ArticlePDF Available

Exploring Intuition and its Role in Managerial Decision Making

Authors:

Abstract and Figures

We review and reconceptualize "intuition," defining intuitions as affectively charged judgments that arise through rapid, nonconscious, and holistic associations. In doing so, we delineate intuition from other decision-making approaches (e.g., insight, ra- tional). We also develop a model and propositions that incorporate the role of domain knowledge, implicit and explicit learning, and task characteristics on intuition effec- tiveness. We close by suggesting directions for future research on intuition and its applications to managerial decision making.
No caption available
… 
Content may be subject to copyright.
EXPLORING INTUITION AND ITS ROLE IN
MANAGERIAL DECISION MAKING
ERIK DANE
MICHAEL G. PRATT
University of Illinois at Urbana-Champaign
We review and reconceptualize “intuition,” defining intuitions as affectively charged
judgments that arise through rapid, nonconscious, and holistic associations. In doing
so, we delineate intuition from other decision-making approaches (e.g., insight, ra-
tional). We also develop a model and propositions that incorporate the role of domain
knowledge, implicit and explicit learning, and task characteristics on intuition effec-
tiveness. We close by suggesting directions for future research on intuition and its
applications to managerial decision making.
The human brain can be a magnificent synthe-
sizer of disparate pieces of nebulous information,
and often formal techniques and procedures
thwart and inhibit this mysterious mechanism
from operating efficiently (Raiffa, 1968: 272).
A classic trade-off noted by decision theorists
is that decision accuracy is often inversely re-
lated to decision speed. Consequently, there has
been pressure to understand how to make high-
quality decisions relatively quickly (see Eisen-
hardt, 1989; Hitt, Keats, & DeMarie, 1998; Perlow,
Okhuysen, & Repenning, 2002). Toward this end,
in numerous articles in the popular business
press and in a steadily growing body of more
scholarly literature, authors have turned to the
notion of “intuition” as a means of managing
this trade-off (e.g., Burke & Miller, 1999; Hayashi,
2001; Khatri & Ng, 2000). As the epigraph sug-
gests, intuition draws on our inborn ability to
synthesize information quickly and effective-
ly—an ability that may be hindered by more
formalized procedures.
Within organizations, intuition has been pos-
ited to help guide a wide range of critical deci-
sions. Research suggests that intuition may be
integral to successfully completing tasks that
involve high complexity and short time horizons,
such as corporate planning, stock analysis, and
performance appraisal (Hayashi, 2001; Isenberg,
1984; Shirley & Langan-Fox, 1996). Agor (1986)
shows how managers use intuitions for strategic
decisions, such as whether to invest capital in a
project or whether to market controversial pre-
scription drugs. Hayashi (2001) frames several
high-profile executive-level decisions, including
the development of the Dodge Viper and the
prime-time launch of Who Wants to Be a Million-
aire, as intuitive or “gut” decisions. Research
further suggests that the need for intuition may
be especially acute in organizations embedded
in turbulent environments (Khatri & Ng, 2000).
The effective use of intuition has even been
seen as critical in differentiating successful top
executives and board members from lower-level
managers and dysfunctional boards (Agor, 1986;
Barnard, 1938; Harper, 1989). Ralph Larsen,
former chair and CEO of Johnson & Johnson,
suggested:
Very often, people will do a brilliant job through
the middle management levels, where it’s very
heavily quantitative in terms of the decision-
making. But then they reach senior management,
where the problems get more complex and am-
biguous, and we discover that their judgment or
intuition is not what it should be. And when that
happens, it’s a problem; it’s a big problem (Ha-
yashi, 2001: 61).
We believe that there have been two major
barriers to a productive discourse on the topic of
intuition within the management literature. The
first concerns the considerable confusion sur-
rounding what intuition is. Although intuition
has a long history in the organizational sciences
(Barnard, 1938; Behling & Eckel, 1991; Isaack,
1978; Peters, Hammond, & Summers, 1974; Pri-
etula & Simon, 1989; Simon, 1987), in the litera-
We thank Lorna Doucet, Patrick Laughlin, Greg Oldham,
Kevin Rockmann, and the participants of the University of
Illinois Organizational Behavior Proseminar Series for their
helpful comments on earlier drafts of this manuscript. We
also extend our thanks to Janet Fitch for assisting us with
our copy editing.
Academy of Management Review
2007, Vol. 32, No. 1, 33–54.
33
ture in this area scholars have failed to agree on
what intuition is and what it does. This concep-
tual confusion comes, in part, from the various
perspectives used to understand intuition. For
example, among Western philosophers, intu-
ition was often perceived as the most pure and
immediate way of knowing (Osbeck, 2001; Wild,
1938). It represented access to divine or inborn
knowledge. In the East, many Buddhists viewed
intuition as a means of obtaining penetrating
knowledge and as a “gateway to a wider and
richer world” (Guenther, 1958: 26).
While some maintain that intuition is a mys-
tical avenue to knowledge (e.g., Ferguson, 1999;
Franquemont, 1999; Vaughan, 1979), researchers
in the areas of management and psychology
have explained intuition through a wide range
of phenomena, including heuristics (Bazerman,
1986; Denes-Raj & Epstein, 1994; Tversky & Kah-
neman, 1983), expertise (Blattberg & Hoch, 1990;
Prietula & Simon, 1989), and nonconscious infor-
mation processing (Epstein, 1990, 1994, 2002;
Kahneman, 2003; Lieberman, 2000). Thus, one
purpose of this paper is to seek out sources of
conceptual agreement or overlap across differ-
ent disciplines and, thus, provide greater clarity
about the concept of intuition.
A second barrier hindering this line of inquiry
is that scholars often fail to distinguish between
when intuitions are used and when they are
used effectively. To illustrate, evidence sug-
gests that individuals are likely to rely on intu-
itive thought processes when they face extreme
time pressures (De Dreu, 2003; Edland & Sven-
son, 1993; Kaplan, Wanshula, & Zanna, 1993;
Kruglanski & Freund, 1983; Maule, Hockey, &
Bdzola, 2000; Suri & Monroe, 2003). Therefore,
intuition may play a significant role in the de-
cisions of firefighters (Klein, 1998), military com-
manders (Kaempf, Klein, Thordsen, & Wolf,
1996), emergency room surgeons (Abernathy &
Hamm, 1995), and corporate executives operat-
ing under severe time constraints (Agor, 1986;
Burke & Miller, 1999; Hayashi, 2001). The mere
use of intuition, however, is not a panacea for
the speed-accuracy trade-off, since its use may
simply facilitate speed at the expense of accu-
racy. Therefore, we need to better understand
those conditions that foster the effective use of
intuition to complement existing work on when
intuition is simply most likely to be used (e.g.,
Ruder & Bless, 2003; Sinclair, Ashkanasy, Chat-
topadhyay, & Boyle, 2002; Woolhouse & Bayne,
2000).
Drawing on recent advances in psychology
and the decision sciences, we suggest that, un-
der certain conditions, intuition may indeed fa-
cilitate rapid and effective decision making in
organizations. Before such gains can be real-
ized, however, we must first understand the
boundary conditions that surround the concept.
We begin with an exploration of what intuition
is and how it is different from other related con-
cepts, such as insight and instinct. We then con-
sider the factors that determine when the use of
intuition in decision making is most effective.
Toward this end, we synthesize findings across
a range of disciplines and formulate a set of
propositions surrounding the effectiveness of in-
tuitive decision making.
WHAT INTUITION IS: BRINGING TOGETHER
INTUITIVE PROCESSES AND OUTCOMES
Having both academic and nonacademic sig-
nificance, “intuition,” perhaps not surprisingly,
has a wide range of terms associated with it,
including gut feelings (Hayashi, 2001), hunches
(Rowan, 1989), and mystical insights (Vaughan,
1979; Wild, 1938). Table 1 provides a sample of
definitions of intuition culled from work in psy-
chology, philosophy, and management.
