brand choice behaviour

Brand Choice Behavior as a Function of Information Load: Replication and Extension
Author(s): Jacob Jacoby, Donald E. Speller and Carol Kohn Berning
Source: Journal of Consumer Research, Vol. 1, No. 1 (Jun., 1974), pp. 33-42
Published by: Oxford University Press
Stable URL: https://www.jstor.org/stable/2488952
Accessed: 21-09-2019 13:15 UTC
REFERENCES
Linked references are available on JSTOR for this article:
https://www.jstor.org/stable/2488952?seq=1&cid=pdf-reference#references_tab_contents
You may need to log in to JSTOR to access the linked references.
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide
range of content in a trusted digital archive. We use information technology and tools to increase productivity and
facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].
Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at
https://about.jstor.org/terms
Oxford University Press is collaborating with JSTOR to digitize, preserve and extend access
to Journal of Consumer Research
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
Brand Choice Behavior as a Function of
Information Load: Replication
and Extension
JACOB JACOBY
DONALD E. SPELLER,
CAROL KOHN BERNING*
The hypothesis that finite limits exist to the amount of information consumers can effectively use was tested by operationalizing information
load in terms of number of brands and amount of information per brand
provided. The results of an experiment involving 192 housewives tend to
confirm this hypothesis.
disclosure" (cf. Howard & Hulbert, 1973; Jacoby, in
For almost any common grocery product, consumers
shopping in the typical American supermarket are able
to make their selection from among numerous competing brands. Most American supermarkets stock
nearly twenty brands of coffee, thirty brands of beer,
and forty brands of dry breakfast cereal, for example.
The consumer obtains information about brand choice
from a variety of sources such as advertising, word-ofmouth communications, the package, and private and
press).
An alternative perspective is held by those members
of the behavioral sciences dealing with human information processing (such as Lipowski, 1973; Miller, 1956;
Moray, 1967; Quastler, 1956; Streufert, 1970) and
those dealing with statistical prediction (Wherry, 1931,
1940) and clinical prediction (Bartlett & Green, 1966;
Kelly & Fiske, 1951). Based upon considerable evi-
public rating services.
dence, this position maintains that there are finite limits
One such source, the package, represents the manufacturer's final opportunity to inform and persuade the
consumer, and usually contains a wide variety of information. Much of this appears because the manufacturer or seller wants it there. Some package
information is required by law (ingredients, weight,
size), and additional information will probably soon
appear as a function of recent FDA rulings and pending
legislation.
to the ability of human beings to assimilate and process
information during any given unit of time, and that
once these limits are surpassed, behavior tends to become confused and dysfunctional. Conceivably, such a
state of information overload can occur in the super-
market. The typical full service American supermarket
displays more than 8,000 different items on its shelves
(Twedt, 1967), most of which are in packages containing an array of more or less complex information. Moreover, not only is the consumer confronted with numerous
There are at least two perspectives one might adopt
regarding this array of information confronting the
consumer. First, there are those who argue that whether
or not the consumer uses the information, it ought to be
complex alternatives, but the situation is one in which
she usually arrives at a purchase decision within a
relatively short period of time.
there because the consumer has a moral, ethical, and
legal right to know. As Bymers has stated:
If there is indeed a point beyond which additional
information produces dysfunctional consequences, the
ramifications for public policy makers, legislators, and
marketers would be substantial. Perhaps most importantly, it would generate attention to issues regarding
"how much?" and "just which?" information should be
retained and, once retained, how best to present it to
Congress has passed the [Truth-in-Lending Law] on
the issue of the right to know rather than on any
evidence of whether or not the consumer uses the
information. . . . Congress was correct. The use the
consumer makes of information is peripheral to
the main issue of right to know. (Bymers, 1972, p.
59).
minimize dysfunctional consequences.
Jacoby, Speller, and Kohn (1974) recently examined
these information overload implications in a consumer
context and found positive linear relationships between
amount of product information and subjective feelings
of satisfaction and certainty, a negative linear relationship with confusion, and a curvilinear (information overload) relationship between amount of information and
the accuracy or the "correctness" of the purchase de-
It is this very issue of "right to know" which serves as
the foundation for the doctrine of "full and affirmative
* Jacob Jacoby is Associate Professor and Carol Berning and
Donald Speller are graduate students in the Department of
Psychological Sciences at Purdue University. This study was
supported in part, by a grant from the Consumer Research
Institute, Inc., Washington, D.C.
33
JOURNAL OF CONSUMER RESEARCH * Vol. 1 * June 1974
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
34
THE
JOURNAL
OF
CONSUMER
RESEARCH
cision. However, the ability to select correctly the "best"
brand was demonstrably poorer at both low and high
of information (price, container size, nutritional com-
levels of information load compared to intermediate
ponents, storage instruction, etc.). Moreover, most of
levels.
these dimensions are relatively complex from an information theoretic perspective. Assume, for example,
that the actual number of "calories per serving" for a
particular brand of rice was. one of the 128 whole integer
values between 50 and 178 calories. To determine which
specific value is involved (e.g., 98 calories per serving)
can require as many as seven bits of information. Each
information dimension was therefore simplified so that
only a single bit would be required to determine the
specific value involved (e.g., high vs. low calories per
serving; high vs. low cholesterol). Sixteen such relatively
"simple" dichotomous information dimensions were
generated for each of the two products.
Because of the substantial implications that these
findings have for public policy decisions, replication attempts using different subjects, products, and improved
methods are necessary. The fundamental ways in which
the current study differs from the earlier investigation are
as follows: (1) Housewives rather than students served
as subjects. (2) Rice and prepared dinners were utilized
as the products of interest rather than laundry detergent.
(3) The item of information presented to the subject
was made to conform to the information theoretic definition of an information "bit," by using dichotomous
information dimensions. (4) Maximum information
load was extended from 72 items to 256 bits. (5) Each
of the variables making up information load (that is,
number-of-brands and bits-of-information-per-brand)
was articulated in terms of four rather than three levels.
