Integrating Multiple Opinions: The Role of
Aspiration Level on Consumer Response to
Critic Consensus
PATRICIA M. WEST
SUSAN M. BRONIARCZYK*
O
thers' opinions, such as reference groups and wordof-mouth of friends, have been shown to influence
consumers' evaluations in addition to, or in place of, product attribute information (Bearden and Etzel 1982; Rogers
1976). Although this research has demonstrated the importance of others' opinions, surprisingly little attention
has been devoted to examining the process by which the
individual consumer integrates the opinions of mUltiple
others.
The purpose of this article is to examine the process
by which consumers integrate critic opinions and attribute
information into product evaluations and how critic consensus affects this process. Consensus refers to the level
of agreement between critics. A high level of agreement
suggests that all concur on the product evaluation-albeit
favorably or unfavorably. When critics disagree, both favorable and unfavorable evaluations will tend to be aired.
We identify conditions under which consumers' evaluations are influenced to a greater extent by agreement or
disagreement among critics using a simple argument
based on consumers' aspiration levels. An aspiration level
is a consumer's goal or expectation for the outcome of
the decision. In situations in which consumers have low
expectations, disagreement among critics raises the possibility that the product may fall short of an acceptable
level, and, hence, consumers prefer critic consensus. Alternatively, when expectations are high, critic disagreement improves the chance of meeting or exceeding the
goal, and, thus, consumers favor critic disagreement.
Importance of Others' Opinions
Consumers are likely to seek others' opinions to reduce
their cognitive effort or uncertainty as the perceived risk
associated with a purchase increases (Dowling and Staelin 1994; Roselius 1971). Consumers may also seek out
others' opinions for guidance on novel products, products
with image-related attributes (King and Summers 1970),
or because attribute information is lacking or uninformative. Attribute information is often conflicting or difficult
to ascertain for experience attributes such as the handling
ability, comfort of ride, and driveability of an automobile
(Bone 1995; Hoch and Ha 1986).
Others' opinions are likely to be especially important
for experiential products because they offer indirect experience on sensory aspects not conveyed by tangible attributes. Holbrook and Hirschman (1982) express dismay
at the traditional models of consumer evaluation, stating
that "many products project important nonverbal cues
that must be seen, heard, tasted, or smelled to be appreciated properly" (p. 134). Examples of such products are
viewing a movie, eating at a restaurant, or sight-seeing.
Consumers purposefully seek out the opinions of others
for evaluating experiential products as demonstrated by
surveys that show that over a third of Americans seek the
*Patricia M. West and Susan M. Broniarczyk are both assistant professors of marketing at the University of Texas, CBA 7.202, Austin,
TX 78712. Thanks to Mark Alpert, Bart Bronnenberg, Steve Hoch,
Wayne Hoyer, Jay Koehler, Leigh McAlister, and participants at seminars at the Wharton School and the University of Chicago for their
helpful comments on an earlier draft. Suggestions or feedback should
be forwarded to Patricia M. West.
38
© 1998 by JOURNAL OF CONSUMER RESEARCH, Inc. - Vol. 25 - June 1998
All rights reserved. 0093-5301/99/2501-0003$03.00
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Four studies examine the process by which consumers integrate critic opinions
and attribute information into their product evaluations and how critic consensus
affects this process. A reference-dependent model is proposed such that consumer response to consensus depends on whether the average critic rating for
an alternative is above or below an aspiration level. Consensus is shown to be
preferred for alternatives above an aspiration level, whereas critic disagreement
is preferred for alternatives below an aspiration level. Consumers exhibited a
tendency to prefer critic disagreement for high-priced products or decisions associated with high social risk because most alternatives fell below their high aspiration levels.
INTEGRATING OPINIONS
Critic Consensus and Aspiration Level
Anecdotal evidence suggests that critic disagreement
is a salient cue to consumers. For instance, the popUlarity
of movie critics Gene Siskel and Roger Ebert is partially
a function of their spirited disagreements. Differences in
critic ratings are frequent (Boor 1990) because ofunrelia-
bility in sensory experiences, different latitudes of acceptance, or heterogeneity in personal preferences. Research
in decision making suggests that a lack of consensus in
opinions can create uncertainty for the consumer (Ellsberg 1961; Hogarth 1989; Meyer 1981).
Prior research has shown that consumers respond negatively to such uncertainty (Jaccard and Wood 1988). Specifically, consumers may completely reject an alternative
with conflicting opinions or ignore the inconsistent information and use a discounted average value for the category as a default valuation for the alternative (Jaccard
and Wood 1988; Meyer 1981; Ross and Creyer 1992).
Alternatively, consumers may use the critic information
by averaging the provided opinions but again discount
this value to adjust for critic disagreement (Meyer 1981 ) .
However, other research suggests that consumers' response to uncertainty will depend on their reference point
(Kahneman and Tversky 1979; Levin et al. 1985; Payne,
Laughhunn, and Crum 1980, 1981). According to Kahneman and Tversky's (1979) prospect theory, when a decision outcome is framed as a gain (above the reference
point), individuals tend to be risk averse, preferring a
certain outcome over an uncertain outcome with equivalent expected value. Conversely, when a decision outcome
is framed as a loss (below the reference point), individuals tend to be risk seeking, preferring an uncertain outcome to an equivalent certain outcome.
This reference-dependent explanation of how consumers respond to consensus is consistent with results observed by Meyer (1981), whose subjects were asked to
evaluate restaurants given critic ratings. He found that for
restaurants whose average critic rating exceeded the mean
value across all restaurants, subjects exhibited decreased
utility when the critics' disagreed about the restaurant
quality. However, for restaurants whose average critic
rating fell below the mean restaurant rating, critic disagreement did not increase utility but rather had no effect.
Further support for the reference-dependent model
comes from Kahn and Meyer (1991), who found that
consumer response to critic consensus regarding an attribute's importance was dependent on whether the attribute
was framed as a gain (utility enhancing) or a loss (utility
preserving) relative to an implicit reference point, the
status quo. Their results show that in the face of critic
disagreement, consumers increased the importance of uti1ity-preserving attributes and decreased the importance of
utility-enhancing attributes in their overall evaluations of
the product. Our research extends and refines this work
by examining how shifting a consumer's reference point
for the decision outcome will influence response to critic
consensus for overall product utility.
We propose that to understand fully how a consumer
will respond to uncertainty in the form of critic disagreement one must know the individual's aspiration level or
expectation for the decision outcome (Payne et al. 1980,
1981 ). Risk aversion is commonly observed for alternatives that meet or exceed an individual's aspiration level,
whereas risk seeking can occur when an alternative falls
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advice of critics when selecting a movie (Wall Street
Journal 1994) and the advice of friends when selecting
a restaurant (Walker 1995).
The importance of others' opinions is corroborated by
the existence of critics, ranging from institutional critics
such as Consumer Reports to individual critics such as
Gene Siskel and Roger Ebert, whose specific purpose is
to disseminate their evaluations of products. The influence
of critics on consumer judgments is substantial because
critics' access to product previews typically makes them
one of the first links in the diffusion of information about
new products. Furthermore, their professional status lends
them credibility. Our research examines consumer use of
others' opinions in the context of critic ratings of experiential products. We focus on overall ratings rather than
on the information content contained in reviews, because
overall ratings have been shown to be more influential
than information content in affecting consumer interest
(Wyatt and Badger 1990).
However, an overall rating is dependent on the other's
perceptions of, and weighting function for, product attributes and experiential aspects that may differ from one's
own (Einhorn and Koelb 1982). For example, a critic's
opinion of a restaurant may depend equally on service,
atmosphere, and food quality, whereas your own opinion
may be heavily influenced by food quality and less influenced by atmosphere. In addition, experiential products
evoke many different emotional responses, thus rendering
the possibility for multiple interpretations of product experience (Eliashberg and Sawhney 1994; Hoch and Ha
1986). This suggests that an individual critic's opinion
may, or may not, be useful in assessing your own opinion.
