Inferential Beliefs in Consumer
Evaluations: An Assessment of
Alternative Processing Strategies
GARYT, FORD
RUTH ANN SMITH*
The purpose o( this research is to investigate the processing strategies consumers
use to form inferences about missing product informalion. We evaluate the relative
effect of attribute information atxiut a partially described brand and about other fully
described brands, the eflect of attribute intercorrelations, and the effect of prompting
inferences. We find that attribute information about a partially described brand has
a greater influence than that about fully described competitive brands, that highly
correlated attributes more consistently influence inferences, and that prompting
inferences produces substantially different results than tess intrusive measures.
M
elusions are supported. First, consumers' inferences
appear to be based on a number of information sources.
Huber and McCann (1982) and Meyer (1981. 1982)
report that consumers infer the value of missing attributes from quality information about attributes of other
brands in a product class (other-brand information).
However, other authors (Johnson and Levin 1985b:
Lutz 1975; Mazis and Adkinson 1976) offer evidence
that inferences derive from the attribute ratings available about the partially described brand itself (samebrand information). Inferences based on these information sources may be described as using an otherbrand or a same-brand strategy, respectively.
Second, regardless of the use of a same- or an otherbrand strategy, consumers appear to adjust their inferences depending on their perception of the level of uncertainty of the available information. Available information may have uncertain or unclear implications for
inferences because it is perceived to be uncorrelated
with the missing attribute (Huber and McCann 1982;
Johnson and Levin 1985b) or because the value of the
missing attribute is highly variable across the product
class (Meyer 1981). In either case, the consistent finding
is that greater uncertainty leads to greater discounting
of the inferred attribute value (Johnson and Levin
1985b; Meyer 1981).
While these findings offer some insights about how
consumers process information to form inferences,
some unanswered questions remain. First, in naturally
occurring environments, both same- and other-brand
attribute information is likely to be available. Therefore,
inferences about missing product attributes may be
subject to the simultaneous influence of both information sources. Since previous research implies that
odels of consumers' evaluative processes often
assume that available information completely
describes each alternative. However, product information is often incomplete, and consumers' judgments
may therefore be based on inferences about missing information. Inferences, or the construction of meaning
that goes beyond what is explicitly given (Harris 1981).
are pervasive in social cognition (Fishbein and Ajzen
1975; Fiske and Taylor 1984. Wyer and Carlston 1979).
suggesting that they may occur frequently in response
to incomplete product information. However, inferential processes are of recent interest to consumer researchers, and the processing strategies underlying inferences are as yet poorly understood. This study,
therefore, was designed to clarify how consumers use
available information to form inferences about missing
product attributes.
INFERENCES AND CONSUMER
INFORMATION PROCESSING
Although relatively few studies of consumers' inferential processes have been completed, two general con•Gar> T, Ford is Professor, Department of Marketing. Kogod College of Business Administration, the American tJniversity. Washington. D,C, 20016, Ruth Ann Smith is Assistant Proressor, Depanment
of Marketing, The R.B, Pamplin College of Business. Virginia Polytechnic Institute and State University. Blacksburg. VA 24061, The
authors' names are listed alphabetically; each contributed equally lo
this work. The assistance of Michael Mazis. Raheel Masood, Brian
Ratchford. Deborah Strauss Salmond. Darlene Smith, and three
anonymous reviewers is gratefully acknowledged. This research was
partially funded by a grant Trom the Kogod College of Business.
363
RESEARCH • V o l , 14 •December 1987
THE JOURNAL OF CONSUMER RESEARCH
364
inferential processes are driven by whatever information
is available, an important question concerns the relative
impact of these two types of information on inferences
when both are present.
A second question concerns the influence of consumers' perceptions of attribute correlations on inferences about missing information. Either same- or otherbrand attributes perceived to have a low correlation with
an unknown attribute may have less certain implications for inferences than do high-correlation attributes.
Although the influence of attribute intercorrelations on
inferences has been noted (Huber and McCann 1982;
Johnson and Levin 1985b; Meyer 1981, 1982), studies
to date have not systematically manipulated this variable, and its effect on the use of same- and other-brand
inference strategies is unknown.
Third, it is unclear how various experimental procedures used to evaluate inference formation may alter
the very process they are designed to measure. Prior
research has operationalized inferences in various ways.