(6) Additional, qualitatively superior dependent
ducts often display at least twenty different dimensions2
The specific information that subjects in each of the
cells received for rice was determined as follows. First,
a 16 (brands) X 16 (bits of information) matrix was
constructed so that the 16 bogus brands, labeled A
through P, appeared as an alphabetically ordered margimeasures were introduced. (7) Finally, the current innal row across the top of the matrix, while the 16 indimensions appeared as a marginal column
vestigation proceeded beyond the. basic question formation
of
information load to examine how package information
down the left-hand side. Next, the specific value of
displays can best be organized.
each dimension for each cell was randomly selected
from the two values that each dimension was permitted
to have(such as high vs. low cholesterol content). The
METHOD
information developed for the 16 X 16 matrix was that
Subjects
presented to the twelve subjects in the most complex
The subjects were 192 paid housewife volunteers
cell. The specific information arrays for the housewives
residing in the greater Lafayette, Indiana community.
in the remaining cells were generated by starting in the
Selection procedures insured a socio-demographically
top left-hand corner of the 16 X 16 matrix and then
heterogeneous sample in terms of age, education, and
working across and down until both the appropriate
family composition.
number of brands and bits of information per brand
were obtained.
Design
The information associated with each "brand" was
placed onto a separate 4" X 6" index card. A different
A 4 (number-of-brands) X 4 (number-of-bits-ofletter of the alphabet appeared at the top of each card
information-per-brand) between-subjects analysis of
to identify that "brand." Thus, for example, subjects
variance design was employed in which subjects were
in
the "8 brands X 12 bits of information" cell each
randomly assigned to one of sixteen experimental cells
received 8 index cards, labeled A through H, with twelve
(n = 12 per cell). There were either 4, 8, 12, or 16
bits of information taken from twelve different informabrands and either 4, 8, 12, or 16 bits of information per
tion dimensions appearing on each card. It should be
brand presented to the consumers for each product.
noted
that providing the product information in such
All subjects responded to information regarding two
a manner presents a simpler crossbrand comparison
products: rice and prepared dinners. In order to avoid
task for the consumer than would be the case if actual
providing subjects with ideas regarding the hypotheses
product
packages were utilized.
of the study and thereby generating possible demand
characteristics (cf. Orne, 1962), each subject remained
in the same "brand x information bits" treatment condition for both products. The order of product presentation was counterbalanced for subjects within each cell.
Operationalizing the Independent Variables
Package Information Load. Examination of current
supermarket packages for various brands of rice and
prepared dinners, as well as discussions with knowledgeable individuals,' revealed that packages for these pro-
Mode of Information Organization. In order to study
the effects of "organized vs. disorganized" and "same
vs. different" informational arrays, both the specific
information and the order in which this information
2 To facilitate communication, the following terminology will
be employed throughout. The term "information dimension"
will be used to refer to a basic category of product information
such as price, calories-per-serving, or type of container, while
the term "information value" will refer to the specific points or
forms that information may assume along these dimensions
such as 32?, 64?, and 73? for price, 42, 50, and 70 for caloriesper-serving, and box, tube, plastic bag, or jar for type of con-
tainer. Thus, information dimensions are associated with pro1 Raymond C. Stokes, the Director of the Consumer Research
Institute, was particularly helpful in this regard.
ducts, and information values are associated with specfic brands.
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
BRAND CHOICE BEHAVIOR AS FUNCTION OF INFORMATION LOAD 35
appeared varied for products, brands, and subjects,
and reflected the kinds of information arrays now
appearing on supermarket products. For rice, half
the subjects received values from the same information
"ideal" brand of the product was like by checking one
of two alternative values for each of the sixteen information dimensions. These alternatives consisted of the
dimensions in the same order for each brand (Ri),
information arrays the subjects later saw during their
shopping trip.
The housewives then began their "shopping" trips. E1
while the other subjects received the identical information presented in a different (scrambled) order for each
brand (R2).
same bits of information used to develop the simulated
sixteen-bits-of-information-per-brand cells. The PD con-
asked the subjects to examine and evaluate all the information for each of the brands they received. Their
task was to choose that brand which they "liked best."
They were instructed to raise their hands the instant
they had completed this decision task. By referring to a
timer which had been activated the instant all subjects
simultaneously received their information cards, E2 was
able to record the amount of time it took each subject
to reach a decision.
Each subject then went on to complete a set of
subjective state scales and, next, to place all the brands
about which she received information in order of decreasing preference to her. After a brief rest period, the
essential procedures were repeated for the second
dition replicated the manner in which information was
product.
The prepared dinner (PD) information was used to
explore the effect of having the same quantity of information per brand, but consisting of different dimensions of information for each brand. More specifically,
the information dimensions presented for each brand of
prepared dinners were determined randomly from the
16 available dimr nsions and were presented in random
order. Under these circumstances, the amount of overlap across information dimensions utilized for the various
brands in a given cell tended to be low (near the theoretical 25 percent level) in the four-bits-of-informationper-brand cells and increased to 100 percent in the
provided to subjects in the earlier Jacoby, Speller and
Kohn (1974) study.
These various information array conditions are hereafter referred to as Rl (same information dimensions
considered in same order for each brand), R2 (same
information dimensions considered in different order for
each brand), and PD (different information dimensions
considered in random order for each brand). Each
subject was placed into a PD cell and either an Rl or
R2 cell, with the number of brands and bits-of-information-per-brand she received the same for both products.
Finally, the subjects responded to two questions de-
signed to determine whether they had understood the
instructions and had been sincere in performing the
various tasks. This was followed by two open-ended
questions which probed for the existence of possible
demand characteristics and were designed to determine
whether the subjects had guessed the purpose of the
experiment. The subjects were then debriefed and
released.
