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The Skeptical Shopper:
How Default Options Affect Choice By What They Tell Consumers
CHRISTINA L. BROWN
ARADHNA KRISHNA*
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*Christina L. Brown is Assistant Professor of Marketing and Aradhna Krishna isProfessor of Marketing at the University of Michigan. The authors would like to thankFred Feinberg, Carl Mela, Joe Urbany, Carolyn Yoon; members of the marketingdepartment at the University of Michigan and the Fuqua School of Business; and
members of the University of Michigan Decision Consortium for comments on thismanuscript. We would also like to thank Mary Wagner for her help in coding Study 2.Correspondence should be directed to the first author (clbrown@umich.edu).
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Abstract
A “default” option is the choice alternative a consumer receives if he/she does notexplicitly specify otherwise. In this article we argue that consumers may treat default
designations as though they contain relevant information about the value of the product;i.e., when our preferences are uncertain, we look to defaults to tell us something aboutthem. More specifically, defaults can invoke a consumer’s “marketplace metacognition”(Wright 2002), his/her social intelligence about marketplace behavior (for example whyand how marketers attempt to manipulate the behavior of consumers). We demonstratethat how the consumer responds to the default depends on whether this social intelligenceis invoked and how it changes the meaning of the default . This “metacognitive” accountof defaults leads to different predictions than accounts based on cognitive limitations orendowment: in particular, it predicts that on some occasions low (less expensive) defaultswill have a greater positive impact on choice than high (more expensive) defaults.Moreover, it predicts the possibility of negative or “backfire” default effects. We report
the results of three experiments that show that how the consumer responds to the defaultwill depend on 1) the ordinal position of the default, 2) whether or not a consumer’smarketplace metacognition is readily accessible, and 3) whether or not a consumer ismotivated and able to use marketplace metacognition to interpret the meaning of thedefault.
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You are purchasing a computer system on-line. There are several options
for monitors: 15”, 17”, or 19”. The standard system comes with 15” (theleast expensive option), but if you want, you can switch to the 17” or 19”
monitor (for more money).
You are purchasing a computer system on-line. There are several options
for monitors: 15”, 17”, or 19”. The standard system comes with 19” (themost expensive option), but if you want, you can save money by switching
to the 17” or 15” monitor.
What is the marketer up to? Why do you think the marketer did what he
did? Does your answer affect which computer you buy?
Almost every consumer has encountered “defaults” when choosing among
alternatives: the “default” option is the one the consumer will automatically receive if
he/she does not explicitly specify otherwise. Although default options are not restricted to
the Internet, the operational advantages of the Internet have made them more pervasive
over the past few years. For example, on the Dell Computer website, computer systems
come in a pre-packaged combination of RAM memory, hard drive size, disk-drive
options, monitor, software, etc. However, if the consumer prefers a bigger hard drive, or a
small monitor, she may adapt the package to her preferences by selecting her preferred
attribute option from a menu. More notoriously, almost every reader of this article will
have encountered the “opt-out” e-mail list, in which the consumer condemns herself to a
lifetime of promotional emails unless she takes the time to “deselect” the “send me
emails” box.
Most existing research on the effects of default options concludes that default
options affect choice by taking advantage of consumers’ cognitive and processing
limitations. For example, Johnson, Lohse, and Bellman (2002) have shown that
consumers who are obliged to “opt out” of an e-mail list are as much as twice as likely to
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participate in the list than consumers who can explicitly choose between receiving and
not receiving the emails, as though they had not noticed the difference. Similarly, Park,
Jun, and MacInnis (2000) find that consumers presented with a “fully-loaded” car and
given the opportunity to remove optional features for a cost savings end up with a more
expensive set of features than those presented with a basic model and given the
opportunity to add features for more money. Park et al.’s explanation is related to
endowment effects or loss aversion (Kahneman, Knetsch and Thaler 1991): they suggest
that people presented with a default alternative shift their reference point to include the
features of the default product, framing the forgoing of these features are a loss. In both
cases, the implication is that defaults affect choice because consumers are unintentionally
manipulated by the marketer’s choice of default. In other words, defaults cause consumer
choices to deviate from their true preferences.
In this article we argue that consumers may also treat default designations as
though they contain relevant information about the value of the product (Prelec,
Wernerfelt, and Zettelmeyer 1997; Wernerfelt 1995); i.e., when our preferences are
uncertain, we look to defaults to tell us something about them. In particular, in some
important circumstances a consumer might conclude that the default option is the one the
marketer prefers to sell. In other words, the default is a marketing tactic that is
interpreted by a consumer’s “marketplace metacognition” (Wright 2002), his/her social
intelligence about marketplace behavior (for example why and how marketers attempt to
manipulate the behavior of consumers). We demonstrate that how the consumer responds
to the default depends on whether this social intelligence is invoked and what it means to
the consumer once invoked. Specifically, we show that how the consumer responds to the
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default will depend on 1) the ordinal position of the default (i.e., whether or not a less-
expensive or more-expensive alternative is the designated default), 2) whether or not a
consumer’s marketplace metacognition is readily accessible, and 3) whether or not a
consumer is motivated and able to use marketplace metacognition to interpret the
meaning of the default.
Importantly, our view of “defaults as a source of marketplace information,”
filtered through a consumer’s prior knowledge of the marketplace, suggests different
empirical results than would default effects generated by inattentiveness on the
consumer’s part (Johnson et al. 2002) or by processing biases such as endowment,
anchoring-and-adjustment (Park et al. 2000), and focus-of-comparison effects (Dhar and
Simonson 1992). A story based on inattentiveness, anchoring, or focus-of-comparison
should apply equally to low (less expensive) and high (more expensive) defaults. A story
based on endowment suggests that a high default will have a greater effect on choice than
a low default.
Previous researchers are undoubtedly correct in their assessment that incomplete
or biased processing helps make consumers more likely to choose default items in many
circumstances. However, when defaults are information-based, we will show that low
(i.e., less expensive) defaults can sometimes have more positive effects than high (more
expensive) defaults, a result that cannot be obtained from existing theories . Even more
remarkably, information-based defaults may create negative or “backfire” effects: if a
consumer believes a marketer is suggesting a default that appears to be in the firm’s best
interests but not the consumer’s, consumers may be less likely to choose an alternative
when it is the default than when no default is indicated.
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In our story about default effects, then, the consumer is not inattentive but
skeptical and alert, reflecting that defaults can invoke the marketplace metacognition of
the consumer to help him/her better predict the value of each alternative (Friestad and
Wright 1994, Wright 2002). We present three studies to support our information-based
explanation for default effects. In Study 1, we confirm the generally positive effect of
default designations on choice among alternatives, and suggest circumstances in which
low (less expensive) defaults may have greater positive effects on choice than high (more
expensive) defaults. In Study 2, we show that the strength and direction of the default
effect depends on whether or not “marketplace metacognition” is clearly invoked, and
whether or not subjects see the marketer as acting for or against the self-interest of the
consumer. In Study 3, we show that information-based default effects depend on whether
the consumer is motivated and able to use his/her marketplace metacognition to interpret
that information.
