Maximizers versus satisficers: Decision-making styles, competence and outcomes

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Judgment and Decision Making, Vol. 2, No. 6, December 2007, pp. 342–350
Maximizers versus satis?cers: Decision-making styles,
competence, and outcomes
Andrew M. Parker1?, Wändi Bruine de Bruin2, and Baruch Fischhoff2,3
1 RAND Corporation, Pittsburgh PA
2 Department of Social and Decision Sciences, Carnegie Mellon University
3 Department of Engineering and Public Policy, Carnegie Mellon University
Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bru-
ine de Bruin et al., 2007). Here, we examine whether this ?nding may be explained by the decision-making styles of
self-reported maximizers. Expanding on Schwartz et al. (2002), we ?nd that self-reported maximizers are more likely
to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence
on others when making decisions, more avoidance of decision making, and greater tendency to experience regret. Con-
trary to predictions, self-reported maximizers were more likely to report spontaneous decision making. However, the
relationship between self-reported maximizing and worse life outcomes is largely unaffected by controls for measures
of other decision-making styles, decision-making competence, and demographic variables.
Keywords: maximizing, satis?cing, decision making, competence, decision style.
1 Introduction
1998, 2000), asking whether, through preference or abil-
ity, individuals make decisions in consistent ways, across
tasks and situations (Bromiley & Curley, 1992). Individ-
Behavioral decision research (Edwards, 1961; Hastie &
ual differences that have been examined include risk aver-
Dawes, 2001; Yates, 1990) characterizes behavior in
sion and risk judgments (Slovic, 1962; Weber, Blais, &
terms of its consistency with the axioms of utility max-
Betz, 2002); preference for rational, intuitive, dependent,
imization (Bernoulli, 1738/1954; von Neumann & Mor-
avoidant, or spontaneous decision-making styles (Scott &
genstern, 1953). A half-century of research has revealed
Bruce, 1985); and decision-making competence (Bruine
both consistency with and departures from that norm
de Bruin et al., 2007; Finucane et al., 2002, 2005; Parker
(e.g., Baron, 2000; Plous, 1993). The latter include “sat-
& Fischhoff, 2005).
is?cing,” choosing an alternative that is “good enough,”
Building on Simon’s work, Schwartz et al. (2002) de-
rather than “maximizing,” selecting the option with the
veloped a scale measuring the degree to which individ-
highest expected utility (Simon, 1978). Such strategies
uals report trying to maximize, rather than satis?ce. It
can be bene?cial — if they save enough cognitive effort
includes items such as “When I watch TV, I channel surf,
to justify any loss in expected payoff (Simon, 1955, 1956,
often scanning through the options even while attempting
to watch one program.” The other items capture ways in
Historically, decision-making research has focused on
which one might explore as much information as possi-
general processes underlying deviations from normative
ble when making a choice. Given the many options often
theory, such as satis?cing instead of maximizing (Lopes,
available in modern life (e.g., TV channels, cars, jobs,
1987). More recently, attention has turned to individual
prospective mates), maximizing is no small feat (Iyen-
differences in decision making (e.g., Stanovich & West,
gar & Lepper, 1999; Schwartz, 2004a; 2004b; Tversky &
?This research was funded by the National Science Foundation
Sha?r, 1992).
(SES–0213782, SES–0433152). The authors thank Jónína Bjarnadót-
Perhaps because of the challenges of successfully im-
tir, Jacob Chen, YoonSun Choi, Rebecca Cornelius, Mandy Hol-
plementing a maximizing strategy, people who attempt
brook, Mark Huneke, Kathleen Pinturak, and Alanna Williams for
to do so fare less well in life, in the sense of experienc-
their assistance. Address: Andrew M. Parker, RAND Corporation,
4570 Fifth Avenue, Suite 600, Pittsburgh, PA 15213–2665; email:
ing less happiness, optimism, self-esteem, and life satis-
[email protected]
faction, while incurring more depression, perfectionism,

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
and regret (Schwartz et al., 2002). Moreover, individuals
We begin by asking whether self-reported maximiz-
who try to maximize may have less constructive decision-
ers tend to report several decision-making styles. One
making styles (Schwartz et al., 2002). For example, aspir-
such measure is behavioral coping, or taking action to
ing maximizers make more upward social comparisons,
resolve dif?cult tasks, rather than working around them
thereby inducing regret and counterfactual thinking about
(Epstein & Meier, 1989; Katz & Epstein, 1991). Because
what might have been. They rely more on external in-
self-reported maximizers may set unattainable goals, they
formation sources (Iyengar, Wells, & Schwartz, 2006),
should report less of such coping. Five other measures
which might lead them to further question their choices.
come from Scott and Bruce’s (1985) suite of decision-
Thus, these decision-making styles may undermine the
making style scales. Self-reported maximizers should re-
very satisfaction that attempted maximizers try so hard to
port engaging in (1) more rational decision making, re-
achieve (Schwartz et al., 2002).