One confusing aspect of past research is the
tendency to call both intuitive processes and
their associated products, or outcomes, “intu-
ition.” For example, Jung (1933), Westcott and
Ranzoni (1963), and Raidl and Lubart (2000-2001)
refer to intuition largely as a process—a way of
perceiving or sorting data. Rorty (1967), in con-
trast, sees intuition primarily as an outcome—as
what one apprehends or recognizes. Others
combine both process and outcome without dif-
ferentiating between them. We believe that in-
tuition is marked by a unique process and out-
come; however, we also believe it is important to
disentangle the two. Thus, we begin by address-
ing intuition as a process and positioning this
process vis-a` -vis the larger “dual processing”
perspective that is currently favored among de-
cision-making theorists, especially in psychol-
ogy. We then build from this perspective to iden-
tify process and outcome characteristics that
historically have been central to many defini-
tions of intuition.
34 JanuaryAcademy of Management Review
Historical Context: Two Information Processing
Systems
Intuition has long been viewed as involving a
form of information processing that differs from
rational, or analytical, processes. Distinctions
between “rational” and “nonrational” human
thought can be traced as far back as Aristotle
(Sloman, 1996). In management research, Bar-
nard similarly distinguished between “logical”
and “nonlogical” modes of thinking, attributing
intuition to the latter:
By “logical processes” I mean conscious thinking
which could be expressed in words, or other sym-
bols, that is, reasoning. By “non-logical pro-
cesses” I mean those not capable of being ex-
pressed in words or as reasoning....This may be
because the processes are unconscious, or be-
cause they are so complex and so rapid, often
approaching the instantaneous, that they could
not be analyzed by the person within whose brain
they take place (1938: 302).
More recently, psychologists have adopted a
dual processing approach, arguing for two dis-
tinct types of information processing systems in
human beings (e.g., Epstein, 2002; Gollwitzer &
Bayer, 1999; Sloman, 1996). One information pro-
cessing system, which from an evolutionary per-
spective is believed by some to be the older of
the two systems (Epstein, 1994; Reber, 1992), in-
volves the automatic and relatively effortless
processing and learning of information (Stano-
vich & West, 2000). This system, which permits
TABLE 1
Definitions of Intuition
Source Definition of Intuition
Jung (1933: 567–568) That psychological function transmitting perceptions in an unconscious way
Wild (1938: 226) An immediate awareness by the subject, of some particular entity, without such aid
from the senses or from reason as would account for that awareness
Bruner (1962: 102) The act of grasping the meaning, significance, or structure of a problem without
explicit reliance on the analytic apparatus of one’s craft
Westcott & Ranzoni (1963: 595) The process of reaching a conclusion on the basis of little information, normally
reached on the basis of significantly more information
Rorty (1967: 204) Immediate apprehension
Bowers, Regehr, Balthazard, &
Parker (1990: 74)
A preliminary perception of coherence (pattern, meaning, structure) that is at first not
consciously represented but that nevertheless guides thought and inquiry toward a
hunch or hypothesis about the nature of the coherence in question
Shirley & Langan-Fox (1996: 564) A feeling of knowing with certitude on the basis of inadequate information and
without conscious awareness of rational thinking
Simon (1996: 89) Acts of recognition
Shapiro & Spence (1997: 64) A nonconscious, holistic processing mode in which judgments are made with no
awareness of the rules of knowledge used for inference and which can feel right,
despite one’s inability to articulate the reason
Burke & Miller (1999: 92) A cognitive conclusion based on a decision maker’s previous experiences and
emotional inputs
Policastro (1999: 89) A tacit form of knowledge that orients decision making in a promising direction
Lieberman (2000: 111) The subjective experience of a mostly nonconscious process—fast, alogical, and
inaccessible to consciousness—that, depending on exposure to the domain or
problem space, is capable of accurately extracting probabilistic contingencies
Raidl & Lubart (2000-2001: 219) A perceptual process, constructed through a mainly subconscious act of linking
disparate elements of information
Hogarth (2001: 14) Thoughts that are reached with little apparent effort, and typically without conscious
awareness; they involve little or no conscious deliberation
Myers (2002: 128–129) The capacity for direct, immediate knowledge prior to rational analysis
Kahneman (2003: 697) Thoughts and preferences that come to mind quickly and without much reflection
Epstein (personal
communication, 2004)
The working of the experiential system
2007 35Dane and Pratt
individuals to learn from experience and reach
perceptions of knowing without conscious atten-
tion (Hogarth, 2001), has been referred to as ex-
periential (Epstein, 1990, 1994, 2002; Epstein, Pa-
cini, Denes-Raj, & Heier, 1996; Pacini & Epstein,
1999), automatic (Bargh, 1996; Bargh & Char-
trand, 1999), tacit (Hogarth, 2001), natural (Tver-
sky & Kahneman, 1983), associative (Sloman,
1996), and system 1 (Kahneman, 2003; Stanovich
& West, 2000).
Bargh and Chartrand (1999) argue that a large
portion of everyday life is determined by this
first information processing system. Insofar as
such processes are rapid, effortless, and often
quite effective, nonconscious processes serve as
“mental butlers” that conveniently manage our
tendencies and preferences (Bargh & Chartrand,
1999). As we explain below, intuition is often
associated with this system (e.g., Epstein, 2002,
Kahneman, 2003; Sloman, 1996).
The second system enables individuals to
learn information deliberately, to develop ideas,
and to engage in analyses in an attentive man-
ner. This system has been referred to by various
names, including rational (Epstein, 2002; Epstein
et al., 1996; Pacini & Epstein, 1999), intentional
(Bargh & Chartrand, 1999), deliberate (Hogarth,
2001), extensional (Tversky & Kahneman, 1983),
rule based (Sloman, 1996), and system 2 (Kahne-
man, 2003; Stanovich & West, 2000). Rational de-
cision-making models, which have garnered the
lion’s share of research on managerial decision
making, utilize this system of information pro-
cessing.
Drawing on the conceptual foundation pro-
vided by dual processing theories, we now turn
to the concept of intuition. Like other authors, we
view the process of intuition as relating to the
domain of the “nonconscious” information pro-
cessing system (e.g., Epstein 1990, 1994, 2002;
Kahneman, 2003). However, in making this case,
we also stress that not all nonconscious opera-
tions are fundamental components of intuition
itself. We have two primary reasons for differ-
entiating intuition from any given nonconscious
system depicted in dual processing theory. First,
the nonconscious systems in dual processing
theories typically involve a larger group of phe-
nomena than are central to intuition. For exam-
ple, research on the nonconscious system has
often focused on learning processes. However,
as we will argue, intuitive processes pertain
less to learning and more to how learned infor-
mation is accessed and used. We view learning
as an input to intuition effectiveness, but do not
see intuition as a learning process per se. Sec-
ond, our focus on both processes and outcomes
of intuition differentiates our work from tradi-
tional research on nonconscious systems, such
as that on the experiental system, which has
focused nearly exclusively on processes only.
Specifically, we conceptualize intuition both by
its process (which we refer to as intuiting), as
well as its outcome (which we term intuitive
judgments).
In constructing a definition of the construct,
we build on and bridge work in psychology,
philosophy, and management; our focus is on
those aspects of intuition that are common and
central to all three. Specifically, our review of
the various literature on intuition has tended to
converge on four characteristics that make up
the core of the construct: intuition is a (1) non-
conscious process (2) involving holistic associa-
tions (3) that are produced rapidly, which (4)
result in affectively charged judgments. We ex-
plore these characteristics in detail below.
Intuiting Is Nonconscious
One of the defining characteristics of intuitive
processing is that it is nonconscious
1
—it occurs
outside of conscious thought. Jung, for example,
defined intuition as “that psychological function
which transmits perceptions in an unconscious
way” (1933: 567–568). Simple perceptions, how-
ever, are not the only type of information that is
transmitted through this means. The noncon-
scious processing of information can occur at
various levels of sophistication (Epstein, 2002;
Pacini & Epstein, 1999), and intuiting can involve
the processing of more complex information
than perceptions. On this point, Epstein and Pa-
cini make the following observation about the
nonconscious, experiential system:
At its lower reaches, it [the experiential system] is
a relatively crude, albeit efficient, system for au-
tomatically, rapidly, and effortlessly processing
1
This characteristic of intuition has been called “uncon
-
scious,” “subconscious,” “preconscious,” and “noncon-
scious” (Epstein, 1994; Hogarth, 2001; Jung, 1933; Reber, 1992;
Simon, 1987). However, each of these terms has slightly dif-
ferent meanings (see Kihlstrom, 1987, for a review). For the
sake of parsimony, we refer to what each of these terms has
in common: they are nonconscious.
