Herding behavior in C2C e-commerce: Empirical investigation in China

The objective of this study is to identify the phenomenon of herding behavior in customers' online purchasing decision. We attempt to explore the effect of historical transaction volume, ratings and price premium on the customers' purchasing decision and their final transaction volume. Based on the panel data collected from Taobao, the largest C2C e-Commerce website in China, linear regression analysis was performed to test the significance of the effects. This study revealed that historical transaction volume, positive ratings and neutral ratings had a significant positive effect on the consumer online purchasing decision, but negative ratings and price premium with a negative effect. We also applied entropy theory to validate the existence of herding behavior from the perspective of information theory, and with a salient result.