Some methods, such as obtaining overall product evaluations (Meyer 1981. Experiment 1), probability or frequency of choice (Meyer 1981, Experiments 2 and 3).
or probability of purchase (Huber and McCann 1982)
are relatively unobtrusive. However, studies where inferences are more directly measured by asking respondents to provide a rating for a missing attribute (Johnson
and Levin 1985a, 1985b) may increase the salience of
that information and thus create demand artifacts
(Johnson and Levin 1985b). Therefore, the effects of
prompting inferences should be compared with a less
intrusive procedure. The present investigation was designed to address these issues.
sumer context and in other settings have consistently
demonstrated that inferences are inversely affected by
negatively correlated information (Yamagishi and Hill
1983), while high positive correlations exert a direct
effect on inferences (Huber and McCann 1982). While
these findings imply that highly correlated same- and
other-brand attributes should more substantially affect
inferences than should attributes with low correlations,
this prediction has not been explicitly tested. Thus, the
second hypothesis states that:
H2: Consumers' inferences will be influenced
more by attributes with high correlations than
by those with low correlations lo a missing
attribute.
The third hypothesis concerns the effect of prompting
inferences about missing information on product evaluations. Sawyer (1975) suggests that research procedures
that alter the salience of stimuli may contaminate dependent measures. This possibility is of particular concern in the present context, since prompting inferences
may cause subjects to attend to information that may
not otherwise have influenced their evaluations or that
may lead to a heightened awareness ofthe researchers'
purpose (Johnson and Levin 1985a). The impact of focusing respondents' attention on missing information
by prompting inferences is addressed by the third hypothesis, which predicts that:
H3: Consumers' inferential processes will be substantially different if inferences are directly
prompted rather than indirectly measured.
METHOD
HYPOTHESES
The first hypothesis concerns the relative influence
of same- and other-brand attribute information on inferences, independent of the ecological correlations
among known and missing attributes. Although prior
research implies that both same- and other-brand attributes will influence an inference, it is reasonable to
expect that the magnitude of their influence will differ
when attribute intercorrelations are the same. Compared to same-brand attributes, other-brand attribute
information has less certain implications for inferences.
Since information that offers clear, unambiguous implications has been found to dominate ambiguous information in inference formation (Hinkle 1976), the
influence of same-brand information is expected to
substantially exceed that of other-brand information.
More formally, this hypothesis is stated as;
HI: Consumers' inferences will be influenced
more by same- than by other-brand attribute
information when attribute correlations are
held constant.
The second hypothesis focuses on the effects of attribute correlations on inferences. Studies in the con-
Design
The hypotheses were evaluated i n a 2 X 2 X 2 x 2
X 2 factorial design. The first two factors represent
same-brand attribute (SBA) and other-brand attribute
(OBA) information, respectively. Each source of information could assume either a high or a low quality rating. The third factor represents the correlation between
the same-brand attribute and the missing attribute
(CSBA), while the fourth factor is the correlation between the missing attribute and the other-brand information (COBA). Both CSBA and COBA assumed either
a high or low level.
These four factors were all treated as within-subjects
factors whose levels were systematically varied for hypothesis testing. Specifically, two same-brand and two
other-brand attributes with either an extreme high (close
to +1) or extreme low (close to 0) ecological correlation
with the missing attribute were assigned either high or
low quality ratings. By operationalizing SBA and OBA
in terms of specific attributes and varj'ing their quality
level, the relative influence on inferences of same- and
other-brand information with various correlations to a
36S
INFERENTIAL BELIEFS
missing attribute could be determined with the greatest
clarity.
The fifth factor, judgment task, was a between-subjects variable consisting of two levels. In one task condition, an inference about the value ofthe missing attribute was directly prompted while no prompt was employed in the second task condition.
As explained in more detail below, the within-subjects
factors were fully crossed to create experimental stimuli
describing various brands of 10-speed bicycles. This
product class was selected because pretests revealed it
to be familiar to college students serving as subjects,
and complex enough to involve multiple attributes with
correlations of different magnitudes with a missing attribute. These stimuli were evaluated by subjects randomly assigned to one ofthe two judgment tasks.
Stimulus Materials
Experimental stimuli consisted of brief profiles of two
comparable brands of bicycles, each described with respect to the quality of two attributes. One bicycle in
each pair was incompletely described in that one attribute rating was provided and one was missing ("not
reported"). For the second brand, both attribute ratings
were available. Therefore, same- and other-brand information were simultaneously available for the judgment tasks. An example ofthe kind of information provided to subjects is presented in Figure A.