36 JanuaryAcademy of Management Review
information while placing minimal demands on
cognitive resources. At higher reaches . . . the ex-
periential system can be a source of intuitive
wisdom and creativity (1999: 463).
In further clarifying the connection between
nonconscious processing and intuition, we re-
emphasize the distinction between intuitive pro-
cesses and outcomes. While the outcomes of
intuiting, intuitive judgments, are clearly acces-
sible to conscious thinking, how one arrives at
them is not. Hence, there is “no awareness of the
rules of knowledge used for inference” during
intuiting (Shapiro & Spence, 1997: 64). Similarly,
Osbeck writes that intuition, from a philosophi-
cal perspective, involves direct apprehension
that is “not mediated by other reasoning or rep-
resentation” (2001: 123). As we discuss below,
this quality differentiates intuition from insight.
Intuiting Involves Making Holistic Associations
A second characteristic of intuiting is that it
involves a process in which environmental stim-
uli are matched with some deeply held (noncon-
scious) category, pattern, or feature. Historically,
this matching process has gone by numerous
names, including awareness (Wild, 1938), appre-
hension (Rorty, 1967), recognition (Simon, 1996),
and seeing (Osbeck, 1999). More recently, Raidl
and Lubart described intuition as involving a
process of “linking disparate elements of infor-
mation” (2000-2001: 219). This linking together of
elements is why many refer to intuiting as being
associative (Epstein, 1994; Epstein et al., 1996;
Kahneman, 2003). Further, because intuiting in-
volves recognizing features or patterns (e.g.,
Klein, 1998), rather than making connections
through logical considerations, it has also been
conceptualized as holistic (Epstein, 1990; Sha-
piro & Spence, 1997). As such, Bowers, Regehr,
Balthazard, and Parker speak of intuition as in-
volving a “perception of coherence (pattern,
meaning, structure)” (1990: 74). In sum, since the
associations in intuition refer to the recognition
of patterns or structures, we refer to this aspect
of intuiting as making holistic associations.
Psychologists and other decision science
scholars suggest that, in making holistic asso-
ciations, individuals nonconsciously map stim-
uli onto cognitive structures or frameworks. Re-
search has typically focused on one of two types
of cognitive structures. The first and most com-
mon line of research examines the role of rela-
tively simple cognitive structures, such as heu-
ristics, in the formation of intuitive judgments
(Bazerman, 1986; Bodenhausen, 1990; Kahneman,
Slovic, & Tversky, 1982; Kahneman & Tversky,
2000; Tversky & Kahneman, 1983). As we will
argue below, this line of research has often con-
cluded that intuitive decision making is inferior
to rational decision-making models.
A second line of inquiry suggests that intuit-
ing may involve the use of more complex, but
still not consciously accessible, cognitive struc-
tures. For instance, drawing on the work of Agor
(1989), Shirley and Langan-Fox (1996: 573) have
argued that intuiting results from a process of
recognition and retrieval in which large num-
bers—perhaps several thousands— of chunks or
patterns stored in long-term memory are ac-
cessed without conscious effort. This stream of
research, focusing largely on the intuitions of
experts (e.g., surgeons making life-and-death
decisions, chess masters engaging in competi-
tion), contends that experts possess highly so-
phisticated, nonconscious cognitive structures
that permit rapid and accurate responses to
highly demanding situations (Dreyfus & Drey-
fus, 1986; Klein, 1998, 2003; Prietula & Simon,
1989; Simon, 1987, 1992, 1996; Simon & Chase,
1973). Such research has tended either to favor
the use of intuition over more rational models or
to position intuition as a useful complement to
analytical thinking. Thus, intuition is seen as a
subset of the entire population of decision-
making approaches successfully used by ex-
perts. However, common to both the heuristic
and expert decision-making perspectives is the
view that individuals nonconsiously make ho-
listic associative connections between the stim-
uli they encounter and their underlying cogni-
tive structures in the process of intuiting.
Making holistic associations is not only a
characteristic of intuiting but also speaks to one
of intuition’s advantages over other decision-
making approaches: our nonconscious ability to
make such categorical connections is greater
than our ability to mimic it consciously. As
Raiffa (1968) argues in the quote that opens our
paper, such ability may be undermined by our
attempts to use more conscious, or rational,
means of making judgments and decisions. It
has even been stated that, in some instances,
rational analysis may prevent people from “see-
ing the obvious” (Pirsig, 1974: 196). As noted
above, conscious thinking appears to rely on
2007 37Dane and Pratt
connections made through a slow and effortful
analysis (Epstein, 1990, 1994; Kihlstrom, 1987).
These properties contrast sharply with the ho-
listic and associative qualities of the experien-
tial system. All told, it comes as little surprise
that intuiting is perhaps better suited than ra-
tional methods to integrate wide-ranging stim-
uli into usable categories of information.
Intuiting Is Fast
A third characteristic of the intuition process,
and the one that has seemed to spark the most
interest among both managers and academics,
is its speed (Bastick, 1982; Burke & Miller, 1999;
Kahneman, 2003; Khatri & Ng, 2000; Myers, 2002).
Although there has been some debate about
whether intuiting is always fast (see Hogarth,
2001), the vast majority of researchers view intu-
iting as quite fast— especially when compared
with the use of rational decision-making pro-
cesses. The centrality of “speed” is seen in the
concepts of intuition used by philosophers (see
Wild, 1938, for a review). Rorty for example,
views this process as involving “immediate ap-
prehension” (1967: 74). Osbeck, in a newer re-
view of the philosophical roots of intuition,
views speed as a defining aspect of intuiting
and notes that Locke and Hume viewed intuition
as “the immediate perception of connection be-
tween ideas” (2001: 121).
This emphasis on speed is echoed in other
more recent perspectives on intuition. Research-
ers who view intuiting—and nonconscious infor-
mation processing more generally—as an evo-
lutionary precursor to more conscious and
analytical thinking point to the advantages of
having an information processing system that
responds quickly to environmental stimuli (Ep-
stein, 1994; Haidt, 2001; Reber, 1992). Kihlstrom
(1987: 1447) similarly argues that processing in-
formation nonconsciously does not require at-
tention and, thus, does not produce the same
information “bottlenecks” that conscious pro-
cessing does.
From a managerial perspective, the speed of
intuiting is not only taken for granted but is
often seen as a primary motivator for develop-
ing and employing intuition at work (Agor, 1986;
Burke & Miller, 1999; Khatri & Ng, 2000; Klein,
2003). Moreover, the speed characteristic of intu-
ition has long been recognized by management
theorists. Barnard proclaimed intuition to be a
component of “non-logical mental processes”
that are capable of handling a “mass of experi-
ence or a complex of abstractions in a flash”
(1938: 305). March and Simon echo Barnard’s
view, asserting that one of the hallmarks of in-
tuiting, in addition to its nonconscious nature, is
its speed:
The distinctive earmarks of intuition are rapid
response (a matter of seconds) and inability of the
respondent to report a sequence of steps leading
to the result— even denial of awareness of such
steps.... what impresses observers about intu-
ition is that responses, especially those of ex-
perts, are frequently correct even though they
seem to have required almost no processing time
or effort (1993: 11).
Intuiting Results in Affectively Charged
Judgments
Although “intuiting” refers to a unique way of
processing information, individuals often use
intuition as a noun—as the product of such pro-
cessing. To differentiate the process and product
facets of intuition, we use the term intuitive
judgment to signify intuition in its outcome
state.
We make reference to “judgments” rather than
some other outcome state, given the strong as-
sociation between intuition and problem solv-
ing. To illustrate, pioneering works in manage-
rial problem solving (Barnard, 1938; Simon, 1987,
1996) and classic works on decision making
(Kahneman et al., 1982; Tversky & Kahneman
1974, 1983) focus explicitly on how individuals
use intuiting to solve problems. This problem-
focused treatment of intuition is echoed in the
work of Policastro (1999), who holds that intu-
ition is a type of knowledge used to orient deci-
sion making.
