Abstract
User generated (e.g., peer-to-peer or word-of-mouth) reviews and professional experts’ reviews are important sources of external information that consumers use in making consumption decisions, but studies of their simultaneous effects is scarce. We develop a conceptual model for hypothesizing the simultaneous effects of the volume and valence of user and expert reviews on sales (i.e., box-office) revenue in the consumption of entertainment products (i.e., movies). We gather and analyze the User Generated Reviews (UGRs) using a text processing algorithm and evaluate resulting semantic networks to validate our approach. Combining these data with other relevant data from multiple sources for all Bollywood movies released over a six month period, we test the hypotheses proposed in the model. We find that, after controlling for effect of expert reviews, both volume and valence of user generated reviews have significant positive association with box-office revenue; however, valence evidences a curvilinear (saturation) effect such that positivity effect shows decreasing returns at high positivity levels. We also find that expert reviews positively affect box office revenue with little evidence of saturation or amplifying effects.
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