Operationalizing the Dependent Variable:
Dysfunctional Consequences
Procedure
Performance Accuracy. The basic operationalization
of dysfunctional consequences was based upon the
The housewives were tested in groups of three to
thirty-two. There were two experimenters, one of whomability of the consumer to choose the "best" brand
available to her. Any choice other than the "best" brand
(E1) remained with the subjects throughout the experiwas considered dysfunctional in the sense that it would
ment, while the other (E2) was stationed on an observanot be as capable of satisfying her desires. However, a
tion deck behind a one-way mirror. As part of El's
introductory remarks, the housewives were told that the problem exists in supplying a universal definition of
"best" in that the combination of product attributes
study "is being funded by the Consumer Research Instiwhich makes a brand "best" for one person may not be
tute of Washington, D.C. and the results will most
the same combination which makes it "best" for a second
probably be provided to congressmen working on conperson. Even experts frequently cannot agree as to which
sumer legislation." Noticeably impressed with this fact,
combination of attributes is "best, in general." Acthe housewives were then asked to be as honest and as
cordingly, an idiographic approach was adopted in which
accurate as they could be in making their responses.
the housewife determined which combination of attriAfter supplying basic demographic data, subjects were
butes was "best" for her.
told that: "This study is concerned with answering the
The "best" brand was operationally defined as that
following questions: How do people go about deciding
which brand to buy out of the many brands of a product
brand of the n brands presented to a given subject which
available on the supermarket shelf?" The subjects were
most closely approximated the profile of the information
then asked to pretend that they were in a supermarket
values for her "ideal" brand on the dimensions provided
for brands in that cell. Each brand's distance from this
shopping for two products (rice and prepared dinners).
Each housewife was next required to indicate (on a 5
ideal was determined by summing the importance scores
of those dimensions on which the value for the brand in
point Likert-type scale) how important each of the
sixteen information dimensions supplied for the first
question did not match that of the "ideal." The brand
product was in helping her decide which brand of that
with the smallest cumulative score across dimensions
product to buy. Next, each subject indicated what her
was operationally defined as the brand closest to the
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
36
THE
JOURNAL
OF
CONSUMER
RESEARCH
ideal, while the brand
probed
with
subjective impressions
the ofgreatest
percent of information cum
was interpreted to be the most distant from the ideal.
used, number of brands considered, and number of
Correctly selecting the brand closest to one's ideal is
dimensions considered. These eleven items are hereafter
hereafter referred to as "Most Preferred Brand (MPB)
collectively referred to as the Subjective State Scales.
Accuracy."
A second operationalization of performance accuracy
consisted of calculating Kendall's coefficient of concordance between each subject's actual preference ranking and the ranking predicted from her description of
her ideal brand. This measure will hereafter be referred
to as "Rank Order Accuracy." The two accuracy measures are somewhat reflective of March and Simon's
(1958) maximizing and satisficing decision strategies.
RESULTS
A thumbnail socio-demographic sketch of the subjects reveals that the majority (82.3 percent) were currently married, had no job outside of the home (61.5
percent), and reported being part of families where the
total amount of annual income was less then $10,000
(52.0 percent). The largest group (48.4 percent) reported having no children living at home. The age of
- Performance Speed. Garretson and Mauser (1963,
respondents seemed to be distributed almost equally
p. 172) contend that the consumer of the future "will
across
six response categories ranging from "24 years
be oriented to buying time rather than product. He will
old or younger" to "65 or older." In contrast, the educatake the myriad of sophisticated products at his disposal
tional level seemed to be normally distributed across
for granted. His chief concern will be to provide himself
eight response categories with "high school graduate"
with free time in which he can conveniently use products
(34.4 percent), "some college" (26.0 percent), and
that function to conserve time for leisure and pleasure."
"college graduate" (17.2 percent), describing most of
In similar fashion, Schary (1971, p. 55) states that:
the subjects.
"Time is an implicit part of every market offering. ProdApproximately 96 percent reported doing their own
ucts are chosen not only because of price, quality,
grocery shopping. In general, these women purchased
features, or even the images created through promotional
prepared dinners more frequently than rice, although
activity, but also because of the potential time expendionly 3.1 percent reported never buying rice while 17.7
tures that they entail." It may be assumed that time,
percent reported never buying prepared dinners. The
itself, is of considerable value and the greater the time
data for quantity of rice and prepared dinners purchased
required to reach a decision, the more dysfunctional
are about what one would expect to be true for comthe process.
parable American housewives.3
Accordingly, a second indicator of dysfunctional conResponses to the ten socio-demographic and shopping
sequences involved measuring the time required to reach
habit items were correlated with the three independent
a decision, that is, the total amount of time which elapsed
variables (number-of-brands, number-of-bits-of-informfrom the point at which the housewife was first given
ation-per-brand, and total-amount-of-information) to
the information about each of the brands, to the point
determine whether the assignment of subjects to cells
at which she indicated reaching a decision about which
was biased according to any of these items. The only
brand she liked best. This span of time was termed
coefficients exceeding .17 were those between age and
"Total Sequence Time" (TST).
number-of-brands (-.407) and age and total-amountSubjective States. Finally, regardless of time to reach
of -information (-.326). Thus, a tendency existed for
a decision or ability to select the "best" brand, subjective
the older subjects to receive fewer brands and less total
states which occur concurrent with and subsequent to
the purchase decision (such as the consumer's feelings
of satisfaction, confusion, certainty with a decision, desire for more information, perceived risk, and so forth)
provide another meaningful basis for evaluating the
effects of information load. As examples, with increasing
information load, accuracy may remain at a fairly constant level while satisfaction increases (for example,
"It was a tough decision, but I feel good because I was
able to handle this complex problem."). Or, especially
at low levels of information load, while accuracy may be
perfect, the consumer may still feel some uncertainty
over the decision and desire more information. Accordingly, the following subjective states were probed: satisfaction; certainty; confusion; likelihood of not having
selected the best buy for the money; likelihood that an
unchosen brand would have been more satisfying; desire
for additional information; likelihood that additional
information would increase certainty and confidence in
the decision; likelihood that additional information
would increase confusion. Three additional questions
information to evaluate.