?ecting their perception of systematic deliberation about
Even when maximizing pays off with better outcomes,
their choices; (2) less intuitive decision making, attempt-
satisfaction with those outcomes still may not follow.
ing to avoid relying on feelings and instincts (e.g., Slovic,
Iyengar, Wells & Schwartz (2006) found that recent col-
Finucane, Peters, & McGregor, 2004); (3) more depen-
lege graduates who described themselves as maximiz-
dence on others, re?ecting interpersonal comparisons and
ers secured jobs with 20% higher starting salaries, but
the quest for information; (4) more avoidant decision
felt less satis?ed during the job search and afterward.
making, postponing decisions to search for more infor-
One possible explanation is that attempting to maxi-
mation and ponder the possibilities; and (5) less sponta-
mize encourages focusing on one easily compared fea-
neous decision making, in the sense of taking more time
ture (salary), while neglecting other features important to
to carefully decide. Finally, we expect self-reported max-
job satisfaction. Were that the case, then those who at-
imizers to report greater regret about their past decisions,
tempt to maximize may make poorer decisions, despite
replicating Schwartz et al.’s (2002) ?nding in a diverse
strongly desiring the opposite. Conversely, in decisions
community sample.
that lack easily compared criteria, would-be maximizers
Subsequently, we take advantage of the diversity of
may face cognitively intractable situations, like those that
Bruine de Bruin et al.’s sample to examine how self-
led Simon to propose the advisability of satis?cing.
reported maximizing varies with socio-demographic vari-
Consistent with these hypotheses, Bruine de Bruin
ables. Finally, we examine whether the correlations be-
et al. (2007) found that people with higher self-ratings
tween self-reported maximizing and the two performance
on Schwartz et al.’s (2002) maximizing scale had lower
measures, A-DMC and DOI, are reduced after controlling
scores on a measure of Decision-Making Competence
for the other styles and demographics.
(DMC), which is described below (r= ?.19, p<.001). In
addition, self-identi?ed maximizers also reported worse
outcomes on the Decision Outcome Inventory (DOI),
which includes 41 negative life events that might re?ect
2 Method
poor decision making. These events range broadly in
their impacts and frequency, and include ruining clothes
in the laundry, having a check bounce, having a mortgage
2.1 Sample
or loan foreclosed, being in jail overnight, and having
been diagnosed with type 2 diabetes (which is more likely
We recruited 360 people from the Pittsburgh area through
among people who have made poor lifestyle choices).
social service organizations (46.1%) and other commu-
The analyses in Bruine de Bruin et al. (2007) focused
nity groups. The social service organizations were lo-
on developing and validating the DMC and DOI mea-
cated in poorer sections of the city and served disadvan-
sures. In that context, Schwartz et al.’s (2002) self-
taged populations. Other community groups were located
reported maximization scale was one of several compari-
in relatively more af?uent locations and did not address
son measures. As a result, the paper reported zero-order
the needs of disadvantaged populations. Among partici-
correlations of maximizing with DMC and DOI, but not
pants responding to demographic questions, ages ranged
with other decision-making styles or demographic char-
from 18 to 88 (M=47.7, SD=17.0); 73.8% were women,
acteristics. In particular, the analyses did not examine
65.5% white, 28.2% African-American, and 6.3% other
the extent to which lower DMC scores and problem-
racial minorities. Highest level of education was 2.8%
atic decision-making styles account for the correlation
no degree, 44.6% a high school degree, 13.0% an asso-
between self-reported maximizing and poorer life out-
ciate’s degree, 29.1% a bachelor’s degree, 9.5% a mas-
comes. Here, we examine this question, using Bruine de
ter’s degree, and 0.9% a Ph.D. Except for the proportion
Bruin et al.’s (2007) diverse community sample and rich
of women, the sample resembles U.S. Census ?gures for
the Pittsburgh area.

