Research on online shopping user behavior based on information cascade

Information cascades are common in real social life, because of information cascades can lead to blind follow-up by users, it is easy to have a bad impact on society. This paper proposes a new method to research on the online shopping user behavior based on information cascades. By collecting date from jd between October 1, 2019 and September 30, 2020, this paper constructs unbalanced panel data, empirically tests the information cascade effect in online shopping users’ Behavior, and study the mixed impact of information cascade and online word-of-mouth on users’ shopping behavior. The results show that the relative popularity of goods has a significant impact on its sales, showing an obvious information cascade effect. The number of comments has no impact on the sales volume of high ranked goods, but has a positive and significant impact on the sales volume of low ranked goods, and the user score has no impact on the sales volume of goods. The law of demand is still valid for high ranked commodity sales. For the lower ranked products, the price represents the quality information of the products and has a positive impact on the sales volume.