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Credibility in online word-of-mouth

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Authors: Natalie Van Hemelen, Tim Smits, Peeter Verlegh. …

Authors: Natalie Van Hemelen, Tim Smits, Peeter Verlegh.

Paper presented at ICORIA 2013 (Zagreb, Croatia)

Please contact @timsmitstim for further information about the study.

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  • 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!