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
2.2 Measures
edge test, with each answer accompanied by a probabil-
ity judgment (on a scale ranging from 50%=just guess-
Self-reported maximizing. We used Schwartz et al.’s
ing to 100%=absolutely sure) that it is correct. Each per-
(2002) 13-item measure of tending to maximize, rather
son’s score is the absolute value of the difference between
than satis?ce, which uses a scale anchored at 1 (=com-
their mean probability judgment and the actual percent-
pletely disagree) and 5 (=completely agree).
age correct. The questions were representatively drawn
Other decision-making styles. We used the 15-item be-
from 17 Complete Idiot’s guides advising on a wide vari-
havioral coping module of the Constructive Thinking In-
ety of decisions. Applying Decision Rules assesses the
ventory (e.g., “When I realize I have made a mistake, I
ability to apply speci?ed decision rules (e.g., elimina-
usually take immediate action to correct it;” Epstein &
tion by aspects) to ten hypothetical choices, with each
Meier, 1989; Katz & Epstein, 1991), with a scale an-
option characterized on several attributes in a table. Con-
chored at 1 (=de?nitely false) and 5 (=de?nitely true).
sistency in Risk Perception assesses the ability to make
Scott and Bruce (1985) provided scales for self-reported
risk judgments that are internally consistent (e.g., giving
attempts to (a) make decisions rationally (4 items; e.g.,
a lower probability to dying in a terrorist attack than to
“I make decisions in a logical and systematic way”),
dying from any cause), with 20 paired judgments. Resis-
(b) base decisions on intuitions (5 items; e.g., “I gener-
tance to Sunk Costs uses ten single-choice sunk cost prob-
ally make decisions that feel right to me”), (c) depend
lems to assess the ability to ignore irrecoverable prior in-
on others (5 items; e.g., “I often need the assistance
vestments, and consider only future consequences when
of other people when making important decisions”), (d)
making decisions. The aggregate Adult Decision-Making
avoid making decisions (5 items; e.g., “I postpone de-
Competence (A-DMC) measure is the unweighted aver-
cision making whenever possible”), and (e) make deci-
age of standardized task scores. It represents the extent
sions spontaneously (5 items; e.g., “I make quick deci-
to which individuals can make decisions normatively —
sions”). The response scale was anchored at 1 (=com-
as a potential correlate of their self-reported attempts to
pletely disagree) and 5 (=completely agree). Finally, we
used Schwartz et al.’s (2002) 5-item measure of the ten-
Decision Outcomes Inventory (DOI). The Decision
dency to feel regret (e.g., “When I think about how I’m
Outcome Inventory elicits self-reports of having experi-
doing in life, I often assess opportunities I have passed
enced each of 41 negative events, varying widely in do-
up”), using the same response scale as Scott & Bruce
main and severity (e.g., threw out food or groceries you
had bought, locked yourself out, got divorced, had an
Adult-Decision-Making Competence. A-DMC has six
unplanned pregnancy). For 35 of these events, respon-
component tasks, selected to cover the skills central to
dents only received credit for avoiding a negative out-
normative theories of decision making (Bruine de Bruin
come if they indicated having made a decision crucial
et al., 2007; Parker & Fischhoff, 2005). The A-DMC
to experiencing it (e.g., only those who reported hav-
tasks were based on ones studied by behavioral decision
ing a driver’s license received credit for not having lost
researchers, drawing on the understanding derived from
it). As a proxy for severity, each outcome was weighted
multiple rounds of experimental research. Resistance to
by the proportion of participants who reported not expe-
Framing uses valence-framing problems (Levin, Schnei-
riencing it (among those who had the opportunity), as-
der & Gaeth, 1998) to measure whether choices are af-
suming that more severe outcomes tend to be less fre-
fected by formally irrelevant variations in how options
quent (as is the case with spending a night in jail, versus
are described. For example, one pair of items asks for
forgetting a birthday). Severity was computed speci?-
quality judgments of ground beef described as either (a)
cally using responses from this sample. Weighted out-
“20% fat” or (b) “80% lean.” Fourteen such pairs are
comes were averaged and subtracted from 0, so that
presented in two sets, with one containing the positively-
higher scores re?ect better outcomes. Thus, the DOI
valenced member of each pair, and the other containing
score re?ects the number of negative outcomes respon-
the corresponding negatively-valenced items. Recogniz-
dents had avoided, out of those they had the oppor-
ing Social Norms asks “out of 100 people your age, how
tunity to experience, weighted by severity.
The A-
many would say it is sometimes OK” to engage in each
DMC and DOI measures are available from the authors
of 16 undesirable behaviors (e.g., “steal under certain cir-
or online at, as
cumstances”). These estimates are compared to the per-
well as in this issue of Judgment and Decision Making
cent of respondents from this study who had reported
earlier that “it is sometimes OK” to engage in each be-
Demographics. Education is assessed from answers to,
havior, with each person’s score being the within-subject
“What is currently your highest level of education?” with
correlation between judged norms and observed norms.
the options of no degree, high school, associate, bachelor,
Under/Overcon?dence uses a 34-item true/false knowl-
masters, and Ph.D. A dummy variable for being recruited

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
Table 1: Relationships among decision-making styles.