We further clarify intuitive judgments as “af-
fectively charged,” given that such judgments
often involve emotions. Chen and Chaiken (1999:
87), for example, suggest that the presence of
“cognitive feelings” may indicate that heuristic
processes are operating. And, more generally,
synonyms for intuition, such as “gut feelings”
and “gut instincts” (Hayashi, 2001; Shapiro &
Spence, 1997), as well as feeling in our marrow”
(Barnard, 1938: 306), reflect an affective compo-
nent to intuitive judgments. Thus, one way that
we identify a judgment as intuitive is that it is
accompanied by affect. For example, Agor (1986)
notes that as executives make intuitive judg-
38 JanuaryAcademy of Management Review
ments, they often experience excitement and
harmony. And Shirley and Langan-Fox define
intuitions as “feelings of knowing” (1996: 564).
The coupling of affect and intuitive judgments
has a long intellectual history. At a very basic
level, these judgments may be thought of as
affective because they are detached from ratio-
nality. Thus, rationality is often associated with
the “head” and intuition with the “heart”—a
common divide in philosophy. However, recent
research suggests other possibilities. To begin
with, intuitive judgments may be triggered by
emotions and affect. Positive mood, for example,
has been linked to an increase in the use of
intuition and a decrease in more rational ap-
proaches to decision making (see Weiss & Cro-
panzano, 1996, for a review). Similarly, manag-
ers often view affect as an important input to
intuition and describe intuitions as “affect-
initiated decisions” (Burke & Miller, 1999). And
Hogarth argues that “emotion and affect can,
therefore, be important inputs to intuitive
thought in the sense that they can induce re-
sponses without corresponding awareness”
(2001: 61).
Moreover, emotions and affect may also play
a role in the intuition process itself and, thus,
result in affect-laden judgments. Epstein (1990,
1994, 2002), for example, ties emotion and intu-
ition through the experiential information pro-
cessing system described above by suggesting
that all processes in the nonconscious (experi-
ential) system are emotionally driven. Bastick
makes a similar argument, suggesting that “in-
tuitive information is accessed through appro-
priate feelings” (1982: 279). Epstein further ar-
gues that the cognitive frameworks in the
experiential system, which he refers to as sche-
mas, are “inductively derived from emotionally
significant experiences” (1990: 170).
Intriguingly, research in neuroscience has
suggested a link between intuition and affect
via activation of basal ganglia in the human
brain (see Lieberman, 2000, for a review). This
line of investigation has shown that basal gan-
glia are engaged through positive affective
stimuli and positive emotional experience, and
these same neural mechanisms play a central
role in engendering the nonconscious associa-
tions that spur intuitive judgments. In essence,
both intuitions and emotional appraisals ap-
pear to arise through highly similar neurologi-
cal pathways. Taken together, evidence from or-
ganizational, cognitive, and neurological
psychology suggests that affect and emotions
are an integral component of intuitive judg-
ments.
In sum, research suggests that affect is asso-
ciated both with the intuiting process and with
intuition as an outcome. We therefore use the
term affectively charged to denote the affective
tenor of intuitive judgments, as well as to reflect
how such judgments were generated (i.e., were
“charged” via an affective process).
Other Elements Associated with Intuition
Our central characteristics of intuition are
based on their commonality to definitions
across philosophy, psychology, and manage-
ment. In addition to their commonality, they also
appear to be the most “core” features. Conse-
quently, we have excluded some additional
characteristics of intuition since they appear to
result from the core characteristics we suggest.
To illustrate, several conceptualizations of intu-
ition involve a feeling of certitude (Shirley &
Langan-Fox, 1996) and a perception that one’s
intuitions are correct— despite the lack of ratio-
nal analysis (Bruner, 1962; Wescott & Ranzoni,
1963). This characteristic, however, likely is due
to the affective and associative properties we
have discussed. As noted, Agor (1986) has ar-
gued that as executives make intuitive judg-
ments, they often experience strong and positive
emotions (e.g., excitement, harmony). Such pos-
itive feelings may, in turn, lead to an enhanced
sense of confidence in an individual’s own judg-
ments (see Tiedens & Linton, 2001, for a discus-
sion). Thus, if I feel good about a judgment, I
must be right about it.
In addition, the holistic, associative properties
of intuition involve recognizing patterns or other
linkages among disparate stimuli. Hence, phi-
losophers have linked intuition with “seeing” or
“recognizing” an answer (Osbeck, 1999, 2001).
Because intuition involves “recognizing” a solu-
tion (Simon, 1996), it is likely that individuals
will have more confidence in their intuition than
in a “wild guess,” which is often made when no
solution is recognizable.
2
2
However, we should be clear that just because an indi
-
vidual has confidence that the solution is a good one does
not mean that the individual will adopt the solution. That is,
2007 39Dane and Pratt
As noted earlier in the paper, we have also
excluded characteristics ascribed to intuition
that seem unique to a particular disciplinary
domain. For example, intuition is associated
with both experiential (Epstein 1990, 1994, 2002)
and system 1 (Kahneman, 2003; Stanovich &
West, 2000) processes in dual processing theo-
ries. Both of these processes are associated with
additional characteristics (e.g., presence of
“vibes,” “seized by emotions,” and “pleasure
driven”) that do not necessarily accord with the
core features of intuition discussed above. Be-
cause not all of these characteristics have tradi-
tionally been associated with intuition, addi-
tional validation is needed before viewing them
as core and central to the concept.
Intuition Defined and Delineated
To summarize, intuitions are affectively
charged judgments that arise through rapid,
nonconscious, and holistic associations. These
characteristics not only capture what we mean
by intuition but also help clarify which types of
decision-making processes are intuitive and
which are not. To illustrate, of all other ways of
making judgments and decisions reviewed here,
only the nonconscious use of heuristics and in-
ternalized patterns of information fall within
what we call intuition. In contrast, we believe
that rational decision making is highly dissim-
ilar to intuition. The former involves the use of
systematic procedures designed to thoroughly
assess all pertinent information, evaluate costs
and benefits, and, ultimately, make a decision
based on conscious deliberation (see Janis &
Mann, 1977, for more detail on rational decision-
making models). In short, it is highly analytic
and relies on logical connections. Moreover, as
we have discussed, rational decision making
involves a completely different type of informa-
tion processing system than the experiential
system utilized in intuition. In brief, intuition
differs from more rational models of decision
making in that it is (1) nonconscious, (2) holistic,
(3) associative, and (4) faster.
In addition, intuition differs from other deci-
sion-making approaches that are typically
viewed as “fast.” For example, intuition is sim-
ilar to guessing only in terms of its speed.
Guessing neither involves affectively charged
judgments nor requires making associations
through nonconscious information processing. It
also lacks the secondary outcome associated
with these two characteristics of intuition: certi-
tude. Intuition is also different from instincts
and insights—terms often used synonymously
with intuition in everyday speech. We follow the
lead of Hogarth (2001) and Epstein (2002) in ar-
guing that biological instincts (e.g., shutting
one’s eyes in the presence of bright light) are
“hardwired” responses or autonomic reflexes to
stimuli. Thus, instincts are innate capabilities
that originate outside the experiential process-
ing system.
Next, insights or “sudden unexpected
thoughts that solve problems” (Hogarth, 2001:
251) may involve experiential processing in the
form of an “incubation period.” However, unlike
intuition, insight is often a lengthy process that
begins with deliberate, analytical thinking that
precedes the incubation period (Hogarth, 2001;
Shirley & Langan-Fox, 1996). Further, when a
solution is gleaned through insight, one “sud-
denly becomes aware of the logical relations
between a problem and the answer” (Lieber-
man, 2000: 110; see also Sternberg & Davidson,
1995, for a more comprehensive treatment of in-
sight). This suggests another distinction be-
tween insight and intuition: in the former one
consciously becomes aware of the logical con-
nections supporting a particular answer or solu-
tion, whereas in the latter one is unable to con-
sciously account for the rationale underlying the
judgment that has arisen.
CONDITIONS INFLUENCING THE
EFFECTIVENESS OF INTUITIVE
DECISION MAKING
Thus far, we have focused largely on the pro-
cess of intuiting and how this process differs
from the processes that guide other forms of
decision making, such as rational analysis. We
now turn our attention more fully to the products
of intuiting—intuitive judgments—and the con-
ditions that explain when these judgments are
most effective.
In research that has focused on the effective-
ness of intuitive decision making, disagreement
abounds as to whether intuitive judgments lead
to effective decisions. To begin with, a substan-
individuals may still distrust intuitive means, regardless of
the veracity of the solution.