In developing these stimuli, four combinations of attribute correlations were created by fully crossing CSBA
and COBA. The specific attributes exhibiting high or
low intercorrelations with the missing attribute were
selected during pretesting in which 10 attributes were
identified as quite important in selecting a bicycle {x
2. 5.5; s.d. £ 1.5 on a 7-point scale). The perceived intercorrelations among all pairs of these attributes were
obtained from the estimates of a convenience sample
{n = 19). Respondents were asked to assume they knew
the quality level of one attribute in a pair and to indicate
the probability that they could predict the quality level
ofthe other attribute given this knowledge. Probabilities
close to 1.0 were interpreted to indicate a high perceived
correlation between attributes.
Four attributes exhibiting relatively symmetrical
conditional probabilities [p {a\b) = p (b\a)] of various
magnitudes and with low standard deviations {s.d.
£ 0.25) were selected for use in the brand descriptions.
One of these, workmanship, was always the missing attribute ofthe partially described brand. The second attribute describing this bicycle (i.e., SBA) was either durability or weight, which reflected high and low correlations, respectively, as indicated by mean conditional
probabilities of 0.74 and 0.33.
The fully described brand in each pair included a
rating of an attribute with either a high or a low correlation with the missing attribute, plus a rating of a
filler attribute. Workmanship (which was also the miss-
FIGURE A
SAMPLE EXPERIMENTAL STIMULUS
Brond D
Brond N
Workmanship
Workmanship
10
Reputation of
Authorized Deolert
5
?
Durability
B
NOTE. In Ifas sUmuKrt Dotti tfie »ame-U»ry) (dur»t]*btyl and oOiB>-t)rftna (wortimanimpl •!•
lnbute« ara higtily corretaied wiih tri« missinQ ami&ute. and txith am raied si a riigri quality
Wvsl (Roputaton of aumoruM) OMWrs Is afliterattiibut*.) Each tuOtact r*c«iv«a a total ol
ing attribute ofthe partially described brand) was selected as the high correlation other-brand attribute under the assumption that it would be the most closely
related to the missing information. Appearance, which
exhibited a moderate conditional probability of 0.62,
was the low correlation attribute ofthe fully described
brand.' The filler attribute, reputation of authorized
dealers, was the second attribute of every fully described
brand and was always rated at the scale midpoint on
quality. The combined effects of its moderate importance (x - 4.09) and constant neutral rating were expected to produce a consistent, but neutral effect on all
judgments. The specific combinations of attributes
constituting each level of CSBA and COBA are presented graphically in Figure B.
The quality ratings ofthe available attribute information {SBA and OBA) were also treated as withinsubjects factors. These ratings were systematically manipulated by assigning either a high value (7, 8, 9. or
10 where 10 = best imaginable), or a low value (0, I,
2, or 3 where 0 = worst imaginable). The missing attribute received no rating and reputation of authorized
dealers was always rated at the scale midpoint of 5. Four
'A medium, rather than a low, correlation was preferred for this
attribute since it is intuitively implausible that an unrelated attribute
of another brand would have any implications for inferring a missing
product dimension.
THE JOURNAL OF CONSUMER RESEARCH
366
FIGURE B
STIMULUS MATERIALS
O t h t r - b r a n d Ottributt
(08A)
COBA • High
Work month ip
COBA - Low
Workmanship
?
Workmanship
Apptaronci
?
CSBA = High
Durability
Dtoltrt' .
Rtpulotion
Durabil ity
5
Somt
Brand
Attribuli
(SBA)
Work month ip
Workmon«hip
Daoltrt'
Raputollon
5
Workmonihip
Apptoronct
?
r>
CSBA = Low
Wtight
Dioltrt'
Reputation
Wtighl
5
Dtoltrt'
Riputot ion
5
•OuraDility. weq-it ana wofhrnansfnp wefe assigootJ o>th«r r»gh (7 8 9 . 0 ' ' 0 | ot low (0 t 2 ex 31 rating*.
•The rBling o' ifvs lil*t attnbute was always S
combinations of aitribuie ratings were created, consisting of high same- and other-brand ratings, low sameand other-brand ratings, high same- and low otherbrand ratings, and low same- and high other-brand ratings. These combinations were then fully crossed with
the four combinations of attribute correlations so that
in the final set of stimulus materials, each combination
of attributes in the four cells of Figure B assumed each
level of attribute ratings.
