Sridhar and Srinivasan (2012) note that consumers’ online ratings of a service are influenced not only by the quality of their service experiences but also by the other online ratings. The results from a model using 7, 499 consumers’ online ratings of 114 hotels support their premise. Other consumers’ online ratings weaken the effects of positive and regular negative features of service experience but can either exacerbate or overturn the negative effect of failure, depending on the quality of failure recovery. For managerial practice, these findings suggest that social influence effects make positive online product ratings a double-edged sword, exacerbating the negative effect of failure and strengthening the benefit of failure recovery.
Ludwig et al. (2012) find that the semantic content and style properties of verbatim online reviews influence online retail sites’ conversion rates. The authors employ text mining to extract changes in affective content and linguistic style properties of book reviews on Amazon.com. They find that the influence of positive affective content on conversion rates is asymmetrical, such that greater increases in positive affective content in customer reviews have a smaller effect on subsequent increases in conversion rate. No such tapering-off effect occurs for changes in negative affective content in reviews. Furthermore, positive changes in affective cues and increasing congruence with the product interest group’s typical linguistic style directly and contingently increase conversion rates.
For managerial practice, these findings suggest that managers should identify and promote the most influential reviews in a given product category, provide instructions to stimulate reviewers to write powerful reviews, and adapt the style of their own editorial reviews to the relevant product category.