When search costs are low, consumers may be motivated to seek multiple critic opinions to resolve the problem (Payne, Bettman, and Johnson 1993; Shugan 1980).
In fact, some periodicals, such as Entertainment Weekly
and Premiere, compile film ratings of multiple critics in
a matrix format for their magazine readers and web site
viewers. The forecasting literature suggests that seeking
multiple opinions is the normatively correct strategy for
dealing with the idiosyncrasies of others' opinions (Clemen 1989; Clemen and Winkler 1986; Hogarth 1977;
Winkler 1989). Taking an average of these opinions increases the reliability of the sensory information and reduces the influence of an outlier opinion. The simplicity
of an averaging strategy makes it attractive for consumers.
The conclusion of a vast number of studies on information
integration is that individuals combine separate pieces of
information into an overall evaluation by averaging them
(Anderson 1996; Kahn and Ross 1993).
39
40
Determinants of Aspiration Level
Tversky and Kahneman (1991) acknowledge that prospect theory does not delineate the factors that influence
a consumer's reference point. For a decision outcome,
this reference point is likely to be an individual's aspiration level as to what would constitute a satisfactory versus
an unsatisfactory outcome (Payne et al. 1980). For instance, a wine connoisseur would be expected to have a
higher standard for an acceptable bottle of wine than an
occasional drinker and thus a higher aspiration or reference level. The connoisseur may therefore treat an average bottle of wine as a loss, whereas the occasional
drinker may treat the same experience as a gain.
We are interested in examining how variables associated with the decision context affect consumers' aspiration level and thus their response to critic consensus. Four
studies are conducted to examine context factors that have
been shown to influence consumers' aspiration levels:
( 1) consumer expectations of product quality in a given
category (Meyer 1981;-Ross and Creyer 1992), (2) the
price of a product alternative (Bettman 1973; Huber and
McCann 1982; Levin, Johnson, and Faraone 1984), and
(3) the degree of social risk involved (Jacoby and Kaplan
1972).
The aspiration level may be determined by the average
quality in a given category, such that alternatives above
(below) the category average are viewed as gains
(losses). This average quality level may be data driven
by the average of the critic ratings across the alternative
set (Meyer 1981) or theory driven by consumer expectations from prior experience (Broniarczyk and Alba
1994). This is examined in study 1. Price may also influence consumers' aspiration levels, as prior research suggests that consumers make price-quality inferences when
evaluating alternatives (Huber and McCann 1982; Levin
et al. 1984), with higher prices associated with higher
quality levels. Higher prices are also associated with
greater financial risk (Jacoby and Kaplan 1972) and thus
are related to a smaller percentage of outcomes deemed
acceptable by a consumer (Bettman 1973). Thus, in study
2 we expect to find that as price increases, consumers'
aspiration levels shift to a higher standard. Moreover,
the social risk associated with a decision is expected to
influence the location of the aspiration level. As social
risk increases, consumers' egos become more vulnerable
and they are expected to set higher standards for an acceptable outcome as a protection mechanism (Dowling
and Staelin 1994; Jacoby and Kaplan 1972). Thus, in
studies 3 and 4 we expect to find that as the perceived
social risk increases, consumers' aspiration levels shift
upward.
We propose that shifts in consumers' aspiration levels
that result from these changes in the decision context will
affect how they respond to critic disagreement. Specifically, we hypothesize that
HI: Consumer response to critic consensus will depend on the aspiration level evoked by the decision context such that
(a) consumers will evaluate an alternative
more favorably when there is critic disagreement than agreement if the average
of its critic opinions is below
aspiration
level;
(b) consumers will evaluate an alternative
more favorably when there is critic agreement than disagreement if the average of
its critic opinions is above an aspiration
level.
an
Critic Opinions and Personal Preference for
Product Attributes
Critic consensus may also have an impact on the relative weight consumers assign to critic opinions versus
their personal preference for product attributes. That is,
critic consensus may affect not only the valuation of the
critic ratings (Hypothesis 1) but also the weight this information receives in consumers' final judgments. In the face
of critic disagreement, consumers may rely more on their
personal preference for product attribute values when
there is a lack of consensus among the critics than when
there is agreement about the quality of a given alternative
(Jaccard and Wood 1988).
H2: Consumers will respond to critic disagreement
by discounting the critic opinions and increasing their reliance on product attribute information in their evaluations.
Infonnativeness of Critic Opinions
Consumers may attempt to resolve inconsistency in
critic opinions by focusing on only a subset of the information (Ganzach 1994). Differential attention to the individual critics is expected to be influenced by critic informativeness. Assuming that each of the critics is equally
consistent in applying his or her judgment policy for eval-
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below an aspiration. For example, imagine two new movies have been released this week and rated by three critics.
Both movies received an average rating of three out of
four stars, but movie A had low consensus (two, three,
and four stars), whereas movie B had high consensus
(three ratings of three stars). We would predict that a
consumer with a high aspiration level (four stars) would
be more likely to choose movie A, whereas a consumer
with a low aspiration (two and one-half stars) would be
more likely to choose movie B. In situations in which
consumers have high expectations, critic disagreement
improves the chance of meeting or exceeding the goal
and, thus, consumers are expected to favor critic disagreement. Alternatively, when expectations are low, disagreement among critics raises the possibility that the product
may fall short of an acceptable level and, hence, consumers are expected to prefer critic consensus.
JOURNAL OF CONSUMER RESEARCH
41
INTEGRATING OPINIONS
uating alternatives, a critic whose ratings exhibit high
variance is more informative than a critic whose ratings
exhibit little variance (Coombs, Dawes, and Tversky
1970; Shannon and Weaver 1949). An earlier study
(West 1996) found that consumers were sensitive to the
informativeness of others' opinions. Therefore, we expect
that they may weigh an informative critic's opinion more
heavily than the opinion of an uninformative critic.
H3: Consumers are sensitive to the informativeness
of critics when integrating their opinions for
evaluation of experiential products.
METHODOLOGY
Stimulus Development
Two criteria guided the selection of product categories
for examining consumer response to critic consensus. First,
we required that the product category be relatively familiar
to the subject. Familiarity with the evaluation task is important because it allows us to better capture how judgments
are formed and how expectations and aspirations influence
evaluations in a naturally occurring environment. This criterion rules out durable goods, which tend to be purchased
infrequently and for which many college students lack experience shopping. Second, we wanted a product for which
consumers typically turn to the opinion of critics for advice.
The categories selected for testing were movies (study 1)
and restaurants (studies 2-4).
A core set of 20 alternatives, each induding three critic
ratings, was developed for use in studies 1- 3 (see Table
1 ) .1 Three goals were established for constructing this
set of alternatives: First, we wanted to create orthogonal
CRITIC RATING INFORMATION
Alternative
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Average
Variance
Critic
A
Critic
9
9
8
8
6
5
5
2
3
2
10
10
10
9
7
6
6
3
3
3
6.20
8.06
9
5
4
1
7
6
7
8
4
6
10
6
5
2
8
7
8
9
4
7
6.15
5.50
B
Critic
C
4
6
6
5
8
4
6
7
7
4
5
7
·7
6
9
5
7
8
7
5
6.15
2.03
Average
Variance
7.33
6.67
6.00
4.67
7.00
5.00
6.00
5.67
4.67
4.00
8.33
7.67
7.33
5.67
8.00
6.00
7.00
6.67
4.67
5.00
8.33
4.33
4.00
12.33
1.00
1.00
1.00
10.33
4.33
4.00
8.33
4.33
6.33
12.33
1.00
1.00
1.00
10.33
4.33
4.00
cntlcs whose average ratings were approximately the
same. Orthogonality among the critics was important to
permit estimation of differential weighting of the three
critics; all critic intercorrelations in Table 1 are less than
.09. Second, in order to test the effect of aspiration level
on subjects' response to critic consensus we needed to
vary the average of the critic ratings as well as the level
of agreement among the critics for a given alternative
(last column). In addition, we needed to have both highand low-consensus alternatives at all levels of average
critic rating. Critic consensus was operationalized as the
variance among the three critic ratings for a given film.
