Research On The Herd Behavior Of Online Shopping Users Based On Information Cascades

In recent years,China's e-commerce industry has experienced great advances,and online shopping has become an important part of modern business activities.With the rapid growth of the number of online shopping users and online retail sales,the number of products on major e-commerce sites has exploded.Online shopping users encounter a serious “information overload” problem,and there is often a lot of uncertainty when they making purchasing decisions.On the one hand,online users often lack sufficient knowledge and time to make reasonable decisions during online shopping;On the other hand,on the e-commerce platform,online shopping users can observe other people's choice easily.Many e-commerce platforms provide online shopping users with decision support tools,such as product rankings and online review information.In such a situation,herd behavior is most likely to occur when online users shopping online.Information cascades is one of the main drivers of herd behavior.Research on herd behavior of online users based on information cascades has become a hotspot in the field of information systems.However,most studies have ignored the moderating effects of product types and product prices.In fact,product types and product prices may also have important impacts on consumer decision-making.Previous research has shown that consumers are more likely to make decisions based on their own knowledge when evaluating search products.However,when evaluating experience products,consumers are very likely to rely on the actions of others.In addition,consumers need to pay more risk when choosing a high-priced product than a low-priced one.The existed research has confirmed that when consumers choose products with higher risk,they will use more decision support tools to help them make decisions.Therefore,we collect the data that occurs in the real environment,conduct an empirical test on the herd behavior of online shopping users from the perspective of information cascades,and further study the moderating effect of product types and prices on the information cascades behavior of online shopping users.From November 6,2018 to March 5,2019,we collect the product data of the Seagull flagship store,the Jules flagship store,the Dabao flagship store and the Hailan Mystery flagship store from Tmall Mall every day.These data build the data set we study.We use panel data regression analysis method and difference-in-difference method to statistically analyze the research data and conduct empirical tests on the research hypotheses.The research found that in online shopping,product ranking has a positive impact on product sales,which is consistent with the predictions of the information cascades literature.Compared with the purchase of search products,online shopping users have more significant information cascades effects when purchasing experience products.Compared with buying low-priced products,online shopping users have a more significant information cascading effect when buying high-priced products.In addition,the information cascades effect of high-priced experience products is the strongest among high-priced experience products,high-priced search products,low-priced experience products,and low-priced search products.The information cascades effect of low-priced search products is the weakest.Comparing low-priced experience products with high-priced search products,the result found that the information cascades when purchasing low-priced experience products is stronger.Moreover,the study found that if only a single dimension of product price or product type is considered,the moderating effect of product price or product type is significant.However,when considering both product prices and product types,the interaction between product prices and product types is significant,and the adjustment effect of product types is significant,but the adjustment effect of product prices is not significant.This shows that if only one-dimensional adjustment effect is considered,the research results may be biased.The research in this paper has important theoretical value for improving and expanding the research on herd behavior of online users,promoting theoretical innovation in the field of e-commerce.In addition,the research in this article has important management implications for online retailers and e-commerce platform managers.Online retailers need to attach great importance to the impact of product rankings and take effective measures to improve product rankings.Moreover,onlineretailers need to develop differentiated marketing strategies for different types and prices of products.For experience products and high-priced products,more resources need to be invested to increase the popularity of the products.Specifically,when they formulating a ranking promotion program,the most resources or costs should be invested for high-priced experiential products,followed by low-priced experiential products,high-priced search products ranked third,and low-priced search products the least.For the managers of electronic commodity platforms,they need to formulate more scientific and reasonable product ranking rules and make them publicly available.They should severely crack down on the false trading of the network pushers and the network sailors,and strive to maintain a normal network economic order.