Decision-making Style
To cope behaviorally
To decide rationally
To decide intuitively
To depend on others
To avoid decisions
.37*** ?.43*** ?.11+
To decide spontaneously
.31*** ?.26*** ?.21***
To feel regret
.47*** ?.31***
+ p<.10; *p < .05; ** p < .01; *** p < .001 two-sided.
from a social service organization targeting residents with
2.4 Analysis strategy
lower levels of socio-economic status was used as a proxy
for socio-economic status (SES; 0 = lower, 1 = higher).
First, we examine Pearson correlations between self-
reported maximizing and the other decision-making
styles, as well as the demographic variables. Then, we
report hierarchical multiple linear regressions predicting
A-DMC, entering maximizing on the ?rst step, the other
2.3 Procedure
the decision-making styles on the second step, and de-
mographics on the third. Finally, we report hierarchical
regressions predicting DOI, entering maximizing and the
Respondents were run in group survey sessions held in
other decision-making styles on the ?rst two steps, demo-
their communities. On a cover letter, respondents were
graphics on the third, and A-DMC on the fourth.
told that the study was about decision styles, and that
they would “be given several decision problems, items
from an intelligence test, as well as questions about de-
3 Results
cision styles, decision outcomes, and demographic in-
formation.” A-DMC tasks were self-paced, in the or-
3.1 Scale properties
der: (a) positive versions of the Resistance to Framing
items, (b) Recognizing Social Norms questions asking if
All eight decision-making style variables had ranges of 1
“it is sometimes OK” to engage in different behaviors, (c)
to 5, with higher scores indicating greater endorsement of
Under/Overcon?dence, (d) Applying Decision Rules, (e)
the style. The mean self-reported maximizing score was
Consistency in Risk Perception, (f) Resistance to Sunk
2.9 (Cronbach ? = .76). Other means were 3.0 for regret
Costs, (g) negative versions of the Resistance to Fram-
(Cronbach ? = .65), 3.8 for behavioral coping (Cronbach
ing items, and (h) Recognizing Social Norms questions
?=.86), 3.8 for rational (? = .85), 3.6 for intuitive (? =
asking about their peers’ reported behaviors. This order
.87), 3.4 for dependent (? = .83), 2.6 for avoidant (? =
maximized the distance between paired tasks (Resistance
.89), and 2.6 for spontaneous (? = .87) decision making.
to Framing, Recognizing Social Norms). Subsequently,
As reported in Bruine de Bruin et al. (2007), A-DMC has
participants completed the decision-making styles mea-
an ? of .85 and test-retest reliability of .73. DOI has an ?
sures, in the order: regret, maximizing, behavioral cop-
of .88.
ing, rational, intuitive, dependent, avoidant and sponta-
neous decision making. Finally, they completed the DOI
3.2 Self-reported maximizing and other
and the demographic questions. Participants received two
decision-making styles
envelopes containing $17.50 each, with the option to do-
nate to the organization that recruited them. As stated
Table 1 presents correlations between self-reported max-
in the recruitment materials: “We will give $35 for your
imizing and the other decision-making styles. Consistent
time and effort. You will be given a choice between
with Schwartz et al.’s account, self-reported maximizing
(a) taking home $35; (b) giving $35 to the organization
is related to less behavioral coping, more depending on
through which you were recruited or (c) taking home
others, and a stronger tendency to avoid decisions. How-
$17.50 and giving the organization $17.50.”
ever, we did not ?nd the expected corrections with self-

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
Table 2: Relationships between decision-making styles and demographics.
To maximize
To cope behaviorally
To decide rationally
To decide intuitively
To depend on others
To avoid decisions
To decide spontaneously
To feel regret
+ p<.10; *p < .05; ** p < .01; *** p < .001 two-sided
Notes: Gender is coded as 0 if male and 1 if female. SES is 1 (higher) if respondent was
interviewed at a social service organization (0 otherwise). Education is coded as 1 if no
degree, 2 if high school, 3 if associates degree, 4 if bachelors degree, 5 if masters degree,
and 6 if Ph.D.
reports of deciding rationally and deciding intuitively —
models predicting A-DMC (left) and DOI (right). Step
and found the opposite of the expected correlation with
1 uses self-reported maximizing as a predictor, Step 2
deciding spontaneously. Replicating a key result from
adds the other seven decision-making styles, Step 3 adds
Schwartz et al. (2002), we ?nd that people who reported
the demographics, and Step 4 adds A-DMC (for the DOI
stronger commitments to maximizing also reported expe-
riencing greater regret.