This variance measure is consistent with Meyer (1981)
and others who have examined cue consensus effects
(Brannick and Brannick 1989; Ganzach 1994, 1995).
Third, besides varying the level of critic disagreement,
we were also interested in manipulating individual critic
informativeness. In order to accomplish this, the three
critics must differ in the variance of their ratings across
the set of 20 alternatives (last row). As indicated in the
table, Critic A (8.06) has a higher variance in ratings
than Critic B (5.50), who has a higher variance in ratings
than Critic C (2.03). The set of alternatives presented in
Table 1 accomplishes all three of these objectives and
was used to construct the stimuli for the first three studies.
STUDY 1
lIn study 4, subjects were asked to make choices given pairs of
alternatives that had a common mean critic rating but differing levels
of critic consensus. Therefore, a separate set of alternatives was constructed for this task.
The purpose of this study was to examine how critic
opinions and attribute information are integrated by subjects to form product evaluations. The product category
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In summary, we expect to find that consumers use both
attribute information and critic opinions in evaluating
product alternatives. Critic opinions are used by consumers to help predict their own preferences. These opinions
offer a form of indirect experience that is particularly
useful for experiential products. When multiple opinions
are provided, the consumer is faced with the task of integrating the information. This task is relatively easy when
the individuals agree, but questions arise when there is a
lack of consensus. Consumers' response to disagreement
in critic opinions is expected to be influenced by the
aspiration level associated with their decision such that
critic disagreement (agreement) results in more favorable
product evaluations for alternatives whose average critic
rating is below (above) the aspiration level. Consumers
may resolve critic disagreement by focusing more attention on product attribute values or attending to a subset
of the critics who have shown a history of providing
informative opinions.
TABLE 1
42
used was movies, which is highly familiar to student participants. We tested how an aspiration level, based on an
average movie quality, influenced subjects' response to
critic consensus.
Subjects and Design
Procedure
Each subject was given a packet containing the experimental materials. Subjects were told that the films that
they would be rating would soon be released in their area
and that a local cinema wanted to know about their level
of interest in the movies. Each of the 100 fictitious movies
was rated on either a lO-point "interest scale" (1 = not
at all interested, 10 = extremely interested) or a lO-point
"liking scale" (1 = horrible movie, 10 = excellent
movie) .3 Subjects completed the rating task at their own
pace.
A follow-up task to assess personal preference for product attributes and average movie quality had subjects rate
80 recently released videos on a lO-point liking scale.
20ther factors are likely to influence consumer preference for a movie
including the director, film previews, and advertisements. However, for
the purpose of experimental control we have restricted our focus to
genre and performers that are often used for classifying movies both in
video stores and books. In order to avoid unrealistic combination~ of
genre and performers, two experts were asked to review the list of
fictitious movies, and changes were made based on their input.
3The results for the interest scale and liking scale were not statistically
different; therefore, the data were pooled together for all of the analyses.
For each video, only the title, genre, and performer information were provided, and subjects were instructed to
rate only the videos they had seen. Finally, subjects selected their five favorite performers from a list of 98
popular actors and actresses. The entire task took subjects
an average of 40 minutes to complete.
Aspiration Level. In this study, subjects' aspiration
level was not manipulated. Subjects' aspirations were based
on their expectations of averages movie quality (i.e., priors
for the category) and the average of the critic ratings provided (i.e., data driven by the alternative set). The average
rating (6.16) of previously viewed videos for the experimental subjects was used as an estimate of "average movie
quality." This estimate of average movie quality was similar to that of an additional 60 pilot subjects and equivalent to
the average of the critics' ratings across the 20 alternatives
described in Table 1.
Measuring Personal Preference. The rank order of
genre and number of favorite performers were summed
together to create a variable labeled "personal preference." To establish a rank ordering of the five film genres,
each subject's ratings of the previously viewed videos
were regressed on a set of dummy variables. The number
of favorite performers that a given fictitious movie contained was computed on the basis of subjects' self reported preference for popular actors and actresses.
Results
The following aggregate-level regression model was
used to test all model predictions using subject ratings as
the dependent variable:
Rating = bo + b l Critic A + b2 Critic B
+ b3 Critic C + b4 Consensus + b5 AL
+ b6 Consensus X AL + b7 Preference
+ bg Preference
X
Consensus
(1)
+ b 9 Preference X AL
+ blO Preference X Consensus
X AL + e,
where the independent variables include the three critic
ratings, Critic A, Critic B, Critic C, the Consensus between the three ratings; AL is a dichotomous variable
representing whether the average of the critic ratings was
above or below the aspiration level (6.16), and Preference
captures the subject's personal preference for the film's
genre and performers. All two-way and three-way interactions between Consensus, AL, and Preference were included. The average parameter estimates of the models
are presented in Table 2.4
4For studies 1-3, hierarchical regressions including all main effects
first and then interactions were performed to test the robustness of the
predicted interaction between consensus and aspiration level. For all
three studies, the hierarchical results are consistent with the estimates
reported in Tables 2-3.
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Eighty-one undergraduate students participated in this
study. The subjects were recruited from a marketing research class and given extra credit points and a coupon
for a free video rental as payment for participating. Each
subject's response to critic consensus was examined by
having individuals rate a series of 100 fictitious movie
descriptions. Each description included three critic ratings
(Critic A, Critic B, and Critic C), the film genre (action/
adventure, comedy, drama, drama/suspense, or romantic
comedy), and the principal and supporting performers
(chosen from a list of 50 top performers). The core set
of 20 alternatives, presented in Table 1, was used to construct 100 movie descriptions by matching each of the
five film genres to one of the 20 triples of critic ratings
and then assigning a genre-appropriate cast of performers
to the film. 2
The order of presentation of the film information (critic
ratings vs. genre and performers) was counterbalanced
by presenting half of the subjects with movie descriptions
that displayed the critic ratings on top of the description,
while the other half of the subjects saw the critic ratings
below the film genre and performers. The ordering of the
three critics was also counterbalanced between subjects.
Each subject rated the 100 movies in one of three different
random orderings.
JOURNAL OF CONSUMER RESEARCH
INTEGRATING OPINIONS
43
TABLE 2
RESULTS FROM STUDIES 1 AND 2
Study 1
Source
Intercept
Critic A
Critic B
Critic C
Consensus
AL
Preference
Consensus x
Preference x
Preference x
Preference x
AL
Consensus
AL
Consensus x AL
Study 2
Estimate
Standard error
t-statistic
Estimate
Standard error
t-statistic
5.62
.19
.06
.07
-.22
.72
.13
.21
.01
.12
-.03
.06
.03
.04
.03
.08
.11
.02
.12
.02
.02
.03
102.20**
6.02**
1.54
2.43*
-2.77"
6.35**
6.99**
1.80+
.69
5.43**
-1.01
4.97
.49
.33
.16
-.26
1.24
.38
.16
-.01
.11
-.03
.03
.03
.02
.02
.03
.05
.02
.05
.02
.03
.03
164.63**
18.41**
13.37**
7.91**
-10.10*'
22.59**
16.08**
3.31*'
-.11
3.47**
-.93
Aspiration Level and Critic Consensus. We observed
a negative main effect of critic consensus, which indicated
that overall, subjects responded less positively to alternatives when there was critic consensus than when there
was critic disagreement (bconsensus = -0.22, t(8,077)
= -2.77, p < .006). Consistent with Hypothesis 1, we
observed a marginally significant interaction between aspiration level and critic consensus (bconsensus x AL = 0.21,
t(8,077) = 1.80, p < .07), which suggested that the
effect of critic consensus was dependent on consumers'
aspiration levels (see Fig. 1). 5 A follow-up analysis in
which the data were split by AL revealed that when the
average of the critic ratings fell below AL, subjects evaluated alternatives more favorably when there was critic
disagreement than when there was critic consensus (p
< .005, one-tailed). Although the difference is not significant, the pattern appeared to reverse when the critic
average exceeded the aspiration level, with subjects tending to evaluate alternatives less favorably when there was
critic disagreement, (p = .17, one-tailed).