THEORETICAL FRAMEWORK
What Is a Default and What Does It Do
We define a default as the alternative the consumer receives if s/he does not
explicitly request otherwise. Defaults are most prominent in cases where a product
consists of a standard configuration of features, which a consumer may add to, eliminate,
or change (as in our opening Internet example). However, defaults are not restricted to
the Internet; all consumer decisions—even innocuous ones or decision not to act—can be
said to involve some form of default: at McDonald’s they will put ketchup on your burger
unless you tell them not to; the personnel department will assume you do not want to
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make a contribution to the company pension fund unless you tell them otherwise
(Schweitzer 1994), etc.
We are interested in “default effects” – the change in likelihood that a particular
alternative is chosen when designated as the default versus a control condition when no
default is designated. It is possible, after all, that defaults exist but do not change the
likelihood of a particular alternative being selected. For example, a computer marketer
might identify one system configuration as the default because it is the one they expect to
be most popular—this default would make the choice easier, but without changing which
computer the consumer ends up with.
However, there is substantial evidence that defaults can change the likelihood that
a particular item is chosen (Johnson, Bellman, and Lohse 2002; Park, Jun, and MacInnis
2000). The supposed positive effect of defaults on choice has been of great public-policy
interest since it suggests that consumers can be made to unintentionally deviate from their
“true” preferences by the identification of a particular option as the default. The
explanations offered by existing research by and large support the characterization of
consumers as accommodating to the perceptual biases imposed by the default frame.
These existing explanations fall into two overall categories: attention-based default
effects and defaults due to biased processing. We will briefly discuss these to show how
they contrast to our own framework.
Attention-Based Default Effects. Consumers may use defaults heuristically, to
reduce the amount of cognitive effort required to reach a decision (Johnson et al. 2002).
In extreme cases the consumer receives the default option because s/he simply has not
noticed that a choice is being asked of him(her). Less extremely, the default diverts
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attention toward the designated alternative and away from thorough consideration of the
undesignated alternatives. This explanation is supported by Johnson et al’s finding
(Johnson et al. 2002, Study 1) that consumers are far more likely to choose the default
when faced with a checkbox that already contains a checkmark (that may be then
removed) than when faced with an empty checkbox (that may then be checked). We will
refer to default effects created by lack of thorough cognitive effort or inattentiveness on
the part of the consumer as “attention-based defaults.” Note that if defaults “work”
merely by drawing attention to the default option at the expense of careful consideration
of its alternatives, this would affect choice regardless of whether the default option is
comparatively inexpensive or expensive. Attention-based explanations for default,
therefore, do not provide a clear explanation for why the strength of the default might
vary according to its rank.
Default Effects Due to Biased Processing . Park et al. (2000) suggest that
consumers anchor on the default option and simply fail to adjust sufficiently away from
the anchor and toward their stable underlying preference. As evidence for this, they show
that subjects presented with a fully loaded car and allowed to eliminate unwanted options
ended up with a significantly more expensive car than subjects presented with a stripped-
down model and allowed to add options. The difference in price paid over the two
conditions is attributed to an anchoring-and-adjustment process (Chapman and Johnson
1999). A related mechanism for such anchoring might be a “focus-of-comparison” effect
(Dhar and Simonson 1992), in which a consumer processes more information and more
favorable information about the focal item than about the alternatives it is being
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compared to. In other words, identification of an alternative as the default encourages
consumers to treat it as the focus of comparison.
As Park et. al. (2000) suggest, this anchoring on defaults might also be attributed
to endowment or loss aversion (Johnson et al. 2002; Park et al. 2000; Schweitzer 1994;
Sen and Johnson 1997). In an endowment-based account, consumers imagine possessing
the default option, thereby reframing all lesser alternatives as losses (Kahneman,
Knetsch, and Thaler 1991; Sen and Johnson 1997). A key feature of the endowment
mechanism is that subjects are less willing to give up the features of their reference
option than they are willing to pay to add features to a lesser option (“willingness to
accept>willingness to pay”). Thus, endowment clearly predicts that high-end defaults
will be stronger positive effects on choice than low-end defaults (Park et al. 2000).
Information-Based Defaults
Our premise is that attention-based and processing-bias explanations omit an
important characteristic of defaults in the real-world marketplace: defaults may contain
information about the value of the choice alternative, which is interpreted in light of a
consumer’s market knowledge.
Wernerfelt and colleagues (Prelec, Wernerfelt, and Zettelmeyer 1997; Wernerfelt
1995) have shown, for example, that consumers can extract information about the
preferences of other consumers from the composition of the choice set. If a consumer is
uncertain about his decision, but knows something about his computer preferences
relative to the preferences of other consumers, this can affect his choice. Prelec et al.
(1997) give the example of museum-goers choosing from among rain ponchos of three
ordered sizes. Subjects choose either from a 32” 34” and 36” set, a 34-36-38” set, a 36-
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38-40” set, or a 38-40-42” set. Even if a subject had no idea how long a poncho typically
is, each presumably knew whether he/she was short, medium, or tall relative to the
general population. Thus, the rank or ordinal position of the choice alternative was more
predictive of choice than the absolute length of the poncho. The authors refer to this
phenomenon as “rank-order inference.”
In the real-world marketplace, the signal offered by the default designation may
represent not just the will of other consumers but also the will of the marketer. If the
consumer comes to believe that the default is what the marketer prefers to sell , it may
activate his/her social knowledge about marketplace tactics and how to respond to them
(his/her “marketplace metacognition,” Wright 2002).1 When marketplace metacognition
is invoked, the default means something new: it is an attempt to persuade that must be
considered more skeptically. Thus, the perceived cause of the default will have a
powerful impact on the value a consumer imputes to the designated alternative.
We propose that whether or not this marketplace metacognition (MM) is invoked
in a default context may depend on which item is identified as the default. Specifically,
the ordinal position of the default (its expense relative to its alternatives) may have an
impact: items that are the most or least expensive in the set of alternatives are more likely
to invoke MM and thus generate information-based effects. Consider our opening
example in which a consumer may choose among three different monitors
1 Borrowing from Wright (2002), we make a distinction here between “marketplace metacognition” and“persuasion knowledge.” Persuasion knowledge is defined as socially focused market intelligence such asnaïve theories and beliefs about marketers’ motives, strategies, and tactics (see also Moreau, Krishna andHarlam 2001); and the folk psychology of persuasion. “Marketplace metacognition” includes not only suchsocially focused metacognition but also self-focused market-related metacognition such as self-knowledgeand self-control, i.e., “knowledge about one’s own knowledge” (Alba and Hutchinson 2000). Our claim isthat both self- and socially-focused market intelligence will affect how one responds to market events suchas defaults.
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(small/inexpensive to large/expensive) in making a computer purchase on-line. The
marketer has three choices when it comes to identifying a default: the least expensive, the
middle option, or the most expensive. Previous research (Wegener and Petty 1995, 2001)
has suggested that extremeness affects evaluative inference (Stapel and Koomen 2000),
and that people are more likely to try to correct a bias if it is blatant rather than subtle
(Stapel, Martin, and Schwartz 1988). Thus we argue that if a marketer persistently
chooses one of the extreme options, this extreme behavior may be more likely to be
noticed, identified as a bias, and require an explanation. If the most expensive alternative
is the default, the consumer is likely to become skeptical of the marketer’s intentions. In
contrast, if the least expensive item is the default, the marketer may appear to be acting
counter to expectations and in the consumer’s self-interest rather than her own. She is
more likely to accept the low default but discount the information offered by the high
default. Thus, in cases with many options, low defaults will be more effective at changing
choice than high defaults:
Study 1 thus seeks a simple empirical confirmation of the impact of default
designations on choice. We expect to re-affirm the positive effect of default designation
on choice among multiple alternatives relative to these same alternatives without a
default designation. We also explore conditions under which “low” defaults might be
more positive drivers of choice than “high" defaults, to support our contention that
consumers treat defaults as though they contain information about value. We expect the
strength or power of the default to affect choice may depend on which alternative is
identified as the default , because identifying lowest or highest-priced options as the
default sends different information to the consumer.
