Abstract
E-commerce platforms have a plethora of information available online in the form of online product reviews and product ratings. Although these product reviews are very helpful to consumers for making their buying decisions, it becomes very difficult to extract relevant information pertaining to product features. In this study, we extend personalization to online product reviews by integrating literature from information systems, computer science and social psychology to understand how task complexity varies in different information environments. In a controlled laboratory experiment users took buying decisions in three different information environments: unstructured voluminous reviews, structured with aspect level summarization of reviews and personalized information by providing personalization based on the stated preferences of the user.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