Personal Preference for Product Attributes. As expected, we observed that preference for a film's genre and
performers is strongly associated with subjects' movie
evaluations (bPreference = .13, t(8,077) = 6.99,p < .0001).
We also observed that personal preference for product
attributes matters more for alternatives whose· average
critic rating exceeds the aspiration level than for alternatives whose average critic rating falls below the aspiration
level (bPreferencexAL = .12, t(8,077) = 5.43,p < .0001).
Inconsistent with Hypothesis 2, our analysis indicates
that subjects do not rely more heavily on their personal
5For graphic illustration purposes, alternatives were classified as high
or low consensus on the basis of a median split of the data; however,
consensus was represented as a continuous variable in the model.
preference for product attributes in the face of critic disagreement (bPreference x Consensus = 0.01, t(8,077) = 0.69,
p > .50 and bpreference x Consensus X AL = -0.03, t( 8,077)
= -1.01, p > .30). Instead of discounting the critic opinions when they disagree, subjects continue to pay attention to the critics. However, the focus of their attention
appears to shift either to the highest of the three critic
opinions for below AL alternatives or to the lowest of
the three critic opinions for above AL alternatives.
Critic Informativeness. Finally, we found support for
Hypothesis 3, the prediction that subjects are sensitive to
differences in the informativeness of individual critics,
and differentially weight them accordingly. The most informative critic's opinion (Critic A) was weighted more
heavily than either the moderately informative critic
(bcriticA-CriticB = .13, P < .01), or the least informative
critic's opinion (bcriticA-CriticC = .12, P < .01), irrespective of the order of presentation of the three critic ratings.
Thus, consumers are sensitive to the diagnosticity of the
ratings provided by the critics.
Discussion
These results suggest a number of important findings
related to consumer information evaluation and predicted
preference. Not surprisingly, our results indicate that consumers use more than product attribute information in
evaluating alternatives. The interaction between aspiration level and personal preference for product attributes
indicates that an alternative needs to be high on both
average critic rating and preference for attributes in order
to receive a favorable evaluation. Surprisingly, critic opinions are taken into consideration even in the face of critic
disagreement. We did not observe consumers shifting
their reliance to product attributes when there is a lack
of critic consensus. Consumers are sensitive to both the
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+p '" .10.
'P'" .05.
"P'" .001.
44
JOURNAL OF CONSUMER RESEARCH
FIGURE 1
ASPIRATION LEVEL EFFECTS ON CONSUMER RESPONSE
TO CRITIC CONSENSUS
Study 1
is also clear that consumers are sensitive to the informativeness of others' opinions. Our results indicate that consumers weight an informative critic's opinion more heavily than an uninformative critic's opinion.
8.50
7.25
6.00
5~82
4.75
5.42
C>
~
0::
STUDY 2
6.95
-+- High Consensus
___ Low Consensus
3.50 - + - - - - - - + - - - - - - - 1
Below
Above
Aspiration Level
Subjects and Design
8.22
7.25
C>
c:
~ 6.00
0::
-+- High Consensus
4.75
3.50
--- Low Consensus
3.54
Below
Above
Aspiration Level
Study 3
8.50
7.25
C>
c:
:a; 6.00
0::
4.75
7.79
4V
/57
4.70
3.50 + - - - - - - - t - - - - - - - i
Below
Above
Aspiration Level
-+- High Consensus
--- Low Consensus
A total of 177 students (both business and nonbusiness) participated in the study and received either extra
course credit or payment of $7.00. Forty-five of the participants were asked to provide additional information regarding their aspiration level.
Consumer reliance on critic opinions for evaluating
various price-tier restaurants was examined by having
subjects rate a series of 80 restaurant descriptions. Each
description included three critic ratings, the cuisine of the
restaurant (Italian, Mexican, Chinese, or seafood), and
the average price of the restaurants' entree offerings (low
= under $10; moderate = $10-$20; expensive = over
$20). Once again, the core set of 20 alternatives, presented in Table 1, was used to construct the 80 restaurant
descriptions by matching each of the four cuisines to one
of the 20 triples of critic ratings. As in study 1, the labeling of the three critics, as well as the order of presentation
of the critic ratings, cuisine, and price information, was
counterbalanced across subjects. Each subject rated the
80 restaurants in one of four different random orders. All
subjects were asked to rank order their preference for the
cuisine types after completing the restaurant rating task
as a measure of personal preference.
Procedure
degree of consensus among the critics and the informativeness of critic ratings.
Consumers' response to critic consensus is influenced
by their aspiration level. When the average rating of the
critics falls below the aspiration level, consumers prefer
variance in critic opinions because these alternatives offer
some opportunity to meet or exceed the consumers aspiration level (one of the critics must have favorably evaluated the product ). However, alternatives with equivalent
mean critic ratings that exhibit high critic consensus offer
no hope of achieving the desired level of utility or satisfaction. Conversely, when the average rating of the critics
exceeds the aspiration level, consumers prefer consensus
in critic opinions because these alternatives are sure winners. In these situations, consumers respond negatively
to critic disagreement because there is a chance their experience may fall short of their expectations (one of the
critics must have evaluated the product unfavorably). It
The procedure used in this study was similar to that
used in study 1. Subjects were given a packet containing
all experimental materials. The opening instructions described the rating task and explained that a new shopping
mall was going to open in the area and the management
was interested in getting students' opinions about potential restaurants to include. Subjects rated the hypothetical
restaurants at their own pace on the same 10-point interest
scale or liking scale used in study 1. 6 After the rating
task, all of the subjects were asked to rank order the four
restaurant cuisines presented. Forty-five of the subjects
were asked to provide additional information about their
aspiration level for the dining experience in the three
60nce again, the results for the interest scale and liking scale were
not statistically different; therefore, the data were pooled together for
all of the analyses.
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Study 2
8.50
The purpose of this study was to replicate the results
found in study 1 in another product category, restaurants,
and to directly manipulate subjects' aspiration level via
the price of the alternatives.
45
INTEGRATING OPINIONS
price-tier restaurants. The entire task took subjects on
average 30 minutes to complete.
Aspiration Level. In order to check whether the price
manipulation influenced subjects' aspiration levels, we
asked 45 subjects to provide a self-report of their aspiration level for the three price-tier restaurants. SpeCifically,
we asked subjects to provide the minimum standard that
they would find acceptable for an inexpensive, moderately
priced, and expensive restaurant. The response scale used
was identical to the restaurant rating scale (1 = horrible
restaurant and 10 = excellent restaurant). The average
aspiration level increased across the three price tiers
(Xlnexpensive = 4.44, XModeratelyPriced = 6.24, XExpensive = 8.32;
F(2, 122) = 97.24,p < .0001).
A similar regression analysis to that performed in study
1 was used to test for the effect of aspiration level on
subjects' response to critic consensus. Subjects' aspiration
level was defined in terms of price and based on the selfreports of 45 subjects (ALlnexpensive = 4.44, ALModerately Priced
= 6.24, ALExpensive = 8.32). Personal preference for restaurant cuisine was based on each subject's rank ordering
of the cuisines. The parameter estimates of the aggregate
model are presented in Table 2.
Aspiration Level and Critic Consensus. Once again,
we observed a negative main effect of critic consensus,
which indicates that overall, subjects responded less favorably to product alternatives in the face of critic consensus than critic disagreement (bconsensus = -0.26, t( 13,229)
= -10.10, p < .0001). Consistent with Hypothesis 1,
we observed an interaction between critic consensus and
aspiration level (bconsensusxAL = 0.16, t(13,229) = 3.31,
p < .0001). The relationship between aspiration level
and critic consensus is illustrated in Figure 1. As in study
1, a follow-up analysis in which the data were split by
AL revealed that when the average of the critic ratings fell
below AL, subjects evaluated alternatives less favorably
when there was critic consensus than when there was
critic disagreement (p < .0001, one-tailed). The direction
of results for average critic ratings that exceeded the AL
was consistent with predictions; although marginally significant (p = .09, one-tailed), subjects appeared to respond move favorably when there was critic consensus
than when there was critic disagreement.