Only one of the 192 subjects reported experiencing
difficulty in understanding the instructions and only one
subject reported being less than overwhelmingly sincere
in responding to the questions. Judging from their
written responses to the open-ended questions at the end
of the study and their oral comments during the debriefing session, none of the subjects came close to
guessing the purposes of the experiment.
Performance Accuracy
The data regarding performance accuracy (that is,
the ability to select correctly one's "best" brand) will
be considered separately for "Most Preferred Brand
Accuracy" and "Rank Order Accuracy."
MPB Accuracy. Table 1 presents the number of sub3 Again, appreciation is acknowledged to Raymond C. Stokes,
a former Senior Vice-President at Comet Rice Mills, Inc., and
Vice-President for Research and Development at Uncle Ben's,
Inc.
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
BRAND CHOICE BEHAVIOR AS FUNCTION OF INFORMATION LOAD 37
TABLE 1
TABLE 2
CORRECTLY SELECTING THEIR "BEST" BRAND
NUMBER OF SUBJECTS (OUT OF 12 IN EACH CELL)
UNDER CONDITIONS OF "SAME VS. DIFFERENT"
NUMBER OF SUBJECTS (OUT OF 6 IN EACH CELL)
CORRECTLY SELECTING THEIR "BEST" BRAND
UNDER CONDITIONS OF SAME INFORMATION
DIMENSIONS PRESENTED IN SAME VS.
DIFFERENT ORDER ACROSS BRANDS
INFORMATION DIMENSIONS
Rice-Same Information Dimensions
Rice I (Same order across brands)
(RI + R2 Combined)
Number of Brands
4
4
8
6
12
7
Number of Brands
4
16
1
2
No. of bits 8 3 5 1 4 13
per
brand
12
16
5
9
6
10
20
31
6
7
4
24
5
15
4
16
16
of
per
brand
5
3
14
2
8
Number of Brands
3
12
6
8
3
16
2
3
0
2
7
12
7
1
0
1
9
10
3
1
13
4
6
4
14
2
1
12
42
Rice 2 (Different order across brands)
4
8
8
9
4
22
15
16
45
jects in each cell who correctly selected their best brand
of rice and prepared dinners. As expected, the subjects
were more accurate when the same information dimen-
sions were provided across all brands than when the
information dimensions were different (81 correct
selections for rice vs. 45 for prepared dinners). More-
over, MPB Accuracy generally decreased for both products as the number-of-brands increased. However, as
the number-of-bits-of-information-per-brand increased,
MPB Accuracy increased for rice; it first decreased and
then increased for prepared dinners.
When these data are plotted in terms of total amountof-information4 MPB Accuracy tended to first decrease,
then increase, and finally taper off for rice, and increase
and then decrease for prepared dinners. Both curves,
particularly the PD curve, display the predicted decrease
in accuracy at the higher end of the total information
load dimension. Parenthetically, the prepared dinner experimental conditions and resultant curve most closely
approximate the experimental conditions and resultant
curve of the earlier study.
Table 2 compares results for the Rl (same information dimensions- values presented in same order) vs.
R2 (same information dimensions-values presented in
scrambled order) manipulation. In general, accuracy
4 When results for total amount of information are plotted
along an axis ranging from 16 to 256 bits, the values entered
above 16, 48, 96, 128, and 192 bits are based on an average
computed across 2 cells, while the values appearing above 64
bits are based on an average calculated across 3 cells (8 brands
X 8 bits/brand; 16 brands X 4 bits/brand; and 4 brands X 16
3
8
12
4
0
16
1
8
No. of Bits 8 1 3 1' 0 5
per Brand 12 1 5 2 2 10
4
5
9
17
4
7
3
6
16
39
Chi Square = 5.52; p < .80
Chi Square = 13.76; p < .20
bits/brand).
1
Number of Brands
bits
16
16
1
Chi Square = 7.75; p < .60
Prepared Dinners-Different Information Dimensions
No.
2
11
81
Chi Square = 6.06; n.s.
4
12
3
No. of Bits 8 2 2 0 4 8
per Brand 12 4 4 4 2 14
28
15
8
3
is lower at the high end of the number-of-brands continuum, and better at the high end of the amount-ofinformation-per-brand continuum. Curves based on the
total-amount-of-information, however, appear linear
with near zero slope and are thus at variance with the
findings of the first study. Finally, there seems to be no
differential advantage to presenting values from the same
information dimensions in the same (Rl) or different
(R2) order across brands (42 vs. 39 correct selections,
respectively, cf. Table 2).
Rank Order Accuracy. Each cell of Table 3 contains
the means and standard deviations of the Kendall coefficients of concordance separately for PD, R, Rl, and
R2 conditions. In contrast to the MPB Accuracy data
(cf. marginal values of Table 1), where accuracy decreases for both products as the number-of-brands increases, we find Rank Order Accuracy stable through
12 brands and then increasing for PD and decreasing
for R at the highest level of number-of-brands (cf. marginal values of Table 3). More similar, but not completely consonant with the MPB Accuracy data, Rank
Order Accuracy exhibits a constant increase across
both products as the number-of-bits-of-information-perbrand increases.
The data indicate that Rank Order Accuracy increases for Rice as the amount-of-information-per-brand
increases; however, separating the data according to RI
and R2 conditions reveals that such increases in agreement between predicted and obtained preference ranking
occur only with R2 (same information dimensionsvalues presented in a different order across brand alternatives), and that there is an actual decrease in
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
38
THE
JOURNAL
OF
CONSUMER
RESEARCH
TABLE 3
MEANS AND STANDARD DEVIATIONS FOR KENDALL'S COEFFICIENT OF CONCORDANCE
CALCULATED BETWEEN THE PREDICTED AND OBTAINED PREFERENCE RANKINGS
OF THE BRAND ALTERNATIVES (n = 12 FOR R & PD, & 6 FOR RI & R2)
BRANDS
4
X
PD
8
S.D.
