Customer behavior based modeling of price dispersion in C2C market

Product price dispersion is an important index to evaluate the efficiency of C2C market. However, the linear models appeared in former researches have some limitations to explain the phenomena of price dispersion. In this work, multi-agent modeling methodology is introduced to model and simulate the process of price dispersion in order to break the restrictions in times and spaces. Three key elements of cause, impact factor and affection measure were analyzed. The product price dispersion evolution model was proposed including business behavior model and customer behavior model that combines business quantity, business credit, and customer type. Repast platform was utilized to simulate the product price dispersion in C2C market, and the history decision times recorded by customer was used to discuss the affection of different index values on price dispersion. All the above work tends to offer a support for the C2C market manager to improve market efficiency.