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H1: Default designations will have a positive impact on the choice
of the designated alternative (relative to the same alternative
without such a designation).
H2: A default designation for the lowest-priced alternative will
have a more positive impact on its choice than a default on thehighest-priced alternative (relative to the same items without
such a designation).
STUDY 1
Design and Procedures
One hundred and seventy-eight undergraduates participated in study 1 for course
credit. Subjects completed a questionnaire described as a study of mass customization on
the Internet, involving the specification of six attributes from the websites of (fictional)
manufacturers in three product categories— the number of musical voices and styles for
music keyboards, the monitor size and hard drive size for computers, and meal options
and transportation options for vacation packages. (See Table 1 for a complete description
of the attribute levels.) These product attributes were chosen because they are typical of
those customizable via the Internet (see www.dell.com, and www.libertytravel.com for
examples), and because they were expected to be somewhat familiar to our subject base.
The specific attribute levels were chosen from a web search of these product categories.
Order of presentation of the categories was counterbalanced. Each product attribute
offered three different ordered levels (low, middle, high). For each of the six attributes,
subjects chose one of the three options – low, middle or high attribute level.
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Table 1 about here.
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Subjects were randomly assigned to one of four between-subjects experimental
conditions—no default, low option indicated as default, middle option as default, or high
option as default. Thus, the design of the study was mixed, with default type (none, low,
medium, high) as a between-subjects factor and the six product attributes a within-subject
factor. Subjects read a brief description of each of the product attributes, then were asked
to indicate their choice among the three alternatives for each of the six attributes.
Subjects in the control “no-default” condition were asked to indicate their preference by
circling the option of their choice.2 “Default” subjects saw either the low, middle or high
option indicated as the default for each of the six attributes. Their instructions reported
that “the manufacturer has indicated a “default” attribute—the value you will get unless
you indicate otherwise by circling a different option.”—but no other reason for this
default attribute was given. Relative prices were expressed as the difference in dollars
between each pair of options (i.e., a non-default option might be described as “30$ more”
or “30$ less” than the default option; see figure 1).
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Figure 1 about here.
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2 This control condition allows us to eliminate many competing explanations for the effects of default onchoice, by allowing us to compare choice of an item designated as the default to its exact peer without sucha default designation– the same product, with the same competitors, at the same difference in price, presented in the same order. Thus, our results cannot be explained by differences in basic preferences fortrading off increased quality and price, by effects of order of presentation, or by the core tendency ofsubjects to choose a compromise option.
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Results
We first performed a simple test of difference in proportions to determine whether
default had a significant effect on the choice probabilities of the three alternatives.3
Overall choice probabilities are given in table 2. A chi-square test confirms that default
affected choice probabilities (χ2(6) = 30.20, p ≤ .0001); in each case, choice likelihood
increased versus the control condition when the item in question was the default: 39.77%
versus 30.43% for the low option; 58.71% versus 49.28% for the middle option, and
25.76% versus 20.29% for the high option. Figure 2 illustrates these effects graphically.
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Table 2 and Figure 2 about here.
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We then performed a fixed-effects conditional logit analysis (McFadden 1974) to
determine whether this overall effect of default on choice was significant, and whether it
occurred regardless of whether the designated default is the low, middle, or high option in
an ordered choice set. (Results are reported in table 3.) The conditional logit model treats
each available alternative as a separate observation, thus including three observations for
each subject for each choice problem. The dependent variable of the model was whether
or not the particular alternative was selected by the subject.
The independent variables included two indicator variables representing the
ordinal position of the option (middle=0,1, high=1,0). These position variables indicate
3 For Studies 1, 2, and 3, we ran each of these models including interactions between the attributes and thecondition variables; none of these interactions were significant, suggesting that the manipulations hadessentially the same effect for the six attributes. We therefore present the results pooled over the sixattributes for each of the three studies.
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whether ordinal position affected choice probability. If, for example, the middle (high)
indicator is positive and significant it implies that people are more likely to choose the
middle (high) option compared to the low option (regardless of default condition). A
second set of indicator variables allowed us to test for default effects while controlling for
differences in underlying preferences for each of the three options (by comparing choice
of a particular alternative when designated as the default to the same alternative without
such a designation). In model 1, this ‘set” consisted of a single variable indicating
whether or not the alternative was designated as the default. In model 2, we include three
separate indicators for the three different default types (low, medium and high) to
determine if there were any significant differences in default effects based on the ordinal
position of the default option.
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Table 3 about here.
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Hypothesis 1: Overall Effects of Default (Table 3, Model 1). We first look at the
likelihood of choosing the low, middle and high options when none is specified as the
default . The indicator variable for the middle alternative is positive and significant ( z =
7.769, p ≤ .001; see table 3), whereas the indicator variable for the high alternative is
negative and significant ( z = -3.598, p ≤ .059), showing that subjects tend to prefer the
middle option over the low or high options (when no option is specified as the default).
This is consistent with a well-documented tendency for people with uncertain preferences
to favor compromise options (Simonson 1989). The effect of the default variable is
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significant and positive, confirming hypothesis 1: a default designation increases the
likelihood an alternative is chosen ( z = 4.968, p ≤ .000).
Hypothesis 2: Low versus High Default (Table 3, Model 2). In a second analysis
we replaced the single default variable with three default indicator variables (i.e., low,
medium, high). The base case is therefore the control (no default) condition. The low
default indicator, for example, shows the effect of the low default on choosing the low
option (vs. the control condition). There are significant positive default effects in the case
where the low item is the designated default ( z = 3.731, p ≤ .000; see figure 2 and table
3), and where the middle item is the default ( z = 2.083, p ≤ .037), but the default effect
for the high option does not reach significance ( z = 1.243, p ≤ .214). Thus, default effects
appeared to be slightly weaker for higher-cost alternatives. However, a test of a model
allowing low and high defaults to differ did not quite outperform a model restricting the
coefficients for low and high defaults (χ2(1) = 2.40, p ≤ .122). Thus, hypothesis 2
received only directional support.
DISCUSSION
Study 1 confirms a significant positive effect of a default designation on choice of
a particular alternative over and above the same alternative without such a designation.
Furthermore, study 1 suggests conditions exist under which a low (less expensive) default
might have a greater positive effect on choice than a high (more expensive) default. This
result could not be derived from an attention-based or focus-of-comparison mechanism,
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and is in conflict with an endowment mechanism.4 Our results are directionally consistent
with our specific claim that a high default may be discounted by the sense that it might be
the result of a marketer’s attempt to persuade. Although the overall positive effect of
default in study 1 was quite strong, study 1 suggests that ordinal position alone may not
invoke MM, or at least may not invoke it for all subjects. Furthermore, a “low>high”
effect would be at odds with previous research, specifically Park et al. 2000, which
showed high defaults that had a greater positive effect on choice than low defaults.