40 JanuaryAcademy of Management Review
tial body of research suggests that the use of
intuition in decision making is generally infe-
rior to other, more rational models (e.g., Dawes,
Faust, & Meehl, 1989; Kahneman et al., 1982;
Meehl, 1954; Schoemaker & Russo, 1993). In con-
trast, a growing body of literature suggests that
for certain people, under appropriate conditions,
intuition may be as good as, or even superior to,
other decision-making approaches (Blattberg &
Hoch, 1990; Hammond, Hamm, Grassia, & Pear-
son, 1987; Khatri & Ng, 2000).
To reconcile these divergent perspectives, we
turn to an exploration of the conditions that in-
fluence whether intuition is effective as a deci-
sion-making approach. Our review suggests
that two broad sets of factors influence intuition
effectiveness: (1) domain knowledge factors and
(2) task characteristics. These factors are de-
picted in Figure 1.
First, one of the primary differences between
research on the effectiveness of intuition con-
ducted by researchers interested in heuristics
and those interested in expert decision making
pertains to the relative emphasis attached to the
existence and accumulation of domain knowl-
edge. While some scholars have tended to focus
primarily on heuristics and heuristic biases that
affect most individuals, regardless of their do-
main knowledge, others have focused more ex-
tensively on expert knowledge structures and
how such structures influence the quality of in-
tuitive decision making within specific do-
mains. We seek to integrate these bodies of
work by examining how various degrees of do-
main knowledge, ranging from simple heuris-
tics to sophisticated “expert” schemas, may in-
fluence the effectiveness of intuition as a
decision-making approach in a given domain.
We also examine how expert schemas may form
via implicit and explicit learning.
Second, research suggests that intuition is
good in some situations but not in others. For
example, research concerned with heuristic bi-
ases has focused on how the use of intuition to
solve highly structured math and probability
problems can lead to highly inaccurate solu-
tions. However, as noted in our introduction, in-
tuition may be most appropriate for “executive”
decisions, which involve strategy, investment,
and human resource management issues. These
types of decisions are far less structured than
math problems. We discuss each set of intuition
effectiveness factors below.
FIGURE 1
Factors Influencing the Effectiveness of Intuitive Decision Making
2007 41Dane and Pratt
Domain Knowledge Factors: Schemas
An individual’s knowledge of a domain is re-
flected in the schemas he or she has about that
domain. We use the term schema generally to
denote various cognitive structures that repre-
sent “knowledge about a concept or type of stim-
ulus, including its attributes and the relations
among those attributes” (Fiske & Taylor, 1991:
98). We suggest that a primary means for deter-
mining when intuition will be effective involves
the nature of schemas employed by the intuiter.
As we discuss below, schemas may be relatively
simple and contain little domain knowledge
(i.e., are domain independent), as in the case of
heuristics (Denes-Raj & Epstein, 1994; Tversky &
Kahneman, 1974). Alternatively, schemas may
be complex and contain much domain knowl-
edge, as in the case of experts’ cognitive maps
(Simon, 1996).
Heuristic schemas. In a well-established body
of research in psychology and the decision sci-
ences, scholars have argued that intuition in-
volves the use of heuristics—mental shortcuts
that reduce the complex tasks of assessing prob-
abilities and predicting values to simpler judg-
mental operations (Tversky & Kahneman, 1974).
When presented with a problem, individuals
can use heuristics to draw associations among
multiple stimuli, to focus on critical information,
and to develop a perception of the right answer
or best route by which to proceed.
While heuristics are often useful for quickly
assessing probabilities and making decisions
in uncertain situations, they may also lead to
severe and systematic errors (Tversky & Kahne-
man, 1974). Indeed, a large portion of decision-
making literature over the past three decades
has focused on heuristic-based judgmental er-
rors. Such studies suggest that while the appeal
of heuristic-based intuition is strong—and that
individuals will often choose to use heuristics,
even when they know it is not rational to do so
(Denes-Raj & Epstein, 1994)—rational processes
for problem assessment are less subject to ran-
dom inconsistencies and systematic distortions
(Schoemaker & Russo, 1993).
We argue that heuristics and other simple
cognitive frameworks are likely to lead to inac-
curate intuitive judgments because they tend to
be “simple” and, thus, may be inadequate to
process complex environmental stimuli. This ar-
gument mirrors the bulk of research on the
shortcomings of heuristics and stereotypes. It
essentially takes a “requisite variety” approach
that the complexity of schemas should match
environmental complexity in order to be effec-
tive (see Weick, 1995). We further suggest that
heuristics may be more domain independent
and may be commonly applied (inappropriately)
across various domains. With regard to domain
independence, the relative lack of domain sen-
sitivity diminishes the effectiveness of intuitive
decision making as simple “rules of thumb” are
indiscriminately applied to an inappropriately
large number of problem domains. With regard
to the frequency of their use, research suggests
that individuals who lack adequate domain
knowledge may have inflated self-assessments
of their own ability to make accurate judgments
(Kruger & Dunning, 1999) and, thus, may have a
higher propensity to apply simple schemas
across a wide variety of situations.
Expert schemas. While the heuristic-based
view of intuition has dominated research on in-
tuition and problem solving, a growing body of
research suggests that that “experts” can make
highly accurate intuitive decisions (Dreyfus &
Dreyfus, 1986; Klein, 1998, 2003; Prietula & Simon,
1989; Simon, 1987, 1992, 1996). We argue that the
main difference between these bodies of re-
search lies in the nature of the schemas of ex-
perts, which are (1) highly complex and (2) do-
main relevant.
Simon and Chase’s (1973) foundational article
on the memory storage patterns of chess mas-
ters and grandmasters provides an early exam-
ple illustrating the role of complex schemas in
guiding the decisions of experts. This study re-
vealed that chess masters are able to recognize
at least 50,000 different configurations of chess
pieces on sight, which are stored or “chunked”
as familiar patterns in long-term memory. When
presented with an arrangement of pieces on a
chessboard, chess masters almost immediately
recognize both the patterns of the chess pieces
and the appropriate strategic moves for the
given situation. Consequently, grandmasters in
speed chess competitions can effectively play
several games simultaneously, even when they
are only allowed a few seconds per move (Simon
& Chase, 1973).
Broadening these findings beyond the chess
domain, “expert” intuition may be aptly de-
scribed as a “pattern matching” process,
whereby information is encoded and chunked
42 JanuaryAcademy of Management Review
into patterns, stored in schemas, and then
equated with environmental stimuli (Simon,
1996). As Prietula and Simon note when discuss-
ing the difference between a novice and experi-
enced foreman:
In fact, the veteran does not scan the environment
and process information any faster than the inex-
perienced foreman; rather, he (or she) has learned
to grasp the meaning of certain patterns of oper-
ations and activity on the plant floor. In a sense,
the foreman does not need to think about this
information; he simply reacts to it (1989: 121).
Scholars advocating for the effectiveness of
expert or “mature” intuition (e.g., Baylor, 2001;
Blattberg & Hoch, 1990; Burke & Miller, 1999) use
the same underlying logic as Simon and his
colleagues: experts have complex cognitive
maps (or schemas) that trigger effective intuitive
judgments.
Despite the promise of these complex sche-
mas for effective decision making, an important
boundary condition applies. Because complex
schemas develop in a particular domain (one’s
area of expertise), they are more likely to lead to
effective decisions in that domain than when
used in a different domain or context. Thus, com-
plex managerial schemas may serve a manager
well at the office but may lead to inaccurate
intuitive judgments at home. This suggests that,
for intuitions to be effective, schemas must be
both complex and domain relevant.
Proposition 1: Individuals who can
bring complex, domain-relevant sche-
mas to bear on a problem are more
likely to make effective intuitive deci-
sions than those who employ heuris-
tics and simpler, domain-independent
schemas.
Domain Knowledge Factors: Learning
In addition to research on the content of sche-
mas, in a growing body of work, researchers are
exploring how individuals come to gain the
complex, domain-relevant schemas needed for
effective intuition. The literature on expertise
discussed above suggests that there may be a
learning component to developing the schemas
that underlie accurate intuitive judgments. In
particular, researchers are coming to connect
the formation of sophisticated cognitive struc-
tures to both explicit and implicit learning. We
briefly review the general relationship between
learning and the formation of complex, domain-
relevant schemas.