By crossing the within-subjects factors, descriptions
of 16 brand pairs were created (2 SBA x 2 OBA X 2
CSBA X 2 COBA), For subjects to evaluate all 16 pairs
would ha\e been excessive, so each subject completed
only a one-fourth replication, consisting of four brand
pairs. The specific stimuli presented to each subject were
selected randomly, subject to the constraint that each
stimulus represented a different cell in Figure B and a
different combination of attribute ratings. Stimuli were
prepared in booklet form, with order of presentation
varied systematically.
Dependent Measures
The primary dependent variable of interest was subjects'evaluations of the four partially described brands
in their stimulus set. These evaluations were based on
two different judgment tasks, with task constituting a
between-subjects factor. Approximately one-half of ihe
subjects were specifically asked to estimate the value of
the missing attribute of the partially described brand
(the "direct" inference condition), while the remaining
subjects provided an overall assessment of each of the
partially described brands in the absence of any specific
reference to the missing attribute (the "indirect" or unprompted inference condition).
In both conditions, subjects also provided overall
evaluations of each of the fully described brands, although these judgments were not an integral part of the
hypothesis tests. Rather, they were obtained to conceal
the purpose of the experiment and to facilitate certain
manipulation checks. All judgments were made on an
11-point scale with anchors of zero (worst imaginable)
to 10 (best imaginable) that appeared directly below the
descriptions of each brand pair.
Subjects and Procedure
Data were collected from undergraduate college students in an introductor\ marketing management course
at a large university. Subjects met in smail groups in a
367
INFERENTIAL BELIEFS
classroom setting, performing all tasks under the supervision of one ofthe investigators. No interactions
among participants were necessary, so demand effects
due to the group setting are assumed to be negligible.
As a cover story, subjects were told that the study involved decision making.
Booklets containing stimulus materials were distributed in random order. The instructions preceding the
stimuli reiterated the cover story and established comparability among the brands to be evaluated by indicating that all were among the 10 best sellers to college
students. This was also intended to establish the relevance ofthe other-brand information for evaluating the
partially described bicycle. Then a thorough description
ofthe meaning ofthe attribute ratings was provided,
and subjects completed a rating task as a comprehension
check. Next, a sample stimulus was presented, which
served to both familiarize subjects with the format and
explain the meaning ofthe "not reported" rating ofthe
partially described brand. Upon completion ofthe main
experimental task, various manipulation checks and
demographic information were obtained. Data were
collected from a total of 407 subjects, of whom 200
made direct inferences, while the remaining 207 were
in the indirect inference condition.' Analysis ofthe hypothesis guessing question revealed acceptance of the
cover story and no knowledge ofthe researchers' purpose. In addition, no statistically significant differences
were found in either the demographic characteristics of
the two groups or their knowledge and experience with
lO-speed bicycles.
consistent quality cues (both high or both low ratings).
Previous findings (Huber and McCann 1982: Meyer
1981) imply that the inferred value ofthe missing attribute would be a discounted mean, resulting in a less
favorable evaluation of partially described brands relative to comparable fully described alternatives. This
assumption was supported with 95 percent confidence
in all but one case, in which the partially described
brand was rated lower with 90 percent confidence. It
should be noted, however, that some of this difference
may be due to a generalized tendency to devalue an
incompletely described alternative (Yates, Jagacinski,
and Faber 1978).^
Third, the attribute intercorrelations perceived by
experimental subjects were evaluated by obtaining estimates ofthe conditional probabilities for all attribute
pairs. The probabilities of predicting the missing attribute, workmanship, conditional on the assumption
of knowledge about durability, appearance, or weight
were high (.v = 0.76), medium (.v = 0.47), and low (.v
= 0.30) respectively, consistent with the levels observed
in pretests and desired for the attribute correlation manipulation.
RESULTS
Manipulation Checks
where:
Before testing the hypotheses, checks on various manipulations and assumptions were conducted. First,
since the attribute ratings used to operationalize SBA
and OBA assumed several values within a level (except
for reputation of authorized dealers), it was necessary
to verify that no systematic differences were present in
the mean high or low ratings assigned. A series of oneway ANOVAs was conducted, and in no case was the
magnitude ofthe difference statistically significant (p
> 0.40).
