Learning When Reading : Evidence from an Online Mobile Reading Platform

Online reading platforms offer a by-chapter purchase method and implement a novel in-chapter online review function to mitigate consumer uncertainty regarding the true quality of e-books. In this study, we seek to uncover how such intervention affects consumer purchase decisions. In particular, we implement a Bayesian learning framework to unveil the consumer learning process enabled by such a by-chapter purchase method. We also investigate the textual patterns of the in-chapter reviews and their impacts on consumer decisions. Our model estimation results show that consumers learn the quality of books within different genres at a different pace. Moreover, our analysis reveals that the in-consumption reviews of different topics regarding their content have heterogeneous effects on consumers’ subsequent purchase decisions. Consumers facing more reviews that comprise a neutral or emotional discussion over the plot and those begging the author to post new chapters would be more likely to read consecutively. Finally, we discover that consumers approaching the end of a book or exposed to a list of chapters with few informative names tend to skip more chapters instead of reading continuously