Explicit learning. Explicit learning occurs
when individuals are consciously aware that
changes are accruing to their underlying knowl-
edge bases (Lovett, 2002). Perhaps the most re-
searched link between explicit learning and in-
tuition has been on how experts, such as chess
grandmasters, come to attain mastery over a
particular domain. The general argument pos-
ited in this research is that experts deliberately
develop a vast repertoire of patterns in memory
that allows them to respond to contingencies in
an automatic and proficient manner (Simon,
1996; Simon & Chase, 1973). Thus, we suggest a
general relationship between explicit learning
and intuition effectiveness.
Proposition 2: Explicit learning will
positively influence the effectiveness
of intuitive decision making through
the formation of complex, domain-
relevant schemas.
However, learning is heightened with certain
types of practice. Research suggests three pri-
mary elements of “good” practice: duration, rep-
etition, and feedback. First, development peri-
ods for mastery tend to be long. With respect to
the relationship between practice and expert
intuition in management, Khatri and Ng argue
that, for managerial intuition to be effective, it
“requires years of experience in problem solv-
ing and is founded upon a solid and complete
grasp of the details of the business” (2000: 58).
More specifically, research suggests that a ten-
year period of intense preparation appears nec-
essary for achieving expertise in a domain (Er-
icsson & Charness, 1994; Ericsson, Krampe, &
Tesch-Ro¨ mer, 1993; Simon & Chase, 1973).
Additional characteristics of practice that
strengthen the link between explicit learning
and the development of complex, domain-
relevant schemas are repetition and feedback.
Ericsson and colleagues, for example, argue
that it is only through “deliberate practice,” in-
volving repetition and successive refinement
through concentration and immediate, accurate
feedback, that an individual will develop the
capacity to perform as an expert (Ericsson &
Charness, 1994; Ericsson & Lehmann, 1996; Erics-
son & Smith, 1991). Similarly, Hogarth (2001) ar-
gues that practice done in “kind” learning struc-
2007 43Dane and Pratt
tures will facilitate effective intuition. Kind
learning structures are those where feedback is
both relevant and exacting. Relevant feedback
is conceptualized as speedy and accurate feed-
back that enables the individual to learn to as-
sign proper causal relationships among deci-
sions, actions, and outcomes. Exacting feedback
implies a significant need for precision. A brain
surgeon, for example, has little room for error
while operating on a patient. Exacting feedback
generally leads to accurate learning because
small errors can have serious consequences.
In sum, we argue that individuals who want to
form complex, domain-relevant schemas must
engage in repetitive practice over a long period
of time. They must also receive feedback about
their performance that is both accurate and ex-
acting.
Proposition 3a: The relationship be-
tween explicit learning and the for-
mation of complex, domain-relevant
schemas will be strengthened when
individuals engage in focused, repet-
itive practice over long periods of
time.
Proposition 3b: The relationship be-
tween explicit learning and the for-
mation of complex, domain-relevant
schemas will be strengthened when
individuals perform in the presence of
“kind” learning structures (rapid and
accurate feedback and exacting con-
sequences).
Implicit learning. While explicit learning may
indeed make for more advanced and effective
intuitive decision making in some situations, a
growing body of research suggests that it may
not always be necessary for the formation of
complex, domain-relevant schemas. Instead,
schemas may develop through implicit learning.
Implicit learning refers to the process by which
one acquires—outside of one’s conscious aware-
ness—knowledge about the structure or pattern
underlying a complex stimulus environment
(Reber, 1989: 219; see also Lewicki, Hill, & Bizot,
1988; Reber, 1992; Reber, Walkenfeld, & Hern-
stadt, 1991; Seger, 1994; Stadler & Frensch, 1998).
Implicit learning differs from its external
counterpart in important ways. Not only are in-
dividuals unaware that such learning is occur-
ring, but research suggests that implicit knowl-
edge is stored in the brain differently from other
types of knowledge. To illustrate, knowledge ac-
quired via implicit learning will be retained
when an individual suffers from amnesia, even
when more explicit knowledge is lost (Seger,
1994). This suggests that although explicit and
implicit learning can occur simultaneously in a
given context, implicit learning involves a dif-
ferent process of knowledge acquisition and
storage.
Both implicit learning and intuition have been
linked to the nonconscious processing system
described earlier. Just as intuition involves a
nonconscious, experiential processing of infor-
mation stored in memory, implicit learning re-
fers to a similar nonconscious process of knowl-
edge acquisition. Reber (1989) has tied implicit
learning to “intuitive knowledge” and argues
that it is through implicit learning that individ-
uals come to form the complex cognitive struc-
tures necessary for intuitive judgments and de-
cisions. In support of this claim, researchers
have linked implicit learning to the acquisition
of grammar rules (Reber, 1989; Reber et al., 1991)
and spatial processing algorithms (e.g., Lewicki
et al., 1988), as well as to other types of knowl-
edge acquisition, such as covariation and puzzle
learning (see Seger, 1994, for a review of implicit
learning tasks).
We believe that implicit learning may result
in the complex, domain-relevant schemas nec-
essary to engender the effective use of intuitive
judgments in managerial decision making. To
illustrate, the veteran foreman noted earlier by
Prietula and Simon (1989), who “has learned to
grasp the meaning of certain patterns of opera-
tions and activity on the plant floor,” may have
developed this proficiency not simply through
explicit learning—since it is unlikely that the
foreman “deliberately practiced” observing op-
erations on the plant floor— but, rather, through
implicit learning as well.
Proposition 4: Implicit learning will
positively influence the effectiveness
of intuitive decision making through
the formation of complex, domain-
relevant schemas.
It is important to note that just as there are
factors that strengthen the relationship between
explicit learning and the formation of complex,
domain-relevant schemas, there are also factors
that strengthen the link between such schema
44 JanuaryAcademy of Management Review
formation and implicit learning. In particular,
while implicit learning is largely automatic,
there is some research that suggests that indi-
viduals may be able to “process stimuli in ways
that allow implicit learning to function more
effectively” (Seger, 1994: 176). Such control may
be afforded by consciously paying attention to
the stimuli in question (Carlson & Dulany, 1985;
Nissen & Bullemer, 1987). Attention, however, is
not focused on attempts to deliberately decipher
cause and effects. As Reber’s research has
shown (Reber, 1976; Reber, Kassin, Lewis, & Can-
tor, 1980), attention directed toward such “hy-
pothesis testing” will lead to substandard per-
formance. Rather, individuals should focus on
stimuli as a whole. For example, while manag-
ers may be unable to consciously notice those
rewards that will best motivate individuals dur-
ing a time of crisis (a type of covariation learn-
ing), they may facilitate the implicit learning of
these patterns by paying attention to both re-
wards and employees during the crisis. Thus,
we build from this body of research and posit
the following.
Proposition 5: The relationship be-
tween implicit learning and the for-
mation of complex, domain-relevant
schemas will be enhanced when indi-
viduals focus attention on the stimulus
environment.
Returning to our initial focus on speed versus
accuracy, we suggest that intuitions are more
likely to be effective when they tap into com-
plex, domain-relevant schemas than when they
involve heuristics. These complex, domain-
relevant schemas, in turn, are more likely to be
developed when individuals engage in focused
and repetitive practice over a long period of
time, when they operate in kind learning envi-
ronments, and when they focus their attention
on the stimulus environment.
Task Characteristic Factors
In addition to factors surrounding the domain
knowledge of the intuiter, evidence suggests
that problem structure may also impact the ef-
fectiveness of intuitive decision making. Accord-
ing to Shapiro and Spence (1997), problems lie
on a continuum of structuredness. At the less
structured end of this continuum lie such prob-
lems as merger and acquisition decisions, new
product planning, and corporate strategy forma-
tion. These unstructured problems are condu-
cive to intuition because of the absence of well-
accepted decision rules for dealing with such
situations. Echoing this argument, other re-
searchers have argued that analytical strate-
gies that work well for problems that are well-
defined are much less effective for ill-defined
problems (Claxton, 1998; Hayashi, 2001). Intu-
ition, as a holistically associative process, may
actually help to integrate the disparate ele-
ments of an ill-defined problem into a coherent
perception of how to proceed. As Shapiro and
Spence (1997) further note, intuition is often more
effective than analysis in enabling individuals
to develop an understanding of the structure of a
complex system. For this reason, intuitive judg-
ments are said to become more effective relative
to rational analysis as a problem becomes in-
creasingly unstructured.