3.4.1 Decision-making competence
3.3 Decision-making styles and demo-
graphic characteristics
Step 1 of Table 3 shows that the self-ratings on the
maximizing scale have a signi?cant negative relation-
Row 1 of Table 2 shows that self-reported maximizing
ship with A-DMC. When all eight styles are considered
was greater for respondents drawn from lower SES lo-
(Step 2), A-DMC scores are signi?cantly correlated with
cations and reporting less education (SES and education
two seemingly contradictory styles: less reported maxi-
were correlated at r = .42, p < .001). It was slightly higher
mizing and less spontaneous decision making.2 Adding
among men and unrelated to age. The rest of the table
the demographics (Step 3) leaves weak signi?cant rela-
shows that each style measure, except depending on oth-
tionships with reported maximizing and spontaneous de-
ers, was signi?cantly correlated with at least one demo-
cision making, while revealing that A-DMC is slightly
graphic variable. The analyses below clarify these rela-
lower for women and much higher for respondents with
more education and higher SES.
3.4 Predicting
3.4.2 Decision outcomes
tence and decision outcomes from
Step 1 of Table 4 shows a signi?cant correlation between
decision-making styles and demo-
reporting more maximizing and experiencing worse de-
cision outcomes. When all eight styles are considered
As mentioned, Bruine de Bruin et al. (2007) found statis-
(Step 2), signi?cantly better outcomes are reported by re-
tically signi?cant pair-wise relationships between several
spondents who report less maximizing, more behavioral
of the decision-making style variables and both A-DMC
coping, more intuitive decision making, and less deciding
and DOI.1 Tables 3 and 4 present hierarchical regression
spontaneously — with marginally signi?cant correlations
with depending on others more and avoiding decisions
1As reported in Bruine de Bruin et al. (2007), each of the A-
DMC components correlated negatively with self-reported maximizing,
2These regressions were run using all planned tests. Follow-up anal-
reaching statistical signi?cance for under/overcon?dence (r = ?.21, p >
yses, removing non-signi?cant predictors, did not qualitatively change
.001) and consistency in risk perception (r = ?.13, p < .05).
the patterns of results presented here.

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
Table 3: Hierarchical linear regressions predicting A-
Table 4: Hierarchical linear regressions predicting DOI.
Predictor Variable
Step 1
Step 2
Step 3
Step 1
Step 2
Step 3
Step 4
To maximize
?.21*** ?.15*
?.26*** ?.15*
cope behaviorally
decide rationally
decide intuitively
depend on others
avoid decisions
decide spontaneously
?.24*** ?.20**
feel regret
Higher SES
Higher SES
14.85*** 5.35***
20.96*** 11.46*** 12.34***
(1, 300) (8, 293)
(12, 289)
(1, 300)
(8, 293) (12, 289)
(13, 288)
Adjusted R2
Adjusted R2
+ p<.10; *p < .05; ** p < .01; *** p < .001 two-sided
Notes: N = 302. Variance in?ation factors range from 1.0
Note: Statistics are standardized regression coef?cients.
to 2.5, indicating only modest multicollinearity.
4 Discussion
less. As with A-DMC (Table 3), spontaneous decision-
making style stood out.3 The correlations with reported
maximizing and spontaneity appear to remain stable with
As predicted, individuals who report a stronger tendency
the addition of the demographic variables (Step 3). Step 3
to maximize are also more likely to report other maladap-
also reveals better DOI for older and higher SES respon-
tive decision-making styles, such as less behavioral cop-
ing, greater dependence on others, more avoiding of de-
cision making, and greater experience of regret. Contrary
Adding the A-DMC (Step 4) reveals that scoring
to predictions, self-reported maximizers are more likely
higher on A-DMC is signi?cantly related to reporting
to report spontaneous decision making. We failed to ?nd
more positive decision outcomes on the DOI, even af-
predicted correlations with rational and intuitive styles.
ter including all the decision style and demographic mea-
Below, we ?rst explain how these ?ndings affect the rela-
sures. DOI scores are also higher for individuals who
tionship of maximizing with A-DMC and DOI, and then
are older, have less education, and come from the higher
discuss each in more detail.
SES locations. Among the style measures, signi?cant
Bruine de Bruin et al. (2007) found that self-reported
positive relationships remain for self-reported maximiz-
maximizers appeared to be poorer decision makers,
ing and deciding spontaneously.4,5
whether measured by a standard measure (A-DMC) or
self-reported outcomes (DOI). Here, we found that self-
3Follow-up analyses, adding each decision style individually, show
that the reduction in the coef?cient for maximizing is due almost en-
reported maximizing and A-DMC were negatively re-
tirely to the addition of the spontaneous decision-style variable.
lated in hierarchical regression analyses that included
4A quadratic maximizing term, added to this equation after Step 1,
other decision-making styles that might characterize
had a standardized beta of .76, p < .05. The positive curvature represents
maximizers, as well as several standard demographic
modestly better reported decision outcomes for those with very low and
very high maximizing scores. Adding this term did not markedly affect
The introduction of spontaneous decision
the standardized coef?cient for maximizing, either alone (standardized
making into the regression models substantially reduced
beta = ?.25) or with the other variables included (standardized beta
= ?.12). Including a quadratic maximizing term had no effect on the
ing is entered into the equation, it is non-signi?cant (standardized beta =
regression predicting A-DMC.