In study 2, we address the question of why high defaults may be quite positive in
some cases (e.g., Park et al. 2000) and weak or even negative in others. We focus on a
critical difference between the paradigm offered in our study 1 and that used by Park et
al. In Park et al. (2000) and related research such as Dhar and Simonson (1992), the
experimental context did not involve an attempt by a marketer to persuade the subject,
which plays a critical role in our explanatory framework. Our “information-based”
explanation for defaults suggests that it is precisely the perception that the marketer is
attempting to persuade the consumer that changes what the default “means” to him/her.
These researchers have shown that outside a persuasive context biased processing will
lead to positive effects of default in general and high default in particular. We argue that
when consumers feel that marketers are trying to bias their (consumers’) choices, they
4 Note that a similar result is given even if consumers are informed only about other consumers (and notabout marketers), if we also assume that individual preferences correlate with product experience. Consider
the heuristic “buy the least expensive item of acceptable or better quality.” Assume that most consumersare not quite certain about what “acceptable quality” might be. Following the reasoning given by Prelec atal. (1997), if a consumer considers his/her needs to be modest relative to other consumers’, s/he will purchase at or below the default. If he considers his needs to be average, he will purchase at the default.High end users, however, are likely to be more experienced and more certain about their preferences(Coupey, Irwin, and Payne 1998), and therefore relatively unaffected by defaults. This explanation impliesthe same aggregate result hypothesized in hypothesis 1: Low defaults will be more powerful than highdefaults, because low-end and medium users will respond to low default, only middle-of-the-road users will
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his/her own interests) recommends the less expensive item and skepticism, resulting in a
reduced or negative effect, when the marketer recommends the more expensive item.
H3: There will be an interaction between the effect of ordinalposition of the default and accessibility of marketplace
metacognition on consumer choice:
a) When a more expensive alternative is the default and
marketplace metacognition is not accessible, there will be a
significant positive “default effect:” i.e., subjects will be more
likely to choose the expensive item relative to its control.
b) When a more expensive alternative is the default and
marketplace metacognition is accessible, the “default effect”
will be weaker or even negative.
c) Marketplace metacognition will have no effect on the choice
likelihood of a low (less expensive) default.
The Role of Counterarguing in Creating Default Effects
Skepticism about the marketer’s intentions or abilities may not cause one’s
overall attitude toward the market to change, but simply change the reasons that are
brought to bear on the decision. Work by Wegener and Petty (the “Flexible Correction
Model;” 1995, 2001) has suggested that if subjects perceive a bias to be present in an
argument, they will be more likely to counterargue (to resist the bias) than if they do not
perceive such a bias. Thus, when subjects recognize a high default as a biased attempt to
persuade (biased by the marketer’s interest in greater sales), they are more likely to argue
against choosing the high item than when it is not the default. If MM is not accessible the
default may not be recognized as a persuasive attempt, thus counterarguments would be
less likely. In contrast, recommending a low default is less likely to be perceived as an
attempt to bias one’s behavior, so the accessibility of MM should not have an effect.
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MM-driven skepticism might instead lead consumers to choose the less-expensive
option because it involves less financial risk (i.e., if I must make a purchase from a
marketer whose intentions are questionable, the least expensive will get me into less
trouble). If MM operates in this fashion, there should be a main effect of the accessibility
of MM on choice of the high option. Alternatively, subjects might conclude that the
marketer is not really competent to provide advice; in this case there should be no real
effect of default designation at all.
Thus in study 2, we will also investigate the mechanisms through which MM
affects choice by asking subjects explicitly for the reasoning behind each of their choices.
Subjects who are discounting the information present in the default should demonstrate
this by giving counterarguments, i.e., reasons to reject the default item (Brown and
Carpenter 2000). Limiting the alternatives each subject sees to only two will also make it
easy to determine whether subjects are taking a supporting (arguing for the choice) or
counterarguing approach (arguing against the unchosen item). If MM is driving choice
effects by making subjects more skeptical in the presence of a perceived bias, then
counterarguing should mediate the effects of default on choice.
H4: When a more expensive item is the default, and subject’s
marketplace metacognition is made more accessible, the
subject will be more likely to report counterarguments
(reasons to reject the unchosen item) than when marketplace
metacognition is not explicitly made accessible. However, when
the less expensive item is the default, accessibility will have no
effect on the likelihood of counterarguments.
H5: The likelihood of counterarguments will mediate the effects of
default and accessibility of marketplace metacognition on
choice.
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STUDY 2
Manipulations
We reasoned that giving subjects more information about the status of the
marketer’s business would make subjects’ marketplace metacognition more accessible.
By reminding them of the marketer as a business with its own goals and motives
(Campbell and Kirmani 2000), we expected to enhance subjects’ motivation to “hold
valid agent attitudes” and concern about manipulation (Friestad and Wright 1994, p. 9).
With this in mind, we created a simple description of “Allbuy.com,” an Internet retailer.
Subjects in the “limited information” condition saw a single paragraph:
Allbuy.com is an Internet-based retailer of a wide variety of products— from electronic goods such as computers and keyboards to consumer
services such as vacation packages. They do not make the products
themselves but offer a wide variety of products that are availableelsewhere. Allbuy allows the customer to choose among several models for
each product by specifying its attributes: for example, you can customizewhat type of monitor and how large a hard drive comes with the computer
you order, or how many meals come with your vacation package.
In the “enhanced information” condition, we added a second paragraph describing
the strengths and weaknesses of Allbuy.com as a business:
Allbuy has become known for its large and well-trained staff dedicated
to selecting a high-quality assortment for presentation on its website. Allbuy has given large discounts in the past but is currently
experiencing great cash-flow difficulties, and there is some chance it
will go out of business in the next few months if customers cannot beconvinced to spend more money very soon.
Note that if the additional information merely serves to lower subjects’ overall
opinions of Allbuy.com or make them seem less trustworthy, the effect of the information
on default would be to reduce the size of the default effects regardless of which item is
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identified as the default. Thus, the effect of the information would be to reduce the size of
default effects regardless of which item is identified as the default. In other words,
consumers should fully discount a low or a high default because the marketer is not a
credible source of information. Our hypotheses, however, suggest that marketplace
metacognition will reduce effects on choice for high defaults but that positive default
effects will persist for low defaults regardless of MM (hypothesis 3 above).
Ideally, therefore, the additional text in our “enhanced information” condition
should not result should in lowering overall opinions of Allbuy.com. It should include
both positive and negative features, so as to be as close to affectively neutral as possible.
In this way, subjects motivated to think well of the marketer can do so, but subjects
motivated to question the marketer’s intent may do that instead. A pre-test comparing the
limited and enhanced descriptions of Allbuy.com showed no significant differences in
attitude (good/bad; favorable/unfavorable; negative/positive) between the versions.
Design and Procedures
Ninety-six undergraduates participated in study 2 for an eight dollar cash
payment. Subjects in study 2 saw the same six problems as those in study 1 (hard drive
and monitor size for computers; number of musical styles and voices for electronic
keyboards, and meal and transportation options for vacation packages). To simplify
interpretation of results and to reduce the number of experimental cells, each subject saw
only two options per attribute – called “low” and “high.”6 Thus, the design of the study
was mixed, with default type (none, low, or high) and information (limited or enhanced)
as between-subjects factors and the six product attributes as a within-subjects factor.
