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Summarizing Customer Reviews: A New Way to Optimize eWOM for Better Purchasing Experience

Chen, Huan; Nikitina, Anastasiia
Master thesis
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Preliminary Thesis.pdf (1.356Mb)
URI
http://hdl.handle.net/11250/2578732
Date
2018
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  • Executive Master of Management [67]
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.
Description
Masteroppgave(MSc) in Master of Science in Strategic Marketing Management - Handelshøyskolen BI, 2018
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Handelshøyskolen BI

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