?.05). Hence, whereas higher DMC can compensate for a maximizing
5When an interaction between A-DMC and self-reported maximiz-
style, it does not moderate it (or vice versa).

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
the relationship between self-reported maximizing and
fect maximizers.
decision-making ability, while other decision-making
Self-reported maximizers reported greater spontaneity,
styles (behavioral coping, deciding rationally, deciding
in the sense of making spur-of-the-moment choices. This
intuitively, depending on others, avoiding decisions, and
result appears contrary to the image of maximizers ago-
feeling regret) did not. Thus, with the exception of spon-
nizing over the “best” option. One possible clue is that
taneity (which we address below), attempting to max-
reporting spontaneity was correlated with reporting de-
imize appears to be a distinct, maladaptive decision-
cision avoidance; perhaps people who postpone making
making style, associated with poor decision making, in
decisions end up making what feel like “spur of the mo-
this diverse community sample.6
The regression co-
ment” choices. It is also possible that maximizers tend to
ef?cient on maximizing was not substantially reduced
see choices as spontaneous because they have dif?culty
in hierarchical analyses where many of the other styles
seeing them as adequately reasoned. As noted (footnote
dropped from signi?cance, suggesting that maximizing,
3), the spontaneous decision-style measure was the only
as measured, may be a more proximal correlate of A-
one that substantially reduced the coef?cients on maxi-
DMC and DOI. Past research has found greater dissat-
mizing in either hierarchical regression.
isfaction among self-reported maximizers (Iyengar et al.,
Self-reported maximizing was, however, unrelated to
2006; Schwartz et al., 2002), a result that might re?ect
the self-reported rational decision-making style measure,
their having higher expectations or lower abilities. The
a seemingly related construct. A speculative explanation
present results suggest that maximizers actually experi-
is that the maximizing scale includes items expressing
ence more negative life outcomes (as measured by the
frustration (e.g., “Renting videos is really dif?cult. I’m
DOI), perhaps as a result of being less competent (as mea-
always struggling to pick the best one.”), whereas the ra-
sured by A-DMC).
tionality items are more neutral (e.g., “When making de-
Consideration of the other decision-making styles may
cisions, I consider various options in terms of a speci?c
help clarify these patterns. Self-reported maximizers re-
goal”). Past research has found that rational decision-
port less use of behavioral coping strategies for reduc-
making scores are positively correlated with competence
ing the stress of unresolved challenges (Epstein & Meier,
and good outcomes, while maximizing is negatively cor-
1989; Katz & Epstein, 1991). Satis?cing could be one
related (Bruine de Bruin et al., 2007; Crossley & High-
such strategy, which Bruine de Bruin et al. (2007) found
house, 2005; Russ, McNeilly & Comer, 1996). How-
to be associated with better decision-making competence
ever, in the presence of the other predictors, the ratio-
and outcomes.
nal decision-making style predicted neither A-DMC nor
Self-reported maximizers report depending more on
DOI, whereas maximizing continued to be negatively re-
others for information, consistent with the accounts of
lated to them. Possibly, the rational decision-making
Schwartz et al. (2002) and Iyengar et al. (2006). While
scale captures self-observation of some behaviors actu-
good advice can improve decisions, consultation can also
ally associated with good decision making, whereas the
undermine effective decision making by encouraging un-
maximizing scale captures self-observation of ineffective
realistic aspirations, focusing attention on readily quan-
ti?ed outcomes, and revealing contradictory advice (Fis-
Self-reported maximizing was not negatively corre-
chhoff, 1992). Perhaps re?ecting these contrary possibil-
lated with self-reports of deciding intuitively, seemingly
ities, self-reported dependence on others is unrelated to
the complement of deciding rationally. An intuitive style
decision-making competence or outcomes.
has sometimes been related to better competence and out-
Self-reported maximizers report greater decision
comes (Bruine de Bruin et al., 2007; Crossley & High-
avoidance, plausibly the result of taking the time to exam-
house, 2005), and sometimes not (Phillips & Strohmer,
ine each option in detail. When that examination fails to
1982; Singh & Greenhaus, 2004). Future research should
yield clearly superior options, the result may be inaction
investigate the possibilities that this is the result of mea-
or actions driven by events outside of individuals’ control
surement or more substantive issues.
