Effects on Consumers' Decision Making and Preferences - Information Flow

Description
One of the main objectives facing marketers is to present consumers with information on which to base their decisions (Anderson and Rubin 1986; Bettman 1975). Presenting such information is not simple, and it contains an interesting dilemma. On the one hand, a vast amount of information could be relevant, even very relevant, to some consumers.

233
? 2000 by JOURNAL OF CONSUMER RESEARCH, Inc. ? Vol. 27 ? September 2000
All rights reserved. 0093-5301/2001/2702-0006$03.00
Controlling the Information Flow: Effects on
Consumers’ Decision Making and Preferences
DAN ARIELY*
One of the main objectives facing marketers is to present consumers with infor-
mation on which to base their decisions. In doing so, marketers have to select the
type of information system they want to utilize in order to deliver the most appro-
priate information to their consumers. One of the most interestinganddistinguishing
dimensions of such information systems is the level of control the consumer has
over the information system. The current work presents and tests a general model
for understanding the advantages and disadvantages of information control on
consumers’ decision quality, memory, knowledge, and con?dence. The results
show that controlling the information ?ow can help consumers better match their
preferences, have better memory and knowledge about the domain they are ex-
amining, and be more con?dent in their judgments. However, it is also shown that
controlling the information ?ow creates demands on processing resources and
therefore under some circumstances can have detrimental effects on consumers’
ability to utilize information. The article concludes with a summary of the ?ndings,
discussion of their application for electronic commerce, and suggestions for future
research avenues.
O
ne of the main objectives facing marketers is to present
consumers with information on which to base their
decisions (Anderson and Rubin 1986; Bettman 1975). Pre-
senting such information is not simple, and it contains an
interesting dilemma. On the one hand, a vast amount of
information could be relevant, even very relevant, to some
consumers. On the other hand, presenting super?uous in-
formation might impede consumers’ ability to make good
decisions (Bettman, Johnson, and Payne 1991; Jacoby,
Speller, and Berning 1974; Malhotra 1982; Scammon 1977).
Therefore the task facing marketers is not simply to present
consumers with every piece of semi-related information but,
rather, to present consumers with information that is ap-
propriate for their speci?c current needs. The dif?culty is
that marketers cannot always knowa priori what information
is needed for any individual consumer. Without knowing
what information is relevant, the amount of information that
is potentially relevant can be very large. In order to solve
this dif?culty, marketers can provide consumers with inter-
active information systems that allow consumers to be ap-
propriately selective in their own information search (Alba
*Dan Ariely is the Sloan Career Development Professor at the Sloan
School of Management, Massachusetts Institute of Technology, Cambridge,
MA 02142 ([email protected]). The author’s deepest thanks are given to
John Lynch and Jim Bettman for making this process fun and seriously
jeopardizing his desire to ever graduate. He also wants to thank Ziv Carmon
and Constantine Sedikides and the faculty members and students at the
Fuqua School of Business, Duke University. Finally, he would like to
extend an olive branch and his gratitude to the editor, associate editor, and
the reviewers.
et al. 1997; Bettman 1979; Bettman and Zins 1979; Hoffman
and Novak 1996; Wilkie 1975). In the spirit of this idea,
the central goal of the current work is to examine the bene?ts
and disadvantages of providing consumers with the ability
to control the ?ow of their information system (control over
what information will be presented, for how long it will be
presented, and what information will follow). Such control
over the information ?ow (information control) represents
a fundamental way in which information systems can react
and change in response to consumers’ actions, creating in-
teraction between the information system and the consumer.
The idea that different information systems provide con-
sumers with different levels of information control has long
been noted in the marketing literature (Bettman 1979; Weitz
1978; Wright 1973). In order to clarify this concept of in-
formation control, consider its levels for television and for
print ads. In the case of television ads, consumers can change
the channel or turn off the television set. Aside from this
limited freedom, consumers have no control over what in-
formation will be presented, in what order, or for how long
this information will be presented. On the other hand, in
the case of print ads, consumers have much more freedom
to choose the order in which to examine the different aspects
of the ad as well as the amount of time and attention to
give these aspects. For example, a consumer can browse
through a newspaper to see which retailer has a certain
model of Macintosh computer rather than paying attention
to adjacent ads.
Although the concept of information control has been
around for some time (Bettman 1979; Weitz 1978; Wright
234 JOURNAL OF CONSUMER RESEARCH
1973), with the development of computers and computerized
networks, understanding information control has become
much more important. This increase in relevance is primarily
due to two characteristics of electronic communication.
First, while traditional mass communication media such as
television and print ads differ on their level of information
control, this difference has not been very large. In contrast,
electronic communication has the potential for extremely
high levels of information control, tremendously increasing
its possible range. Second, while traditional communication
media have a ?xed level of information control (e.g., tele-
vision has a very low level of information control), the level
of information control of electronic communicationchannels
is variable and can be chosen by the marketer or information
provider.
BENEFITS AND DISADVANTAGES OF
INFORMATION CONTROL
Much like information search (Hagerty and Aaker 1984;
Ratchford 1982), control over the information ?ow seems
to have both advantages and disadvantages (bene?ts and
costs). In terms of bene?ts, information control allows con-
sumers to deal with information systems that better ?t their
individual informational needs and are more ?exible (Klein-
muntz and Schkade 1993; Schkade and Kleinmuntz 1994),
whereas in terms of the costs, information control requires
the user to invest processing resources in managing the in-
formation ?ow. In the next sections, the mechanisms un-
derlying the advantages and disadvantages associated with
information control will be presented in more detail. The
empirical part of the article will test the different aspects of
information control, and the results will be discussed with
regard to their implications for interactive media and in
particular to electronic communication and commerce.
Advantages of Controlling the Information Flow
Initial support for the bene?ts of information control
comes from work on learning relationships in probabilistic
environments (see Hammond, McClelland, and Mumpower
1980; Hammond et al. 1975). In an interesting paper, Klay-
man (1988) examined how control over the learning envi-
ronment in?uences subjects’ ability to learn probabilistic
relationship among attributes. Learning these relationships
was done under one of two learning environments. In the
interactive environment subjects determined for themselves
the con?guration of the stimuli to be tested (size, shape, and
shading), while in the noninteractive environment subjects
were given a speci?c and predetermined learning environ-
ment. The results showed that compared with subjects who
were given a ?xed learning environment, subjects who de-
signed their own learning environment were more effective
learners and had a better command of the environments’
underlying structure.
Similar results were also found by Kuhn and Ho (1980)
in a paper on the development of children’s thinking. In this
work, Kuhn and Ho (1980) showed that children who could
choose the games in which they wanted to engage (a high
level of control) had an improved ability to create new rea-
soning strategies compared with yoked (a low level of con-
trol) and control subjects. This improvement in reasoning
ability was attributed by the authors to an improvement in
the anticipatory schemas regarding the outcomes of their
actions. That is, control not only improved understanding
of a speci?c task but it also caused a more global improve-
ment in formal operations.
Combined, these results suggest that information control
improves performance by improving the ?t between actions
and outcomes and by improving anticipatory schemes (see
also work on the development of the visual system, Held
and Hein [1963]). In addition, increasing the ability to con-
trol information ?ow should also increase consumers’ ability
to explore and understand the information structure. Thus,
the core hypothesis of the current article is that information
control is bene?cial because having an interactive and dy-
namic information system can maximize the ?t between
heterogeneous and dynamic needs for information and the
information available (Alba and Hutchinson 1987; Einhorn
and Hogarth 1981; Payne, Bettman, and Johnson 1993).
