Abstract: This study focuses on the value differences and evolutionary patterns of data assets across distinct application scenarios, proposing a practical framework for scenario-based dynamic pricing. A system dynamics model is developed based on a dual-scenario classification of “self-use” and “transaction-oriented” data applications, structured around development, application, and risk dimensions. Simulation functions are embedded to capture coupling effects and time delays. Using Vensim , multi-scenario simulations and sensitivity analyses are conducted to identify key drivers and feedback loops in the value evolution process. The simulations show that development contributes foundationally to asset growth, application value demonstrates strong amplification effects, and risk control improves system stability. Flow efficiency, value derivation, and data integrity are identified as the most elastic variables influencing value outcomes. The proposed model offers a structured and adaptive approach to valuing data assets under diverse scenarios.

Key words: Dynamic pricing, Data assets, System dynamics, Value assessment；Contextualization； Simulation experimen