Elsevier

Computers in Human Behavior

Volume 28, Issue 5, September 2012, Pages 1974-1984
Computers in Human Behavior

Effects of attribute and valence of e-WOM on message adoption: Moderating roles of subjective knowledge and regulatory focus

https://doi.org/10.1016/j.chb.2012.05.018Get rights and content

Abstract

The current study proposes a model to test whether online review valence and attributes have an effect on credibility, and whether regulatory focus and subjective knowledge have moderating effects. Three hundred nineteen university students participated in online experiments with a 2 (positive vs. negative review valence) by 2 (objective vs. subjective review attributes) between subject design. The experiment demonstrated that objective and negative online reviews have a significant positive and negative impact, respectively, on message credibility, which affects review adoption. The results also showed that the moderating effect produced by objective information and a consumer’s subjective knowledge is supported. This study contributes to explaining the inconsistent results between review valence/attribute and credibility found in previous studies.

Highlights

► Previous studies of e-WOM such as review valence result in inconsistent conclusions. ► Research for effects produced by different review attributes is under-researched. ► An experiment shows that objective and negative online reviews have an impact on credibility. ► Subjective knowledge has a moderating effect.

Introduction

Word-of-mouth communication (WOM), in which peer consumers share information about products/services, is one of the most influential communication media in delivering product/service information provided by consumers (Alreck and Settle, 1995, Arndt, 1967). WOM communication overcomes shortcomings of seller-centric marketing communication messages in that it provides useful information by peer consumers, who have purchased and experienced products/services (Mahajan, Muller, & Kerin, 1984). Consumers trust peer consumers more than they trust advertisers or marketers (Lee and Youn, 2009, Sen and Lerman, 2007) and evaluate products/services using information that other people provide (Bone, 1992, Brunkrant and Cousineau, 1975, Herr et al., 1991, Laczniak et al., 2001). Previous studies show that WOM communication affects evaluations of, attitudes towards, and intentions to purchase products/services (Bone, 1992, Harrison-Walker, 2001, Herr et al., 1991). Development of network technology and ubiquitous distribution of the Internet have transformed traditional face-to-face WOM communication into computer-mediated WOM (e-WOM) communication. Consumers now use the Internet to share experiences and opinions. Consumers can write their product experiences and read peer consumers’ product evaluation on different platforms such as retailers’ websites, brand community, independent websites, consumer blogs, and other platforms (Herr et al., 1991, Lee and Youn, 2009). While some consumers provide experience-based product information (review posters), others read product information provided by peer consumers (reviewers). There are several differences between traditional WOM and e-WOM. First, unlike face-to-face WOM, e-WOM arises from an unlimited number of unknown consumers, which produces vast amounts of unfiltered products/services information. This anonymous nature of the posted reviews about products in online environments makes it difficult for consumers to determine the quality and credibility of the e-WOM (Lee & Youn, 2009). Second, e-WOM contains both positive and negative product information from experienced peer consumers (Lee, Rodgers, & Kim, 2009). Even though posted negative reviews are infrequent (Chiou & Cheng, 2003), they are viewed as more influential (Herr et al., 1991; Lee & Youn, 2009). Consumers tend to perceive negative product information as more diagnostic than that of a positive one (Herr et al., 1991). Third, consumers’ reviews are easily read and observed in an online environment. Online consumers’ reviews are normally provided in text formats, the quality and contents of which are thus easily retrieved, read, and evaluated. Accordingly, e-WOM studies should consider all of these characteristics.

Previous research on e-WOM has studied how online reviews have influenced message credibility and acceptance. Review valence (positive vs. negative message) has been the most frequently investigated topic. However, results from this stream of previous studies are inconsistent. These inconsistent results may imply further research is needed. In addition to review valence, attributes of online reviews such as contents and quality should also be investigated to better understand the impact online reviews have on message credibility. However, this stream of research is relatively scarce and results are mixed (Klein and Ford, 2003, Park and Kim, 2008). Building on this prior tradition of research, the current study aims (1) to investigate the effects of review valence and attributes on e-WOM credibility, which has a subsequent impact on review acceptance, and (2) to investigate the moderating impact of reviewer characteristics including regulatory focus and subjective knowledge on the links between review valence/attributes and e-WOM credibility.

Following this introduction, Section 2 provides a review of previous research related to e-WOM and related constructs. Section 3 describes the research model and proposes the hypotheses to be tested. Section 4 describes the research methodology of the empirical study. Section 5 reports on the testing of the hypotheses and presents a discussion. Section 6 presents implications, limitations, and suggestions for future research.