Within this general heterogeneity argument, information
control seems to have two possible bene?ts: the ?rst has to
do with heterogeneity between consumers (Beatty and Smith
1987; Furse, Punj, and Stewart 1984; Jacoby, Chestnut, and
Fisher 1978), and the second has to do with heterogeneity
within consumers over time (Hauser, Urban, and Weinberg
1993). The ?rst component of heterogeneity (which will be
termed “individual heterogeneity”) is conceptualized as a
stable overall difference in individuals’ preferences for in-
formation presentation and processing. For example, one
consumer may prefer to view information by attributes,
while another might prefer to view the same information by
products. Consequently, consumers would choose different
preferred formats on a permanent basis. One example for
such a difference is the differential preference consumers
have for content in “push technology” on-line media. The
second, and more interesting, component of heterogeneity
(which will be termed “dynamic heterogeneity”) is concep-
tualized here as the changing needs for information during
the information acquisition process itself (see Beach 1993;
Wright and Barbour 1997). The notion of dynamic heter-
ogeneity is that the bene?ts of controlling the information
?ow arise from the fact that information control allows for
testing and updating hypotheses based on one’s mental
model. The human brain is assumed to be a sense-making
organ, and having control over the environment permits
information acquisition to be integrally linked into the act
of sense-making. Having control over the stimuli allows
consumers to generate and test the hypothesis in which they
are interested. Such conceptualization of dynamic hetero-
geneity relates to the idea of constructive preferences and
contingent strategies, where the information presented itself
changes the need for future information (Payne et al. 1993;
Slovic, Grif?n, and Tversky 1990). As an example of this
dynamic heterogeneity component, consider a consumer
CONTROLLING THE INFORMATION FLOW 235
who notices a diagnostic difference on some attribute that
changes his perception of different attributes and hence his
needs for future information (see Ariely and Wallsten 1995;
Montgomery 1983).
These two aspects of information control (individual het-
erogeneity and dynamic heterogeneity) are typically con-
founded or correlated in most real world information sys-
tems. High levels of information control often allow the
users of information systems to have an overall strategy for
the information presentation, while at the same time ena-
bling them to pick speci?c characteristics of the information
itself. Nevertheless, the task of teasing these two aspects
apart could be theoretically important and will be dealt with
later (experiment 3). To summarize, although the exact or-
igin of the bene?ts related to information control is not yet
clear, there are theoretical reasons to suspect that there is
much potential for these bene?ts to emerge. However, as
mentioned earlier, there are also reasons to suspect that in-
formation control can be associated with increased demands
on processing resources and therefore could have a negative
effect on consumers’ ability to process information (Bettman
1975; Bettman, Payne, and Staelin 1986; Scammon 1977).
The ideas underlying the processing costs of information
control are presented in the next section.
Disadvantages of Controlling the Information
Flow
In a highly interactive environment, having to control the
information ?ow can be seen as a task in itself (see Posner
1986; Treisman and Davies 1973). In such environments,
consumers have to perform two tasks: one is to understand
the information and the second is to manage the information
?ow (choose what information will be presented ?rst, for
how long, what aspects of the information will be perused
next, and in what order, etc.). If processing resources are
limited (Broadbent 1971; Kahneman 1973; March 1978;
Treisman 1969), such dual tasks can cause consumers in
highly interactive environments to have reduced resources
available to process the information itself (Anderson 1983).
More direct evidence supporting the idea that a secondary
task can increase cognitive load and hence impede perform-
ance in the primary task comes from work on learning tactile
mazes. Bongard (1995) showed that increased control over
punishment contingencies causes subjects to have higher
cardiovascular activity, increases the load on their cognitive
capacity, and as a consequence decreases their performance
on a comprehension task. Similarly, in their work on learn-
ing tactile mazes, Richardson, Wuillemin, and MacKintosh
(1981) demonstrated that subjects who had control over the
pattern of maze learning showed worse performance and
learning speed compared to the passive (yoked) subjects
who only experienced the maze and did not determine the
search pattern within it. In sum, both of these studies on
dual tasks show that under some conditions, the need to
make decisions in one task (controlling the task) increased
demand on cognitive resources and, because of cognitive
limitations, decreased performance in the comprehension
task.
Controlling the information ?ow in computerized search
tasks is different from traditional dual tasks in two important
ways (see Posner 1986; Shiffrin and Schneider 1977; Spelke,
Hirst, and Neisser 1976). First, while in the dual task lit-
erature the tasks are usually independent from each other,
in our case the two tasks of processing the information and
managing it are related and depend on each other. Second,
this dependency is in the “wrong direction.” In the dual task
literature there is a main task and a secondary task, and
limited capacity is demonstrated by lower performance on
the secondary task. In our case, the main task of under-
standing the information is dependent on the secondary task
of managing it. In other words, in order to perform well on
the main task (understand and judge the information), sub-
jects have to be able to perform well on the secondary task
(manage the information system). Despite these interesting
differences, the ideas of increased demands due to additional
tasks and their potential detrimental effects are applicable
and most likely even stronger due to their dependency.
Summary and Hypotheses
To summarize, it seems that information control has both
positive and negative effects on performance. The positive
effect is due to the value of the information itself combined
with the user’s ability to select and process the speci?c
information that is most relevant to the user (heterogeneity).
The negative effect is due to the additional resources de-
manded by the task of managing the information ?ow cou-
pled with limited processing capacity. In addition, consid-
ering information control as a task by itself with its own
demands brings to mind notions regarding learning and au-
tomaticity over time (Alba and Hutchinson 1987; Bryan and
Harter 1899; Spelke et al. 1976). As consumers continuously
engage in such tasks, the cognitive effort required for con-
trolling the information ?ow can be reduced, which can free
some of the cognitive resources for processing the infor-
mation itself.
A central prediction of these ideas is that for very simple
electronic stores, having high information control will be
better than having low information control. However, when
dealing with electronic stores that are more complicated to
understand and use, the pattern of results will be different.
In such cases, the implication is that on initial use consumers
who have high information control will suffer a larger per-
formance loss than consumers who have low information
control. However, with increased experience, consumers
who have high information control will be able to improve
faster and perform better. Therefore the overall prediction
is a three-way interaction between the level of information
control, the cognitive load imposed by the information sys-
tem, and the amount of experience with the interface. The
form of the interaction is that having high information con-
trol in a simple system always provides an advantage, but
for more complicated systems having high information con-
236 JOURNAL OF CONSUMER RESEARCH
trol is initially detrimental, and its positive effects reveal
themselves only over time.
Thus far, general conceptualization for information con-
trol and its mechanism has been presented. The remainder
of the current work is organized as follows: the ?rst three
experiments primarily address the bene?ts of information
control in terms of ability to process and integrate infor-
mation. Experiment 1 examines performance in the context
of an agent/principal task, and experiment 2 examines per-
formance for one’s self. Having demonstrated the advan-
tages of increased information control, experiment 3 at-
tempts to tease apart the two different heterogeneity
components underlying the bene?ts of information control
(individual heterogeneity and dynamic heterogeneity). After
achieving a better understanding of the potential bene?ts of
information control, experiment 4 tests the full set of ideas,
particularly the costs associated with information control.
Finally, experiment 5 examines the consequences of infor-
mation control for memory and knowledge structure about
the decision environment.
EXPERIMENT 1: IS INFORMATION
CONTROL USEFUL?
