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Discrete Dynamics in Nature and Society
Volume 2016, Article ID 9354519, 19 pages
Research Article

Exploring Determinants of Attraction and Helpfulness of Online Product Review: A Consumer Behaviour Perspective

1School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China
2Department of Management, University of Bristol, Bristol BS8 1TZ, UK

Received 8 August 2016; Accepted 5 October 2016

Academic Editor: Francisco R. Villatoro

Copyright © 2016 Xu Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


To assist filtering and sorting massive review messages, this paper attempts to examine the determinants of review attraction and helpfulness. Our analysis divides consumers’ reading process into “notice stage” and “comprehend stage” and considers the impact of “explicit information” and “implicit information” of review attraction and review helpfulness. 633 online product reviews were collected from Amazon China. A mixed-method approach is employed to test the conceptual model proposed for examining the influencing factors of review attraction and helpfulness. The empirical results show that reviews with negative extremity, more words, and higher reviewer rank easily gain more attraction and reviews with negative extremity, higher reviewer rank, mixed subjective property, and mixed sentiment seem to be more helpful. The research findings provide some important insights, which will help online businesses to encourage consumers to write good quality reviews and take more active actions to maximise the value of online reviews.