The effect of homophily on perceived risk and
the relative effect of demographic indicators on
perceived demographic homophily in OCRs
Ton van den Berg (S2892294)
Master thesis Msc. Marketing Management
July 13
th, 2017
Agenda
1
Introduction & Research QuestionConceptual Models
Research Designs
Homophily
2
1. Introduction (1)
• Customers often experience some kind of perceived risk during
their purchase decisions. Especially in an online setting
1.
– Customers WTP when perceived risk
2.
– Several studies found that OCRs reduces the perceived risk of customers
during their online purchase decisions
1, 2.
– Some studies even argue that OCRs are one of the most effective
information sources for reducing perceived risk online
1.
• How to further abate the degree of perceived risk in OCRs?
– Homophily: the degree to which people are similar regarding certain
attributes
3.
• Several theories and mechanisms suggests that homophily decreases risk in OCRs, such as: the cognitive dissonance theory , the cognitive balance theory, hedonic fluency model, the liking principle theory, the social comparison theory, social identity theory, social network theory, the attractiveness model and the uncertainty reduction
1. Introduction (2)
2 dimensions of homophily
– Demographic homophily: the degree to which people are similar regarding demographic
indicators such as gender, age, occupation, location and education
3.
– Perceptual homophily: refers to the degree to which people are similar regarding values,
attitudes, beliefs and lifestyles
3.
Validity of generalizations of homophily in most studies questionable
– Current OCR studies mainly focus on demographic homophily, lacking the perceptual
dimension.
1. Introduction (3)
Therefore, this paper has conducted two studies:
• Study 1: Examine the joint effect of both perceptual and demographic
homophily on perceived risk.
– Relevant for academics: first study measuring joint effect in OCRs. – Relevant for practitioners to decrease risk and increase sales online.
• Study 2: Examine the relative strength of demographic indicators on
perceived demographic homophily.
– Relevant for academics to have a solid construct.
– Relevant for practitioners due to increased machine learning.
1. Research Question
“What is the effect of homophily on perceived risk in OCRs and what is the relative
effect of each demographic indicator towards perceived demographic
homophily?”
• 1. What is the effect of demographic homophily between sender and perceiver on perceived risk in OCR?
• 2. What is the effect of perceptual homophily between sender and perceiver on perceived risk in OCR?
• 3. What is the effect of demographic and perceptual homophily on perceived risk?
1. Hypotheses
• H1: Perceived demographic homophily has a negative effect on the degree of perceived risk. • H2: Perceived perceptual homophily has a negative effect on the degree of perceived risk.
• H3: The negative effect of perceived perceptual homophily is stronger on the degree of perceived risk than the negative effect of demographic homophily.
• H4: The negative effect of demographic homophily on perceived risk becomes more negative in the presence of perceived perceptual homophily.
• H5: The negative effect of homophily on the degree of perceived risk is weaker when individuals have an individualistic rather than an collectivist orientation.
• H6-8: The negative effect of homophily on the degree of perceived risk is stronger when:
– controlled for individuals with a prevention and promotion focus. – controlled for individuals experience with OCRs.
– controlled for individuals attitudes towards OCRs.
• H9: Location homophily has the strongest relative effect on perceived demographic homophily, followed by age, occupation, gender, and name homophily respectively.
2. Conceptual models
Study 1
• Homophily on perceived risk
Study 2
3. Research Designs
Study 1
Homophily on perceived risk
•
Multiple regression analysis
•
2x2 between subject design
•
30 x 4 = 120 respondents needed
15Study 2
Demographic indicators on demographic homophily
Demographic /
Perceptual
Similar
Dissimilar
Similar
C1
C2
Dissimilar
C3
C4
• Decompositional choice-based
conjoint-analysis
• 4 choice sets (8 choice alternatives)
• 120 respondents is sufficient
15Sample:
• 146 respondents.
• Gender: 44,5% male, 55,5% female.
• Age: average 33 years (S.D. 13,13).
3. Manipulation of
Homophily
How to match respondents with dissimilar or similar demographic
and/or perceptual traits?
3. Manipulation of
Homophily
Stimuli back-end Qualtrics
3. Stimuli (1)
Study 1
3. Stimuli (2)
Study 2
Demographic indicators on demographic homophily
4. Results study 1
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Constant 2,735*** 2,649*** 2,830*** 2,623*** 2,074*** 2,590*** 2,118*** Demo ,158 ,340 -,115 ,337 ,311 ,338 -,092 Per -,431** -,264 -,896 -,270 -,246 -.261 -,700 Demo*Perc -,353 -,343 -,349 -,392 -.357 -,345 Indi -,036 ,020 Indi*Demo ,085 ,069 Indi*Per ,123 ,083 Prevention ,007 ,005
Hypotheses
4. Results study 2
Attributes and levels β Standard Error Z-score P-value
Name Similar 0,16 0,05 2,96 0,00 Dissimilar -0,16 0,05 -2,96 Age Similar 0,26 0,09 1,27 0,00 Dissimilar -0,26 0,09 -1,27 Gender Similar 0,33 0,08 2,16 0,03 Dissimilar -0,33 0,08 -2,16 Occupation Similar 0,92 0,11 8,30 0,00 Dissimilar -0,92 0,11 -8,30 Location Similar 0,15 1,00 0,00 1,00 Dissimilar -0,15 1,00 -0,00
A similar name, age, gender and occupation is of significant utility to perceive demographic homophily
Individuals do not need to share a similar residence in order to perceive demographic homophily
4. Results study 2
Attributes and levels β Range Importance
5. Discussion study 1
Homophily on perceived risk
•
Study 1 found no significant effects of demographic homophily, perceptual
homophily and their joint effect on the degree of perceived risk in an OCR setting.
•
In addition, the degree of perceived risk significantly increases by individuals with
a positive attitude towards OCRs.
– Postive attitudes towards OCR use heuristics > having less involvement and
elaboration when reading not reading the OCR thoroughly may lead to an increase in perceived risk.
Limitations study 1
•
Hard to perceive risk in an artificial experiment. imagine to book a hotel… Thus,
the amount at stake and the subjective uncertainty may be too defective. Hence,
insufficient measurement of perceived risk.
•
The manipulation, using the piped text insertion may have been too obvious.
•
Positive OCRs, instead of negative OCRs, may exert less risk (i.e. another individual
has positive experience with the hotel), which may subsequently result in less
5. Discussion study 2
Demographic indicators on demographic homophily
•
The demographic indicator ´occupation´ has the strongest relative effect towards
perceived demographic homophily, followed by gender, age, name and location.
– Indicate the lifestyle of another individual with occupation 16. For example, when the
occupation of the reviewer is ‘student’, one can associate it with some sort of lifestyle of the individual. A lifestyle involves motivation and choice of individuals which could have a strong effect on perceived homophily9, hence making occupation of such importance.
– Choice domination
Implications study 2
•
Academics: insert occupation as a demographic indicator to measure the
demographic homophily concept.
5. Discussion
Future Research
Study 1
• Conduct study with negative
OCRs rather than positive OCRs.
• Study the effects on other goods
such as search goods.
• For external validation purposes,
future research may study the
effects with respondents of other
nationalities
Study 2
• Study the relative importance of
additional demographic
indicators such as family cycle or
race.
• Examine the interaction effects
between demographic indicators.
Questions?
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