In order to test the effects of information control, a simple
IHS (Interactive Home Shopping) simulation was created
in which subjects were given information about different
cameras and were asked to rate the overall quality of these
cameras. Subjects performed this task under either high or
low levels of control over the information ?ow. In the High-
InfoControl condition subjects had complete freedom in se-
lecting the sequence characteristics in which the information
was displayed, whereas in the Low-InfoControl condition
subjects had no freedom in determining the information’s
sequence characteristics, and they viewed the information
in a manner similar to viewing a movie.
Method
Subjects. Thirty-six subjects participated in this exper-
iment for class credit. In addition, a reward of $20 was
promised to the subject with the best overall performance.
During the task each subject examined and rated nine dif-
ferent cameras, taking approximately 10 minutes. Subjects
were randomly assigned to either the High-InfoControl or
Low-InfoControl conditions.
Task. In order to determine decision quality, it is useful
to compare the judgments subjects make to a set of optimal
judgments. For this reason an agent/principal task was util-
ized. In this task, subjects were given the importance
(weight) that the principal places on the different attributes
(we will refer to those as the principal’s utilities) and were
asked to make judgments according to these utilities (Ariely
and Wallsten 1995; Huber, Ariely, and Fischer 1998; West
1996). One could argue that such agent tasks are not com-
mon; however, many of the decisions we make in our day
to day lives are indeed agent tasks. For example, when we
buy presents, go to restaurants or movies, and even buy
food at the grocery store, the focus of many of these de-
cisions is aimed at pleasing others and not ourselves.
At the onset of the experiment subjects were introduced
to the task, given explanation about the product category,
and were given three examples of the cameras in the set
(including the best and the worst). Each of the cameras was
depicted along four dimensions (lens, body, shutter, and
engine), which were described and explained to the subjects.
Ratings on these four dimensions were on a common 0–100
scale, with low numbers representing low desirability levels
and high numbers representing high desirability levels. All
other attributes were said to be equal. During the main task
subjects were asked to use the computer interface to learn
about the different cameras so that they could rate them
according to the principal’s utilities.
The nine different cameras were divided into three sets
of three cameras each. Each of these three sets (composed
of three cameras) was presented on a different trial for sub-
jects to examine and evaluate. On each of the three trials,
subjects ?rst viewed information regarding the three cam-
eras in the set and were then asked to rate each of them on
a scale from 0 (not attractive at all) to 100 (very attractive).
This task was repeated three times for each subject, so that
nine cameras were examined and evaluated in total. Order
of the cameras within and between trials was counterbal-
anced between subjects.
Stimuli. The stimuli were structured based on three lev-
els (30, 60, and 90) for each of the four attributes (lens,
body, shutter, and engine), which were combined to yield
the 3
4
basic orthogonal design (see Addelman 1962). By
using this approach the stimuli represented the entire range
on the different attributes while at the same time keeping
the correlations between the different attributes at zero, thus
allowing maximally ef?cient estimates of utilities (attribute
importance weights). These nine cameras constituted the
basic camera set upon which all stimuli were based. The
principal’s “true” utilities were computed by assigning un-
standardized weights of lens 85, body 70, shutter 55, and
engine 40. By plugging each camera’s (0–100) scores on
those four dimensions into the principal’s objective function,
the overall value and rank order of each camera was cal-
culated. Finally, in order to avoid regular values (such as
multiples of 10) and to make the cameras appear more re-
alistic, a small random component (?10 percent) was added
to each of the values on each of the cameras. This random
component was such that the rank ordering of the different
cameras was not changed and values of 100 or above were
excluded.
Procedure. The interface was presented as a hierar-
chical information system with three cameras represented at
the top layer of the hierarchy, the names of the four attributes
at the second level, and their values at the third level (see
Fig. 1). Subjects were randomly assigned to pairs, and within
each pair one subject was assigned to the High-InfoControl
condition and one to the Low-InfoControl condition. During
CONTROLLING THE INFORMATION FLOW 237
FIGURE 1
AN EXAMPLE OF THE SCREENS IN THE HIERARCHICAL
INFORMATION SYSTEM
NOTE.—Panel A represents the highest level of the system, panel B the
middle one, and panel C the lowest level. Note that subjects in the Low-
InfoControl condition viewed only the screens represented in panel C.
the task, subjects in the High-InfoControl condition had
three minutes
1
to viewthe information before rating the three
cameras in a set. During this time the High-InfoControl
subjects were free to choose which pieces of information to
view and for how long. Selection of information was done
by using the mouse and clicking on different parts of the
screen (see Fig. 1). Subjects in the Low-InfoControl con-
dition were exposed to the same value information in the
same order and timing as the High-InfoControl counterpart
to whom they were yoked. These subjects could not control
their ?ow of information, nor did they get the screens that
allowed them to control the information ?ow (panels 1A,
1B). Once the time for examining the information was up,
subjects in both conditions were asked to rate the three
cameras in the set on a scale from 0 (the worst of all) to
100 (the best of all).
Results
In order to test whether information control has an impact
on performance in an agent/principal judgment task, two
types of performance measures were created: a rating-error
measure and a weighting-error measure. The rating-error
1
This value (as well as many of the other speci?c values used) was based
on pilot experiments carried out with slightly different interface and stimuli.
measure examines the difference between the subjects’ and
the principal’s overall ratings. The weighting-error measure
examines the ?t between the declared importance weights
of the principal (the true utilities) and the recovered utilities
based on subjects’ responses. These two types of measures
will be discussed next.
The rating-error measure was composed of the mean ab-
solute difference between the ratings each subject gave to
the nine different cameras and their true ratings according
to the principal (mean absolute rating error). Results for the
rating-error measure showed that performance was better
(i.e., closer to 0) in the High-InfoControl condition (M p
) than in the Low-InfoControl condition ( , 11.56 M p18.7
, ). This result indicates that subjects t(17) p5.35 p ! .001
in the High-InfoControl condition rated the different cam-
eras in higher agreement with the principal, implying that
they had better ability to integrate the information in this
task.
The weighting-error measure was very different in nature
and was based on the differences between recovered and
true utilities. In order to develop this measure, the ratings
of each individual subject were regressed on the values used
for the nine different cameras (Ratings pb ?b ?
0 Lens
). The overall results showed that the b ?b ?b
Body Shutter Engine
?t of the models were better in the High-InfoControl con-
dition ( p 0.90) than in the Low-InfoControl condition ¯ r
( p 0.77, , ), indicating that subjects ¯ r t(17) p2.57 p ! .01
in the High-InfoControl condition used their utilities (re-
gardless of their exact value) in a much more consistent
way than subjects in the Low-InfoControl condition. How-
ever, consistency does not necessarily imply better perform-
ance. Imagine, for example, a situation in which subjects in
one of the conditions simplify the task by consistently using
only one of the attributes to make their judgments. In such
cases the regression model would capture almost all of the
variance and hence yield a very high ?t. Nevertheless, be-
cause of the simpli?cation process these subjects would per-
form very poorly on the task of acting according to the
principal’s utilities. Therefore it is clear that in addition to
the overall ?t, a more careful look is required at the match
between the utilities recovered by the regression models and
the true utilities of the principal.
In order to examine the utility ?t, the recovered utilities
for each subject were estimated and transformed to a com-
mon scale in which the sum of the utilities was equal to 1.
This transformation was done by dividing each of the re-
covered utilities by the sum of the four recovered utilities.
