Authors: Natalie Van Hemelen, Tim Smits, Peeter Verlegh. Paper presented at ICORIA 2013 (Zagreb, Croatia) Please contact @timsmitstim for further information about the study.

1. Credibility in E-WOM
How review perceptions impact their
persuasiveness
Natalie Van Hemelen (KULeuven), Tim Smits (KULeuven) & Peeter Verlegh (UVA)
ICORIA 2013 (Zagreb, Croatia)
Slideshare: timsmitstim

2. Theoretical background: Introduction
• e-WOM & online consumer reviews increasingly popular
• Online consumer reviews
o “Online recommendations about products, services,
organizations or brands, based on consumers’ personal
experiences”
o E.g., Yelp

3. Succes and impact of online review sites
• People attach a lot of importance to the non-commercial
opinion of social others (Fong & Burton, 2004)
• Online reviews (often) perceived as impartial (Anderson 2012)
People are less suspicious about their credibility
o 72% trust online reviews as much as personal recommendations
o 58% trust products that have positive online reviews
Reviews have a strong persuasive impact on attitudes

4. Predictors of a review’s effect
• Both valence and credibility are straightforward and proven
predictors of a review’s effect
• Floh and collegeaus (2009): many researchers only take perceived
valence into account (see also Sussan et al., 2006; Willemsen et al.,
2012), neglecting variation in its perceived credibility
• Review’s valence and credibilty cannot be assumed to be
independent from each other...
Current study: Combined persuasive impact of perceived valence and
credibility

5. Hypotheses (1)
• Valence: Straightforward effect
H1: Positive reviews (vs negative ones) will increase the
attitude towards the product
• Credibility: Moderated effect
H2a: For positive reviews, higher credibility will increase
the attitude towards the product
H2b: For negative reviews, higher credibility will decrease
the attitude towards the product

6. Hypotheses (2)
• But, valence is also likely to affect credibility...
• Rationale: Negative information  Attention  Source questioning
• H3: Positive reviews (vs negative ones) wil increase the
review’s perceived credibility

7. Moderated mediation model
*Type 1 Model as outlined by Preacher, Rucker & Hayes (2007);
Model 74 in Hayes (2012)

8. Method (1)
• Procedure & participants
o Between subjects design with 2 conditions (positive vs negative
review)
o 89 Bachelor students of a Flemish University College
• 62 men (69,7%), 27 women (30,1%)
• Between 18 and 24 years old (M = 19,22; SD = 1,81)
• Visit a restaurant regularly (M = 4,71, SD = 1,189)
o Online study
• Read one of the 2 reviews: valence manipulation
• Attitude restaurant: 10 semantic differential items
qualitative – not qualitative, creative – uncreative, attractive – unattractive,… (α = .953, M =
4.135, SD = 1.116)
• Credibility review: 4 semantic differential items
honest – dishonest, credible – incredible,…(α = .687, M = 3.862, SD = 1.645)

9. Method (2)
• Stimuli

10. Results
• Proposed model confirmed!
*Bootstrapping Macro SPSS (model 74), Hayes et al. (5000 samples)

11. Hypothesis 1
Valence review Attitude
restaurant
b = 1.511, p < .001

12. Hypotheses 2a & 2b
* p < .001

13. Hypothesis 3

14. Moderated mediation model
b = 1.511*
(b = -1.318*)
*p < .001

15. Take-home-message
Valence and credibility jointly predict a review’s effect on
product/service attitudes.
Future research
• In our study the findings only hold for one type of reviews
o When reviews were phrased as rather high-level (“abstract”)
appraisal, a similar but non-significant pattern emerged
o In a follow-up study, we replicated the findings of this paper
o In other follow-up studies we want to test whether the
findings also hold for other types of reviews, products,...
• Future research can further investigate why exactly negative
reviews are perceived as less credible than positive ones

16. Thank you for your attention!