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Helpfulness of online consumer reviews: readers' objectives and review cues

Helpfulness of online consumer reviews: readers' objectives and review cues
Helpfulness of online consumer reviews: readers' objectives and review cues
With the growth of e-commerce, online consumer reviews have increasingly become important sources of information that help consumers in their purchase decisions. However, the influx of online consumer reviews has caused information overload, making it difficult for consumers to choose reliable reviews. For an online retail market to succeed, it is important to lead product reviewers to write more helpful reviews, and for consumers to get helpful reviews more easily by figuring out the factors determining the helpfulness of online reviews. For this research, 75,226 online consumer reviews were collected from Amazon.com using a Web data crawler. Additional information on review content was also gathered by carrying out a sentiment analysis for mining review text. Our results show that both peripheral cues, including review rating and reviewer's credibility, and central cues, such as the content of reviews, influence the helpfulness of reviews. Based on dual process theories, we find that consumers focus on different information sources of reviews, depending on their purposes for reading reviews: online reviews can be used for information search or for evaluating alternatives. Our findings provide new perspectives to online market owners on how to manage online reviews on their Web sites.
Consumer decision-making process, dual process theory, eWOM (electronic word of mouth), online consumer review, review helpfulness
99-126
Baek, Hyunmi
2bc4cdf5-297f-4fd3-87f6-ad93cc891aef
Ahn, Joongho
a29e90f1-99d2-42c6-9593-fd99767a0125
Choi, Youngseok
928c489e-7c5b-42fc-bad8-77ce717ba106
Baek, Hyunmi
2bc4cdf5-297f-4fd3-87f6-ad93cc891aef
Ahn, Joongho
a29e90f1-99d2-42c6-9593-fd99767a0125
Choi, Youngseok
928c489e-7c5b-42fc-bad8-77ce717ba106

Baek, Hyunmi, Ahn, Joongho and Choi, Youngseok (2012) Helpfulness of online consumer reviews: readers' objectives and review cues. International Journal of Electronic Commerce, 17 (2), 99-126. (doi:10.2753/JEC1086-4415170204).

Record type: Article

Abstract

With the growth of e-commerce, online consumer reviews have increasingly become important sources of information that help consumers in their purchase decisions. However, the influx of online consumer reviews has caused information overload, making it difficult for consumers to choose reliable reviews. For an online retail market to succeed, it is important to lead product reviewers to write more helpful reviews, and for consumers to get helpful reviews more easily by figuring out the factors determining the helpfulness of online reviews. For this research, 75,226 online consumer reviews were collected from Amazon.com using a Web data crawler. Additional information on review content was also gathered by carrying out a sentiment analysis for mining review text. Our results show that both peripheral cues, including review rating and reviewer's credibility, and central cues, such as the content of reviews, influence the helpfulness of reviews. Based on dual process theories, we find that consumers focus on different information sources of reviews, depending on their purposes for reading reviews: online reviews can be used for information search or for evaluating alternatives. Our findings provide new perspectives to online market owners on how to manage online reviews on their Web sites.

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More information

Published date: 1 January 2012
Keywords: Consumer decision-making process, dual process theory, eWOM (electronic word of mouth), online consumer review, review helpfulness

Identifiers

Local EPrints ID: 437735
URI: http://eprints.soton.ac.uk/id/eprint/437735
PURE UUID: fdbc30f0-3e72-40bf-87c2-b3642ff50e70
ORCID for Youngseok Choi: ORCID iD orcid.org/0000-0001-9842-5231

Catalogue record

Date deposited: 13 Feb 2020 17:31
Last modified: 16 Mar 2024 06:23

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Contributors

Author: Hyunmi Baek
Author: Joongho Ahn
Author: Youngseok Choi ORCID iD

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