Second, it was necessary to determine whether subjects in the indirect inference condition had incorporated inferential beliefs about the missing attribute into
their evaluations ofthe partially described brands. This
was accomplished by comparing the overall ratings of
brand pairs in which CSB.A and COBA were either both
high or both low and in which SBA and OBA provided
'The sample sizes used in this research provided high power under
even small effect sizes. For example, the power for the teMs of the
main effects and two-way interactions was approximately 0.82 with
alpha = 0.05, even assuming a small effect size (Cohen 1977. p. 312),
Hypothesis Tests
The research hypotheses imply the following model
of inference formation:
A'j = SBA + OBA + CSBA + COBA
+ SBA . CSBA + OBA • COBA
(I)
A'J = inferred value of attribute A of brand j
SB.A = quality rating of any other attribute ofthe same
brand' i.e.. SBA * .A,
OB.A = quality rating of any attribute of some other
brand, inclusive of OBA = Aj
CSBA = ecological correlation between Aj and SBA
COBA = ecological correlation between Aj and OBA
The model suggests that consumers' inferences are a
function of same- and other-brand attribute information,
the correlations between available and missing attributes,
and the interaction between the information source (sameor other-brand) and correlation. In the context of this
model, suppon for Hypothesis 1 would consist of a significant main effect of SBA and no significant effect of
OBA since the influence of same-brand attribute ratings
'Table 1 and Figures C and D offer further evidence that inferences
were incorporaied into evaluations of partially described brands. The
similar configuration of results in the indirect and direct inference
tasks argues thai even when inferences were not prompted, they were
nevcnheless incorporated into respondents' judgments- The lower
R- for the direct condition, however, suggests less consistcncv in
prompted inferences.
368
THE JOURNAL OF CONSUMER RESEARCH
TABLE 1
ANALYSIS OF VARIANCE RESULTS
Direct inference condition
Source of variation
Entire model
SBA
OBA
CSBA
COBA
SBA.OBA
SBA.CSBA
SBA.COBA
OBA.CSBA
OBA.COBA
CSBA.COBA
SBA.OBA.CSBA
SBA.CSBA.COBA
OBA.CSBA-COBA
SBA.OBA.CSBA.COBA
Error
R^
Sums of
squares
2244.39
1932.25
14.61
.61
1.45
2,99
281,49
.34
333
7.21
.04
.00
1.05
.29
.00
2806.57
Indirect inference condition
d.f. '
a
15
1
1
.0001
.0001
.0439
.6811
.5254
,3617
,0001
.7578
.3354
.1567
.9195
1,0000
.5895
.7780
1,000
^^}
1 ^
1
1
1
1.
tl
1
1
1
1
2
797
.443
is expected to e.xceed that of other-brand information in
inference formation. Similarly, significant SB,A«CSB,A
and OBA •COBA interactions would be consistent with
Hypothesis 2, which predicted that highly correlated attributes will influence inferences more than attributes with
low correlations.* Hypothesis 3. which posited that directly
prompting inferences will substantially alter the processes
underlying their formation, cannot be directly tested in
the context of this model. However, a different configuration of results for the direct and indirect judgment tasks
would constitute indirect suppon for this prediction.
Analysis of variance was used to test the model, and
the results are summarized in Table 1. The ratings used
to operationalize SBA and OBA were treated as dichotomous (high or low) rather than continuous (7. 8,
9. 10 or 0, 1. 2, 3) in the analysis, and the data for the
direct and indirect inference conditions were analyzed
separately. Preliminary inspection of the results indicates that the ANOVAs for both judgment tasks are
highly significant {p < O.OOOI). Moreover, the R's are
relatively high (0.443 in the direct and 0.656 in the indirect inference condition), indicating that the significant results are not merely a result of the large sample
size.
Hypothesis 1 stated that consumers' inferences would
be influenced more by same-brand attribute information than by other-brand information when attribute
correlations are held constant, or that the main effect
*None of the other effects was predicted to be statistical!) significant.
Significant main effects of CSBA and COBA were noi expected since
the treatments contained under each included both high and low
attribute quality ratings that were expected to neutralize each other.
Sums of
squares
d.f.
