| dc.description.abstract | The prosperity of online shopping contributes to the explosive growth of eWOM.
Customer reviews are considered as one of the most important types of eWOM.
While assisting customers in forming comprehensive overviews of products and
services, the sheer number of reviews may cause information overload and reduce
customers’ satisfaction with decision making and purchase experiences.
In this study, we propose a new type of decision aid tool – a feature-based review
summary to address the issue. Based on theoretical and empirical work in
marketing, decision making, and support systems, we develop a set of hypotheses
and tests through two experiments using manipulated e-commerce websites selling
cameras.
Though review summary’s effectiveness in moderating the relationship between
information overload and process satisfaction is not proved directly, we find that
the summary increases customers’ perceived review helpfulness, which
subsequently increases customers’ process satisfaction under conditions of limited
information overload.
Our research is an interdisciplinary study that explores the role of feature-based
review summary in assisting customers’ purchase decision making under conditions
of information overload. Theoretically, it contributes to the literature by testing the
efficiency of a summary as a decision facilitating tool. Practically, it demonstrates
the usefulness of feature-based summary for popular search products showing a
certain level of similarity. | nb_NO |