6 The low and middle attribute levels from Study 1 were retained and the high attribute level was dropped.
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Subjects read the introductory paragraphs (containing the information manipulation) and
were told that their product choices would help us assess the likely mix of products
Allbuy.com would sell over the next few months. Then, subjects saw all six problems in
counterbalanced order.
To determine whether the likelihood of counterarguments might be affecting our
default results, subjects were asked to write a brief sentence explaining why they made
the choice they did after each of the six problems (each response was coded as primarily
supportive of the choice or counter to the unchosen item). Finally, subjects answered
several seven-point scale questions assessing overall attitude towards Allbuy
(good/favorable/positive), opinions of Allbuy’s product quality, price, stability,
knowledgeability, sincerity, trustworthiness, reliability, and whether or not the firm was
“trying to serve their own needs” rather than “trying to serve my needs”.
Results
Hypothesis 3: Choice Results. Table 4 shows the choice results for each cell. A
chi-square test confirms that the overall likelihood of choosing the high or low option
differed by experimental cell (χ2(5) = 11.72, p ≤ .02). Over the entire dataset, 51.0%
chose the low option and 49.0% chose the high option. Table 4 reports the cell means and
figure 3 illustrate the results graphically.
---------------------------------------------
Figure 3 and Table 4 about here.
---------------------------------------------
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We used a logit model with robust standard errors to determine the effects of the
manipulation on choice (see table 5). Since there were just two options to choose from,
the dependent variable was “choice of the high option”. Independent variables were
indicators for the low and high defaults, an indicator variable for the information
condition, and interactions of defaults and information. 50.5% of subjects chose the high
option in the limited information condition versus 47.5% in the enhanced information
condition ( z = 1.11, n.s.). Thus it appears that the information manipulation did not
encourage subjects to dislike Allbuy or see it as more risky, thereby inclining them
towards the less-expensive choice. The low default increased choice of the low option
(57.8%, vs 50.0% in the control condition; hypothesis 3c), while the high default
increased choice of the high option (55.0% vs. 50.0% in the control condition).
Consistent with our expectation that only high defaults would be interpreted
differently when MM was accessible, the high default* information interaction was
significant ( z = -2.22, p ≤ .026) but the low default* information interaction was not ( z = -
.12, n.s.). Thus, hypotheses 3a, 3b, and 3c are supported.
In the “enhanced information” condition (see figure 3), the high default had a
slightly negative effect on choice (47.9% vs. 54.4%, n.s.). The pattern was reversed in the
“limited information” condition: the high default increased choice of the high option
(62.1% vs. 45.8%, z = 1.643, p ≤.051). The low default had a slightly positive effect on
choice in the enhanced information condition (59.4% vs. 45.6%, z = 1.353, p ≤ = .09), but
it had little effect on the choice of the low option in the limited information condition
(56.2% vs. 54.2%, n.s.). This confirms hypothesis 3c and previous research (Park et al.
2000). Thus, we find that although expensive defaults may have a positive effect on
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choice in the limited-information condition, they can have a limited or even negative
effect in the enhanced information case.
Finally, we measured attitude as the mean of a subject’s response to the
good/favorable/positive scale questions. Mean attitude toward Allbuy was positive (2.447
on a 7-point zero-centered scale; significantly different from 0, t(93) = 6.233, p ≤ .0001).
An ANOVA showed no significant effect of either manipulation (information, default
type) or their interactions on good/favorable/positive scale questions; thus, any choice
effects may not be attributed to a generally more negative attitude toward the
manufacturer. Also, neither the default manipulation nor the information manipulation
significantly affected the perceived price, quality, or trustworthiness of the marketer, nor
did the manipulations affect the perception that the marketer was serving his own needs
rather than the customer’s.
---------------------------------------------
Table 5 about here.
---------------------------------------------
Hypothesis 4: Likelihood of Counterarguments. We now turn to the idea that MM
works by making counterarguments more likely in the high default case. Reasons for
choice provided by subjects were coded by two judges. Each judge coded the reasoning
as either a “support argument” or a “counterargument”. A “support argument” was a
positive reasoning strategy in favor of the chosen option (for example, “bigger is better”).
A “counterargument” was a negative reasoning strategy against the unchosen option (for
example, “I don’t really need a big hard drive.”). Inter-rater agreement after initial coding
was 90.81% (kappa = .8128, z = 19.26, p ≤ .001); conflicts were resolved by discussion.
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Across all conditions, 45.3% of subjects offered counterarguments in explanation
for their choice. A chi-square test confirmed that the percent of counterarguments
differed significantly by experimental cell (χ2(5) = 13.56, p ≤ .02). Subjects in the
enhanced information condition were not more likely to counterargue than subjects in the
limited information condition (45.3% vs. 45.3%), suggesting that the information
condition itself did not make subjects more skeptical. Furthermore, subjects exposed to a
default (either high or low) were slightly less likely than control subjects to counterargue
(39.3% vs. 46.3%, although this difference was not significant), suggesting also that the
mere presence of a default did not make subjects skeptical. However, as expected,
subjects in the high default/enhanced condition were more likely to report
counterarguments (46.8%) than were subjects in the high default/limited condition
(33.0%, z = 1.952, p ≤ .025). Information condition had no effect on counterarguing for
subjects exposed to a low default (51.6% vs. 48.4%, n.s.). This is consistent with
hypothesis 4, which proposed that making marketplace metacognition more accessible
would increase counterarguing against the more expensive option (as subjects attempt to
correct for perceived bias) but that MM would have no effect on counterarguments when
the less expensive option was the default.
Hypothesis 5: Mediating Effects of Counterarguing. Hypothesis 5 proposed the
likelihood of counterarguing would mediate the effects of default and information
conditions on choice. Table 5, model 1 shows the effects of information and default on
the likelihood of choosing the higher option. Table 5, model 2 shows the effects of these
same conditions on the likelihood of counterarguments, confirming that subjects in the
high default/enhanced condition were more likely than subjects in the high default/
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limited condition to counterargue ( z = 2.74, p ≤ .02). Finally, as shown in table 5 (model
3), when “counterargument” was added as a covariate to our original analysis, it had an
extremely powerful effect on choice ( z = 12.81, p ≤ .001), and the effects of default as
well as the default*information condition become statistically insignificant ( z = -.06,
n.s.). In other words, the change in likelihood of counterarguments fully mediated the
effects of default, information, and their interactions on choice, confirming hypothesis 5.
DISCUSSION
Study 2 confirms that subjects treated the default as though it contained legitimate
information about the marketplace. One way to understand the difference between study
1 and study 2 effects is that the mere presence of a default designation may not by itself
convey information about preferences to a consumer unless it is interpreted by his/her
marketplace metacognition. If one has no theory about why a marketer chose to designate
a particular item as the default, the designation can only affect behavior through
attention-based or biased-processing mechanisms described by previous researchers.
Making marketplace metacognition more accessible by reminding subjects of the
marketer’s business status changed the meaning of the default: instead of being an
unbiased recommendation, it was evaluated in the context of the consumer’s expectations
that businesses will act in their own financial self-interest by attempting to increase
sales.. MM had this effect not by because it made subjects pessimistic about the quality
of the marketer’s advice, or by changing overall attitudes toward the marketer, but
because it gave subjects a motivation to draw a particular conclusion and making
motivation-consistent reasons more accessible. When a firm in trouble offers a high
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default, it serves to make counterarguments (reasons against the default) more accessible.
