Abstract
Digital goods are increasingly produced by average individuals in a serialized fashion. However, it is unclear whether users engage in herding in the consumption and purchase of such digital goods and what the moderators of the herding effect are. Thus, we propose a simultaneous equations model based on herding theory to theoretically examine users’ potential herding behavior through two competing effects: the private signal effect and the sequential actions effect, which refer to the impact of the private signals and observed sequential actions of others on user quality inference and herding, respectively. The model is implemented in a hierarchical Bayes framework, and it is estimated using data from the top Chinese literature site. The empirical results suggest that users engage in rational herding in both digital book consumption and purchase on the focal site and that the herding bias is surprisingly stronger for purchasing. Product features significantly mitigate the herding bias, while the reputation of the producer and competition exacerbate the herding effect. The impact of this rational herding is also quantified. This study offers new insights and important theoretical and managerial implications for marketing researchers, amateur producers, marketing managers, and publishers.