By using this approach, the recovered utilities could be di-
rectly compared with the principal’s (true) utilities. Next,
the mean absolute deviations between the true weights for
each of the four attributes and the four (transformed) weights
estimated for each subject were calculated and compared
across the two InfoControl conditions. The results showed
that the mean of this weighting-error measure was smaller
for subjects in the High-InfoControl condition ( ) M p6.4
than for subjects in the Low-InfoControl condition (M p
, , ). Since this difference score is 11.9 t(17) p4.43 p ! .001
238 JOURNAL OF CONSUMER RESEARCH
FIGURE 2
THE PRINCIPALS AND RECOVERED UTILITIES FOR THE HIGH
AND LOW INFOCONTROL CONDITIONS
NOTE.—Each set of utilities is converted to a scale such that the sum of
utilities in each set is equal to one.
a composite of four different attributes, one can also examine
the ?t between the two sets of utilities separately for each
of the attributes. As can be seen in Figure 2, subjects in
both conditions seemed to overestimate the two most im-
portant attributes (lens and body) and underestimate the two
least important attributes (shutter and engine). However, this
tendency was much stronger for subjects in the Low-
InfoControl condition, which is the main reason for their
diminished match and ?t with the principal’s utilities.
Discussion
The goal of experiment 1 was to test whether differences
in the level of control over the information ?ow produce
differences in task performance. The results clearly support
the notion that increased information control leads to in-
creased performance for this simple task. This performance
increase held for both the rating-error and weighting-error
measures. The rating-error measure showed that subjects in
the High-InfoControl condition rated the different cameras
in a way that was more consistent with the principal. The
weighting-error measure showed that subjects in the High-
InfoControl condition were more consistent in their use of
the model and matched the principal’s utilities better. In
addition, looking at the differences for the four individual
utilities revealed an interesting pattern in which subjects in
the High-InfoControl condition treated the weights of all
four attributes differentially, while subjects in the Low-
InfoControl condition simpli?ed the task and treated the two
most important attributes similarly.
EXPERIMENT 2: THE SELF-EXPRESSION
EXPERIMENT
So far the discussion of information control has been
expressed in terms of individual preferences, while exper-
iment 1 utilized an agent/principal task. By using such a
task, subjects did not express their own preferences but,
rather, the utility structure of a known principal. The de-
cision to use such an agent/principal task was made in order
to achieve better measures of decision quality and accuracy.
However, using such a task assumes that the process for
expressing a principal’s utilities is similar to the process by
which one’s own utilities are expressed. Although consum-
ers commonly engage in agent tasks when purchasing goods
for others (West 1996), being an agent for a principal with
well-known and articulated utilities is not as common.
Therefore, the goal of experiment 2 was to test if the same
pattern of results hold when expressing one’s own prefer-
ences. Note that the assumption made in experiment 1 (and
again in experiments 3 and 4) is that the task of expressing
utilities for one’s self and for others does not interact with
the factors manipulated in these experiments. In general this
assumption seems reasonable, but nevertheless it is desirable
to test it empirically.
Method
Subjects. Forty subjects participated in this experiment
in exchange for $10. In addition, a reward of $20 was prom-
ised to the subject with the best overall performance. During
the task each subject examined and rated 36 different cam-
eras, taking approximately 40 minutes. Subjects were ran-
domly assigned to either High or Low InfoControl
conditions.
Task, Stimuli, and Procedure. The overall task was
similar to the task in experiment 1, involving the same cam-
eras and the same basic interface. There were, however, three
main differences between the procedure used in this exper-
iment and the one used in experiment 1. First, subjects in
this experiment were asked to make judgments for them-
selves and not for the principal. Second, in order to increase
the stability of the data, subjects examined and rated the
three sets of three cameras twice, making it a total of 18
cameras during the main task (this was also done in ex-
periment 3). Finally, since in this experiment there was no
principal and therefore there was no standard of perfect
performance, subjects’ own ratings were used as a bench-
mark for their own performance. For this purpose, subjects
were also asked to engage in two concurrent rating tasks of
nine cameras that were based on the same structure of the
cameras in the main task but different in their values. During
each of the concurrent rating tasks, subjects simultaneously
saw descriptions of nine cameras and were asked to give
each of them an overall rating on the same scale they used
CONTROLLING THE INFORMATION FLOW 239
to evaluate the cameras in the main task. By using this
procedure, the concurrent rating task was simpler than the
main task since it required no information search or memory.
The utilities extracted from these two concurrent rating tasks
were used as the standard for that particular subject.
Results
Because in this experiment there was no agent, the per-
formance measures used were based only on subjects’ con-
sistency and not on performance accuracy. This drawback
of self-preference measures is the main reason for using
agent/principal tasks. First, as in experiment 1, the rating
judgments for each subject were regressed on the structure
of the orthogonal design. The overall ?t of the individual’s
utility models to the rating (r) was taken as the consistency
with which each subject used his own utilities and was in
turn interpreted as a measure of performance level. Aside
from the logical base for using consistency as a surrogate
for performance level, additional support for this interpre-
tation comes from the relatively high correlation between
these two measures of weighting-error in experiment 1 (r p
0.68). The consistency results gave rise to the same con-
clusion as in experiment 1, where subjects in the High-
InfoControl condition had a higher average consistency (¯ r
p 0.85) than subjects in the Low-InfoControl condition
( p 0.74, , ). ¯ r t(19) p2.70 p p.014
In addition to the consistency aspect of the weighting-
error measure, an additional measure of weighting error was
introduced in the current experiment. This measure was of
a different nature, and it was based on the differences in
the recovered utilities between the hierarchical information
search task and the concurrent rating task. In essence this
measure compares the attribute weighting when all the in-
formation is presented concurrently to when it is presented
sequentially. Therefore, the difference between these two
tasks can be used as an indication of the ability to integrate
information over time, where smaller differences indicate a
higher ability to integrate information over time. To con-
struct this measure, a regression model was used on the
concurrent rating tasks to recover each individual subject’s
utilities (based on 18 evaluations). Next, for each subject,
the standardized utilities recovered from the concurrent rat-
ing tasks were compared to the standardized utilities recov-
ered from the hierarchical information task. The mean ab-
solute difference between these two was taken as a measure
of ability to consistently make judgments across tasks. The
results for this aspect of the weighting-error measure were
again in the same direction, where subjects in the High-
InfoControl condition had a higher judgment consistency
( ) than subjects in the Low-InfoControl condition M p6.8
( , , ). M p18.1 t(19) p1.75 p p.096
Discussion
The goal of experiment 2 was to test whether the con-
clusion drawn from experiment 1 generalizes to individual
preferences. Two measures of weighting error were used to
evaluate performance in this self-task, and both indicated
that performance in a simple task improves with increased
information control. Therefore, the main conclusion from
experiment 2 is that the results of experiment 1 do not seem
to be due to the agent/principal task. Rather, the increase in
performance associated with increased information control
generalizes to expressions of both utilities for one’s self and
others. The following two experiments therefore will utilize
an agent/principal task, while the conclusions will be as-
sumed to hold for both agent/principal and self-tasks alike.
EXPERIMENT 3: BENEFITS OF
INFORMATION CONTROL?
After establishing that for simple information systems,
information control seems to improve subjects’ ability to
make good decisions, the next logical question one needs
to ask concerns the origin of these bene?ts. Earlier, it was
suggested that the source of these bene?ts is the heteroge-
neity in information needs (Beach 1993; Payne et al. 1993;
Wright and Barbour 1997). More speci?cally, it was sug-
gested that information control has two main components
for its possible bene?ts; the ?rst has to do with heterogeneity
between consumers, and the second has to do with heter-
ogeneity within consumers over time (individual hetero-
geneity and dynamic heterogeneity, respectively). A third
explanation entailing anticipatory schemas was also offered
as a different type of bene?t that highly interactive envi-
ronments could offer.