3452,66
3183.72
15
1
.09
1
1
10.67
.24
.02
236.44
.00
4.19
2.96
.00
.59
.05
.39
13,50
1808,82
1
1
1
1
1
1
1
1
1
1
2
a
.0001
.0001
.8449
.0289
.7449
.9236
.0001
1.0000
.1704
^491
1.0000
.6059
.8790
.6756
.0489
612
.656
of SB,A would be significant while that for OBA would
not. Table 1 reveals a highly significant main effect of
SBA in both the direct and indirect inference conditions
{p < 0.0001). In fact. 86 percent of the sums of squares
accounted for by the direct condition model and 92
percent by the indirect condition model are attributable
to the quality ratings of the same-brand information,
indicating its strong influence on respondents' inferences.
As expected, the main effect of OB.A was not significant in the indirect inference condition, but in the direct condition, the other-brand information did exert
a significant influence on inferences {p < 0.05). However, this effect accounts for less than 1 percent of the
total variance explained, suggesting that the significance
is attributable mainly to the large sample size raiher
than to any practical importance of other-brand information in inference formation.
Figure C presents a more detailed analysis of the relative effects of same- and other-brand information on
inferences. The top panel of the Figure presents the hypothesized configuration of means. It was expected that
when SBA was rated high, the inferred value of the
missing attribute, (A'j), should exceed the value inferred
when SBA was rated low. However, there should be no
difference in A'j between the high and low levels of OBA.
The observed means for the direct and indirect inference conditions are displayed in the lower panel. Both
are highly consistent with the predicted pattern. The
mean value of^^ varies directly with the level of SBA.
but is virtually the same regardless of the level of OBA.
Thus, despite the statistical significance of OBA in the
direct condition, the results overw helmingly support the
greater influence of same-brand information in the
369
INFERENTIAL BELIEFS
FIGURE C
FIGURE D
HYPOTHESIS 1
HYPOTHESIS 2
Hypothesized configurotian of tneans
.Hypothesized configuration of meons
High
' quality
rating
Same-brond
attribute (SBA)
Other-brand
attribute (OBA)
Low
' quqiity
rating
Low
quality
rating
High
quollty
roling
High
corre l o tion
Low
correlation
2. Observed configuration of means
Direct inference condition
2. Observed configurotion of means
Indirect inference conditian
Direct inference condition
Indirect inference condition
High TT
quality I
6 3 0 rating
587 • SBA
. High
^ ^
quality
^,-'''''^6,56 rating
522
5,06
3.99
2,37
3,14
257
Low
2,(X) quollty
roting
Low
quality
rotmg
High
quality
roting
Low
quality
rating
High
quality
roting
process of inference formation, and Hypothesis 1 is
therefore accepted.
Hypothesis 2 predicted that consumers' inferences
would be influenced more by attributes with high correlations than by those with low correlations to a missing attribute. Evidence in support of this hypothesis would consist of significant SBA*CSBA and
OBA •COBA interactions. More specifically, the configuration of means for A, should conform to that presented in the top panel of Figure D. That is. if attribute
intercorrelations influence inferences as predicted, a
highly correlated attribute with a high rating should result in a higher value for A) than would a low correlation
attribute with a similar high rating. Conversely, a highly
correlated attribute with a low rating should produce a
lower value for,*l] than would a low correlation attribute
with a low rating. In other words, there should be less
discounting of inferences based on highly correlated attributes.
The ANOVA results in Table 1 reveal that for both
the direct and indirect inference conditions, the
SBA • CSBA interactions are highly significant {p
< 0.0001), as expected. Moreover, in both cases, the
interaction accounts for a substantial portion of total
Low
correlotion
High
correlation
Low
,53 quOhty
foting
2
Low
COrrelO-
tion
High
correlation
variance explained by the models (12 percent and 7
percent in the direct and indirect inference conditions,
respectively), indicating that the effects are not spurious.
However, the OBA«COB,A interactions are not significant for either of the judgment tasks, probably reflecting the overwhelming reliance on same-brand information for inference formation as described previously.
Regardless, the discussion ofthe cell means will be confined to those for the same-brand interactions.