In contrast, when a firm in trouble offers a low default, consumers do not view it
skeptically and do not attempt to counterargue its effects.
Explanations based on discounting of the marketer’s abilities or based on
differences in perceived financial risk imply a fairly involved cognitive process in which
subjects review the information provided by the default, draw a conclusion about the risk,
trustworthiness, or competency of the marketer, and correct their initial inclinations
according to this conclusion. Our explanation is much simpler and less cognitive
demanding of the consumer – skepticism in the presence of a high default merely changes
the relative accessibility of reasons for and against choice. It does not require the
consumer to draw a thoughtful or permanent conclusion about the marketer’s abilities and
intentions. Although she might do so, our theory does not require it and study 2 does not
show that she has.
In study 3, we provide additional evidence that marketplace metacognition is the
construct underlying information-based defaults. In particular, we propose that
individuals differ in the degree to which MM is well-formed and thus accessible
(Bearden, Rose, and Hardesty 2001). Secondly, we distinguish MM from category
expertise. Although the two are likely to be correlated, they will generate different default
effects. Consumers extremely high in category-level expertise are likely to have
developed well-defined preferences (Coupey, Irwin, and Payne 1998). Expert consumers
may in fact have plenty of marketplace metacognition but no motivation or need to access
it. They know what they want. In contrast, novice consumers have a motivation seek
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outside information in defaults, and to rely heavily on external sources of advice or
information.
However, extracting information from defaults requires some degree of naive
theory about the marketer's intentions. Thus, novice consumers who are also low in MM
will not be able to access theories to distinguish between the signal provided by low,
rather than high, default effects. Default effects for these novice/low-MM consumers will
resemble the high>low pattern created by positively biased processing and established by
Park et. al 2000. In contrast, novice consumers who are high in MM will become
skeptical only of high defaults, but not low, creating the low>high effect established in
study 2. In other words, in both studies 2 and 3 the accessibility of MM creates
information-based defaults; in study 2 this is done via experimental manipulation,
whereas in study 3 this is a measured individual-difference variable.
In short, information-based default effects require that consumers be both
motivated and able to access marketplace metacognition to interpret market signals.
Thus, expertise and MM should interact to create the effect. Thus, study 3 will show both
convergent and discriminate validity by showing individual-difference effects that are
inconsistent with expertise alone and require MM to explain them.
H6: Subjects with low levels of expertise will be more subject to default
effects than subjects with high levels of expertise.
H7: Subjects with low levels of expertise and low levels of marketplace
metacognition will be more positively affected by more expensive default
than less expensive defaults, relative to their controls.
H8: Subjects with low levels of expertise and high levels of marketplace
metacognition will be more positively affected by less expensive defaults
than more expensive defaults, relative to their controls.
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Results
Sixty undergraduate subjects participated in study 3 for a $6 cash payment.
Marketplace metacognition scores were calculated by summing across all 31 self-
confidence measures for each subject. Subjects were then divided into low/high MM
groups via a median split based on their mean response to the scales (with negative items
reverse-scored). Subjects were also divided into novices/experts via a median split on the
expertise scales. A chi-square test confirms that there were significant differences in
choice probabilities based on experimental conditions (χ2(11) = 18.56, p≤ .069). A logit
analysis with robust standard errors used “chose high” as the dependent variable, and
indicator variables for low default, high default, novice status, and low/high MM status,
and their interactions. Table 6 shows the choice probabilities for all subjects broken out
by novice/expert status and by low/high MM. Figure 4 shows the results graphically.
---------------------------------------------
Table 6 and Figure 4 about here.
---------------------------------------------
Hypothesis 6: Novices versus Experts. There was a negative main effect of novice
status on choice of the high option (i.e., experts prefer expensive products; z = -2.15, p ≤
.016): Novices in both the low-default condition (53.5% vs. 49.0%) and the high-default
condition (54.7% vs. 51.0%) showed an increased likelihood of choosing the default
relative to its control. In contrast, experts showed slight decreases in the likelihood of
choosing the default, although these decreases were not by themselves significant (35.6%
vs. 37.6% control for the low default condition, and 60.2% vs. 62.5% control for the high
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default condition). Taken together, these results show a significantly higher default
effects for novices than for experts ( z = 3.998, p ≤ .001). Thus, hypothesis 6 is supported.
Hypotheses 7 and 8: Low versus High-MM Novices. H7 and H8 together proposed
that low-MM novices would not become skeptical, but that high-MM novices would.
Thus default effects for low-MM novices should be positive, particularly for high
defaults, consistent with the low-information cells for study 2 and with Park et al. 2000
(hypothesis 7); in contrast, default effects for high-MM novices should be positive for
low defaults and weak or negative for high defaults, consistent with the enhanced-
information cells for study 2 (hypothesis 8). The logit analysis showed a significant three-
way interaction between high default, high MM, and novice status consistent with these
hypotheses, such that low-MM novices responded positively to high defaults but high-
MM novices responded negatively ( z = -2.38, p ≤ .01). Similarly, there was a modest
three-way interaction between low default, high MM, and novice status, such that low-
MM novices did not respond to low default but high-MM novices responded positively ( z
= -1.39, p≤ .082).
Table 6 and Figure 4 illustrate these differences clearly. Low-MM novices were
significantly more likely to choose the high default versus its control (55.9% vs. 40.0%).
They were slightly more likely to choose the low default versus its control (61.9% vs.
60.9%), although this difference was not by itself significant. Thus, hypothesis 7 was
supported. In contrast, high-MM novices were somewhat less likely to choose the high
default versus its control (52.8% vs. 62.5%), and somewhat more likely to choose the low
default versus its control (45.5% vs. 37.5%). Thus, hypothesis 8 was confirmed.7
7 Figure 4 also illustrates an interesting if unanticipated effect: High-MM experts (who are confident thatthey want the high option specifically) reacted negatively to low defaults: 31.0% of high-MM experts
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GENERAL DISCUSSION
We have presented a series of three experiments supporting our explanation that
under some circumstances consumers treat defaults as though they contained information
about the relative value of the alternatives (Prelec et al. 1997). More specifically, they are
consistent with our claim the consumer treats defaults as though they tell her something
about the intentions of marketers themselves. To interpret this information, the consumer
calls on her social intelligence of the marketplace, her “marketplace metacognition”
(Wright 2002). Thus, conditions that make marketplace metacognition more accessible
also serve to moderate default effects.
However, these effects of default are not uniformly positive. Selecting a high
(more expensive) item as the default may even have a negative (backfire) effect. These
results are not explainable by mechanisms proposed in previous research: attention-based
mechanisms make no prediction about the strength of default based on relative expense,
and loss aversion or endowment-based explanations predict the opposite result (that high
defaults will be stronger than low defaults). We do not mean to suggest that these
mechanisms are not operative, but argue that they cannot fully explain our data. Thus, our
results add to the explanations provided for default effects in the literature.
When defaults are information-based, the meaning of the default to the consumer
changes based on what metacognitions are invoked (Loewenstein 2002). In Study 1, we
suggested that manipulating the “extremeness” (ordinal position) of the default may make
choose the low item when it was the default, versus 39.9% when it was not. This suggests perhaps that thecontent of the MM of experts differs from that of novices, for example it may include the notion thatmanufacturers endorsing inexpensive goods are trying to pawn off low-quality items. We will discussdifferences in the content of MM in the concluding discussion of this paper.
