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

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

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

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

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

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

Moderated mediation model

*Type 1 Model as outlined by Preacher, Rucker & Hayes (2007); Model 74 in Hayes (2012)

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)

Method (2)• Stimuli

Results

• Proposed model confirmed!

*Bootstrapping Macro SPSS (model 74), Hayes et al. (5000 samples)

Hypothesis 1

Valence review Attitude

restaurant

b = 1.511, p < .001

Hypotheses 2a & 2b

b = .141, p

= .129

b = .495*

* p < .001

Hypothesis 3

b = .347, p < .001

Moderated mediation model

b = .347*

b = .1

41, p =

.129

b = .495*

b = 1.511*(b = -1.318*)

*p < .001

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 papero 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

Thank you for your attention!