A second regression analysis was performed in order
to test whether the average of the product category or
aspiration level via price provides a better explanation of
subjects' response to critic consensus. This involved a
two-step process, similar to the procedure used for testing
for a mediating relationship between variables (Baron
and Kenny 1986). The model was first estimated using
the average of the critic ratings, AV = 6.17, as a dichotomous variable to test for differential response to critic
consensus based on the set of alternatives. We observed a
negative interaction between consensus and average critic
Personal Preference for Product Attributes. We observed that preference for a restaurant's cuisine is strongly
associated with subjects' ratings (bPreference = .38,
t(13,229) = 16.08,p <.0001). Consistent with study 1,
we observed that personal preference for product attributes matters more for alternatives whose average critic
rating exceeds the aspiration level (bPreference x AL = 0.11,
t(13,229) = 3.47, p < .0005). Once again, we did not
find support for Hypothesis 2; there is no evidence that
subjects rely more heavily on their personal preference
of product attributes in the face of critic disagreement
(bPreferencexConsensus = -0.01, t(13,229) = -0.11, p >
.90). Subjects continue to pay attention to critic opinions
instead of discounting for disagreement. However, in the
face of disagreement the focus of their attention seems
to shift to either the high critic rating (below AL) or the
low critic rating (above AL).
Critic Informativeness. The results support Hypothesis
3 and indicate the subjects are sensitive to differences in
the informativeness of individual critics, and differentially
weight them accordingly. The most informative critic's
opinion was weighted more heavily than either of the
other critics' opinions (bcriticA-CriticB = .16, P < .001;
bCriticA- CriticC = .33, p < .0001; bCriticB-CriticC = .17, P
< .001).
Discussion
The results from study 2 indicate that aspiration level,
rather than the average of the product category, influences
how consumers will respond to a lack of consensus among
critic opinions. Here, a high price creates high aspirations,
and most product alternatives are likely to fall short of
subjects' expectations, placing them in the domain of
losses. Subjects respond with risk-seeking behavior,
whereby alternatives with critic disagreement are rated
more favorably than alternatives with critic agreement.
Conversely, a low price creates low aspirations, and thus
most product alternatives are likely to meet or exceed
subjects' expectations, placing them in the domain of
gains. Here we observe risk aversion, resulting in alternatives with high critic consensus being rated more favorably than alternatives where the critics disagree:
7Because the aspiration level for the moderately priced restaurants
was equivalent to the average of the critic ratings across alternatives,
we restricted this analysis to expensive and inexpensive restaurants only.
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Results
rating (bconsensusxAV = -0.09, t(8,618) = -1.90, p
< .05). The price-tier-specific aspiration level, AL, was
then added to the model, along with interactions between
AL and Consensus, and AL and Preference. 7 When the
aspiration level was included in the model, this interaction
disappeared and instead we observed a positive interaction between consensus and aspiration level (bconsensus x AV
= 0.08, t(8,618) = 0.90, p > .36; bconsensus x AL = 0.22,
t(8,618) = 2.95,p < .003) consistent with a referencedependent model.
JOURNAL OF CONSUMER RESEARCH
46
Our other results are also highly consistent with those
of study 1. Once again, we observed an interaction between aspiration level and personal preference for product
attributes, which indicated that critic opinions and/ or
product attributes appear to act as a screening mechanism
for evaluating alternatives. Again, we did not observe
consumers shifting their reliance to product attributes
when there was a lack of critic consensus. Finally, consumers were shown to be sensitive to the informativeness
of others' opinions and weight an informative critic's
opinion more heavily than an uninformative critic's opinIon.
STUDY 3
Subjects and Design
Fifty-three students participated in this study for compensation and a lottery chance. Consumers' response to
critic consensus under different levels of perceived social
risk was examined by having subjects rate 20 restaurant
descriptions. Social risk was manipulated within subjects
by varying the decision context for evaluating restaurants,
either as a first date (high social risk) or dining with
a friend (low social risk). Each restaurant description
included only three critic ratings; alternatives were generated using the core set of 20 critic triples presented in
Table 1. Similar to studies 1 and 2, the ordering of the
three critics, as well as the random order of restaurant
presentation, was counterbalanced across subjects. Unlike
in study 2, subjects rated the 20 low-risk and the 20 highrisk alternatives in separate blocks that were counterbalanced across subjects.
Procedure
The procedure used was similar to that used in studies
1 and 2. The opening instructions described a scenario in
which the subject had accepted a job and moved to an
unfamiliar city. The subject was asked to evaluate various
local restaurants for dining with a friend who came to
help them move or for dining with an attractive new
neighbor s/he met while moving in. Subjects were told
that all of the restaurants were in the same price range
and given an explicit budget constraint ( "your company
provides a $35 dining allowance"). All subjects were
exposed to both decision contexts (dining with a friend
Aspiration Level. In order to check whether the social
risk manipulation influenced subjects' aspiration levels,
we asked each of the subjects to provide a self-report of
their aspiration level for the two decision contexts. As in
study 2, subjects were asked to provide the minimum
standard that they would find acceptable for a restaurant
given the social context of the dining experience. The
response scale used was identical to the restaurant rating
scale (1 = horrible restaurant and 10 = excellent restaurant). As expected, the average aspiration level for the
two social contexts differed significantly (XPriend = 5.41,
XPirstDate = 7.00; F(1, 104) = 36.99,p < .0001).
Results
A regression analysis similar to that used in studies 1
and 2 was used to test the effect of aspiration level on
subjects' response to critic consensus. Gender was included
as a covariate in the analysis, as males and females may
differ in the perceived risk associated with dating. Although males tended to rate restaurants lower, on average,
than females (bGender = - .09, t( 2,056) = -2.13, p < .04),
there is no evidence of gender differences in response to
critic consensus or aspiration level. A test for order effects
of the two scenarios revealed no difference in either subjects' evaluations or response to critic consensus.
Subjects' aspiration levels were defined at the individual level based on their self-report for the two social
contexts. The parameter estimates of the aggregate model
are presented in Table 3.
Aspiration Level and Critic Consensus. We observed
a nonsignificant negative relationship between subject ratings and critic consensus (bconsensus = -0.02, t(2,056)
= -1.03, p = .2). As predicted by Hypothesis 1, we observed a significant interaction between critic consensus and
aspiration level (bconsensus x AL = 0.07, t( 2,056) = 2.04, p
< .04). The relationship between aspiration level and critic
consensus is illustrated in Figure 1. A follow-up analysis in
which the data were split by AL indicates a negative effect
of critic consensus below AL (p < .05) and a positive effect
of critic consensus above AL (p < .05).
As in study 2, we were interested in testing whether
the average of the product category or a risk-defined aspiration level better explains subjects' response to critic
consensus. Therefore, a second regression analysis was
performed with the same two-step process reported earlier. We found that when the model was estimated using
the average of the critic ratings to test for differential
response to critic consensus we observed a negative
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The purpose of this study was to replicate the aspiration
level results found in study 2 using another manipulation
of aspiration level, in this case social risk rather than
price. This is important because the financial limitations
of our student subject population in study 2 may have led
them to perceive high-price-tier restaurants as potential
options only if someone else was paying. Unlike in study
2, we did not incorporate subjects' personal preference
for restaurant cuisine because the joint nature of the decision task renders individual preference less relevant.
and a first date). Subjects rated the hypothetical restaurants using the same lO-point liking scale as in studies 1
and 2. After the rating task, all subjects were asked to
provide additional information about their perceptions of
the risk involved in choosing a restaurant for a first date
versus for dining with a friend, as well as their aspiration
levels in the two dining situations. The task took an average of 25 minutes to complete.
