Word-of-Mouth, Observational Learning, and Product Adoption: Evidence from an Anime Platform

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We quantify the effects of word-of-mouth and observational learning on consumers' product adoptions. Understanding whether these two forces provide different and unique information or whether one is redundant in the presence of the other is crucial for companies' information provision strategies. We differentiate between the effects of word-of-mouth and observational learning from friends (personal network) and the effects of word-of-mouth and observational learning from the whole community (``community network). The relative importance of word-of-mouth and observational learning at each network level provides guidance for companies regarding their platform design. Our unique data come from an online anime platform containing individual-level data on users' networks, product adoptions, and ratings of animes. Our results reveal two segments of users: a small segment of Enthusiasts who tend to watch more animes and to adopt them earlier, and a larger segment of Regular Watchers who tend to watch fewer animes and to adopt them later. For both segments of users, word-of-mouth from the community network is the largest driver of users' product adoptions followed by observational learning from the community network. Thus our results show that word-of-mouth and observational learning provide unique and different information that individuals use in their product adoption decisions and that the community network is the primary source of information. Lastly, using our results, we test for image utility, for observational learning creating product awareness versus transferring unobserved quality information, and for rational herding.