Impact of Online Review Grouping on Consumers' System Usage Behavior

Abstract

Information overload is one of the major challenges for online shoppers. One possible solution to this aforementioned problem is to take advantage of the interactive decision aids (IDAs). Prior studies on IDAs have mainly focused on information overload problems caused by the products (e.g., recommendation agents) and hence, have overlooked the information overload problems related to online reviews. However, online reviews are becoming more popular and turning into a major information source in consumer purchase decisions. To bridge this gap, this study investigates the effect of message grouping, an IDA approach supporting review browsing, onto the consumer's information processing and system usage intention. An experiment with a one-factor, three-level design was conducted to test the proposed research model. It is noted that grouping customer reviews into task-related categories significantly increases users' perceived usefulness, system satisfaction and intention to use the system next time. However, grouping customer reviews into task-distracting categories may significantly decrease users' perceived usefulness, system satisfaction and intention to use the system.