Fashion Information Cascades and Friends-Based SNS
In this research paper, two researchers examine the friends-based SNS (social-network service), involving social connections formed through shared interests for a certain product. They can be thought of as clubs of buyers, where members exchange information about products and share preferences with each other. The network operates by allowing users to add their friends, families, and coworkers to these groups. To set up the point of their paper, they discuss other researchers’ Hirshleifer and Teoh’s work, which argued that during decision making, information in SNS spreads rapidly by imitating information in other nodes, causing the “information cascade” phenomenon that we also learned in class. This lead the original two researchers to direct the purpose of their paper to analyze the characteristics of this friends-based SNS network that are the influential variables to explain the fashion information cascade phenomenon.
Some of the paper’s assumptions and conclusions were both interesting and relevant to the course. The researchers acknowledged that strong connections between communities affect product proliferation, and not just connections inside these communities. This relates to our class discussion about how certain clusters may adopt a product, but with weak ties to others, those other clusters may not adopt at all — explained by the idea that if the cluster density is greater than some threshold q, the cluster will not adopt.
Their conclusions explained many marketing implications, but there were a couple that had unique insights. First, in order to increase the similarities in the preferences, interests, and recommendation information among the community members, there must be an increase in social and conversational comfort, importance of social relationships, and relationship intimacy reciprocity. The reason why this is so important is because people with similar interests are likely to buy similar products in similar environments — and to increase those connections among communities that was mentioned before, this is crucial and can allow product interest to spread dramatically. This is paralleled in class in which we learned that we could simply add edges among nodes to connect clusters and make them one cluster so that a product is adopted easily. Second, another marketing finding was that in order to increase the perceived usefulness of the recommended fashion information and inspire the fad-like behavior that results from following recommended information in the community, the members must have a significant sense of belonging and participation. This makes sense, and sheds some light in considering that although we’ve talked about how a person may adopt a product if some fraction of their friends has adopted the product, this may be too naive of an approach; how closely tied a consumer feels to their friends is also a consideration when considering product adoption in the context of the network.
Source: https://www.mdpi.com/2071-1050/10/5/1474