.44
.30
12
X
16
S.D.
.60
.15
X
.58
Overall
S.D.
.13
X
.59
S.D.
.10
X
.55
t- 4 R .48 .33 .48 .20 .63 .12 .47 .09 .51
RI
O
.35
.30
.40
.14
.61
.11
.48
.11
R2
.61
.33
.57
.23
.65
.14
.45
.09
PD .54 .37 .47 .21 .61 .13 .67 .09 .57
R
.53
.34
.61
.14
.69
.16
.50
.12
.58
Z
O 8 RI .65 .33 .60 .13 .67 .17 .49 .13
R2
.41
.38
.62
.16
.71
PD
.65
.25
.57
.16
.56
.15
.14
.51
.63
.12
.11
H3 R .58 .31 .60 .22 .65 .14 .60 .13
O 12 RI .68 .30 .53 .24 .69 .12 .65 .13
z
R2
tt
Z
.47
.31
.67
.20
.62
.16
.55
.10
PD .71 .24 .73 .12 .61 .18 .72
R .57 .30 .73 .11 .72 .12 .61
.17
.14
R2
.07
16
R2
.53
.60
.36
.24
.77
.69
.13
.07
.64
.79
.12
.07
.55
.68
PD
X
.58
.59
.59
.65
R
X
.54
.61
.67
.55
agreement as the bits-of-information-per-brand increases
for RI (same information dimensions-values presented
in same order across brand alternatives). In contrast,
the Rank Order Accuracy for R, R1, and R2 exhibit
similar patterns when they are plotted against numberof-brands.
A plot of the Kendall coefficients from Table 3 according to the total-amount-of-information (i.e., numberof-brands x bits-of-information-per-brand) reveals that
Rank Order Accuracy increases rapidly for both prepared dinners and rice, then tapers off with increases in
total-amount-of-information, and finally displays a small
decrease for rice. Almost the total amount of improvement in Rank Order Accuracy occurs at the very low
end of the total-amount-of-information continuum, and
the results appear nearly linear with near zero slope
from 48 bits onward. Two Newman-Keuls analyses applied to these data reveal no statistically significant
differences across the nine concordance means for
rice, and only two significant differences for prepared
dinners (& at 16 bits vs. & at 128 bits, p < .05; F3 at
16 bits vs. 61i at 256 bits, p < .01).
.60
.61
.17
.69
.66
ber-of-bits-of-information-per-brand were statistically
significant. Thus, scrambled vs. same order of information dimensions had no effect (F - .46; p - .508).
Performance Speed
Table 5 presents (separately for prepared dinners and
rice) the mean number of seconds that elapsed from
the time at which the housewife received the information to the time at which she raised her hand indicating
that she had selected her "most preferred brand." While
Total Sequence Time increased as total amount of information increased, the marginal means in Table 5
reveal a direct linear relationship between TST and the
number-of-brands available, and a small curvilinear
relationship between TST and number-of-bits-of-information-per-brand for the data combined across both
products.
An analysis of variance based upon the TST data
(Table 6) resulted in significant main effects for the
TABLE 4
SUMMARY RESULTS OF FOUR SEPARATE ANALYSES
OF VARIANCE APPLIED TO THE CONCORDANCE
COEFFICIENTS CALCULATED BETWEEN THE
Table 4 presents the results of separate analyses of
variance conducted for PD, R, Rl, R2 Rank Order
Accuracy. In each instance, the main effect due to
PREDICTED AND OBTAINED BRAND
number-of-bits-of-information-per-brand is statistically
PREFERENCE RANKINGS
(CF. TABLE 3)
significant, or nearly so. In contrast, the amount of variance due to number-of-brands is significant only for R
P.D. Rice RI R2
and R2. In no instance was the number-of-brands X
F p F p F p F p
number-of-bits-of-information-per-brand interaction significant. To probe for possibly meaningful interaction
Brands (B) 1.30 .274 4.54 .005 1.45 .233 3.72 .015
Bits/Brand
effects, another analysis of variance was conducted using
(B/B) 4.90 .003 3.99 .009 3.90 .012 2.25 .087
Rl and R2 as levels of a single factor. However, only
the main effects due to the number-of-brands and num-
B x B/B .48 .888 .48 .888 1.28 .260 .65 .750
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
BRAND CHOICE BEHAVIOR AS FUNCTION OF INFORMATION LOAD 39
TABLE 5
TABLE 6
AVERAGE TOTAL SEQUENCE TIMES (IN TERMS OF
SECONDS) FOR RICE (R), PREPARED DINNERS (PD),
AND OVER BOTH PRODUCTS COMBINED (C)
Number of Brands
4
R
':
4
PD
C
R
v
8
Xd
156
8
12
196
217
386
155
239
75
155
217
158
149
115
185
301
R
173
186
304
C
183
207
354
208
290
335
396
16
PD
C
182
154
182 324 545
185 303 466
df
F
p
Error (Between) 176
Within
Products (P) 1 18.629 .001
B x P 3 4.645 .004
B/B X P 3 1.672 n.s.
B X B/B X P 9 1.412 n.s.
Error (Within) 176
285
4- R 127 187 283 387
?
Soutrce
Brands (B) 3 37.822 .001
Bits/Brand (B/B) 3 5.736 .001
B x B/B 9 2.867 .004
PD 223 253 230 430
C 186 184 208 360 234
E 12 PD 194 229 404 457
TO TOTAL SEQUENCE TIME DATA
Between
16
241
SUMMARY OF ANALYSIS OF VARIANCE APPLIED
277
mc 170 198 256 381
Note: Because of rounding errors, means for the combined
products (C) may be one or two seconds off means calculated
from the separate R and PD values.
number-of-brands, the number-of-bits-of-informationper-brand, and type-of-product (rice vs. prepared dinners), as well as significant interactions for number-ofbrands X bits-of-information-per-brand, and numberof-brands X type-of-product. The product main effect
is interesting in that subjects spent a full minute
longer working with the prepared dinner information
than with the rice information (282 vs. 221 seconds).