In order to separate these three explanations, two new
conditions were introduced (Known-InfoControl and Self-
InfoControl). In the Known-InfoControl condition, subjects
viewed the information much like subjects in the Low-
InfoControl condition, but with advance knowledge of the
search strategy. This was done by giving subjects in this
condition a map describing the search strategy for each of
the three trials in the experiment. This map was based on
a grid which showed the sequence of information that they
would be exposed to on the next trial (shutter for camera
1, shutter for camera 3, lens for camera 2, etc.), but without
specifying their actual information. As in the Low-Info-
Control condition, the search itself (as well as the map) was
based on the search pattern of the matching subject in the
High-InfoControl condition. In the Self-InfoControl con-
dition, subjects were asked to indicate their search strategy
for each next trial, and this strategy was carried out for
them. In order to indicate their preferred sequence of the
information, subjects were given an empty matrix repre-
senting the different cameras and attributes. They were then
asked to indicate the sequence in which they wanted to view
the different pieces of information.
By examining these four experimental conditions and the
differences in their performance, the two types of hetero-
geneity explanations could be separated. In order to under-
stand how these comparisons can isolate these two effects,
consider Table 1, in which the four different experimental
conditions are presented with their different components.
240 JOURNAL OF CONSUMER RESEARCH
TABLE 1
THE FOUR EXPERIMENTAL CONDITIONS USED IN EXPERIMENT 3, THEIR SOURCE OF BENEFITS, AND THE RESULTS OF THE
MEAN RATING ERROR (BASED ON THE DIFFERENCE BETWEEN THE PRINCIPAL’S AND SUBJECTS’ RATINGS)
Comparison
Condition
A ?t to own
overall strat-
egy: individual
heterogeneity
Knowledge
of strategy:
anticipatory
schemas
Reacting to
the informa-
tion: dynamic
heterogeneity
Rating error: mean
(SE)
High-InfoControl
Y
Y Y 12.85 (.56)
Self-InfoControl Y
Y N
21.75 (.97)
Known-InfoControl
N
Y N 21.87 (1.06)
Low-InfoControl N
N
N 21.99 (.80)
The effect of dynamic heterogeneity can be estimated by
the difference in performance between High-InfoControl
and the Self-InfoControl conditions. The effect of individual
heterogeneity can be estimated by the difference in per-
formance between Known-InfoControl and Self-InfoControl
conditions. Finally, the role of anticipatory schemas in gen-
eral can be estimated by the difference in performance be-
tween the Known-InfoControl and Low-InfoControl
conditions.
Method
Subjects. One hundred forty-four subjects participated
in this experiment for class credit. In addition, a reward of
$20 was promised to the subject with the best overall per-
formance. During the task, each subject had an initial prac-
tice trial with the information system, followed by the main
test. Subjects were randomly assigned to four experimental
conditions (High-InfoControl, Low-InfoControl, Self-
InfoControl, and Known-InfoControl).
Task, Stimuli, and Procedure. The overall task was
the same as in experiment 1, involving the same cameras,
the same basic interface and the same responses. There were
two main differences: the way information control was con-
ceptualized in the two new conditions, and the addition of
a practice trial at the beginning of the experiment. The prac-
tice trial had to be used for both the Self-InfoControl con-
dition and the Known-InfoControl condition, because with-
out it, these subjects could not understand the relationship
between the strategy and the information. In order to keep
all four conditions equivalent in terms of experience, this
practice trial was used for all four conditions. Moreover,
practice was the same for subjects in all four conditions and
was based on the High-InfoControl condition, allowing the
subjects to extract the most comprehensive understanding
of the task at hand.
Results
In order to examine the differences in performance be-
tween the four different experimental conditions, a rating-
error measure was created. Similar to the measure used in
experiment 1, this measure was composed of the mean ab-
solute differences between the ratings subjects gave to the
different cameras and their true ratings (for the principal).
Comparing this measure across the different conditions (see
Table 1) showed a signi?cant omnibus effect of InfoControl
(F(3, 105) p 30.1, p ! .001).
Earlier, three planned comparisons were presented in or-
der to isolate the source of the bene?ts of information control
(see Table 1). These three comparisons were between Self-
InfoControl and Known-InfoControl to examine individual
heterogeneity (F(1, 969) p0.11, p p .92), between High-
InfoControl and Self-InfoControl to examine dynamic het-
erogeneity (F(1, 969) p 7.54, p ! .001), and between
Known-InfoControl and Low-InfoControl to examine An-
ticipatory schemas (F(1, 969) p 0.10, p p .92). Thus,
dynamic heterogeneity, but not individual heterogeneity or
anticipatory schemas, appears to be a signi?cant source of
bene?ts in this interactive information system. In addition,
as can be seen in Table 1, the only difference among the
four conditions was due to the improved performance in the
High-InfoControl condition (F(1, 969) p 87.69, p ! .001).
The rating error in the other three InfoControl conditions
showed no observable difference (F(2, 969) p 0.04, p p
.84). The similarity of performance in the Low-InfoControl,
Known-InfoControl, and Self-InfoControl conditions again
indicates that knowing the search strategy or being able to
?t it to an individual’s stable informational needs (individual
heterogeneity) did not improve performance. The same re-
sults emerged for the overall ?t measure (r), with High-
InfoControl ( p 0.89), being higher than Self-InfoControl ¯ r
( p 0.65), Known-InfoControl ( p 0.61), and Low- ¯ ¯ r r
InfoControl ( p 0.56). ¯ r
CONTROLLING THE INFORMATION FLOW 241
Discussion
The goal of experiment 3 was to try and separate out the
different facets that may contribute to the bene?ts of infor-
mation control observed in experiments 1 and 2. Two ex-
planations for these advantages were offered, one based on
heterogeneity between consumers (individual heterogene-
ity), and the other based on heterogeneity within consumers
over time (dynamic heterogeneity). In addition, a third as-
pect involving anticipatory schemas was also suggested and
tested. The four experimental conditions were designed to
tease apart these three types of explanations by comparing
performance in the different conditions (see Table 1). The
results indicated that neither knowing the structure of the
information ?ow nor being able to control it a priori matters.
Dynamic heterogeneity, on the other hand, seems to be the
most important contributor to the advantages associated with
information control. In sum, the bene?t of information con-
trol in our case did not stem from overall individual dif-
ferences but from the freedom to change search strategy in
reaction to the information acquisition process itself (dy-
namic heterogeneity).
EXPERIMENT 4: COSTS OF
INFORMATION CONTROL?
The ideas presented earlier suggest that information con-
trol has two main components, processing bene?ts and pro-
cessing cost. The processing bene?ts were hypothesized to
be related to dynamic heterogeneity in information needs
(Bush and Burnett 1987; Hauser et al. 1993), while the
processing costs were hypothesized to be due to processing
resource limitations (Broadbent 1971; Kahneman 1973;
Treisman 1969). In turn, it was suggested that if the pro-
cessing costs are due to processing limitations, then higher
levels of information control should be more sensitive than
lower levels of information control to a manipulation of
cognitive load (complexity) and to the level of learning over
time (Bryan and Harter 1899; Hoef?er and Ariely 1999;
Klayman 1988).
Speci?cally, it was hypothesized that when dealing with
simple information systems, the processing costs for search-
ing and integrating information are lower than the pro-
cessing capacity and therefore the overhead caused by hav-
ing highly demanding systems does not amount to much.
