Abstract

With the improvement of China's Internet penetration and a shift in consumption consciousness, user scale and market size of online trading reached a new height, and C2C e-commerce has the most rapid development. As the seller and buyer of online transaction in a state of isolation in time and space, there is serious information asymmetry. So the reputation problems that exist in the online trading have become the concern of many people. The seller reputation can evaluate the past behavior of seller. Hence, the higher reputation can reduce the potential risk of the transaction and increase the transaction tendencies and actions of buyers. Due to the biggest market share of the C2C e-commerce platform in China and a higher awareness of user groups, Taobao.com is selected as research subject. We collected 1379 useful seller reputation information from five merchandise categories. Then, hypotheses about the influence of online sales volume and price were put forward, and the research model was established. Next, correlation analysis and linear regression analysis was employed to test hypotheses and the research model in the C2C online trading environment. The results showed that reputation rating and reputation score has a significant positive effect on sales volume and price, and there is a negative impact on the sales of the existence of violation. Match degree of description, seller attitude and delivery speed in the dynamic rating have a greater impact on sales price than volume. Match degree of description and delivery speed has a promoting role. Freight borne by the seller has a positive impact on sales volume.

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