This can be interpreted as indicating that more time
must be devoted to reading-in and especially processing
information for different alternatives when information
dimensions are different across alternatives (PD) than
when the same information dimensions are provided for
each alternative (R). An alternative explanation is that
the type of information for prepared dinners is qualitatively or substantially different from that for rice. Examination of this material, however, provides little support for this possibility.
dinners (replication condition) than the rice condition.
In general, the scales intercorrelate in ways which reflect
positively on the validity of the data. Considering only
statistically significant values, feelings of satisfaction
and certainty were positively intercorrelated (PD, r .789; R, r .793) and negatively correlated with feel-
ings of confusion (satisfaction: PD, r - -.342; R, r
-.261; certainty, PD, r -.415; R, r - -.351), of
not having obtained the best buy (satisfaction: PD, r =
-.357; R, r - 283; certainty: PD, r - .438; R,
r = -.335), and of feeling that another brand was
better (satisfaction: PD, r - -.193; R, r = -.205;
certainty: PD, r - -.403; R, r = -.307). Of particular interest, degree of satisfaction was positively related
to percent of available information that the housewife
reported using (PD, r - .200; R, r - .216).
The relationship of the subjective state data to the
three independent variables (number-of-brands, number-of-bits-per-brand, and total-amount-of-information)
are particularly interesting. First, the strongest relationship for both products was a negative one between moreinformation-wanted and total-amount-of-information
provided (PD, r = -.443; R, r = -.218). Also, moreinformation-more-certain was negatively correlated with
both number-of-bits-per-brand (PD, r = -.390; R, r
-.274) and total-amount-of-information (PD, r
-.378; R, r - -.253). Except for the four relation-
Subjective States
Responses to the eleven subjective state measures
were considered separately for each product. Since many
subjects had difficulty comprehending what was meant
by "How many of the attributes did you seriously con-
sider in making your choice?," this last subjective state
scale was dropped from all subsequent analyses. Four
additional variables (Total Sequence Time, number-ofbrands, number-of-bits-of-information-per-brand, and
total-amount-of-information) were added to form sets
of fourteen variables considered separately for rice and
prepared dinners.
Pair-wise intercorrelation matrices for these fourteen
variables were. constructed separately for rice and prepared dinners. These data reflect essentially the same
pattern of relationships obtained by Jacoby, Speller, and
Kohn (1974) although this is more true for the prepared
ships described above and the significant positive
relationship between total-amount-of-information and
degree-of-certainty (PD, r -.322; R, r - .126), none
of the remaining 19 relationships between the first eight
subjective state dependent measures and the three independent measures reach statistically significant levels for
rice, while most are statistically significant or nearly so
for prepared dinners. Finally, self report of the number-of-brands-considered is positively related to the
number-of-brands (PD, r - .184; R, r - .236) and
total-amount-of-information actually available (PD,
r = .192; R, r .200).
Next, the three independent variables were deleted,
and analyses of variance were applied to the remaining
data. The findings were: first, that the number of statistically significant relationships obtained with the prepared dinner condition is substantially higher than that
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
40
THE
JOURNAL
OF
CONSUMER
obtained for rice; second, significant number-of-brands
RESEARCH
parisons is likely to be regarded as hopelessly complex.
X amount-of-information-per-brand interaction effects When a choice is that difficult, there may be a tendency
to give up trying to compare the alternatives. Instead,
are virtually nonexistent; and third, and most noteworthy, the number-of-bits-of-information-per-brand the choice may be made impulsively" (p. 313-314).
produced substantially more significant main effects than Evidence from research conducted as an extension to
did the number-of-brands factor. These latter two find- the present investigation tends to support the Hendrick
et al. assertion. Total Sequence Time (which is equivaings are consistent with the results obtained in Jacoby,
Speller, and Kohn (1974).
Finally, the effect of having the same information
dimensions presented in the same (R1) vs. a different
(R2) order was examined by treating these two conditions as levels of a single factor. These analyses reveal
that only two of the 48 F tests in which this factor was
involved were statistically significant (p < .05), approximately what would be expected on a chance basis
alone. Accordingly, it appears that the information organization arrays described by this factor had no differential effect upon the housewives' subjective states.
DISCUSSION AND CONCLUSIONS
lent to Hendrick et al.'s decision time) can be conceptualized as consisting of several subcategories of time
expenditures which may be represented as follows: TST
= (Read-in Time) + (Central Processing Time) +
(Response Time). Analogous to the manner in which
data are first fed into a computer prior to being analyzed,
Read-in Time represents the amount of time the consumer devotes to placing information into her decisionmaking system prior to processing this information.
Using a comparable sample of housewives and the
identical brand information stimuli as in the present
study, Jacoby, Kohn, and Speller (1973) found that
consumers continued to spend time acquiring package
information as the number-of-brands increased; how-
When plotted against total-amount-of-information,
ever, they actually reduced time 'spent to acquire
three of the four major performance accuracy curves
information once the number-of-bits-information-per(MPB Accuracy for rice and prepared dinners, and
brand began to exceed twelve. That is, these housewives
Rank Order Accuracy for rice) display the predicted
reacted to "too much" information by giving it less
decrease in accuracy at the higher end of the continuum
attention, i.e., by "tuning it out." The fact that some
and the fourth curve (Rank Order Accuracy for preavailable information is not even permitted to enter the
pared dinners) shows a tapering off which could be indecision-making system means that this information
terpreted as a possible prelude to a decline. The most
cannot possibly be subsequently evaluated during central
marked overload effect occurred when the MPB Acprocessing. As a result, consumer choice behavior under
curacy measure was applied to the perpared dinner data.
conditions where there are numerous relevant informaIt is noteworthy that in terms of information organization dimensions for each of several alternatives may be
tion, the PD condition is more representative of current
more impulsive than is currently believed.