Intellective versus judgmental tasks. We ar-
gue that the notion of “problem structure” is
captured in the distinction between intellective
and judgmental tasks (Laughlin, 1980; Laughlin
& Ellis, 1986; McGrath, 1984). According to
Laughlin, intellective tasks involve a “definite
objective criterion of success within the defini-
tions, rules, operations, and relationships of a
particular conceptual system,” whereas judg-
mental tasks involve “political, ethical, aes-
thetic, or behavioral judgments for which there
is no objective criterion or demonstrable solu-
tion” (1980: 128). Laughlin (1980) views the intel-
lective/judgmental distinction as a continuum,
as opposed to a strict dichotomy.
While intuition theorists have not referred
specifically to intellective and judgmental
tasks, research has shown that intuition may be
most effective for moral judgments (Haidt, 2001),
aesthetic ratings (Hammond et al., 1987; Wilson
& Schooler, 1991), and the like. Further, research
has shown that intuition is relatively weaker
than rational analysis for tasks involving defi-
nite objective criteria (MacGregor, Lichtenstein,
& Slovic, 1988; McMackin & Slovic, 2000). Thus, it
appears that intuitive judgments may be more
effective than rational approaches to decision
making on judgmental tasks, whereas the con-
verse is true for intellective tasks. This suggests
the following proposition.
Proposition 6: As the problem structure
associated with a task becomes more
2007 45Dane and Pratt
judgmental, the effectiveness of intui-
tive decision making will increase.
Returning again to our discussion of speed ver-
sus accuracy, intuition is most likely to effec-
tively manage this trade-off when it is brought
to bear on judgmental tasks.
Factors influencing task characteristics: Envi-
ronmental uncertainty. While we showed earlier
that the domain knowledge factors concerning
intuition effectiveness are rooted in a sizable
body of work on explicit and implicit learning,
relatively little has been said about concepts
that may be linked to intuition effectiveness and
task characteristics. The work that does exist
suggests that the type of environment in which
an organization operates may influence the ef-
fectiveness of intuitive decision making among
managers (Agor, 1986; Khatri & Ng, 2000; Shapiro
& Spence, 1997). In one of the few empirical
studies in this area, Khatri and Ng (2000) found
moderate support for their thesis that, during
times of environmental uncertainty, the use of
intuitive decision making among executives re-
sults in greater organizational performance.
Unfortunately, based on this study alone, it is
difficult to conclude why this result was found.
However, one likely possibility is that during
times of environmental instability, managers
have to collect and sort through a large, and
often incomplete, amount of data in a short time
(Khatri & Ng, 2000). That is, decision-making
tasks in these environments may be nonroutine.
Building on this perspective, we suggest that
environmental uncertainty results in a shift
away from structured problems and standard
operating procedures and is likely to result in a
multitude of “plausible alternative solutions,”
rather than a single objective criterion for suc-
cess. Under such conditions, decision-making
scenarios may move from the intellective end of
the task continuum toward the judgmental end.
Thus, the positive relationship found between
environmental uncertainty and the effective-
ness of intuitive decision making may be medi-
ated by the task characteristics described
above.
Proposition 7: The relationship be-
tween environmental uncertainty and
the effectiveness of intuition is medi-
ated by judgmental task characteris-
tics.
Possible Relationships Among Effectiveness
Factors
In considering the two broad sets of factors
that we view as determining the effectiveness of
intuitive decision making, we have said little
about whether there are any connections be-
tween these two sets of factors. That is, we have
yet to discuss whether domain knowledge fac-
tors are in some way tied to task characteristic
factors in the model we have proposed (Figure
1). While a variety of linkages may be possible,
a highly likely possibility concerns linking the
most effective domain knowledge characteris-
tic— expertise—with the most desirable type of
task for intuition—judgmental.
As noted above, the individuals most capable
of making the associations that trigger accurate
intuitive judgments are those who possess com-
plex, domain-relevant cognitive structures
within a particular domain. Such individuals
may be referred to as experts (Chi, Glaser, &
Farr, 1988; Dreyfus & Dreyfus, 1986; Prietula &
Simon, 1989; Shanteau & Stewart, 1992). In Fig-
ure 1 we identify a link between expertise and
intuition effectiveness via the direct connection
drawn from complex, domain-relevant schemas
to the effectiveness of intuitive decision making.
However, this argument raises the question of
whether the relationship between schema type
and intuition effectiveness is always of a simi-
lar magnitude across various types of tasks. Ev-
idence suggests that the answer to this question
is not necessarily.
As we have suggested, the holistic and asso-
ciative properties of intuition may help to inte-
grate the disparate elements of an ill-defined, or
judgmental, problem into a coherent perception
of how to proceed. Experts may be especially
well-suited to draw these holistic associations
on judgmental tasks because the sophistication
of their cognitive structures may permit them to
integrate the components of an ill-structured
problem with relative ease. Such an interaction
is implied in many of the examples in the be-
ginning of our paper. For example, the develop-
ment of the Dodge Viper and the prime-time
launch of Who Wants to Be a Millionaire both
involved highly experienced executives faced
with ill-structured tasks.
In contrast, well-defined or intellective tasks
may not call for the same extent of holistic and
associative connections. As argued above, such
46 JanuaryAcademy of Management Review
tasks may be approached more effectively
through analytical procedures. Moreover, re-
search suggesting that the intuition of experts is
ineffective has tended to examine decision mak-
ing involving highly structured tasks (Bazerman,
1986; Dawes et al., 1989; Kahneman et al., 1982).
Hence, we argue that our posited link between
complex, domain-relevant schemas (as pos-
sessed by experts) and effective intuition may
be stronger when experts are working on judg-
mental tasks. Accordingly, we suggest the fol-
lowing.
Proposition 8: The relationship be-
tween complex, domain-relevant sche-
mas and the effectiveness of intuitive
decision making is moderated by task
characteristics such that as tasks be-
come more judgmental, the strength of
the relationship will increase.
DISCUSSION AND IMPLICATIONS
We have attempted to better delineate what
intuition is
3
and when people are likely to use it
well. In this effort we have synthesized a large
and disparate body of research on intuition and
moved the field forward through the develop-
ment of several theoretical propositions. How-
ever, it is sometimes only in taking stock of what
is known that it becomes clear what is not.
While this review helps address many issues
regarding intuition, it raises several other is-
sues, and several additional avenues for re-
search, as well. Our comments in this section
concern the issues we feel are most critical to
bear in mind when conducting further research
on intuition.
Intuition “Use” Factors
While we have focused extensively on the fac-
tors contributing to the effectiveness of intuitive
decision making, we have said little about the
conditions in which individuals tend to trust in
or rely on their intuitions. Intuition “use” factors
are critical, because even if we can foster intu-
itions that are accurate (e.g., through complex,
domain-relevant schema), these intuitions must
be “trusted” if they are to be followed. Con-
versely, intuitions that develop through heuris-
tics and more simplistic schemas may, in many
circumstances, be sufficiently compelling to be
used as primary inputs to decision making, de-
spite their relative imprecision and dubious ac-
curacy.
Research on intuition suggests a variety of
conditions in which we are most likely to use our
intuitions rather than to invoke and rely on ra-
tional analysis. Among the most common are
the presence of positive moods (e.g., Bless,
Bohner, Schwarz, & Strack, 1990; Elsbach & Barr,
1999; Isen, Means, Patrick, & Nowicki, 1982;
Ruder & Bless, 2003; Schwarz, Bless, & Bohner,
1991) and the role of stable individual differ-
ences in thinking style (Briggs & Myers, 1976;
Pacini & Epstein, 1999; see also Jung, 1933). How-
ever, there may be other, less explored use fac-
tors that merit further attention.
