Information Cascades in E-Commerce
Common sense would dictate that customers want to buy products that are highly rated by other customers. Qihua Liu, Shan Huang, and Liyi Zhang further explore this concept in their paper The influence of information cascades on online purchase behaviors of search and experience products. We learned in class that information cascades are essentially the concept of “following the crowd”, more formally, to what extent you will imitate others even if your private information suggests that you should do otherwise. We also discussed how marketers need to somehow make buying decisions of early adopters while potentially hiding their satisfaction (if the product is truly a bad product) to create information cascades that work for them. Liu, Huang, and Zhang use data from a large Chinese e-commerce site to determine the effects of information cascades in real life. They found that users’ choice of products was indeed heavily influenced by product popularity rankings. Additionally, they found that volume of reviews was not a big influential factor for products with high rankings, but it indeed was for products with low rankings. This follows the information cascade theory that we learned in class that people are likely to ‘follow the crowd’. More interestingly, they found that user ratings actually didn’t have much of an effect on users’ purchase decisions. This is surprising to me because I always look at user ratings whenever I buy something online. One possible explanation for this is that to get to a high ranking, a product’s user ratings must pass a certain point. I don’t think many people would buy a product with a 1 star ratings, even if it was ranked #1 or #2. However, products with 1 star ratings won’t usually get to #1 and #2. The authors also state that their results that ratings don’t impact sales differ from another study’s, suggesting that this issue is very complex.
As for me, I wonder whether there’s a tipping point ranking wise that elevates your product to the next level of success. I can’t imagine that the changes in sales when one increases ranking is constant. For example, I wonder whether moving from #4 to #3 or moving from #3 to #2 in ranking makes a bigger relative difference. This is something I’d love to further research.
Source: https://www.researchgate.net/profile/Liyi-Zhang-2/publication/299503546_The_influence_of_information_cascades_on_online_purchase_behaviors_of_search_and_experience_products/links/59c7a678a6fdccc71923d3db/The-influence-of-information-cascades-on-online-purchase-behaviors-of-search-and-experience-products.pdf