(Fischhoff, in press). The perils of these processes might
Self-reported maximizers tend to report experiencing
contribute to the ?nding that reporting greater decision
more regret, replicating, with a diverse community sam-
avoidance was correlated with worse decision-making
ple, a result that Schwartz et al. (2002) attributed to unfa-
competence and decision outcomes. Experimental stud-
vorable social comparisons. Bruine de Bruin et al. (2007)
ies have found greater avoidance as the number and qual-
found that people who express more regret have worse
ity of decision options increases (Dhar, 1997; Tversky &
decision-making competence and outcome scores (Bru-
Sha?r, 1992), decision features that might particularly af-
ine de Bruin et al., 2007), suggesting that the feeling
might be warranted.
6This conclusion does not exclude the possibility that there may be
positive (or negative) externalities to maximizing, realized by others
In this diverse sample, we found more self-reported
around the maximizer.
maximizing among men (as found in some samples by

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
Schwartz et al., 2002), less educated people, and ones in-
terviewed at an organization serving lower SES individ-
uals. On the other decision-making style measures: (a)
Baron, J. (2000). Thinking and Deciding, 3rd Ed. New
there were no other gender differences; (b) older individ-
York, NY: Cambridge University Press.
uals reported more behavioral coping and more rational
Bernoulli, D. (1738/1954). Exposition of a new theory on
and intuitive styles; (c) lower SES individuals reported
the measurement of risk. Econometrica, 22, 23–36.
less behavioral coping, being less rational, more avoidant,
Bromiley, P., & Curley, S. P. (1992). Individual differ-
more spontaneous styles, and more regretful; (d) individ-
ences in risk taking. In J. F. Yates (Ed.), Risk-taking
uals with less education reported less behavioral coping,
behavior (pp. 87–132). New York, NY: John Wiley &
being more rational, more avoidant, and more sponta-
Bruine de Bruin, W., Parker, A. M., & Fischhoff, B.
As with previous studies, we report correlations. Al-
Individual differences in Adult Decision-
though it is tempting to interpret the results as show-
Making Competence. Journal of Personality and So-
ing that good outcomes and decision-making competence
cial Psychology, 92, 938–956.
follow from attempting to satis?ce (rather than maxi-
Crossley, C. D., & Highhouse, S. (2005). Relation of job
mize), the opposite is also possible. Negative life ex-
search and choice process with subsequent satisfaction.
periences, or recognized limits to one’s decision making
Journal of Economic Psychology, 26, 255–268.
could encourage people to maximize, hoping that it will
Dhar, R. (1997). Consumer preference for a no choice
lead to better outcomes. That might be particularly true
option. Journal of Consumer Research, 24, 215–231.
for low SES individuals, who tend to face a world with
Edwards, W. (1954). The theory of decision making.
greater risks and fewer resources.
Psychological Bulletin, 51, 380–417.
The relationships among the decision-making styles
Epstein, S., & Meier, P. (1989). Constructive thinking: a
(e.g., the positive correlation between maximizing and
broad coping variable with speci?c components. Jour-
spontaneity) also raise the possibility of more complex
nal of Personality and Social Psychology, 57, 332–350.
relationships, including mediation or third-variable ex-
Finucane, M. L., Mertz, C. K., Slovic, P., Schmidt, E.
Experimental studies (e.g., manipulating
S. (2005). Task complexity and older adults’ decision-
maximizing pressure) might provide causal evidence.
making competence. Psychology and Aging, 20, 71–
Prospective designs might identify temporal emergence
of different tendencies — as reported by Parker & Fis-
Finucane, M. L., Slovic, P., Hibbard, J. H., Peters, E.,
chhoff (2005), whose 18–19 year old respondents had
Mertz, C. K., & Macgregor, D. G. (2002). Aging and
entered a longitudinal study between ages 10–12. Our
decision-making competence: An analysis of compre-
conclusions also depend on the reliability and validity of
hension and consistency skills in older versus younger
our measures – as seen in some of the discussion (above)
adults. Journal of Behavioral Decision Making, 15,
about the meaning of various scales. With correlated pre-
dictors, unreliability complicates the identi?cation of in-
Fischhoff, B. (1992). Giving advice: Decision theory
dependent effects.
perspectives on sexual assault. American Psychologist,
These results show the importance of distinguishing
47, 577–588.
between intent (style) and action (competence). The hi-
Fischhoff, B. (in press). Assessing adolescent decision-
erarchical regressions ?nd that styles and competence do
making competence. Developmental Review.
little to diminish either’s ability to predict DOI. Other re-
Hastie, R., & Dawes, R. M. (2001). Rational choice in
sults ?nd that self-reported maximizing, a style that en-
an uncertain world: The psychology of judgment and
dorses a feature common to normative models of deci-
decision making. Thousand Oaks, CA: Sage.
