The Secret behind “Hot Sale” – Information Cascade and Online Shopping Trends
Source:
https://dl.acm.org/doi/abs/10.1145/3482632.3487492
https://ieeexplore.ieee.org/abstract/document/8451903
Information cascades tend to occur when people make decisions based on the popular trend of choices or adopt how others approach certain issues, and the decisions are in order. Nowadays, internet connects people closer to each other, providing a more significant potential for information cascade, which influences trends such as online shopping behavior. For example, since other people’s purchase records of certain items are readily available on online shopping sites (while people cannot quickly get these data in offline shops), people tend to make their decisions based on others’ previous choices, such as total sales volume, ranking, or product rating.
Specifically, in the article “Research on Online Shopping User Behavior Based on Information Cascade,” the authors Mingsheng Zhao and Yueshu Zhao argue that online consumer behavior can be heavily influenced by information cascade. They note that the information asymmetry nature of online shopping makes users difficult to truly perceive the qualities of products, so they rely more on the decision of other users. This observation let me think of the guessing “majority blue” and “majority red” experiment discussed in class, where the one ball each participant draw is equivalent to the limited product information one can observe during online shopping, while the previous participants’ decision act in the same way as the online purchasing records of a product. Similarly, people can only know what others eventually decided to buy from the records (and perhaps more concrete information from comments), but not why they bought it.
Interestingly, the study also found out that online reputation or qualitative reviews will have less impact on product sales when users are highly affected by information cascade, which means that people are influenced heavily by the popularity ranking of products (number of sales) rather than concrete reviews provided by others. The strong positive correlation between the popularity ranking of certain goods and the following sale volume indicates a potential for polarization: the popular goods tend to become extremely popular when the information cascade continues, while it is hard to promote the sale of lower rank goods once the trend has formed. In some cases, researchers even observe the failure of demand law, that price has no significant impact on the sale volume of low-popularity items, which means lower prices will not attract people to buy non-popular items online.
This paper provides an excellent example of applying the cascade model and Bayes’ rules we learned in class to real-world cases to understand and predict consumer behavior. In the future, more studies might be conducted on ways to use information cascades to design marketing strategies to increase sales for specific products in the business field. It can also help promote particular prosocial behavior, such as the government could publish data showing many people have received COVID vaccination to encourage more people to get the vaccination.