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consumers more skeptical of high defaults and more accepting of low defaults. However,
Study 1 results implied that information-based defaults would not be particularly
powerful unless the potential information contained in the default were interpreted ; i.e.,
unless the consumer brought to bear a theory or theories about why a marketer might
make a particular item the default. In other words, a default is not informative unless the
consumer has an idea what it means.
In study 2, we confirm this idea that the ordinal position of the default and a
consumer’s marketplace metacognition interact to create information-based default
effects. In doing so, we also shed some light on why previous researchers have found a
positive effect of expensive defaults (Park et al. 2000), whereas we have found negative
effects in some cases. Moreover, study 2 provided some support for the cognitive process
underlying MM effects: Rather than directly making consumers more pessimistic about
the marketer’s abilities, the accessibility of MM appears to have changed subjects’
motivation to draw a particular conclusion, making motivation-compatible reasoning
more accessible (Brown and Carpenter 2000; Kunda 1991; Wegener and Petty 1995).
Thus, counterarguments (arguments against accepting the default) were highly accessible
in the high default case (when the marketer presumably was acting in its own self-interest
and against the consumer’s). In contrast, the same accessibility made support arguments
highly accessible in the low default case (when the consumer was more favorably
inclined toward the marketer because it appeared to be acting against its own self-interest
and for the consumer’s). The reasons—specifically the counterarguments--made
available via marketplace metacognition fully mediated the effects of the accessibility
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manipulation on choice, providing strong evidence for our proposed theoretical
mechanism.
In study 3, we showed additional support for information-based or
“metacognitive” defaults in the form of convergent and discriminant validity. We saw
that the accessibility of marketplace metacognition varies across individuals, resulting in
default effects similar to those generated by direct manipulation in study 2. Furthermore,
we saw that the effects of MM on default effects are empirically distinct from the effects
of category expertise. Novices in study 3 with high levels of marketplace metacognition
were able to discriminate between what a low default and what a high default might mean
to them. Low-MM novices, however lacked the knowledge base to allow them to
discriminate between low and high defaults, while expert subjects lacked the motivation
to determine a marketer’s intent (presumably because these experts already knew what
they want). This complex relationship supports the importance of MM rather than
expertise alone as a key moderator of default effects.
A practical extension of this work would be to other forms by which a default
may be designated: i.e., via drop-down menus, via pre-configured bundles of attributes
that might then be customized, or via order of presentation. Although our research
spanned three diverse consumer categories (computers, electronic keyboards, and
vacation packages), default effects in other categories may of course differ. We would
expect, based on our theory, that product categories regarding which most consumers are
highly confident and familiar to be relatively immune to information-based defaults. Our
product categories involved fairly expensive purchases; product categories with
extremely low levels of involvement might be less likely to generate backfire effects
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driven by skepticism. Both these boundary conditions suggest that cognitive capacity
and/or cognitive load may have a powerful effect on defaults. Moreover, marketplace
metacognition seems not only content-specific but culturally specific: cultures that have
different knowledge and expectations about the marketplace should respond differently to
defaults. These would be fruitful grounds for future research.
From a managerial perspective, our results suggest that some care should be taken
in the selection of defaults. To the extent that defaults are also driven by attention-based
mechanisms, manufacturers may continue to see defaults have a positive effect on choice
as is typically the case for post-purchase or post-registration opt-out mailing lists
(Johnson et al. 2002). However, firms that consistently propose the most expensive
product as the default may lose their credibility and be subject to a “backfire” effect.
AN OPTIMISTIC VIEW:
FUTURE DIRECTIONS FOR THE STUDY OF METACOGNITION AND PRIOR
KNOWLEDGE IN DECISION MAKING
Defaults are pervasive in modern consumer life; they are not limited to the
Internet but have merely been made more relevant by its arrival. To our minds, however,
the primary significance of default effects is not that they reflect a new technology, but
that they are carriers of meaning – they transmit information about the marketplace to the
consumer. They are one of a broad array of marketer-generated techniques that may
change in value to the consumer based on how he/she interprets them.
Factors Affecting the Use of Marketplace Metacognition. Our studies use a text-
based description of the marketer and the presence or absence of a default designation to
provoke information-based effects. But marketplace metacognition could be primed in
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many other ways, just as many other features of a shopping environment may invoke
skepticism. Will a high number of alternatives suggest the marketer is indifferent among
them and make consumer neglectful of the marketer’s default recommendations? Does
the presentation of unordered categorical alternatives (rather than the ordinal alternatives
presented in our studies) ever invoke skepticism? These and similar questions would be
worth exploring in future research
The Content of Marketplace Metacognition. Our “low>high” effect rests on one
very simple assumption about the content of marketplace metacognition: a shared notion
that marketers prefer to sell more expensive rather than less expensive products. This
notion does not require complex market knowledge—for example it is not necessary for
consumers to ‘know’ that expensive products are also high-margin products, although
they may in fact believe this. It is only necessary for marketers to appear to act in a self-
interested way (according to whatever naïve theories the consumer might have), thus
generating skepticism and greater access to counterarguments. Consumers with different
theories about where marketer’s self-interests lie may well generate different effects than
we propose here; in fact, study 3 offers a tempting hint of such behavior: High-MM
experts were actually less likely to choose the low default than its control. Although this
effect was unexpected, it is quite consistent with our theoretical explanation if we
concede that experts (in contrast to novices) might believe that marketers like to pass off
low-quality goods to the undiscriminating. The content of marketplace metacognition and
its heterogeneity across different classes of consumers would be fertile area for future
research.
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The Social Benefit of Information-Based Effects. Information-based effects need
not necessarily be negative. For example, if a consumer has specific beliefs about a
particular category, invoking this prior knowledge could have a positive impact on the
consumer’s reasoning process. If a computer firm is known as an expert systems
integrator, or if an apparel firm is known as an arbiter of taste, firm-specific information
effects are likely to be positive, particularly for expert consumers who are aware of the
risks of mismatched computer hardware or the risks of wearing last year’s styles.
In the face of an overwhelming flood of evidence that consumers’ preferences are
perennially uncertain and must be constructed from the bits and pieces of information
floating around the brain, it seems critically important to appreciate how the consumer
herself or himself construes the situation the marketer has put him/her in. What is Firm X
up to? Why did they make the decision to do it that way? How should I as a consumer
respond to it? The default effects we have documented here are only one result of
consumers’ constant search for informative cues about their own preferences. Our studies
take a “dynamic” perspective on the study of consumer decision-making: one in which
the outcome is mutually determined by the marketer’s design and the consumer’s
interpretation of it. There has been a surge of recent interest in the research community in
such dynamic perspectives (Briley, Morris, and Simonson 2000; Campbell and Kirmani
2000; Friestad and Wright 1994; Iyengar and Lepper 1999, among others). Optimistically
this perspective no longer excludes the consumer’s viewpoint on marketing problems
(Bazerman 2001; Loewenstein 2001) for the eminently practical reason that we cannot
correct predict consumer behavior without it.
