Paper Info
Title
Online Customer Reviews And Product Sales: The Moderating Role Of Signal Characteristics
Abstract
Although considerable research has been conducted to investigate how online reviews influence product sales, understanding of why consumers rely on online reviews and the effect of interactions between key metrics (volume, valence, and variance) on product sales is very limited. We develop a research framework by applying information economics and signaling theory to demonstrate that online reviews have an impact on product sales because reviews act as market signals that contain information about the quality of products. The characteristics of signals (intensity, valence, consistency, and clarity) help consumers in reducing search cost and improving evaluations on product quality. We propose that signal intensity and signal consistency moderates the relationship between online reviews and product sales. Regarding methodological contribution, we propose a multilevel text mining approach to analyze online reviews by considering nested structure of reviews and uniqueness of individual review. The results of a pilot study and discussions are presented as well.
Year
Venue
Keywords
2017
AMCIS 2017 PROCEEDINGS
Online review, information economics, signaling theory, multilevel modeling, latent Dirichlet allocation
Field
DocType
Citations 
Customer retention,Advertising,Customer to customer,Computer science,Customer reviews,Customer advocacy,Marketing
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Ying Wang100.34
Miguel I. Aguirre-Urreta25510.70
Jaeki Song363734.38