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Tsinghua Science and Technology 2015, 20(3): 293-305 https://doi.org/10.1109/TST.2015.7128942
Open Access | Issue | Published: 19 June 2015

Analysis of Review Helpfulness Based on Consumer Perspective

Show Author's Information Yuanlin Chen,  Yueting Chai( ),  Yi Liu,  Yang Xu
National Engineering Laboratory for E-Commerce Technologies, Tsinghua University, Beijing 100084, China.
DNSLAB, China Internet Network Information Center, Beijing 100190, China
Keywords:
consumer preference, online decision making, review helpfulness, behavior analysis
Cite this article:
Chen Y, Chai Y, Liu Y, et al. Analysis of Review Helpfulness Based on Consumer Perspective. Tsinghua Science and Technology, 2015, 20(3): 293-305. https://doi.org/10.1109/TST.2015.7128942
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Abstract Full text About this article

When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provide a highly convenient channel for consumers to generate and retrieve product reviews. In addition, consumers can also vote reviews perceived to be helpful in making their decision. However, due to diverse characteristics, consumers can have different preferences on products and reviews. Their voting behavior can be influenced by reviews and existing review votes. To explore the influence mechanism of the reviewer, the review, and the existing votes on review helpfulness, we propose three hypotheses based on the consumer perspective and perform statistical tests to verify these hypotheses with real review data from Amazon. Our empirical study indicates that review helpfulness has significant correlation and trend with reviewers, review valance, and review votes. In this paper, we also discuss the implications of our findings on consumer preference and review helpfulness.


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About this article

Analysis of Review Helpfulness Based on Consumer Perspective

Show Author's information Yuanlin Chen, Yueting Chai( ), Yi Liu, Yang Xu
National Engineering Laboratory for E-Commerce Technologies, Tsinghua University, Beijing 100084, China.
DNSLAB, China Internet Network Information Center, Beijing 100190, China

Abstract

When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provide a highly convenient channel for consumers to generate and retrieve product reviews. In addition, consumers can also vote reviews perceived to be helpful in making their decision. However, due to diverse characteristics, consumers can have different preferences on products and reviews. Their voting behavior can be influenced by reviews and existing review votes. To explore the influence mechanism of the reviewer, the review, and the existing votes on review helpfulness, we propose three hypotheses based on the consumer perspective and perform statistical tests to verify these hypotheses with real review data from Amazon. Our empirical study indicates that review helpfulness has significant correlation and trend with reviewers, review valance, and review votes. In this paper, we also discuss the implications of our findings on consumer preference and review helpfulness.

Keywords: consumer preference, online decision making, review helpfulness, behavior analysis

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Publication history

Received: 12 February 2015
Revised: 07 April 2015
Accepted: 15 April 2015
Published: 19 June 2015
Issue date: June 2015

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© The authors 2015

Acknowledgements

This work was financially supported by DNSLAB, China Internet Network Information Center.

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