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To our minds, information-based effects of marketplace metacognition are a
positive sign of consumers’ ability to cope with persuasive attempts rather than a sign
that they are subject to normatively inappropriate framing effects. Furthermore, our
results suggest that consumers do eventually become less vulnerable to defaults: high-
MM consumers clearly discriminated between types of defaults even when their expertise
in the category was low. Consumers’ knowledge of the marketplace may serve them well,
after all.
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REFERENCES
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TABLE 1
STUDY 1: ATTRIBUTE LEVELS
Attribute Low Middle High
Number of Musical Voices (Keyboard) 16 32 64
Number of Musical Styles (Keyboard) 10 20 40
Monitor Size (Computer) 17” 19” 21”
Hard Drive Capacity (Computer) 10.0 GB 13.6 GB 16.8 GB
Meals Included (Vacation Package) None Breakfast Breakfastand dinner
Transportation Included (Vacation Package) None Car Car anddriver
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TABLE 2
STUDY 1: CHOICE PROBABILITIESa
Default
Percent Choosing: Control(no default)
Low Middle High
Low Option 30.43% 39.77% 21.59% 23.48%
Middle Option 49.28% 41.67% 58.71% 50.76%
High Option 20.29% 18.56% 19.70% 25.76%
aThe shaded cells suggest an effect of default designation on choice of the default option: subjects were
most likely to choose a particular option when it was the default, compared to the control column to theleft.
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TABLE 3
STUDY 1: RESULTS
(Conditional fixed-effects logistic regression)
Model 1 Model 2Independent Variable Coef.
(Std. Err.) Z Coef.
(Std. Err.) Z
Middle Option .5600(.0721)
7.769 *** .6328(.0960)
6.589 ***
High Option -.3172(.0881)
-3.598 *** -.2120(.1122)
-1.890 ***
Default (any) .3731(.0751)
4.968 *** --- ---
Low Default --- --- .5752(.1542)
3.731 ***
Middle Default --- --- .3120(.1498) 2.083 **
High Default --- --- .2122(.1707)
.1243
Log likelihood -1091.15 -1089.89 a
* significant at p ≤ .05, ** significant at p ≤ .01, *** significant at p ≤ .001
a
We also tested this model against a model restricting the low and high defaultcoefficients to be equal (LL = -1091.43).
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TABLE 4
STUDY 2: CHOICE PROBABILITIESa
Default Condition
InformationCondition
Choice Control (NoDefault)
LowDefault
HighDefault
Total
Limited Low Option 54.2% 56.2% 37.8% 49.5%
High Option 45.8% 43.8% 62.1% 50.5%
Enhanced Low Option 45.6% 59.4% 52.1% 52.5%
High Option 54.4% 40.6% 47.9% 47.5%
Total Low Option 50.0% 57.8% 45.0% 51.0%
High Option 50.0% 42.2% 55.0% 49.0%
aTo see the effects of default designation, compare the choice of an option when it is the
default to its control in the left-hand column. For example, in the 2 nd row illustrating thelimited information condition, we can see that 62.1% of subjects in the high defaultcondition chose the high option, whereas only 45.8% of subjects in the control conditiondid so.
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TABLE 5
STUDY 2: RESULTS
Model
% Choosing HighOption)
Model 2
(%Counterarguing)
Model 3
(% Choosing HighOption)
IndependentVariable
Coef.(Std. Err.)
Z Coef.(Std. Err.)
Z Coef.(Std. Err.)
Z
--- --- --- --- ---
Low Default -.0842(.3130)
-0.27 -.2630(.3722)
-0.71 -.4661(.5172)
-0.90
High Default .6611(.3227)
2.05 * -.9076(.3854)
-2.36 * -.0337(.5577)
-0.06
Information .3453(.3100)
1.11 -.7273(.3728)
-1.91 * -.3388(.5367)
-0.63
Low Default*Info -.4735(.3834) -.12 .8550(.4681) 1.83 * .1787(.6441) 0.28
High Default*Info -.9227(.4156)
-2.22 * 1.309(.4770)
2.74 *** -.0507(.7256
-0.07
Counterarguments --- --- --- --- 4.069(.3178)
12.81 ***
Constant -.1671(.2566)
-0.65 1.984 0.70 -2.1467(.4632)
-4.63 ***
Wald χ2 (df) 16.62 (5) 10.74 (5) 179.62 (6)
* Significant at p ≤ .05, ** significant at p ≤ .01, *** significant at p ≤ .001
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TABLE 6
STUDY 3 – CHOICE PROBABILITIESa
Default Condition(Enhanced Information)
Expertise MarketplaceMetacognition
Choice Control(No Default)
LowDefault
HighDefault
Tota
Novice Low MM Low Option 60.0 61.9 44.1 54.3
High Option 40.0 38.1 55.9 45.7
High MM Low Option 37.5 45.5 47.2 43.0
High Option 62.5 54.5 52.8 57.0
Total Novice Low Option 49.0 53.5 45.3 49.1
High Option 51.0 46.5 54.7 50.9
Expert Low MM Low Option 36.2 40.0 41.7 39.2
High Option 63.8 60.0 58.3 60.8
High MM Low Option 39.9 31.0 38.3 36.0
High Option 61.1 69.0 61.7 64.0
Total Expert Low Option 37.5 35.6 39.8 37.6
High Option 62.5 64.4 60.2 62.4
Total Low Option 42.9 43.3 42.4 42.9
High Option 57.1 56.7 57.6 57.1
aTo see the effects of default designation, compare the choice of an option when it is thedefault to its control in the left-hand column. For example, in the 1 st row, we can see that55.9% of low-MM novices in the high default condition chose the high option, whereasonly 40.0% of low-MM novices in the control condition did so.
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FIGURE 1
STUDY 1: SAMPLE STIMULUS
High Default, Number of Voices
Number of Voices
The number of types of sounds the keyboard can mimic; for example, you can makeeach note sound like a violin, marimba, human voice or choir, electric guitar, etc.
Circle or fill in the box for the level of attribute you prefer. [If you do not circle one,the manufacturer will automatically provide the level indicated by a mark.]
16 voices
32 voices ● 64 voices
$90 different$40 different
$50 different
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FIGURE 2
STUDY 1: PERCENT CHOOSING DEFAULT VERSUS CONTROLa
9.4
-7.6
-2.1
-8.8
9.4
-0.6
-6.9
1.5
5.3
-10
-8
-6
-4
-20
2
4
6
8
10
Low Default Middle
Default
High Default
Choosing MiddleChoosing Low
Choosing High
ai.e., the percentage of subjects in the low default condition choosing the low option was
9.4 higher than the percent choosing this option in the control (no-default) condition.
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FIGURE 3
STUDY 2: PERCENT CHOOSING DEFAULT VERSUS CONTROLa
2.0
13.8
16.3
-6.5
-10
-5
0
5
10
15
20
Limited Enhanced
.
High
Low
ai.e., the percentage of subjects in the limited information condition choosing the highoption was 16.3 higher than the percent choosing this option in the control (no-default)condition.
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FIGURE 4
STUDY 3: PERCENT CHOOSING DEFAULT VERSUS CONTROLa
1.9
8.0
3.8
-8.9
0.6
-5.3-9.7
15.9
-30
-20
-10
0
10
20
30
Novices/Low MM Novices/High MM Experts/Low MM Experts/High MM
Low Default High Default
ai.e., the percentage of low-MM novices in the high default condition choosing the high
option was 15.9 higher than the percent of low-MM novices choosing this option in thecontrol (no-default) condition.