Title :
Why Aren´t the Stars Aligned? An Analysis of Online Review Content and Star Ratings
Author :
Mudambi, Susan M. ; Schuff, David ; Zhewei Zhang
Author_Institution :
Temple Univ., Philadelphia, PA, USA
Abstract :
Consumer-generated product evaluations posted on online retailer or third party web-sites have been shown to increase buyer trust and aid consumer decision making. These online reviews typically have two components: star ratings and review text. This can communicate a complex, conflicting message to consumers, as the text of a review carries more nuance than what can be communicated through a simple numerical score. Misalignment between the star rating and the text can lead to increased consumer cognitive processing costs, suboptimal purchase decisions, and lower overall utility of the review site. This study seeks to understand where this misalignment is mostly likely to occur. We find that star rating/review text misalignment occurs more often for (1) experience goods, and (2) goods that receive high star ratings. Misalignment is especially pronounced for experience goods with high star ratings.
Keywords :
Web sites; consumer behaviour; content management; decision making; purchasing; retail data processing; trusted computing; buyer trust; consumer cognitive processing costs; consumer decision making; consumer-generated product evaluations; experience goods; numerical score; online retailer; online review content; review site; review text misalignment; star ratings; suboptimal purchase decisions; third party Web sites; Cameras; Classification algorithms; Consumer behavior; Decision making; Educational institutions; Guidelines; Software; internet retailers; machine learning; online reviews; search and experience goods; text mining;
Conference_Titel :
System Sciences (HICSS), 2014 47th Hawaii International Conference on
Conference_Location :
Waikoloa, HI
DOI :
10.1109/HICSS.2014.389