Yunhui Fan / Central University of Finance and Economy
Shuhang Guo / Central University of Finance and Economy
Mingjia Hang / Central University of Finance and Economy
The past decades has witnessed a boom in online music industry as a result of rapid development of information technology. This emerging field, however, lacks appropriate pricing methods. In order to coordinate with the marketing strategies of online music and guarantee satisfactory returns for both sellers and buyers of online music, a pricing model based on Stackelberg Model and Particle Swarm Model is proposed. This paper starts with an introduction of several traditional methods for pricing online products. Then it demonstrates Hypothesis and relevant variables in the new model, categorizes online musical products into different groups according to their qualities and uses PSO algorithm to acquire price and quantity trends of online music, which contribute to solving the optimal price at given time. Finally, the paper compares the model with traditional pricing models to test the validity of online music.