47
INTEGRATING OPINIONS
TABLE 3
RESULTS FROM STUDIES 3 AND 4
Study 3
Source
Intercept
Critic A
Critic B
Critic C
Consensus
AL
Gender
Consensus x AL
Gender x Consensus
Gender x AL
Gender x Consensus x AL
Study 4
Estimate
Standard error
t-statistic
6.13
.88
.70
.43
-.02
-.09
-.09
.07
.03
.03
.07
.05
.02
.02
.02
.04
.05
.04
.04
.03
.82
.08
131.40**
37.15**
30.19**
20.03**
-1.03
-1.90
-2.13*
2.04*
.79
.41
.80
Estimate
.18
3.13*
-.04
-.10
-.14
.21
-.22
-.09
-.16
.11
.80
1.80
3.99*
4.11*
.78
2.18
interaction between consensus and average rating
(bconsensus XAV = -0.11, t(2,111) = -2.03, p < .05).
However, when subjects' aspiration levels were included
in the model, this interaction disappeared and instead we
observed a positive interaction between consensus and
- 0.11 , t (2,109 )
aspiration level (bconsensus x AV
= -1.49,p > .13; bconsensusxAL = 0.20, t(2,109) = 2.88,
p < .004).
Informativeness of Critics. Once again, the results
support Hypothesis 3 and indicate that the subjects are
sensitive to differences in the informativeness of individual critics and differentially weight them appropriately.
The most informative critic's opinion was weighted
more heavily than either of the other critics' opinions
(bcriticA-CriticB = .18, P < .001; bCriticA-CriticC = ,45, P
< .0001; bCriticB-CriticC = .27, P < .001).
Discussion
Consistent with studies 1 and 2, we observed that
changes in the decision context affect consumers' aspiration levels and thus their response to critic consensus. As
social risk associated with the decision increased, subjects
set a higher standard for acceptability, resulting in the
average ratings of most product alternatives falling below
their aspiration level. In this loss domain, subjects rated
alternatives with critic disagreement more favorably than
critic consensus because those alternatives offered some
possibility, albeit sometimes remote, that the aspiration
level could be achieved. However, low perceived social
risk resulted in a low aspiration level, and subjects responded with risk aversion for the predominately gains
domain. The pattern of results corroborate the earlier
findings that the effect of critic consensus on product
evaluations depends on consumers' aspiration levels.
STUDY 4
In each of the previous studies, we have examined the
effect of critic consensus and aspirations on alternative eval-
uation. Our results indicate a positive effect of critic disagreement when an alternative falls below expectations,
and conversely a negative effect of critic disagreement for
alternatives exceeding expectations. This final study will
examine whether the proposed model can also account for
consumer choice. In choice, alternatives falling below the
aspiration level may be discarded from consideration with
minimal influence of critic consensus (Meyer 1981). As
in study 3, aspiration level is manipulated via the social
risk associated with the decision context.
Subjects and Design
One hundred thirty-nine students participated in this
study for extra course credit. Response to critic consensus
in differing social contexts was examined by having subjects choose between restaurant pairs with equal mean
critic ratings but differing levels of critic consensus. Each
restaurant in the pair was rated by three critics on a 100point scale (100 = excellent restaurant, 0 = horrible restaurant).
Two pairs of restaurant alternatives were constructed
that varied in mean critic rating (40, 80); each pair contained a low-variance (10.69) and high-variance (170.7)
option (low variance = 36, 40, 44; 76, 80, 84; vs. high
variance = 24, 40, 56; 64, 80, 96). Three filler pairs with
moderate variance were used to establish the range of the
scale (mean ratings of 30, 60, and 90). The presentation
of the alternatives was counterbalanced for mean critic
rating, position of the high-variance option, and order of
the critic ratings. As in study 3, social risk was manipulated within subject by varying the decision context of
the choice task, either as a first date (high social risk) or
dining with a former roommate (low social risk). Decision context was counterbalanced between SUbjects.
Procedure
As in study 3, the opening instructions outlined the
decision scenario (dining with a former roommate or a
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'p s; .05.
"p oS .001.
48
JOURNAL OF CONSUMER RESEARCH
first date). Subjects examined five pairs of restaurants in
each decision context and were asked to choose the preferred option in each pair. The three filler pairs preceded
the two focal pairs. A distracter task was completed prior
to examining the second decision context and subsequent
choices for the same five restaurant pairs. After the choice
task, subjects provided additional information about their
aspiration levels in the two dining scenarios. The task
took an average of 15 minutes to complete, including the
distracter task between the two decision contexts.
Results
A categorical analysis was performed to test the effect
of aspiration level on response to critic consensus. A test
for order effects for the two scenarios revealed no difference in subjects' choices or response to critic consensus.
Gender was included as a covariate in the model, but,
unlike in study 3, we observed a gender difference in
response to critic consensus. In particular, males were
more likely to choose the low-consensus alternative than
females (male = 57 percent, female = 45.5 percent,
bGender x Consensus = -0.22, X2 (548) = 4.11, p < .05).
Once again, aspiration level was defined at the individual level on the basis of subjects' self-reports for the
two decision contexts. A disproportionate number of our
observations fell below (n = 425) rather than above (n
= 123) subjects' aspiration level because of relatively
high minimum standards. Consensus in critic ratings was
represented as a dichotomous variable (low vs. high).
The parameter estimates of the model are presented in
Table 3.
Consistent with studies 1-3, we observed a significant
interaction between critic consensus and aspiration level
(bconsensusxAL = 0.21, X2(548) = 3.99, p < .05). When
the pair's mean critic rating fell below their aspiration
level, subjects tended to choose the option with critic
disagreement (56.2 percent) more often than the option
with critic consensus (43.8 percent). However, when the
mean critic rating of the pair was above their aspiration
level, subjects were less likely to choose the option in
which critics disagreed (44.3 percent) than the option
with critic consensus (55.7 percent). A test for the simple
effects of the interaction once again indicates that critic
consensus had a negative effect below AL (p < .01, onetailed), and perhaps because of low sample size there
was a nonsignificant positive effect above AL (p = .17,
one-tailed) .
GENERAL DISCUSSION
We investigated how consumers integrate critic opinions and attribute information into their product evalua-
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Aspiration Level. As in studies 2 and 3, subjects were
asked to provide the minimum standard that they would
find acceptable for a restaurant given the social context of
the dining experience. The average aspiration level for the
two social contexts differed significantly (XRoommate
= 59.45, XPirstDate = 74.87; t(l, 138) = 11.38,p < .0001).
tions. The results from all four studies indicate support
for the reference-dependent model. Consumers respond
differently to critic disagreement depending on whether
or not product quality or performance is perceived as
above or below their aspiration level. Our results show
that when experts' average opinions indicate that an alternative falls short ofthe aspiration level, consumers prefer
disagreement among opinions because at least one critic
rating (highest) suggests that they may meet or exceed
their aspiration level. However, when the experts are in
consensus that an alternative falls short of a consumer's
aspiration level, the consumer has no hope of achieving
the desired level of utility or satisfaction. Conversely,
when experts' average opinions indicate that a product's
quality or performance meets or exceeds the aspiration
level, consumers no longer prefer variance among opinions and may actually prefer consensus. This suggests
that consumers are concerned about falling below their
aspiration level and thus focus their attention on the low
ratings. For these acceptable alternatives, consensus is
preferred because disagreement raises the possibility that
their experience may fall short of their expectations.
Prior research has demonstrated that consumers' aspirations are influenced by the perceived risk associated
with a decision outcome. We directly manipulate the perceived risk and thus aspirations via price and social risk.
Consumers exhibit a tendency to prefer critic disagreement for high-priced products or decisions associated with
high social risk. This is due to the high expectations associated with these contexts, which results in most alternatives falling below the consumers' aspiration levels.
