hailing Application

This study explores how dynamic pricing strategies by Transportation Network Companies (TNCs) affect users’ satisfaction and continuous usage behavior. While prior research has emphasized technical aspects, behavioral impacts remain underexplored, despite reports that 85% of Uber users are dissatisfied with cancellations and excessive pricing. This research investigates the roles of dynamic pricing, price fairness, price sensitivity, and privacy concerns in shaping user behavior. Quantitative method was applied using Structural Equation Modeling (SEM), with data collected via online surveys from 446 ride-hailing app users or former users in JABODETABEK, Indonesia, between April and May 2025. Non-probability sampling was used, and SmartPLS4 tested eleven hypotheses, eight of which were significant. Results indicate that continuous use of ride-hailing services under dynamic pricing is primarily influenced by users’ perceptions of fairness and overall value, while privacy concerns and price sensitivity have less impact. Findings provide insights into improving TNC pricing strategies and user retention. Keywords—Dynamic Pricing, Ride-Hailing, Customer Satisfaction, Continuous Usage Behavior, Price Fairness