The observed cell means for the inferred value ofthe
missing attribute for various levels of CSBA are displayed in the lower panels of Figure D for the direct
and indirect inference conditions, respectively. As hypothesized, the means for the highly correlated attributes are more extreme than those for low correlation
attributes in both judgment tasks. Since there were no
differences in the values ofthe available attributes, these
results indicate that respondents relied more heavily on
cues from highly correlated attributes when forming
inferences, but placed less emphasis on low correlation
attributes. Thus. Hypothesis 2 is partially supponed in
that the predicted effect of attribute intercorrelations
was observed for the same-brand information. Howe\er,
respondents appear to rely so little on other-brand in-
370
THE JOURNAL OF CONSUMER RESEARCH
formation that any effect of attribute correlations was
swamped by the impact ofthe same-brand information.
In addi;ion to the predicted effects, statistically significant effects were observed in the indirect inference
condition for CSBA and the four-way interaction. Since
both effects account for less than 1 percent ofthe total
\ariance explained, and since the interaction is largely
uninterpretable, these effects are assumed to be a function of the sample size and to have no practical implications for interpreting the data.
Hypothesis 3 predicted that consumers" use of available information in forming inferences will differ if inferences are prompted (as in the direct inference condition) rather than unprompted (as in the indirect inference condition). Although no direct test of this
hypothesis is possible, the ANOVA results in Table I
offer indirect support in that the overall R^ is substantially lower in the direct condition (0.443) than in the
indirect condition (0.656). This would seem to suggest
that when inferences are prompted, respondents use
available information in a less consistent manner, increasing the noise in their estimates ofthe value ofthe
missing information. In particular, the effect of
prompting inferences seems to focus attention some\^hat less strongly on the same-brand information. For
example, although the main effect of SBA was high!>
significant in both conditions, it accounted for 86 percent ofthe variance explained in the direct condition
compared to 92 percent in the indirect condition.
This may be due to the nature of the judgment tasks
performed in the two conditions. In the indirect inference condition, respondents were asked for an overall
assessment ofthe partially described brand, for which
they knew one attribute rating. In ihe direct inference
condition, they were asked to estimate the value ofthe
missing attribute. While SBA seems to have been the
dominant source of information to perform both tasks,
it may have seemed less relevant with respect to OB.A
for the direct task than when forming an overall evaluation of a partially described brand. Thus, consistent
with the hypothesis, prompting inferences seems to alter
the salience of available same- and other-brand information.
DISCUSSION
The results of this investigation show that consumers
consistently employ a same-brand strategy in inference
formation, even when other-brand attributes are more
highly correlated to missing information than are samebrand attributes. It was also found that more highly
correlated attributes exert a more consistent effect on
inferences than do low correlation attributes, and that
prompting inferences produces greater heterogeneity in
their value than do less direct measures.
These results are important for several reasons. First.
it is overly simplistic to conclude that correlations bemissing and available attributes explain inference
formation. If only same- or only other-brand information is available, correlations may provide an adequate account of inferences. When both sources of information are present, however, the effect of attribute
correlations appears to be swamped by the observed
preference for same-brand information in forming inferences. Specifically, even low-correlation information
substantially affects inferences if it pertains to the partially described brand. Other-brand information, regardless of its correlation, does not appear to affect inferences when same-brand information is present.
Second, the results have several methodological implications. It is clear that research on consumers' inferential processes must explicitly control for ecological
correlations between available and missing product attributes. Moreover, the operationalization of the dependent variable in such studies matters. In the present
study, prompting an inference about the specific value
of a missing attribute produced results quite different
in magnitude, if not in overall pattern, from that produced by not prompting. This finding underscores the
need to develop good, unobtrusive measures of inferential processes.
The approach used in this study was similar to that
found in other studies (Huber and McCann 1982: Meyer
1981) and involved obtaining overall evaluations of
partially described brands. Although a manipulation
check indicated that these judgments did reflect inferences about missing product attributes, greater consistency in judgments was observed among respondents
in this condition compared to the direct inference condition. This seems counterintuitive since the inferences
would be expected to introduce some noise into the
data. leading to less consistency. .Mthough the precise
cause of this is difficult to ascertain with certainty, it
ma> indicate that prompting inferences substantially
alters the normal same-brand strategy. Regardless, further evaluation of the procedure seems appropriate.
From a theoretical perspective, the observed preference for a same-brand strategy implies that for decisions
within a product category, a particular instance ofthe
categor\' rather than the entire category may be more
influential in inference formation. Thus, a specific
brand would have difficulty "free riding" on market
information, such as product class averages. Moreover,
this finding implies that policy decisions on information
disclosure should consider the perceived correlations
between information already available in the environment and information for which disclosure is being
considered. If adequate signals are provided by other
attributes for which information is available, the need
for disclosure is diminished. However, since consumers
seem uncomfortable using other-brand signals, arguments based on the availability of product class information are less compelling, especially considering that
information is discounted substantially.
