Research of online review helpfulness based on negative binary regress model the mediator role of reader participation

With the ever-increasing popularity of online reviews, understanding what makes an online review helpful has attracted increasingly more attention from both academics and practitioners. Using Elaboration Likelihood Model as the theoretical framework, this study aims to investigate the effects of specific information cues derived from the review message (difference with average rating and review title depth) and the reviewer (reviewer history expertise and reviewer network centrality degree) on online consumer reviews helpfulness. The results of negative binominal regression show that: reader participation is positively related to online review helpfulness; difference with average rating, review title depth and reviewer network centrality positively affect reader participation; while reviewer history expertise is negatively associated with reader participation; reader participation exerts significantly mediating effect between online review cues and online review helpfulness, to be more specific, reader participation fully mediates the effect of reviewer history expertise on online review helpfulness and partially mediates the effects of other three variables' on online review helpfulness.