Section snippets

Previous research toward e-WOM

Online review studies can be classified into three categories: review quantity, review valence, and review attribute. First, the number of online reviews, whether they are positive or negative, is an important factor influencing consumers’ evaluations of online reviews (Chen et al., 2004, Duan et al., 2008). The number of reviews posted by consumers may be a signal of product popularity. In addition, an increase in the number of reviews relates to an increase in the amount of information. When

Research model and hypotheses

The research model proposed in the present study is shown in Fig. 1. Five different hypotheses are proposed. The first hypothesis proposes the relationship between review credibility and review adoption. The credibility of e-WOM is defined as the extent to which one perceives a review as believable, true, or factual (Cheung et al., 2009, Nabi and Hendrinks, 2003). Wathen and Burkell (2002) pointed out that when consumers are reading online reviews, they make evaluations of the message’s

Research design

The present study used experiments with 2 (positive vs. negative review valence) by 2 (objective vs. subjective review attributes) between subject designs. A total of 319 university students were randomly assigned to one of the four conditions; in order to motivate the respondents to participate in the present online survey, researchers told the respondents that about 20% of them may win a lottery worth approximately $20 when they complete the survey. Each respondent was identified with an

Manipulation checks

In order to check the levels of the respondents’ perceptions of review valences and attributes, several items asked the respondents whether the online reviews were positive or negative, objective or subjective at the end of the questionnaire. To check the manipulation for review valence, respondents were asked “how positive or negative the previous online reviews were” on a seven-point Likert scale. Results from the t-test showed that the group exposed to positive reviews rated higher than the

Discussion

The literature review showed that (1) there were inconsistent results between review valence and message credibility, and (2) research studying the effect produced by review attributes such as objective vs. subjective online reviews is relatively scarce and also inconsistent. The results of this study indicate that moderating variables may possibly influence the constructs such as individual and/or situational differences. The results in the present study demonstrate that negative and negative

Acknowledgments

The authors would like to express a sincere gratitude to the two anonymous reviewers for their helpful comments.

References (62)

  • J. Lee et al.

    The effect of negative online consumer reviews on product attitude: An information processing view

    Electronic Commerce Research and Applications

    (2008)
  • C. Park et al.

    Information direction, website reputation and eWOM effect: A moderating role of product type

    Journal of Business Research

    (2009)
  • D. Park et al.

    The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews

    Electronic Commerce Research and Applications

    (2008)
  • S. Sen et al.

    Why are you telling me this? An examination into negative consumer reviews on the web

    Journal of Interactive Marketing

    (2007)
  • J. Yang et al.

    Experiential goods with network externalities effects: An empirical study of online rating system

    Journal of Business Research

    (2010)
  • J.W. Alba et al.

    Dimensions of consumer expertise

    Journal of Consumer Research

    (1987)
  • Alreck, P. L., & Settle, R. B. (1995). The importance of word-of-mouth communications to service buyers. In Proceedings...
  • J. Arndt

    Role of product-related conversations in the diffusion of a new product

    Journal of Marketing Research

    (1967)
  • R.M. Barron et al.

    The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations

    Journal of Personality and Social Psychology

    (1986)
  • S. Basuroy et al.

    How critical are critical reviews? The box office effects of film critics, star power, and budgets

    Journal of Marketing

    (2003)
  • P.F. Bone

    Determinants of WOM communication during product consumption

  • M. Brucks

    The effects of product class knowledge on information search behavior

    Journal of Consumer Research

    (1985)
  • R.E. Burnkrant et al.

    Informational and normative social influence in buyer behavior

    Journal of Consumer Research

    (1975)
  • P. Chatterjee

    Online review: Do consumers use them?

    Advances in Consumer Research

    (2001)
  • Chen, P. Y., Wu, S. Y., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales. In...
  • M.Y. Cheung et al.

    Credibility of electronic word of mouth: Informational and normative determinants of on-line consumer recommendations

    International Journal of Electronic Commerce

    (2009)
  • E. Clemons et al.

    When online reviews meet hyper-differentiation: A study of the craft beer industry

    Journal of Management Information Systems

    (2006)
  • S. Doh et al.

    How consumers evaluate eWOM messages

    CyberPsychology and Behavior

    (2009)
  • S.T. Fiske

    Attention and weight in person perception: The impact of negative and extreme behavior

    Journal of Personality and Social Psychology

    (1980)
  • G.T. Ford et al.

    Consumer skepticism of advertising claims: Testing hypotheses from economics of information

    Journal of Consumer Research

    (1990)
  • K.S. Freeman et al.

    Effect of contact information on the credibility of online health information

    IEEE Transactions on Professional Communication

    (2009)
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