The impact of review valence and awareness of deceptive practices on consumers’ responses to online product ratings and reviews

ABSTRACT

Many online retailers and some manufacturers/service providers have recently been engaging in questionable practices, where product reviews are often fabricated and/or posted without sufficient clarity and objectivity. Across an exploratory study and two main studies, we empirically examine this phenomenon and observe a pattern of effects that suggests that review valence (i.e., the average number of rating-stars a product receives) influences product attitudes and intentions, but that these outcomes are significantly impacted by the extent to which consumers are aware of potentially deceptive online review practices. Awareness of deceptive practices was found to differentially influence attitudes and intentions, depending upon whether the star-ratings were perfect (5/5 stars), highly positive (4.9/5 stars), or generally positive (4.5/5 or 4.7/5 stars). Participants’ perceptions of the e-retailer’s manipulative intent were also shown to mediate these effects, with higher perceptions of perceived manipulative intent yielding less favorable product attitudes and reduced purchase intentions.

KEYWORDS:

• Online retailing
• electronic word-of-mouth (eWOM)
• review valence
• deceptive online product ratings
• manipulative intent
• persuasion knowledge

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. The notion of a ceiling effect, i.e., whether a perfect 5-star rating may be perceived by consumers as being ‘too high’ and thus, less impactful, is one of the foci of our second study.

2. Using participants from Amazon’s Mechanical Turk (N = 100; 43% female; median age = 29; 69% Caucasian), who were paid $.50 for taking a 3-minute survey, we conducted a price pretest. Participants were shown a screenshot for an electric toothbrush and its specifications (same as in Appendix A, except without review or price information), and answered two questions: (1) How much do you think this electric toothbrush is worth?; and, (2) How much do you think this electric toothbrush costs? The mean price for Q1 was $32.56, and $39.91 for Q2. Hence, a price of $34.99 was determined to be realistic, and was used in our subsequent empirical investigation.

3. Although not hypothesized, we also examined the valence x awareness interaction on manipulative intent. Results showed that the valence x awareness interaction was a significant predictor of manipulative intent (F(2, 284) = 7.47, p <.001; see Table 3). Among those in the aware condition, the review valence condition of 4.9 led to significantly higher perceptions of manipulative intent than the 4.7 and 4.5 conditions, while there was no significant effect of valence on manipulative intent among participants in the unaware condition (see Figure 1 for a graph).

4. The augmented measure was designed to tap into additional underlying reasons for participants’ perceptions of manipulative intent, consistent with the ad credibility literature discussed in an earlier section of this paper (Cotte, Coulter, and Moore 2005). The 12-item scale, utilizing measures of star-rating credibility and manipulative intent, was found to be internally consistent (α =.97). Factor analysis results (with varimax rotation) yielded a one-factor solution.

5. Study 1 participants were excluded from participating in Study 2.

6. We again investigated the valence x awareness interaction on manipulative intent, and found it to be a significant predictor of manipulative intent (F(1, 310) = 4.03, p <.05; see Table 4). Participants perceived manipulative intent in both conditions, but inferences were greater in the aware condition (vs. unaware condition). Follow-up tests suggest there were no difference in manipulative intent between the aware and unaware groups within the 4.5-star rating condition, while those in the aware group (compared to the unaware group) reported significantly greater perceptions of manipulative intent within the 5.0-star rating condition (see Figure 3 for a graph).

7. To assess whether older vs. younger individuals would respond differently to the online reviews (perhaps because of differences in perceived trustworthiness; Smith and Anderson 2016), we reran these analyses with age as a covariate. No differences in results were observed.

Additional information

Notes on contributors

Ismail Karabas

Ismail Karabas is an Assistant Professor of Marketing at the Department of Management, Marketing, Business Administration, and Logistics and Supply Chain Management, Murray State University, Murray, KY.

Ioannis Kareklas

Ioannis Kareklas is an Assistant Professor of Marketing at the University at Albany, State University of New York, Albany, New York, U.S.A.

T.J. Weber

T.J. Weber is an Assistant Professor of Marketing at the Orfalea College of Business, California Polytechnic State University, San Luis Obispo, California, U.S.A.

Darrel D. Muehling

Darrel D. Muehling is a Professor of Marketing at the Carson College of Business, Washington State University in Pullman, Washington, U.S.A.