The interaction we observed between aspiration level
and consensus is consistent with what Ganzach (1994,
1995) refers to as evidence for use of simplifying heuristics (i.e., conjunctive and disjunctive evaluation rules) to
deal with inconsistencies in information. Use of a disjunctive rule is indicated by individuals' focusing more attention on high than on low values. Conversely, use of a
conjunctive rule is indicated by individuals' focusing
more attention on low than on high values. Cognitive
responses would need to be collected to confirm this processing explanation.
Our results also shed further insight into consumer reaction to information uncertainty (Jaccard and Wood
1988). Counter to prior research, we did not observe a
negative effect of disagreement on consumer evaluations;
in fact, we observed that alternatives are rated more favorably in the face of disagreement than consensus. However, this result was driven by the fact that our subjects
had high aspiration levels, and thus the majority of alternatives fell within the domain of losses where we expected to see risk seeking. In addition, our mediation
analyses point out the need to measure consumer aspirations (i.e., reference point) rather than rely on a central
tendency measure ( category average) to predict consumer
response to consensus. Finally, we did not find that consumers attach less weight to critic opinions, relative to
product attribute values, in the face of critic disagreement.
INTEGRATING OPINIONS
8Two scoring rules were used for judging opinion extremity: (I) the
number of alternatives that a given critic gave the highest or lowest
rating among the three critics; (2) the number of "outlier" opinions
based on the endpoints of the scale (ratings of I, 2, 9, or 10). On the
basis of these scoring rules, and an examination of Table I, we observed
little difference in the number of times that Critic A (18) and Critic B
( 16) gave the highest or lowest rating relative to Critic C (8). Similarly,
Critic A (7) and Critic B (5) provided outlier opinions with roughly
the same frequency as Critic C (0). The extremity hypothesis would
predict little difference in weight between Critic A and Critic B, but
significantly less weight was assigned to Critic C. Alternatively, the
informativeness hypothesis would predict a linear ordering of the three
in terms of weight: Critic A > Critic B > Critic C. Our results indicate
that for study I, Critic A > Critic B = Critic C; and for studies 2 and
3 Critic A > Critic B > Critic C. This pattern is more consistent
with the informativeness hypothesis (Hypothesis 2) than the extremity
hypothesis.
In the real world, informativeness may act as a heuristic
for deciding to attend to a particular critic opinion. A
critic who consistently rates products as below or above
average runs the risk that his or her opinion will no longer
be valued by consumers. The task presented here did not
allow subjects to assess the level of fit between their own
opinion and the opinions of the individual critics. Future
research examining how consumers use critic opinions
when they have the opportunity to assess the value of
those opinions is warranted. Some research suggests that
critics may be hired on the basis of their ability to predict
the preferences of their target market (Eliashberg and
Shugan 1997). As our research design did not enable
examination of the interaction between critic consensus
and informativeness, future research might also examine
this topic.
This research allows us to extend the missing-information paradigm (Levin et al. 1985) to account for how
consumers respond in the face of conflicting or inconsistent information. Camerer and Weber (1992) recently
reviewed the research on ambiguity across multiple disciplines and concluded that "uncertainty about the composition of an urn of balls is just one kind of missing information. Feeling ignorant about football or politics, having
doubts about which of several experts is right, wondering
whether your child has a predisposition to the side effects
of a vaccine, or being unsure about another country's
economy are all manifestations of missing information"
(p. 360). Consumer research has focused on missing information about product attributes and needs to examine
other forms of consumer uncertainty (Muthukrishnan
1995) . We expect that the results demonstrated here may
generalize outside of the domain of critic opinions to
any source of information with repeated observations. For
example, in financial markets where performance measures are readily available, response to stock volatility
may depend on both expected returns and consumer aspirations.
Finally, there are two limitations of this work that warrant consideration. First, although our results are theoretically of interest and robust across decision contexts, drivers of aspirations, evaluation, and intended choice, the
magnitude of the interaction between consensus and aspiration level is not very large. This poses a practicallimitation when there are individual differences in aspiration
level. However, it provides insight into why it may be
difficult to observe main effects of consensus in practice.
Second, Bettman (1973, 1975) points out that the perceived risk involved in a decision is determined by the
importance of the decision outcome, as well as consumers' perceptions of their chance of finding an acceptable
product. Although we have focused on the affect of aspiration level on consumers' response to consensus, the
importance of the decision is also likely to influence their
response to uncertainty. As the importance of the decision
increases, the potential regret associated with making a
bad selection may cause consumers to exhibit caution in
their choices.
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This may be due to the fact that consumers recognize the
deficiency of product characteristics in capturing experiential products or the difficulty of predicting the interplay
among attribute values. For instance, a consumer may
like both Meryl Streep and Mel Gibson but be unsure if
this acting combination has anyon-screen chemistry.
Consumers are more likely to face uncertainty for the
experiential products studied here because of their sensory
nature and the need for direct experience. The experiential
aspect of products is a continuum (Holbrook and Hirschman
1982) with even functional products composed of some
experience attributes such as dependability, convenience,
ease of use, and performance quality. Future research should
examine the impact of critic consensus for functional products and whether salience directed to experience attributes
reduces the importance of tangible attributes.
Of further interest is the integration of specific product
attribute information and summary evaluative ratings. Our
results indicate an interaction between aspiration level
and preference for product attribute values, which suggests that one of these sources may be acting as a screening mechanism for evaluating potential alternatives.
Given our data, we cannot determine the exact order of
processing. However, it is clear that either personal preference for a product's attributes exerts a stronger influence on consumer evaluations for those receiving favorable critic evaluation, or critic ratings are given more
weight when an alternative's attributes are appealing. The
collection of process data would be required to resolve
this uncertainty. Future research also needs to examine
the role of the informative content in critic reviews in
shaping consumer learning of product attributes (West,
Brown, and Hoch 1996).
In addition, consumers appear to be sensitive to the differential informativeness of individual critics and weight their
opinions accordingly. An alternative explanation is that consumers base their judgments on the extreme opinions for a
given alternative rather than learn the informational value
of a given critic. However, our results cast doubt on this
alternative explanation, given that Critic A and Critic B
were weighted differentially in studies 1-3 but were equally
likely to report extreme or outlier opinions. 8
49
JOURNAL OF CONSUMER RESEARCH
50
CONCLUSION
[Received April 1996. Revised August 1997. Brian
Sternthal and Robert E. Burnkrant served as editors
and Robert J. Meyer and Joel Huber served as
associate editors for this article.]
REFERENCES
Anderson, Norman (1996), A Functional Theory of Cognition,
Mahwah, NJ: Erlbaum.
Baron, Reuben M. and David A. Kenny (1986), "The Moderator-Mediator Variable Distinction in Social Psychological
Research: Conceptual, Strategic, and Statistical Considerations," Journal of Personality and Social Psychology, 51
(June), 1173-1182.
Bearden, William O. and Michael J. Etzel (1982), "Reference
Group Influence on Product and Brand Purchase Decisions," Journal of Consumer Research, 9 (September),
184-194.
Bettrnan, James R. (1973), "Perceived Risk and Its Components: A Model and Empirical Test," Journal ofMarketing
Research, 10 (May), 184-190.
- - - (1975), "Information Integration in Consumer Risk
Perception: A Comparison of Two Models of Component
Conceptualization," Journal of Applied Psychology, 60
(June), 381-385.
Bone, Paula Fitzgerald (1995), "Word-of-Mouth Effects on
Short-Term and Long-Term Product Judgments," Journal
of Business Research, 32 (March), 213-223.
Boor, Myron (1990), "Reliability of Ratings by Professional
Movie Critics," Psychological Reports, 67 (August),
243-257.
Brannick, Michael T. and Joan P. Brannick (1989), "Nonlinear
and Noncompensatory Performance Evaluation," Organizational Behavior and Human Decision Processes, 44, 97122.
Broniarczyk, Susan M. and Joseph W. Alba (1994), "Influence
of Prior Beliefs, Frequency Cues, and Magnitude Cues
on Consumers' Perceptions of Comparative Price Data,"
Journal of Consumer Research, 21 (September), 219235.