Under such conditions, performance in the High-InfoControl
condition would be superior to the one in the Low-Info-
Control condition. On the other hand, once the information
systems become more complicated (by increasing search
cost, processing cost, or reducing cognitive capacity), the
predictions are very different. In such cases, the overhead
caused by having highly demanding systems can cause pro-
cessing demands to exceed capacity. Under these conditions
it is expected that performance in the High-InfoControl con-
dition would be lower than performance in the Low-
InfoControl condition. Another test of these ideas has to do
with learning. When consumers have opportunity to learn
over time, the resources demanded by controlling the task
can be reduced, which will cause performance in the High-
InfoControl to improve more rapidly. Thus, even if high
levels of information control are initially inferior to low
levels, over the long run high levels of information control
could prove to be more bene?cial. Based on these ideas, the
overall expected result is a three-way interaction in which
increased information control will always be bene?cial for
simple information systems. However, for complicated in-
formation systems increased information control would be
initially detrimental and its bene?ts would increase with
experience.
Note that by examining together two separate sources of
cognitive capacity (cognitive load and learning), the ex-
pected interaction pattern eliminates many alternative ex-
planations. For example, one alternative explanation for the
difference between high and low information control could
be in terms of motivational differences between these con-
ditions. Such main effects explanations cannot account for
the expected learning effects over time or for the expected
interactions between cognitive load and information control.
Method
Subjects. Seventy-two subjects participated in this ex-
periment in exchange for $10. In addition, a reward of $20
was promised to the subject with the best overall perform-
ance. During the task each subject examined and rated 18
different cameras, which took approximately 20 minutes.
Subjects were randomly assigned to one of the four exper-
imental conditions (High or Low InfoControl crossed with
high or low cognitive load).
Design, Task, Stimuli, and Procedure. Both the task
and the stimuli used in this experiment were identical to
those used in experiment 1, with two notable differences in
the procedure. The ?rst difference involved the cognitive
load manipulation and hence the interface manipulation, and
the second involved the length of the task and the number
of trials within it. Note that the level of experience with the
interface can be viewed as a second manipulation of cog-
nitive load. The idea here is that over time, the resources
demanded by the navigation task can be diminished below
the capacity constraints, allowing the bene?ts of information
control to emerge. Since testing this notion involves learning
over time, it was important to conduct the experiment over
a larger number of trials so that the effects of learning could
be observed. In order to achieve this goal, each subject in
experiment 4 observed and rated six sets of three cameras
each. The structure of the ?rst three sets was identical to
those in experiments 1, 2, and 3. This structure was repeated
twice, for a total of six trials and 18 evaluations. After
completing the six trials, subjects were asked how con?dent
they were in their judgments and also how much they liked
the interface. Experiment 4 was therefore a 2 (cognitive
load) by 2 (InfoControl) by 6 (experience) mixed design,
with cognitive load and InfoControl manipulated between
subjects and experience (the repeated trials) manipulated
within subjects.
242 JOURNAL OF CONSUMER RESEARCH
FIGURE 3
MEAN RATING-ERROR MEASURE, BASED ON THE ABSOLUTE
DIFFERENCE BETWEEN THE PRINCIPAL’S AND SUBJECTS’
RATINGS
NOTE.—Plotted by InfoControl, cognitive load, and trial.
Cognitive load was manipulated on two levels (Low-Load
and High-Load), which was achieved by manipulating the
ease with which the information could be processed. In the
Low-Load condition, the values of the cameras were pre-
sented as a single number on a scale from 0 to 100, while
in the High-Load condition, the values of the cameras were
presented as a compound of three numbers. Speci?cally,
each of the values on each of the attributes was presented
as a function of quality, durability, and reliability. The values
on these components were determined randomly, with the
restriction that their sum be equal to the original value they
represented. Subjects were told that the agent had equal
weights for all three components and that in order to get
the value of the attribute they needed to combine (add) the
values of all three components. This manipulation increased
the number of steps needed to integrate and judge the in-
formation without providing any added informational
bene?t.
Results
Similar to experiments 1, 2, and 3, the rating-error mea-
sure was composed of the mean absolute difference between
the ratings each subject gave to the different cameras and
their true ratings (for the principal). However, because one
of the main objectives of experiment 4 was to examine
changes in performance level over time, the rating-error
measure was based on the mean absolute differences for
each individual trial (three cameras). This rating-error mea-
sure was then compared across the six trials, cognitive load,
and InfoControl levels. As illustrated in Figure 3, the results
replicate the main effect of InfoControl in the Low-Load
condition while showing a very different pattern in the High-
Load condition. In the High-Load condition, InfoControl
was initially not bene?cial, and its bene?ts only emerged
over time. The results also suggest that the only condition
under which learning occurred was the High-InfoControl/
High-Load condition and, moreover, that this learning oc-
curred rather rapidly. In order to test this improvement over
time, the rating-error’s linear trend across the six trials was
estimated for each subject and compared across the different
conditions. Testing these trends revealed a signi?cant
InfoControl by cognitive load interaction (F(1, 34) p4.38,
p p .044), with the only trend that was signi?cantly dif-
ferent from zero being the one for the High-InfoControl/
High-Load condition. These results, coupled with the overall
interaction between InfoControl and cognitive load (F(1, 34)
p7.18, p p.011), give further credence to the notion that
controlling demanding interfaces should be viewed as dual
tasks susceptible to processing demands and capacity
constraints.
In addition to the rating-error measures, it is also impor-
tant to examine the weighting-error measures in order to
estimate the veridicality and consistency with which subjects
executed their judgment policies. Examining these measures
is important because they represent subjects’ ability to in-
tegrate the information and perform the task at hand. In
order to get the different weighting-error measures, subjects’
ratings were ?rst regressed on the orthogonal structure of
the stimuli. For each subject this was done twice, once for
each of the two stimulus replications (?rst and second sets
of nine cameras). Note that for a smaller number of cameras
ef?cient estimates could not be obtained. These weighting-
error measures were then compared across the four exper-
imental conditions and the two sets. The overall ?t of these
regression models showed the same interaction pattern noted
earlier, where the three-way interaction (InfoControl by cog-
nitive load by set) was signi?cant (F(1, 34) p 6.18, p p
.018). This interaction was such that during the ?rst three
trials (set 1) High-InfoControl was bene?cial for the Low-
Load condition but detrimental for the High-Load condition.
However, as experience accumulated this pattern changed,
and High-InfoControl was always bene?cial.
As mentioned earlier, it is possible to have an overall
good ?t for the model and still have a large mismatch with
the utilities of the principal. For this reason all sets of utilities
were transformed to a common scale in which the sum of
the utilities was equal to 1. Examining the mean of the
absolute differences between these sets of utilities and the
agent’s utilities points to the same result noted earlier, where
the three-way interaction (InfoControl by cognitive load by
set) was signi?cant (F(1, 34) p 4.21, p p .048). Once
again, during set 1 High-InfoControl proved bene?cial under
the Low-Load condition and detrimental under the High-
Load condition. In addition, the pattern of these results was
different with the accumulation of experience, where High-
InfoControl was always bene?cial.
Finally, it is interesting to examine not only the objective
CONTROLLING THE INFORMATION FLOW 243
measures of performance but also some subjective mea-
sures. Regarding the Liking question, there was no effect
for the cognitive load manipulation. However, there was
a large effect for InfoControl where subjects in the High-
InfoControl condition liked the interface more (Mp66.1)
than subjects in the Low-InfoControl condition (Mp36.7,
F(1, 34) p 19.8, p ! .001). This was independent of cog-
nitive load, as indexed by the nonsigni?cant cognitive load
by InfoControl interaction (F(1, 34) p 1.24, p p .28).
