The Power of Incentive Fulfillment Retaining and Rewarding Research Respondents
E_WOM THESIS PRESENTATION
1. “The effect of consumer
expertise on consumer
behavioral intentions
The role of Involvement
and online consumers’
reviews”
Erasmus University of Rotterdam
School of Economics , department of Marketing
Evangelia Makri : 347524
Supervisor: Gui Liberali
Co-reader: Nuno Camacho
December 2012
2.
3. Does every piece of information “make sense” to
everyone???
Do they all think alike?
5. We want technical
information-
attributes*
We want to know the
beneficial aspects of
the product*
An example of different informational needs
*Source: Park & Kim, 2008; Everett Rogers, 1962
6. …so what can a marketer do?
• When and how they should change their strategies
of providing information?
• Should they offer both attribute-centric and benefit-
centric information in their ads?
NO!!
Why? Time-consuming
Costly
Ineffective
Source: D. Maheswaran, B. Sternthal,1990
7. Introducing the voice of people:
Online word of mouth
Influence Purchase intentions
Affect consumers’ information adoption
Increase product sales
Build Brand equity
Source: Chevalier and Mayzlin, 2006; Bambauer-Sachse and Mangold 2011
8. 6in 10 online shoppers say UGC have a significant impact on
consumers’ buying behavior
Source: http://www.rswus.com/resources/survey-results
9. “Almost 3 in 10 marketers say they have shifted at least half of their
marketing spending from traditional to digital advertising
over the past 3 years”
Source: http://www.rswus.com/resources/survey-results
10. But why is e-WOM so important?
• Fro the usto ers’ perspe ti e:
The users who write these reviews are most of times former users at any given stage
of the product life cycle. Their reviews can be attribute or benefit centric and
satisfy the informational needs of potential o su ers
• From the marketers perspective:
Measurable
Traceable
Easier to control than traditional WOM
11. Research Problem
So…consumers are affected by e-WOM
But.. they are unique and have:
Different informational needs (attribute-centric vs. benefit-centric)
Different cognitive process (cognitive theory)
Different levels of expertise regarding products (experts vs. novices)
Different levels of Involvement (high vs. low, ELM Theory)
12. Research Question
“How do different levels of consumer’s expertise, product involvement
(high vs. low),and different types of online consumer reviews (benefit
centric online consumer reviews vs. attribute centric online consumer
reviews) will affect consumer’s purchase intention, attitude toward the
product, perception of risk and perceived informativeness of online
consumers’ reviews?
13. Literature review: Independent variables and moderators
• Research gap, contradictory studies (Wagenheim & Bayon , 2004
• “The ability to perform product related tasks with success” (Alba &
Hutchinson,1987)
• Two ways of measuring expertise : subjective and objective knowledge
(Park & Kim,2008)
Expertise
• Multidimensional variable
• Enduring and situational (Bloch & Richins , 1983)
• Situational involvement has stronger effects than product class
involvement (Mittal , 1995)
Involvement
• attribute-centric vs. benefit centric online consumer reviews
• impact of online consumer reviews greater than marketing-generated
content (Chiou & Cheng, 2003)
Type of the review
14. Literature review: Dependent variables
• Part of trustworthiness (Dickinger,2010)
• Part of usefulness (Venkatesh & Davis, 2000)
• Three dimensional (Park & Kim)
Informativeness
• subjective judgment of a consumer
• contradictory theories (Hu et al. 2008; Duan et al. 2008)
Purchase Intentions
• Predisposition of a consumer about a product that can change
(ELM theory)
Attitude towards the product
• Five dimensions (Dholokia, 2001)
• Riskiness in the purchase (Eroglu &Machleit, 1990)
• E-wom is a risk reducer (Engel et. al., 1995)
Perception of risk
15. Hypothesis Development
Hypothesis 1a: Perceived informativeness is higher for consumers with high level of
expertise when provided with reviews framed as attribute centric than reviews framed
as benefit centric.
Hypothesis 1b: Perceived informativeness is higher for consumers with low level of
expertise when provided with reviews framed as benefit centric than reviews framed
as attribute centric
Hypothesis 2a: For consumers with high expertise reviews framed as attribute-centric
have a stronger effect on the purchase intention than reviews framed as benefit centric.
Hypothesis 2b: For consumers with low expertise reviews framed as benefit-centric have
a stronger effect on the purchase intention than reviews framed as attribute centric.
Cognitive fit theory
16. Hypothesis 3a: In the high involvement condition, the impact of attribute centric reviews on
purchase intention is greater than the impact of benefit centric reviews
Hypothesis 3b: In the low involvement condition, the impact of benefit centric reviews on
purchase intention is greater than the impact of attribute centric reviews
Hypothesis 3c: In the high involvement condition, the impact of attribute centric reviews on
attitude towards the product is greater than the impact of benefit centric reviews.
Hypothesis 3d: In the low involvement condition, the impact of benefit centric reviews on attitude
towards the product is greater than the impact of attribute centric reviews
Hypothesis Development
ELM theory
17. Hypothesis Development
Hypothesis 4a: Attribute centric reviews will lower the effect of perceived risk in the high
involvement situation than benefit centric reviews
Hypothesis 4b: Benefit-centric reviews will lower the effect of perceived risk in the low
involvement situation than attribute centric reviews.