Downloaded from http://jcr.oxfordjournals.org/ by guest on September 11, 2016
Critic opinions play an important role in consumer
evaluation of products, particularly so for experiential
products. But, critics do not always agree. Therefore, understanding how consumers react to critic disagreement
is of vital importance to companies who rely on expert
opinions to disseminate information about their products.
Our results suggest that consumers' expectations and aspirations regarding the decision outcome playa crucial role
in determining how a person will respond in the face of
critic disagreement. The average expectation of product
quality in a category, price of given alternative, and social
risk associated with a decision are all shown to influence
a consumer's aspiration level. This aspiration level is important because it determines whether a given product is
perceived as meeting (a gain), or falling short of (a loss),
expectations. To the extent that consumers are driven to
meet or exceed their aspiration level, they are likely to
respond favorably to critic disagreement.
Camerer, Colin and Martin Weber (1992), "Recent Developments in Modeling Preferences: Uncertainty and Ambiguity," Journal of Risk and Uncertainty, 5, 325-370.
Clemen, Robert T. (1989), "Combining Forecasts: A Review
and Annotated Bibliography," International Journal of
Forecasting, 5, 559-583.
- - - and Robert L. Winkler ( 1986), "Combining Economic
Forecasts," Journal of Business and Economic Statistics,
4 (January), 39-46.
Coombs, Clyde H., Robyn M. Dawes, and Amos Tversky
(1970), Mathematical Psychology: An Elementary Introduction, Englewood Cliffs, NJ: Prentice-Hall.
Dowling, Grahame R. and Richard Staelin (1994), "A Model
. of Perceived Risk and Intended Risk-Handling Activity,"
Journal of Consumer Research, 21 (June), 119-134.
Einhorn, Hillel J. and Clayton T. Koelb ( 1982), "A Psychometric Study of Literary-Critical Judgment," Modem Language Studies, 12 (3), 59-82.
Eliashberg, Jehoshua and Mohanbir S. Sawhney (1994),
"Modeling Goes to Hollywood: Predicting Individual Differences in Movie Enjoyment," Management Science, 40
( September), 1151-1173.
- - - and Stephen M. Shugan (1997), "Film Critics: Influencers of Predictors," Journal of Marketing, 61 (April),
68-78.
Ellsberg, Daniel (1961), "Risk, Ambiguity and the Savage
Axioms," Quarterly Journal of Economics, 75,643-669.
Ganzach, Yoav (1994), "Inconsistency and Uncertainty in
Multi-Attribute Judgment of Human Performance," Journal of Behavioral Decision Making, 7, 193-211.
- - - (1995), "Attribute Scatter and Decision Outcome:
Judgment versus Choice," Organizational Behavior and
Human Decision Processes, 62 (April), 113-122.
Hoch, Stephen J. and Young-Won Ha (1986), "Consumer
Learning: Advertising and the Ambiguity of Product Experience," Journal of Consumer Research, 13 (September),
221-233.
Hogarth, Robin M. (1977), "Methods for Aggregating Opinions," in Helmut Jungermann and Gerard de Zaeuw, eds.,
Decision Making and Change in Human Affairs, Boston:
Dordrecht 231-255.
- - - (1989), "On Combining Diagnostic 'Forecasts':
Thoughts and Some Evidence," International Journal of
Forecasting, 5, 593-597.
Holbrook, Morris B. and Elizabeth C. Hirschman ( 1982), "The
Experiential Aspects of Consumption: Consumers Fantasies, Feelings, and Fun," Journal of Consumer Research,
9 (September), 132-140.
Huber, Joel and John McCann (1982), "The Impact of Inferential Beliefs on Product Evaluations," Journal of Marketing
Research, 19 (August), 324-333.
Jaccard, James and Gregory Wood (1988), "The Effects of
Incomplete Information on the Formation of Attitudes toward Behavioral Alternatives," Journal of Personality and
Social Psychology, 54 (April), 580-591.
Jacoby, Jacob and Leon B. Kaplan (1972), "The Components
of Perceived Risk," in M. Venkatesan, ed., Proceedings
of the Third Annual Conference of the Association for Consumer Research, College Park, MD: Association for Consumer Research.
Kahn, Barbara E. and Robert J. Meyer (1991), "Consumer
Multiattribute Judgments under Attribute Uncertainty,"
Journal of Consumer Research, 17 (March), 508-522.
INTEGRATING OPINIONS
Rogers, Everett M. ( 1976), , 'New Product Adoption and Diffusion," Journal of Consumer Research, 2 (March), 290201.
Roselius, T. (1971), "Consumer Rankings of Risk Reduction
Methods," Journal of Marketing, 35, 56-61.
Ross, William T., Jr. and Elizabeth H. Creyer (1992), "Making
Inferences about Missing Information: The Effects of Missing Information," Journal of Consumer Research, 19
(June), 14-25.
Shannon, Claude E. and Warren Weaver (1949), The Mathematical Theory of Communication, Urbana: University of
Illinois Press.
Shugan, Steven M. (1980), "Cost of Thinking," Journal of
Consumer Research, 7 (September), 99-111.
Tversky, Amos and Daniel Kahneman (1991), "Loss Aversion
in Riskless Choice: A Reference-Dependent Model,"
Quarterly Journal of Economics, 104 (4),1039-1061.
Walker, Chip (1995), "Word of Mouth," American Demographics, 17 (July), 38-44.
Wall Street Journal (1994), "A 'Thumbs Up' Pulls in the
Audience," March 25, B1.
West, Patricia M. (1996), "Predicting Preferences: An Examination of Agent Learning," Journal of Consumer Research, 23 (June), 68-80.
- - - , Christina L. Brown, and Stephen J. Hoch (1996),
"Consumption Vocabulary and Preference Formation,"
Journal of Consumer Research, 23 (September), 120135.
Winkler, Robert L. (1989), "Combining Forecasts: A Philosophical Basis and Some Current Issues," International
Journal of Forecasting, 5, 605-609.
Wyatt, Robert O. and David P. Badger (1990), "Effects of
Information and Evaluation in Film Criticism," Journalism Quarterly, 67 (Summer), 359-368.
Downloaded from http://jcr.oxfordjournals.org/ by guest on September 11, 2016
- - - and William T. Ross, Jr. (1993), "An Experimental
Look and How People Combine Forecasts," working paper, Wharton School, University of Pennsylvania.
Kahneman, Daniel and Amos Tversky (1979), "Prospect Theory: An Analysis of Decision under Risk," Econometrica,
47 (March), 263-291.
King, Charles W. and John O. Summers (1970), "Overlap in
Opinion Leadership across Consumer Product Categories," Journal of Marketing Research, 7 (February), 4350.
Levin, Irwin P., Richard D. Johnson, and Stephen V. Faraone
(1984), "Information Integration in Price-Quality Tradeoffs: The Effect of Missing Information," Memory and
Cognition, 12 (January), 96-102.
- - - , Richard D. Johnson, Craig P. Russo, and Patricia Deldin ( 1985), "Framing Effects in Judgment Tasks Varying
Amounts of Information," Organizational Behavior and
Human Decision Processes, 36, 362-377.
Meyer, Robert J. (1981), "A Model of Multiattribute Judgments under Attribute Uncertainty and Informational Constraint," Journal of Consumer Research, 8 (November),
428-441.
Muthukrishnan, A. V. (1995), "Decision Ambiguity and Incumbent Brand Advantage," Journal of Consumer Research, 22 (June), 98-109.
Payne, John W., James R. Bettman, and Eric R. Johnson
(1993), The Adaptive Decision Maker, New York: Cambridge University Press.
- - - , Dan J. Laughhunn, and Roy Crum (1980), "Translation of Gambles and Aspiration Level Effects on Risky
Choice Behavior," Management Science, 26 (10), 10391060.
- - - , Dan J. Laughhunn, and Roy Crum (1981), "Further
Tests of Aspiration Level Effects in Risky Choice Behavior," Management Science, 27 (8), 953-958.
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