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An investigation into online reviewers' behavior

An investigation into online reviewers' behavior Purpose – The current research aims to explore variables that explain the differences in online reviewers' behavior. Design/methodology/approach – The authors' panel dataset is compiled from Amazon.com's book section and uses publicly available information about reviewers in combination with the reviews they wrote. The authors utilize the Pareto/NBD model with time-invariant covariates. The model's parameters are estimated using maximum likelihood estimates (MLE) with MATLAB software. Findings – This study contributes to the literature by exploring how the characteristics of reviews and the reviewers might shape consumer review frequency and continuity. Specifically, the authors' results show that review ratings, comments on a review, and helpful votes have a positive association with review frequency and continuity. Furthermore, the length of the textual review has a positive relationship with review frequency, but a negative relationship with review continuity. Relative to anonymous reviewers, people who write reviews and use their real names post reviews less often, but their review continuity is longer. Originality/value – This paper is the first to identify empirically variables that explain review frequency and continuity, thus enabling companies to gain a better understanding of their reviewer base and hence to manage online word-of-mouth more efficiently. It is the first study to apply a well-known behavioral model to address online review behavior. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Marketing Emerald Publishing

An investigation into online reviewers' behavior

European Journal of Marketing , Volume 47 (10): 16 – Sep 20, 2013

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0309-0566
DOI
10.1108/EJM-11-2011-0625
Publisher site
See Article on Publisher Site

Abstract

Purpose – The current research aims to explore variables that explain the differences in online reviewers' behavior. Design/methodology/approach – The authors' panel dataset is compiled from Amazon.com's book section and uses publicly available information about reviewers in combination with the reviews they wrote. The authors utilize the Pareto/NBD model with time-invariant covariates. The model's parameters are estimated using maximum likelihood estimates (MLE) with MATLAB software. Findings – This study contributes to the literature by exploring how the characteristics of reviews and the reviewers might shape consumer review frequency and continuity. Specifically, the authors' results show that review ratings, comments on a review, and helpful votes have a positive association with review frequency and continuity. Furthermore, the length of the textual review has a positive relationship with review frequency, but a negative relationship with review continuity. Relative to anonymous reviewers, people who write reviews and use their real names post reviews less often, but their review continuity is longer. Originality/value – This paper is the first to identify empirically variables that explain review frequency and continuity, thus enabling companies to gain a better understanding of their reviewer base and hence to manage online word-of-mouth more efficiently. It is the first study to apply a well-known behavioral model to address online review behavior.

Journal

European Journal of MarketingEmerald Publishing

Published: Sep 20, 2013

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