The con?dence measure showed the same basic pattern
with no effect for the cognitive load manipulation, but a
positive effect for increasing InfoControl. For this mea-
sure, subjects in the High-InfoControl condition had more
con?dence in their ratings (M p 74.7) than subjects in
the Low-InfoControl condition (M p 55.3, F(1, 34) p
27.4, p ! .001).
Discussion
The results of experiment 4 clearly support the ideas pre-
sented earlier in the following ways: ?rst, the data show
that in Low-Load conditions, when the demands on pro-
cessing resources are low, increased information control is
bene?cial. However, in High-Load conditions, when the de-
mands on processing are higher, the results are somewhat
different. In this case, on initial trials High-InfoControl is
detrimental to performance, and it is only with increased
experience that the bene?ts of High-InfoControl emerge.
From both a theoretical and practical perspective alike the
most interesting point is that it is exactly the High-Load
conditions, where controlling the information ?ow is least
attractive initially, for which there is the most improvement
over time. In other words, the results from experiment 4
(i.e., the slopes with respect to trials) are also interpretable
in terms of differential rates of learning in high and low
information control environments. The other interesting re-
sults relate to the subjective measures of performance. These
subjective measures are important because they are likely
to be the most important inputs into decisions regarding
future use of information systems. In sum, experiment 4
demonstrates the bene?ts of high levels of information con-
trol (replicating previous experiments and extending the re-
sults to subjective measures) but also its associated pro-
cessing costs.
EXPERIMENT 5: THE MEMORY AND
KNOWLEDGE EXPERIMENT
Thus far the discussion of the advantages and disadvan-
tages of information control has been related to short-term
consequences and outcomes. In other words, the measures
used in the ?rst four experiments examined the immediate
outcomes of the information search process and how they
were in?uenced by information control, cognitive load, and
experience. However, in many contexts it is important to
examine not only concurrent performance (at the time of
the task) but also to examine different aspects of future
performance. Experiment 5 was designed to test some of
the long-term implications of information control on other
dimensions of learning and performance, for example, mem-
ory and understanding of the structure of the task environ-
ment. The perspective taken in this experiment is that con-
sumers will choose to use and stay with a certain information
provider only under conditions of long-term bene?ts. In
other words, we need a consumer’s-eye analysis of not only
the immediate bene?ts of information control—which might
dictate trial—but also an analysis of what long-term bene?ts
an information system provides.
One way to examine understanding of the problem space
is to measure the level of implicit memory and implicit
knowledge consumers have for the information (Brunswik
1955). In order to examine consumers’ memory and knowl-
edge, it is ?rst important to conceptualize these constructs
in the context of current tasks. Memory is conceptualized
as the accuracy by which the speci?c values presented in
the task could later be identi?ed. Knowledge is conceptu-
alized as the level by which the relationship between the
levels of the different attributes is internalized. Together,
these two tasks capture the understanding consumers have
for both the speci?c values presented in the task (memory)
and the relationship between them (knowledge). Thus, the
goal of experiment 5 is to examine incidental memory and
knowledge as a consequence of information control.
Method
Subjects. Forty subjects participated in this experiment
in exchange for $10. In addition, a reward of $20 was prom-
ised to the subject with the best overall performance. During
the experiment, each subject examined and rated nine dif-
ferent cameras, followed by a memory and knowledge task.
Each subject took approximately 40 minutes to complete
the experiment. Subjects were randomly assigned to either
the high or low InfoControl conditions.
Stimuli. The stimuli used in this experiment were based
on the same basic camera stimuli used earlier but with a
correlated, rather than orthogonal, relationship between the
values on the different attributes. The exact correlational
structure used was: body p lens # 0.75; shutter p lens
# 0.50; engine p lens # 0.25. This relationship was set
so that the value of the lens was the same as the values
used in previous experiments, and the values of all three
other attributes were determined in relation to it with the
addition of a small random component (?10 percent). In
order to allow for unique identi?cation, the values were
constrained such that no value appeared more than once.
Task. After rating three sets of three cameras, subjects
in this experiment completed an incidental memory task and
a correlation knowledge task. The reason for choosing in-
cidental rather than intentional learning tasks was to capture
the secondary and long-term implications of information
control. If subjects were aware that the goal of the exper-
iment was to test their memory and knowledge, they would
have set their goals to perform optimally on these measures.
244 JOURNAL OF CONSUMER RESEARCH
FIGURE 4
AN EXAMPLE OF THE MEMORY TASK
NOTE.—All the values used during the last trial are presented outside of the
matrix, and subjects were asked to drag them to their correct location in the
matrix.
In such a case, the relevance of these measures as an in-
dication of future use would have been diminished (since
they would re?ect immediate and not long-term bene?ts).
In the incidental memory task, subjects were given the val-
ues for the three cameras used in the last trial they expe-
rienced and were asked to place them (drag with the mouse)
in their correct location in a matrix that represented the
information system (see Fig. 4). In the correlation knowl-
edge task (relationship between the different attributes), sub-
jects were presented with a single attribute value for each
one of nine new cameras, and were asked to predict the
values of the other three attributes for each of these cameras.
Procedure. The procedure in this experiment was dif-
ferent than the one used in experiment 1 in two important
ways. First, since decision quality was not the topic of con-
cern, there was no need for accuracy measurements. There-
fore, subjects were asked to perform the task for themselves
and not for a principal (as in experiment 2). Second, the
memory and knowledge tasks were introduced at the end
of the experiment.
Results
Based on the memory board procedure (see Fig. 4), two
types of memory measures were created. The ?rst related
to the accuracy of placing the values in the matrix (memory-
accuracy), and the second related to the order in which
values were placed in the matrix (memory-structure). The
notion of the memory-accuracy measure is simple. The more
accurate subjects are in their memory for the different val-
ues, the higher will be the proportion of values that are
correctly placed in the matrix. The notion of the memory-
structure measure is substantially different, and it relates to
the structure and organization of information in memory.
This measure is based on the assumption that the order in
which the matrix is regenerated re?ects some aspects of the
organizational structure of the information in memory.
Therefore, analogous to information search measures (Payne
et al. 1993), the order in which the different values were
placed in the matrix was taken as an indicator for memory
structure and its cohesiveness.
For the memory-accuracy measure, each subject received
a score that re?ected the proportion of values placed exactly
in their correct location. These results showed that the sub-
jects in the High-InfoControl condition had more accurate
memory (M p 0.50) than the subjects in the Low-Info-
Control condition (M p0.24, t(19) p3.56, p ! .002). The
same result also appeared when the memory-accuracy mea-
sure was de?ned less rigidly. This was done by counting
responses that were either on the same row or the same
column as the right response as correct.
Demonstrating that the amount of memory was higher
for subjects in the High-InfoControl condition, the next
question has to do with the organization of memory. The
memory-structure measure was based on the proportion of
consecutive values (all adjacent pairs of values) that were
placed either on the same attribute or the same camera. This
memory-structure measure showed that subjects in the High-
InfoControl condition had a more organized memory struc-
ture (M p 0.73) than the subjects in the Low-InfoControl
condition (Mp0.56, t(19) p2.172, p p.042). In addition,
one can calculate this measure separately for consecutive
placements on the same attribute and for consecutive place-
ments on the same product. Doing the analysis in this way
revealed that the advantage subjects in the High-InfoControl
condition have was a result of their consecutive placement
on the same product (t(19) p 2.74, p p .012), but not on
the same attribute (t(19) p 0.9, p p .93).
