Master Thesis Defense
Online reviews versus samples: the role of review valence,
trailer and source credibility in the case of TV series
Student:
Andreana V. Gosteva Supervisors: Dr. Jenny van Doorn (1st)
Introduction
• Online Reviews (indirect product experiences)
- Increasingly popular for assessing product worth (Chevalier and Mayzlin, 2006)
- Around 92% of online customers read and relate literal review comments
to their buying decisions
- People who consulted product recommendations are inclined to select recommended goods twice as often (Senecal and Nantel, 2004)
• Source of review
-
Consumer reviews : have a very significant impact on sales since they are perceived as more quality representative (Cheong and Morrison, 2008) - Expert reviews: known for their integrity they are a respected source of information for assessing product quality (Chen and Xie, 2005)• Sampling
(direct product experiences)- Aims at helping consumers visualize the quality of a product
- Free of charge (or reduced cost of trial) (Heiman et al., 2001)
Problem Statement and Research Questions
However :
× Review valence can lead to higher uncertainty
× Sampling helps the challenge of valence and volume of reviews
(Godes and Mayzlin, 2004) but rather poorly investigated in marketing
× Lack of evidence under which circumstances online reviews and/or samples work optimally (Hu et al., 2009)
× Information credibility is a major concern in predicting consumer’s actions (Grewal et al., 1994)
× Expert vs. non-expert reviews have showed unclear results (Senecal and Nantel, 2004)
Conceptual Model & Hypotheses
Review Valence Positive/Negative Trailer Present/Absent Source of Credibility Expert/User Willingness to watch H2• H1: Negative reviews (as opposed to positive ones) will decrease the intentions to watch a TV show.
• H2: The presence of a trailer (as opposed to the absence of trailer) will increase the willingness to watch a TV show.
• H3: A trailer has a significant positive effect on watching intentions when reviews are negative.
• H4a: The impact of a review on watching intentions is stronger when it is given by an expert.
• H4b: An expert review (as opposed to user review) decreases the effect of sampling on consumption for a TV show.
H3
H4a
Methodology
• Online Questionnaire• Between-subjects Analysis: 2 (review valence: positive/negative) x 2 (trailer: present/absent) x 2 (source of review: expert/user)
• Participants
• Conditions:
• TV Show:
- “Go On”; Trailer Length (89s); IMDb site layouts - positive review – 9 stars; negative 3.2
- review valence and source of credibility manipulations
Scenario # Participants Review Valence Trailer Source Of Credibility
1 31 Positive Yes User
2 33 Negative Yes User
3 25 Negative No User
4 27 Positive No User
5 27 Positive Yes Expert
6 26 Negative Yes Expert
7 35 Positive No Expert
Methodology Contd.
• Manipulation Checks:
- Review Valence
“I think the review was: ….(positive/negative)”, F(1,241) =1315.331, p=0.000 “I think the review was… (favorable/unfavorable)”, F(1,241)=972.437,p=0.000
- Source of Review
“In my opinion, the source of the review is….(expert/not an expert)”,
F(1,241)=380.549, p=0.000
• Reliability (α > 0.7) and Correlations ( -1≤ r ≥1) • Linear Regression : dummy coding
M positive M negative
Q1 1.692 6.271 Q2 1.818 5.978
M expert M user
Regression Results
*Full model: F(10, 230)=15.815, p=0.000; Adj. R2 = 38.2 %
Hypothesis Supported Results
H1: Negative reviews (as opposed to positive ones) will decrease the intentions to watch a TV show.
Yes
The effect of review valence is significant, F (10,230)= - 6.257, p< .05(p=.000). Negative reviews decrease watching intentions, positive reviews increase watching intentions.
H2: The presence of a trailer (as opposed to the absence of trailer) will increase the willingness to watch a TV show.
Yes Trailer as predictor of willingness to watch is significant, F (10,230)=3.263, p< .05(p= .001) and it increases watching intentions when present.
H3: A trailer has a significant positive effect on watching intentions when reviews are negative.
Yes
The interaction between negative reviews and trailer was significant, F (10, 230)=4.541,
p<.05(p=.000) and it resulted in increased watching intentions.
H4a: The impact of a review on watching intentions is stronger when it is given by an expert.
No
An expert review did not moderate the impact of review valence on watching intentions as it had no significant effect at all, F (10, 230)=
- 0.148, p>0.05 (p=0.882)
H4b: An expert review (as opposed to user) decreases the effect of sampling on consumption for a TV show.
No
The interaction between trailer and expert review was significant, F (10, 230)=4.05,
Conclusions and Discussion
Review Valence does matter: negative reviews lower the likelihood of watching the show while positive reviews increase it (e.g. Lin and Huang (2005); Park et al., 2007).
Trailer increases willingness to watch:
trailer as a sampling option is a strong quality signal that decreases insecurities about the product (Donath, 2007)
consumers were enabled to assess directly (sampling) and indirectly (review) the value of the product themselves which reduces uncertainty (Hu et al., 2009).
Trailer has a significant positive effect on watching intentions when reviews are negative:
a negative review causing uncertainty can be offset by sampling
when given more information and an option to review a sample, a consumer seems to be willing to try a product
Conclusions and Discussion
(Contd.)An expert review increases the effect of sampling:
the effect of trailer increased the watching intentions which only strengthened the relationship
respondents were able to decide whether or not the sample fits the review content
The impact of trailer differs for negative and positive reviews:
negative expert reviews decreased the inclination to watch the show
correlation between valence and expertise: negative expert recommendations do influence consumers
Limitations and Future Research
• Limitations:
- only 1 type od experience goods used
- the design might be constraint
- opinions prior to viewing the show were not measured
• Future Research:
- include more review options(e.g. mixed, neutral)
- measure pre- and post- viewing/reading impressions - test different sequences of review and sample
