How can social commerce be boosted? The impact of consumer behaviors on the information dissemination mechanism in a social commerce network

Abstract

This paper investigates how various consumer behaviors influence sales volume in social commerce through information dissemination. We use a modified SIR dynamic model to study these effects and how they vary under different maximum message lifetimes and as the number of network nodes varies. We conduct parameter sensitivity analysis to measure the influences of consumer behaviors on the sales volume. The simulation results indicate that consumer behaviors during information dissemination can significantly influence the outbreak size of the information and the sales volume. Specifically, a higher information-spread probability will increase the outbreak size of the message. A higher first-purchase probability could accelerate the increase in sales volume, especially when the maximum message lifetime is long and the number of nodes is large. Besides, the regular-purchase behavior has a positive impact on the acceleration, while the discard-information behavior after the first purchase has an opposite effect. We verify our model using data collected from two websites: Sina Weibo and Taobao. This study helps social commerce marketers understand how consumer behaviors can influence sales volume through information spread and aids them in modeling this mechanism.