How Do Consumers Evaluate the Identical Product on Competing Online Retailers? A Big Data Analysis Approach Using Consumer Reviews

Date
2016-11-09
Authors
Kang, Ji Hye
Jang, Sungha
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
Journal Issue
Series
Department
Abstract

For big data analysis practice, this study collected both types of consumer review data, a structured form (i.e., review ratings) and an unstructured form (i.e., review text), on a fashion item from two different online retailers. Using the collected data, this study aims to identify 1) consumers' evaluation criteria on a fashion product, 2) positive or negative sentiment toward the product, and 2) the impact of these identified variables on consumers' ratings. For online retailers, Amazon.com and Macys.com were selected for comparison. The results identified six evaluation criteria from consumer reviews such as authenticity and inside design and revealed that Macy's online consumers are, in general, more satisfied with the fashion product and have more specific evaluation criteria satisfying themselves, compared to Amazon.com's consumers. The results suggest that product and service attributes influencing consumers' satisfaction and evaluation are different across online retailers and its consumers, even on the same product.

Comments
Description
Keywords
Citation
DOI
Source