"real world" information displays than is the format
The results obtained with the subjective state variaused in presenting rice information. A similar organizables confirrm the findings of Jacoby, Speller, and Kohn
tional format yielded similar results (Jacoby, Speller, and (1974). Subjects feel more satisfied, more certain, less
Kohn, .1974). In sum, the five accuracy curves from
confused, and desire less additional information as the
both studies suggest that providing substantial amounts total-amount-of-information they have increases even
of package information can result in poorer purchase
though they make poorer purchase decisions! Similar
decisions.
results were obtained by Kelly and Fiske who note that,
The relationship of total-amount-of-information to
while clinical prediction is actually made less efficient by
Total Sequence Time is positive and linear: as the totalthe inclusion of too many predictors, providing this
additional information "results in a feeling of confidence
amount-of-information to be processed increases( at
least up to 256 bits of information), so too does the
on the part of the [expert] clinician" (1951, p. 202).
amount of time expended to input and evaluate this
These findings are also consistent with the results of
information. Conceivably, there is some point (e.g., 500 other investigations in the consumer behavior realm.
bits, 5,000 bits, 50,000 bits, etc.) beyond which such
More specifically, and assuming that the expressed detime expenditures begin to level off and then decrease
sire by these subjects for more information would, under
or cease altogether.
When total-amount-of-information is partitioned into
its components, the data indicate that Total Sequence
Time is positively and linearly related to number-ofbrands and curvilinearly related to number-of-bits-ofinformation-per-brand. This latter relationship is
consistent with Hendrick, Mills, and Kiesler (1968)
who found a curvilinear relationship between decision
time and complexity, where complexity was defined as
"the number of different dimensions or attributes perceived as relevant to the choice." These authors reasoned
as follows: "A choice which involves. ... many com-
appropriate circumstances, lead to subsequent information acquisition behavior, both Swan (1969) and Katona and Mueller (1955) found that satisfaction was
inversely related to actual information seeking. Similarly,
the greater the degree of uncertainty (and, therefore,
the higher the degree of perceived risk), the greater the
amount of information seeking (Bauer, 1960; Cox,
1967; Sheth and Venkatesan, 1968).
While the findings are basically consistent with those
obtained in Jacoby, Speller, and Kohn (1974), examination of the respective performance accuracy curves seems
to imply that housewives can contend with greater
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
BRAND CHOICE BEHAVIOR AS FUNCTION OF INFORMATION LOAD 41
may involve organizing and integrating the discrete inamounts of informational input than can university stuformation bits into large "information chunks." In this
dents. The highest value on the total-amount-of-informaregard, an interesting question concerns the extent to
tion dimension was 72 in the earlier study and 256 in the
which a brand or manufacturer's name represents a
present investigation. One possible explanation for the
chunk of information. Conceivably, the consumer who
housewives' seemingly greater ability may be that the
places great reliance upon brand and manufacturer name
housewives simply concentrated and tried harder on this
has earlier made some direct, cross-brand comparisons
task. The housewives all seemed to approach this study
Yery seriously, particularly after being informed that theon the specific information dimensions she considers
important, arrived at impressions of the various alternaresults "would be provided to Congressmen working on
tives based on these comparisons, and then, via a learnconsumer legislation." Moreover, for most of these
ing process, has associated the specific information with
women, being on a university campus and participating
the appropriate brand name. Thereafter, the brand
in a scientific investigation was a relatively novel exname may serve as the basic device for summarizing
perience. In contrast, the typical student subject probaand evoking some or all of the other information conbly participated in at least one investigation during the
immediately preceding year and accepted the entire
tained on the package.
procedure rather casually.
In conclusion, the research conducted thus far suggests that there are finite limits to the consumer's ability
to accommodate substantial amounts of package information within a limited time span. However, numerous
questions remain to be answered and additional research
is required before any definitive conclusions or public
policy decisions can or should be made based on these
data. In particular, the following four questions must be
A second explanation for the ostensibly superior
performance of the housewives resides in the fact that,
while the housewives had more information to contend
with, it was relatively simple information in comparison
to that provided to the students. That is, the information provided to the housewives came from 2-point di-
mensions while the information provided to the students
came from articulated, 7-point dimensions. In this regard, the earlier study more closely approximated most
real world product information displays. Packages for
different brands of rice typically do not take only one
of two points (high versus low), but usually assume
many different specific values along an information dimension such as price.
A final explanation for the differential housewifestudent performance may be that, as a result of the
numerous years of shopping experience, housewives
have developed an ability to accomodate the large
amounts of product information conveyed by super-
market packages.
Regardless of how simple the information provided to
the housewives was, 256 bits represents a considerable
amount of information to contend with. Indeed, the
vast amount of behavioral science literature consistently
finds performance decrements at much lower levels of
information load. This suggests that, in order to avoid
being overwhelmed by this substantial amount of in-
formation, certain processes and strategies were employed to reduce the amount of information actually
utilized in reaching a decision. Evidence already exists
(e.g., Hansen, 1969; Olson and Jacoby, 1972), to indicate that consumers base their purchase decisions on
their most important three to five product attribute dimensions rather than on all available information. Increased empirical attention to the variety of models
addressed.
1. Is there, in fact, an optimal information load in
consumer decision making?
2. If so, does this optimal load vary as a function of
the type of consumer population being considered
(e.g., housewives, college students, the elderly,
the economically disadvantaged, the undereducated, children and adolescents, etc.)?
3. Assuming that the amount of information provided to the consumer should be limited, which
kinds of information should be provided? (Obviously, answers to this question must be provided
on a product-by-product basis.)
4. Given that we know which information should
be provided, how should it be organized? This
question includes display order, letter size, package panel-front, side, back, top, bottom, position
on panel, and other questions of information
which is to be provided to the consumer.
Until such time as definitive answers to these questions
are provided, policy makers would be wise to proceed
with caution before providing consumers with additional
complex information.
REFERENCES
Abramson, Norman. Information Theory and Coding. New
directed at understanding the order in which different York: McGraw-Hill, 1963, p. 12.