sion making, is negatively related to the ability to follow
Kahneman, D., Slovic, P., & Tversky, A. (1982). Judg-
normative decision-making strategies (A-DMC). Thus,
ment under uncertainty: Heuristics and biases. New
the self-reported tendency to maximize is associated with
York: Cambridge University Press.
worse life outcomes, while the ability follow normative
Katz, L., & Epstein, S. (1991). Constructive thinking and
rules is associated with better ones. If these relationships
coping with laboratory-induced stress. Journal of Per-
are indeed causal, then teaching both normative decision-
sonality and Social Psychology, 61, 789–800.
making skills and the importance of satis?cing might help
Iyengar, S. S., & Lepper, M. R. (1999). Rethinking the
people to achieve better outcomes.
value of choice: A cultural perspective on intrinsic mo-
tivation. Journal of Personality and Social Psychology,
76, 349–366.

Judgment and Decision Making, Vol. 2, No. 6, December 2007
Maximizers versus satic?cers
Iyengar, S. S., Wells, R. E., & Schwartz, B. (2006). Do-
Simon, H. A. (1956). Rational choice and the structure of
ing better but feeling worse. Looking for the “best”
the environment. Psychological Review, 63, 129–138.
job undermines satisfaction. Psychological Science,
Simon, H. A. (1957). Models of man, social and ratio-
17, 143–150.
nal: Mathematical essasys on rational human behav-
Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All
ior. New York: Wiley.
frames are not created equal: A typology and critical
Simon, H. A. (1978). Rationality and process and product
analysis of framing effects. Organizational Behavior
of thought. American Economic Review, 68, 1–16.
and Human Decision Processes, 76, 149–188.
Singh, R., & Greenhaus, J. H. (2004). The relation be-
Lopes, L. L. (1987). Between hope and fear: The psy-
tween career decision-making strategies and person-
chology of risk. Advances in Experimental Social Psy-
job ?t: A study of job changers. Journal of Vocational
chology, 20, 255–295.
Behavior, 64, 198–221.
Parker, A. M., & Fischhoff, B. (2005).
Slovic, P. (1962). Convergent validation of risk-taking
making competence: External validation through an
measures. Journal of Abnormal and Social Psychol-
individual-differences approach. Journal of Behav-
ogy, 65, 68–71.
ioral Decision Making, 18, 1–27.
Slovic, P., Finucane, M. L., Peters, E., & McGregor, D.
Phillips, S. D., & Strohmer, D. C. (1982). Decision-
G. (2004). Risk as analysis and risk as feelings: Some
making style and vocational maturity. Journal of Vo-
thoughts about affect, reason, risk, and rationality. Risk
cational Behavior, 20, 215–222.
Analysis, 24, 311–322.
Plous, S. (1993). The psychology of judgment and deci-
Stanovich, K. E., & West, R. F. (1998). Individual dif-
sion making. New York: McGraw-Hill, Inc.
ferences in rational thought. Journal of Experimental
Russ, F. A., McNeilly, K. M., & Comer, J. M. (1996).
Psychology: General, 127, 161–188.
Leadership, decision making and performance of sales
Stanovich, K. E., & West, R. F. (2000). Individual dif-
managers: A multi-level approach. Journal of Per-
ferences in reasoning: Implications for the rationality
sonal Selling & Sales Management, 16, 1–15.
debate? Behavioral and Brain Sciences, 23, 645–726.
Schwartz, B. Ward, A., Monterosso, J. Lyubomirsky, S.,
von Neumann, J. & Morgenstern, O. (1953). The the-
White, K., & Lehman, D. R. (2002). Maximizing ver-
ory of games and economic behavior. Princeton, NJ:
sus satis?cing: Happiness is a matter of choice. Jour-
Princeton University Press.
nal of Personality and Social Psychology, 83, 1178–
Tversky, A., & Sha?r, E. (1992). Choice under con?ict:
The dynamics of deferred decision. Psychological Sci-
Schwartz, B. (2004a). The paradox of choice: Why more
ence, 3, 358–361.
is less. New York: Harper Perennial.
Weber, E. U., Blais, A. -R., & Betz, N. E. (2002).
Schwartz, B. (2004b, April). The tyranny of choice. Sci-
A domain-speci?c risk-attitude scale: Measuring risk
enti?c American, 290, 70–76.
perceptions and risk behaviors. Journal of Behavioral
Scott, S. G., & Bruce, R. A. (1995). Decision mak-
Decision Making, 15, 263–290.
ing style; Development and assessment of a new mea-
Yates, J. F. (1990). Judgment and decision making. En-
sure. Educational and Psychological Measurement,
glewood Cliffs, NJ: Prentice Hall.
55, 818–831.
Simon, H. A. (1955). A behavioral model of rational
choice. Quarterly Journal of Economics, 59, 99–118.