Estimating the Effect of Online Consumer Reviews: An Application of Count Data Models

Sangwon Park

doi:10.1007/978-3-319-44263-1_9

Estimating the Effect of Online Consumer Reviews: An Application of Count Data Models

Sangwon Park

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Citations (Scopus)

Abstract

This study estimates the effect of online consumers’ star ratings on perceived evaluations of consumer reviews such as usefulness and enjoyment. The data includes 5090 online reviews of about 45 restaurants located in London and New York respectively. The results reveal curvilinear (U-shaped) relationships between star ratings and usefulness and enjoyment. That is, online consumers perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings. Additionally, the findings of this research indicate the usefulness of the negative binomial model, which allows researchers to manage the features of count data as well as address the heteroscedasticity in linear regression and the overdispersion problem in the Poisson regression model.

Original language	English
Title of host publication	Tourism on the Verge
Publisher	Springer Nature
Pages	147-163
Number of pages	17
DOIs	https://doi.org/10.1007/978-3-319-44263-1_9
Publication status	Published - 2017

Publication series

Name	Tourism on the Verge
Volume	Part F1056
ISSN (Print)	2366-2611
ISSN (Electronic)	2366-262X

Bibliographical note

Publisher Copyright:
© 2017, Springer International Publishing Switzerland.

Keywords

Count data models
Information evaluation
Negative binomial model
Online consumer reviews

Access to Document

10.1007/978-3-319-44263-1_9

Cite this

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abstract = "This study estimates the effect of online consumers{\textquoteright} star ratings on perceived evaluations of consumer reviews such as usefulness and enjoyment. The data includes 5090 online reviews of about 45 restaurants located in London and New York respectively. The results reveal curvilinear (U-shaped) relationships between star ratings and usefulness and enjoyment. That is, online consumers perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings. Additionally, the findings of this research indicate the usefulness of the negative binomial model, which allows researchers to manage the features of count data as well as address the heteroscedasticity in linear regression and the overdispersion problem in the Poisson regression model.",

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doi = "10.1007/978-3-319-44263-1\_9",

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AB - This study estimates the effect of online consumers’ star ratings on perceived evaluations of consumer reviews such as usefulness and enjoyment. The data includes 5090 online reviews of about 45 restaurants located in London and New York respectively. The results reveal curvilinear (U-shaped) relationships between star ratings and usefulness and enjoyment. That is, online consumers perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings. Additionally, the findings of this research indicate the usefulness of the negative binomial model, which allows researchers to manage the features of count data as well as address the heteroscedasticity in linear regression and the overdispersion problem in the Poisson regression model.

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KW - Information evaluation

KW - Negative binomial model

KW - Online consumer reviews

UR - https://www.scopus.com/pages/publications/85089194879

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BT - Tourism on the Verge

PB - Springer Nature

ER -

Estimating the Effect of Online Consumer Reviews: An Application of Count Data Models

Abstract

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Bibliographical note

Keywords

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