After establishing that subjects in the High-InfoControl
condition had better memory-accuracy and memory-struc-
ture, the next question addresses their knowledge regarding
the relationship between the different attributes (correlation
knowledge). In the knowledge task, subjects received the
level of a lens on a new camera and were asked to predict
its values on the other three attributes (body, shutter, and
engine). The knowledge measure was composed of the mean
absolute differences between the real value of the different
attributes and the estimates subjects gave for them. Exam-
ining this measure showed that subjects in the High-
InfoControl condition had better knowledge (M p 24.18)
than subjects in the Low-InfoControl condition (Mp29.76,
t(19) p 4.137, p ! .001). The same result emerged when
examining each of the attributes separately.
In addition, this experiment included the same subjective
measures of performance as experiment 4. The con?dence
measure showed the same basic pattern, where subjects in
the High-InfoControl condition had more con?dence in their
ratings (M p 79.9) than subjects in the Low-InfoControl
condition (Mp66.7, F(1, 34) p3.28, p ! .002). The liking
CONTROLLING THE INFORMATION FLOW 245
measure showed that subjects in the High-InfoControl con-
dition liked the interface more (M p74.3) than subjects in
the Low-InfoControl condition (M p 43.9, t(19) p 5.55,
p ! .001). Note that these results replicate and extend the
conclusions drawn from experiment 4 to tasks in which
subjects expressed their own preferences.
Discussion
The goal of experiment 5 was to start examining long-
term implications of information control. Speci?cally, it was
suggested that incidental memory and knowledge would
capture some of the long-term bene?ts of an information
system. The results showed that subjects in the High-
InfoControl condition had both better memory and knowl-
edge of their environment. The memory-accuracy measures
indicated that subjects in the High-InfoControl condition had
a more accurate memory for the information itself, while
the memory-structure measure showed that they also had a
better and more consolidated organization of information in
memory. Aside from the memory-related measures, the cor-
relation knowledge task examined what subjects internalized
about the relationship between the values of the different
attributes. The results for the knowledge measure also
showed that subjects in the High-InfoControl condition had
a higher level of knowledge for the relationship between
the values of the different attributes. Finally, experiment 5
also included two subjective measures of performance level
(similar to experiment 4). Both the con?dence and the in-
terface liking measure showed that subjects had a better
perception of the information system under the higher level
of InfoControl. Although the measures of con?dence, liking,
memory, and knowledge seem to suggest that information
control has long-term implications and bene?ts, this inter-
pretation should be taken with some caution. Speci?cally,
the limitation in interpreting these results is that the mea-
sures for these constructs were taken after the experience
took place. Therefore, with these results in mind we still do
not know whether, initially, consumers would be attracted
to or would shy away from highly interactive information
systems.
GENERAL DISCUSSIONS AND
MANAGERIAL IMPLICATIONS
The current work illustrates that the environment in which
consumers encounter information has a substantial impact
on the way this information is evaluated and integrated.
Speci?cally, interactive communication that gives consum-
ers control over the content, order, and duration of product-
relevant information causes information to have higher value
and to become increasingly usable over time. The experi-
ments presented here demonstrate that control over the in-
formation ?ow has a substantial impact on consumers’ abil-
ity to integrate, remember, and understand inputs to their
judgments. Although the current work was carried out in
the context of electronic communications, the applicability
of the current results reaches beyond computerized inter-
faces. The same conceptual principles should extend to the
analysis of any communication medium conveying infor-
mation to be integrated over time (salespeople, television,
and print advertising, for instance, could be compared in
similar terms).
The overall results of the experiments presented here are
both straightforward and promising for interface and com-
munication design. First, the subjective reports showed that
subjects in the High-InfoControl conditions both liked the
interface more and had more con?dence in their judgments
compared with subjects in the Low-InfoControl conditions.
Apart from these subjective measures, it was also shown
that highly interactive information systems can help con-
sumers integrate information and express utilities more con-
sistently and accurately. If we consider the task of expressing
a principal’s utilities as analogous to expressing one’s own
utilities (taking into account the parallelism of results shown
in experiments 1 and 2), then the conclusion is that a highly
interactive system can allow for a better match between
judgments and underlying utilities. In addition, it was shown
that the value of information control does not simply stem
from the ability to narrow-cast content that is more related
to a shopper’s interests. Rather, this advantage stems from
the dynamic ?exibility of the information system and its
ability to change during the information search and the hy-
potheses formulation process.
In conclusion, one could claim that marketing commu-
nication has gone through waves of interactive communi-
cations. Initially, marketing was interactive, with the ma-
jority of marketing communication being carried out by
salespeople and at the local general store. Subsequently,
mass communication became more prevalent, and for the
most part interactivity left marketing communications. With
new developments in computers and computerized net-
works, marketers have the potential to integrate interactive
communication systems back into mass communication
(Deighton 1996). This is potentially wonderful news, be-
cause marketers can provide consumers with the advantages
of information control without burdening the information
provider with tremendous costs. However, it is also impor-
tant to note that information control is not a panacea, and
some caution should be taken when utilizing it. In particular,
when the cognitive load is high (when the task is novel or
dif?cult), High-InfoControl can be harmful. Therefore,
when designing a communication system and considering
the appropriate level of information control, marketers
should pay attention to the processing demands of the in-
formation system (Carroll 1997; Simon 1969), the experi-
ence of the consumer with the same and similar systems,
and the learning process over time.
FUTURE DIRECTIONS
1. Preference for Controlling the Information
Flow
All the experiments presented here forced subjects to use
computerized interfaces for some time and measured the
246 JOURNAL OF CONSUMER RESEARCH
outcomes of this experience. In the real world, consumers
are not randomly assigned to conditions, and it is question-
able whether they will demand more interactive interfaces
in situations where the current research shows they are ben-
e?cial. In other words, for many marketing applications the
important question is not whether a certain interface causes
higher performance if used but, rather, whether it is used at
all. Therefore in order to understand the role of information
control in marketing applications, one needs to study pref-
erences and not just performance.
2. Motivation and Information Control
Aside from resulting in differences in the ability to pro-
cess and integrate the same information, there is the question
of whether information control would increase consumers’
motivation to search for and understand information. We
know that consumers tend to dedicate more time to activities
that are more pleasurable. Therefore, much as consumers
who enjoy shopping spend more time at it than those who
do not, one can ask whether a highly interactive information
system would increase total time spent in computerized en-
vironments. Some evidence in this direction has come from
work on optimal stopping rules (Saad and Russo 1996),
which demonstrated that under conditions that allow more
free search (High-InfoControl), people examine more in-
formation before they reach a point at which they feel they
have suf?cient information to make a decision. In addition,
the ability to command a situation, that is, having control
over its different aspects, has been shown to increase the
pleasure of the event itself (Averill 1973; Gatchel and Proc-
tor 1976; Shapiro, Schwartz, and Astin 1996; see also Son-
oda 1990; Wine?eld and Fay 1982). Understanding such
motivational factors is extremely important, because in the
long run it will determine consumers’ ability to fully utilize
interactive and electronic communication channels.
3. Interactivity
Finally, the current work has concentrated on one aspect
of interactive communications, namely, controlling of the
information ?ow. Although this type of control can be con-
sidered one central aspect of interactive communication, it
is also obvious that a broad understanding of interactive
communications will reach far beyond this relatively narrow
de?nition. Other more general and broad de?nitions of in-
teractive communications could examine characteristics of
the information system itself, as well as the dialog between
information systems and their users.
[Received May 1998. Revised December 1999. Robert E.
Burnkrant served as editor, and Eric J. Johnson served
as associate editor for this article.]
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