Word-of-Mouth in Personal Networks and Community Networks
https://pubsonline.informs.org/doi/abs/10.1287/mksc.2019.1155
The study, Word of Mouth, Observed Adoptions, and Anime-Watching Decisions: The Role of the Personal vs. Community Network, focuses on diffusion in different network levels. The effects of other people’s adoptions and word-of-mouth are quantified on consumer’s product decisions. The personal network, which included friends, and the related adoptions and word-of-mouth was studied in comparison to the community network, which included the entire community, and its related adoptions and word-of-mouth.
In the study, an online anime platform was observed, and the results revealed the adoptions and word-of-mouth within both the personal network and the community network had positive effects on the consumer’s own decision to watch a particular anime.
The platform contained information on a user’s friendship network, product adoptions, ratings of animes, and more. It was found that word-of-mouth from the community network played the most important role in the decision-making of a particular user. Although word-of-mouth was observed to have a greater influence on the decision to watch a particular anime or not, observed adoptions (observing other people watch a particular anime) also served an important role.
This study is related to the topics of network diffusion and information cascades that we learned about in class. Following the model for information-based cascades, there is a decision to make. This is the decision of whether or not to watch a particular anime. People make decisions in a sequence can be mirrored by a user on the anime network that is able to see what animes other people in the community network are watching. The users are able to see what animes people are watching but generally do not know the exact reason why others are watching a particular anime.
It is an example of an information cascade because as users see that many others in the community are watching a particular anime, they decide to watch that particular anime as well. This would be an example of an indirect benefit. If so many other people seem to enjoy that anime, the user is more likely to think they would enjoy it as well. As an information-based benefit, the behavior of others conveys information that is useful to the user, and they follow the “wisdom of the crowd”.
In a way, it can also be related to network diffusion because this cascade stays within users of the anime network, and it would probably be harder for this information to travel to non-users.