DYNAMIC PRICING IN THE SHARING ECONOMY: A CLASSIFICATION STUDY BASED ON USER BEHAVIOR

Abstract

Dynamic pricing has become a fundamental mechanism in the sharing economy, yet its interaction with user behavior remains underexplored. This study aims to systematically classify user behavioral patterns and analyze their influence on dynamic pricing strategies. Using a mixed-methods approach, we collected and analyzed large-scale transaction data from ride-sharing and accommodation platforms, combined with user surveys to identify behavioral traits. The findings reveal three distinct user archetypes: price-sensitive bargain seekers, convenience-oriented premium users, and flexibility-driven spontaneous bookers. Each archetype responds uniquely to dynamic pricing fluctuations, affecting platform revenue and user retention. Notably, price-sensitive users exhibit high elasticity but low loyalty, while premium users prioritize service quality over cost. The study underscores the importance of segment-specific pricing models to optimize platform performance and enhance user satisfaction. These insights provide actionable strategies for sharing economy platforms to refine their pricing algorithms and foster long-term engagement.