Finally, several issues for further research emerge
from this study. First, subjects" almost complete reliance
371
INFERENTIAL BELIEFS
on same-brand information raises questions about
whether the other-brand cues were strong enough. Perhaps a stronger treatment, such as the product class
average, would have produced greater reliance on the
other-brand cues. Second, since only intrinsic cues were
provided in the brand descriptions, an obvious extension ofthis study would be to consider the impact of
extrinsic cues on inferential strategies (Szybillo and Jacoby 1974). Finally, it would be useful to determine if
there are certain conditions under which the samebrand inference strategy becomes less desirable than an
other-brand strategy. For instance. little or no variance
about the product class mean for a certain attribute
might enhance the implications of the mean for inferring the value of the attribute for a specific brand compared to information about highly correlated attributes
of the partially described brand itself. The pervasiveness
of consumers' inferences in product evaluations provides ample justification for efforts in each of these
areas.
[Received July 1985. Revised May 1987.]
REFERENCES
Cohen. Jacob (1977), Statistical Power Analysis for the Behavioral Sciences, Rev. ed.. New York: Academic Press.
Fishbein. Martin and leek Ajzen (1975). Belief Attitude. Intention, and Behavior, Reading. MA: Addison-W'esley.
Fiske, Susan T. and Shelicy E. Taylor (1984). Social Cofmiuon,
Reading. MA: Addison-Wesley.
Harris, Richard J. (1981), "Inferences in Information Pro-
cessing." in ThePsycholosyofLearninf;and.\foiivati(in.
Vol. 15, ed. Gordon A. Bower, New 'I'ork: Academic
Press. 81-128.
Hinkle. Ronald Leiand (1976), "The Role of Stimulus Clarit>
in Impression Formation." unpublished M.A. thesis.
University of Illinois. Urbana-Champaign, IL 61820.
Huber, Joel and John McCann (1982), "The Impact of Inferential Beliefs on Product Evaluations," Journal of
Marketing Research. 10 (August), 324-333.
Johnson, Richard D. and In^in P. Levin (1985a), "Explicit
Inferences in Price-Quality Judgments." paper presented
at the annual meeting of the Midwestern Psychological
Association, Chicago.
and Irwin P. Levin (1985b), "More Than Meets the
Eye: The Effect of Missing Information on Purchase
Evaluations," Journal of Consumer Research. 12 (2).
169-177.
Lutz. Richard (1975), "First-order and Second-order Cognitive Effects in Attitude Change," Communication Research. 2(3), 289-299.
Mazis. Michael B. and Janice E. Adkinson (1976). "An Experimental Evaluation of a Proposed Corrective Advertising Remedy," Journal of Marketing Research. 13
(May). 178-183.
Meyer. Robert J. (1981), "A Mode! of Multiattribute Judgments Under Attribute Uncertainty and Informational
Constraint," Journal of Marketing Research. 18 (November). 428-441.
(1982),) "A Descriptive
Model of Consumer Inforp
mation Search Behavior," Marketing Science. 1
93-121.
Sawyer. Alan G. (1975). "Demand Artifacts in Lahoraior\
Experiments in Consumer Research," Journal of Consumer Research. 1 (4). 20-30.
Szybillo. George J. and Jacob Jacoby (1974). ••Intrinsif versus
Extrinsic Cues as Determinants of Perceived Product
Q u a l i t y . " Journal
of .Applied Psychology.
59(1), 74-78.
Wyer. Robert S., Jr. and Donal E. Carlston (1979), Social
Inference and Attribution. Hillsdale, NJ: Lawrence Erlbaum.
1'amagishi, Toshio and Charles T. Hill (1983). "Initial
impression Versus Missing Information as Explanations
of the Sei-Sizc Eff"ecl." Journal of Personality and Soctal
Psychology 44 (5). 942-951.
Vates, }. Frank, Carolyn M. Jagacinski. and Mark D. Fabcr
(1978). "Evaluation of Partiall> Described MuliiattHbute
Options." Organizational Behavior and Human Performance. 21 (April). 240-251.