ELM theory
Laurent and Kapferer,1985: perception of risk is an after effect of situational
involvement
18. Hypothesis Development
Hypothesis 5a: The effect of cognitive fit on perceived informativeness is greater for the high
involvement condition than the low involvement condition
Hypothesis 5b: The effect of cognitive fit on purchase intention is greater for the high involvement
condition than the low involvement condition
Hypothesis 5c: The effect of cognitive fit on attitude towards the product is greater for the high
involvement condition than the low involvement condition
Hypothesis 5d: The effect of cognitive fit on perceived risk is greater for the high involvement
condition than the low involvement condition
• When a cognitive fit emerges consumers tend to be more stable towards
their preferences in a high-involvement condition (Oliva et al, 1995)
• Involvement affects significantly the cognitive process of a consumer (Park&Do-Hyung,2007)
20. Experimental design
Type of reviews High Involvement Low Involvement
Attribute 1 2
Benefit 3 4
2x2 between subject factorial design
Participants randomly assigned to one of the four conditions
21. Experimental Product: Tablet Pc
Search good
Technological oriented product: many online consumer reviews
Aids the classification of experts and novices
Respondents should be sufficiently familiar with the product
Tablet PCs are currently quite popular
(31% of U.S. internet users report to have a tablet)
24. Stimuli development: Involvement scenarios
• High Involvement scenario (goal directed):
Imagine yourself working for a multimedia company and you need to make a purchase
of a tablet PC in a short period of time. Your decision will be important as the tablet
will aid you in executing your tasks more efficiently. Please read the following product
characteristics a d o li e co su e s’ e ie s a d a s e the follo i g uestio s:
• Low Involvement scenario (stripped of goal direction):
Imagine yourself wanting to buy a tablet PC for fun. Please read the following product
characteristics and online consumer reviews and answer the following questions:
27. Validity of constructs and sample size
Construct measurements with proven validity and reliability
(Cronbach’s alpha higher than 0.80)
Factor analysis to improve validity
Type of reviews High Involvement Low Involvement
Attribute n=40 n=33
Benefit n=34 n=41
Total of
148
Participants
76 male , 72 female
82.4% between 18 to 30 years old
64.2% Greek nationality
53.4% income range 501-1000 euros
43.2% University graduates , 47.3% Master students or graduates
28. Control and manipulation checks
• Control for price
• Control for brand effects
• Control for review positiveness
• Control general susceptibility and credibility of E-wom
Manipulation of Involvement was successful, F (1,146) =8.987, p <0.001
30. Results: Informativeness
Experts with attribute centric reviews: M high-involvement =6.096 vs. M low-involvement =5.318
Novices with benefit centric reviews : M high-involvement =5.789 vs. M low-involvement =5.625
F (1,140) =199.2, p<0.05
32. • Participants may not have been satisfied by the number of reviews
• Manipulation was successful but the differences between means were not as high as
expected
33. Experts with attribute centric reviews: M high-involvement=6.519 vs. M low-involvement=5.136.
Novices with benefit centric reviews : Mhigh-involvement=6.289 vs. M low-involvement=6.094
F (1,140) = 12.476, p<0.05
34. Results: Attitude towards the product
df F Sig.
TypeofReview 1 2.117 0.148
Involvement 1 0.324 0.570
TypeofReview *Involvement 1 0.135 0.714
Error 144
• Participants may have been affected by other extrinsic effects such as the design of the
product
35. Results: Attitude towards the product
Experts with attribute centric reviews: M high-involvement=6.258 vs. M low-involvement=5.736
Novices with benefit centric reviews : Mhigh-involvement=6.316 vs. M low-involvement=5.925
F (1,140) = 38.292 p<0.05
36. Results: Perception of risk
df F Sig.
TypeofReview 1 0.406 0.525
Involvement 1 29.375 0.000
TypeofReview *Involvement 1 6.718 0.011
Error 144
37. Results: Perception of risk
Source df F Sig.
Involvement 1 177.012 0.000
TypeofReview 1 51.141 0.000
Expertise 1 603.231 0.000
Involvement *TypeofReview 1 16.176 0.000
Involvement * Expertise 1 118.721 0.000
TypeofReview * Expertise 1 53.213 0.000
Involvement *
TypeofReview * Expertise
1 3.046 0.083
Error 140
Perception of risk could be an antecedent of Involvement
Investigate more dimensions
The simple interaction Type of review x Expertise not as expected
38. Conclusions
Expertise plays a critical role of moderating the
relationship between the type of review
informativeness and purchase intention
Cognitive fit is affected by involvement (for
informativeness, purchase intention and
attitude towards the product)
Perception of risk needs to be examined by
future researchers
Cognitive hypothesis>ELM hypothesis
39. Managerial implications
Data mining
review mining and summarization aims
to e tra t users’ opi io s to ards spe ifi produ ts fro reviews
and provide an easy-to-understand summary of those opinions
to pote tial u ers
CRM technologies
Aid the categorization of Experts vs. Novices
by taking into consideration:
their product preferences
their reviews preferences
their activity through the website
their experiences regarding a specific product
Source: Kantardzic (2011), Meng and Wang (2009)
40. Limitations and future research
Small sample size
No control group as a baseline
Brand effects may show different results
Mixed reviews may provide interesting results
Involvement and perception of risk needs further examining