Bartlett, C. J. and Calvin G. Green. "Clinical Prediction:
types of informational elements are incorporated into the
Does One Sometimes Know Too Much?" Journal of
decision process (cf. Bettman, 1972; Haines, 1972;
Olson and Jacoby, 1972), as well as models which focus
on information cut-off thresholds (cf. Kau and Hill,
1972) should provide insight into these "selective"
cognitive processes.
Another possible strategy employed by the "real
world" consumer to cope with extensive infonnation
Counseling Psychology, 13 (1966), 267-270.
Bauer, Raymond. "Consumer Behavior as Risk Taking,"
in Robert S. Hancock, Dynamic Marketing for a
Changing World. Chicago: American Marketing Association, 1960, 389-398.
Bettman, James R. "Decision Net Models of Buyer Information Processing and Choice: Findings, Problems,
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms
42
THE
JOURNAL
OF
and Prospects." Paper read at the Association for
Consumer Research Workshop on Information Processing, 1-2 November 1972, at University of Chicago.
Bymers, Gwen. "Seller-Buyer Communications: Point of
View of a Family Economist," Journal of Home Economics, 64 (1972), 59-63.
Cox, Donald F. Risk Taking and Information Handling in
Consumer Behavior. Boston: Harvard University
Press, 1967.
Garretson, R. C. and Ferdinand F. Mauser. "The Future
Challenges Marketing," Harvard Business Review, 41
(1963).
Haines, George H., Jr. "Process Models of Consumer Decision Making." Paper read at the Association for
Consumer Research Workshop in Information Processing, 1-2 November 1972, at University of Chicago.
Hansen, Fleming. "Consumer Choice Behavior: An Ex-
perimental Approach," Journal of Marketing Research, 6 (1969), 436-443.
Hendrick, Clyde, Judson Mills, and Charles A. Kiesler.
"Decision Time as a Function of the Number and
Complexity of Equally Attractive Alternatives,"
Journal of Personality and Social Psychology, 8
(1968), 313-318.
Howard, John A. and James Hulbert. Advertising and the
Public Interest: A Staff Report to the Federal Trade
Commission. Chicago: Crain Communications, Inc.,
1973.
Jacoby, Jacob. "Consumer Reaction to Information Dis-
plays," in S. Divita, Advertising and the Public Interest. Chicago: American Marketing Association, in
press. Currently available as Purdue Papers in Consumer Psychology, No. 130.
Jacoby, Jacob, Carol A. Kohn, and Donald E. Speller.
"Time Spent Acquiring Product Information as a
Function of Information Load and Organization."
Proceedings of the American Psychological Association's 81st Annual Convention, 8 (1973), 813-814.
Jacoby, Jacob, Donald E. Speller, and Carol A. Kohn.
"Brand Choice Behavior as a Function of Information
Load," Journal of Marketing Research, 11 (1974),
63-69.
Katona, George and Eva L. Mueller. "A Study of Purchase
Decisions," in Lincoln Clark, Consumer Behavior:
The Dynamics of Consumer Reaction, Vol. 1. New
York: New York University Press, 1955, 74-75.
Kau, P. and L. Hill. "A Threshold Model of Purchasing
Decisions," Journal of Marketing Research, 9 (1972),
264-270.
CONSUMER
RESEARCH
Kelly, Everett L. and Donald W. Fiske, The Predictions
of Performance in Clinical Psychology. Ann Arbor,
Michigan: University of Michigan Press, 1951.
Lipowski, Z. J. "Affluence, Information Inputs and Health,"
Social Science and Medicine, 7 (1973), 517-529.
March, James G. and Herbert Simon. Organizations. New
York: Wiley, 1958.
Miller, George A. "The Magical Number Seven, Plus or
Minus Two: Some Limits on our Capacity for Proces-
sing Information," Psychological Review, 63 (1956),
81-97.
Moray, Neville. "Where is Capacity Limited: A Survey
and a Model," Acta Psychologica, 27 (1967), 84-92.
Olson, Jerry and Jacob Jacoby. "Cue Utilization in the
Quality Perception Process," in M. Venkatesan, Proceedings, Third Annual Conference of the Association
for Consumer Research, 2 (1972), 167-179.
Orne, Martin T. "On the Social Psychology of the Psychological Experiment: With Particular Reference to
Demand Characteristics and Their Implications,"
American Psychologist, 17 (1962), 776-783.
Quastler, Henry. "Studies of Human Channel Capacity,"
in C. Cherry, Information Theory, Third London
Symposium, London: Butterwirths, 1956.
Schary, P. B. "Consumption and the Problem of Time,"
Journal of Marketing, 35 (1971), 50-55.
Sheth, Jagdish N. and M. Venkatesan. "Risk-Reduction
Processes in Repetitive Consumer Behavior," Journal
of Marketing Research, 5 (1968), 307-310.
Streufert, Sigfried. "Complexity and Complex Decision
Making: Convergences Between Differentiation and
Integration Approaches to the Prediction of Task Per-
formance," Journal of Experimental Social Psychology, 6 (1970), 494-509.
Swan, J. E. "Experimental Analysis of Predecision Information Seeking," Journal of Marketing Research,
6 (1969), 192-197.
Twedt, Dik W. "What Effect Will the 'Fair Packaging and
Labeling Act' Have Upon Marketing Practices?"
Journal of Marketing, 31 (1967), 58-59.
Wherry, Robert J. "A New Formula for Predicting the
Shrinkage of the Coefficient of Multiple Correlation,"
Annuals of Mathematical Statistics, 2 (1931), 440451.
- . "The Wherry-Doolittle Test Selection Method,"
in W. H. Stead and C. L. Shartle, Occupational Counseling Techniques. New York: American Book Company, 1940.
This content downloaded from 194.254.129.28 on Sat, 21 Sep 2019 13:15:48 UTC
All use subject to https://about.jstor.org/terms