To illustrate, research might explore the role
of the body in intuition. Bastick (1982) directly
ties intuition with “body knowledge,” and Agor
(1986) and Hayashi (2001) link the use of intuition
with specific “body cues.” More generally, affec-
tive descriptions such as “gut feelings” tie
changes in emotions to bodily changes. In a
fascinating study, Bechara, Damasio, Tranel,
and Damasio (1997) found that individuals
asked to play games where the rules are not
known, but which differ in terms of their level of
risk, will generate skin conductance responses
before engaging in high-risk games, even before
they have consciously understood that the
games are risky. This suggests that the body
may “know” and be transmitting information
outside of conscious awareness. Further, as
Bodenhausen (1990) has shown, circadian varia-
tions impact the use of heuristic stereotypes
such that individuals who are most alert in the
morning (“morning people”) are more likely to
rely on heuristic processing of information late
in the evening, whereas “night people” exhibit
the opposite pattern. While promising, research
that examines the connection between the body
and the use of intuition remains scant.
More “macro” determinants of use, such as
cultural factors, may also play a role in intuition
3
We should note that we have been viewing intuition as
a relatively homogenous concept. Wild (1938), however, ar-
gued for the existence of aesthetic, moral, and religious
intuition. Further, he noted that intuition can arise from
divine sources and from the collective unconscious—and not
just from our own experientially based cognitive schemas.
Future research may help to disentangle what have been
perceived as different “types” of intuition (e.g., managerial
versus mystical intuition).
2007 47Dane and Pratt
use. For example, cultures with a low emphasis
on “uncertainty avoidance” (Cyert & March,
1963; Hofstede, 2001) are willing to “take un-
known risks” and are “comfortable with ambi-
guity and chaos” (Hofstede, 2001: 161). Because
intuitive judgments are, by their very nature,
difficult to justify rationally and often involve
unknown levels of risk, cultures low in uncer-
tainty avoidance may be more inclined than
other cultures to favor intuitive judgments in
decision making. The “masculine versus femi-
nine” cultural distinction (Hofstede, 2001) may
also account for differences in the use of intu-
ition across cultures. In particular, feminine cul-
tures, which emphasize the importance of feel-
ings over logic, may be inclined to accept forms
of judgment that are tied to affect and emotion.
If, as we contend, intuition is tied to affect and
emotions, intuitive decision making may be re-
spected and employed in feminine cultures.
Consistent with this argument, Hofstede (2001:
318) notes that managers in feminine cultures
are expected to use intuition and deal with feel-
ings.
More generally, research should be done to
more explicitly link intuition use factors with
those factors we have identified as being inte-
gral to intuition effectiveness. For example, it
may be the case that learning processes link the
two models: as individuals use intuition more,
they may become more effective in its use. Other
factors may also be common to both intuition
use and effectiveness. For example, judgmental
tasks such as moral and aesthetic problems,
which may be particularly conducive to intuitive
problem solving, may also trigger the use of
intuition (Haidt, 2001; Hammond et al., 1987).
Interplay Between Intuition and Analysis
In our attempt to differentiate intuition from
other decision-making approaches, such as ra-
tional models, we did not discuss at length
when and how different ways of knowing might
complement each other. Researchers who advo-
cate a dual process approach assume that these
two systems of knowing work together in mak-
ing decisions. In a similar vein, Simon (1987)
asserts that effective managers do not have the
luxury of choosing between analysis and intu-
ition—real expertise involves the use of both
types of decision making. And Hodgkinson and
Sadler-Smith (2003: 261) argue that the ability to
switch between “habits of mind” and “active
thinking” is the ultimate skill in today’s organi-
zations.
Researchers have put forth a variety of recom-
mendations about how to use intuitions in com-
bination with more rational decision making.
For example, Blattberg and Hoch (1990) exam-
ined the specific weightings that should be ap-
plied to rational models and intuitive judg-
ments, respectively, in making decisions. In
assessing the accuracy of brand managers’ pre-
dictions of coupon redemption rates as com-
pared to a mathematical forecasting model, they
determined that a 50/50 weighted combination
of model forecast and manager intuition leads
to more accurate predictions than either deci-
sion-making method in isolation.
Shapiro and Spence (1997) further argue that
the ordering of the two types of decision making
is also important. They suggest that intuition
should be recorded first, followed by a more
thorough analytical assessment of the problem.
The degree to which rational decision making
should be emphasized, however, should depend
on the nature of the task (e.g., structured or un-
structured). In contrast, Agor (1986) argues that
many managers use intuition after engaging in
rational analyses, for the purpose of synthesiz-
ing and integrating the information gathered
and analyzed. Unfortunately, while many pro-
vocative ideas about the interplay between ra-
tional and intuitive decision making have been
suggested, empirical research in this area, par-
ticularly in the field of management, remains
insufficient.
Beyond Decision Making
We have focused primarily on the role of intu-
ition in decision making. However, intuition
may have other positive benefits as well. To
illustrate, some preliminary work suggests a
link between intuition and creativity. Langer
(1989: 117), for example, has suggested that cre-
ativity arises through an “intuitive experience of
the world,” whereas rational thinking serves
only to confirm “old mindsets” and “rigid cate-
gories.” Likewise, Poincare´ (1969: 210) has de-
clared that logic is the “instrument of demon-
stration,” and intuition the “instrument of
invention.” However, with the exception of a few
studies (e.g., Raidl & Lubart, 2000-2001), little em-
pirical research has connected intuition to cre-
48 JanuaryAcademy of Management Review
ativity. In light of the growing interest in creativ-
ity in the management sciences, unpacking how
intuition ties in with creative thought may yield
valuable theoretical contributions to this line of
research.
Next, recent appeals for additional scholarly
work on business ethics (e.g., Donaldson, 2003)
suggest a need for fresh perspectives on moral
reasoning and ethical decision making in orga-
nizations. As noted above, Haidt (2001) has ar-
gued that moral judgments are intuitive. Thus,
by better understanding how intuitive judg-
ments are made, we might better identify the
conditions under which individuals disregard
their intuitions (i.e., their moral sense of ethical
behavior) and engage in actions that conflict
with principles of ethics in organizations.
Managerial Implications
We believe that research on intuition is inher-
ently practical. In this paper we have suggested
factors that may lead managers to make good
decisions quickly. Thus, organizations that wish
to facilitate effective intuiting need to concen-
trate on promoting ongoing and deliberate prac-
tice in kind learning environments. They may
also encourage managers to be mindful of their
environments in order to facilitate implicit
learning. By remaining alert and viewing prob-
lems from multiple perspectives, “mindful”
managers may form new cognitive categories
and distinctions (see Langer, 1989) that bolster
the complexity and domain relevance of their
schemas. Finally, we have suggested that man-
agers should be wary of using intuitions when
faced with intellective tasks.
In this discussion section we have also sug-
gested how future research might better under-
stand the relationship between intuition effec-
tiveness and use, thus ensuring that individuals
feel comfortable “trusting their gut” when ap-
propriate (e.g., when the individual has domain
expertise and is working on a judgmental task).
Moreover, we believe that better understanding
how intuition and rational analysis work to-
gether will result in an even more complete pic-
ture of decision effectiveness among managers
and other organizational members. Beyond de-
cision making, understanding how intuition
plays a role in creativity and ethics seems crit-
ical to improving key organizational processes.
In addition to highlighting the promises of
intuition, our research also reveals potential
challenges and barriers to facilitating effective
intuitions. To illustrate, one could argue that the
rapid rate of change that characterizes current
organizational environments makes intuitive
decision making more necessary today than it
has been in the past. However, it is also true that
job mobility is increasing. As a result, individu-
als are less likely to engage in a significant
degree of focused practice in a particular do-
main (Prietula & Simon, 1989). In our language,
this suggests that individuals may not be able
to form complex, domain-relevant schemas—
and, thus, must rely more often on simple sche-
mas and heuristics. This is likely to result in the
less effective use of intuitive judgments at a
time when their use is increasingly critical. Ac-
cordingly, organizations that retain members for
long periods of time in similar job domains may
be more likely than others to provide members
with sufficient conditions to develop complex,
domain-relevant schemas. This suggests a need
to reduce the rate of member turnover in order to
foster the development of more effective intui-
tive decision making among members. Reten-
tion is critical if one is to keep highly special-
ized knowledge workers—a crucial component
to competing in a “knowledge economy.”
Keeping experts, however, is only one chal-
lenge in utilizing experts in a knowledge econ-
omy (Matusik & Hill, 1998). Ideally, the informa-
tion from experts can be captured by the
organization (Hammer, Leonard, & Davenport,
2004; Osterloh & Frey, 2000). Can the complex,
domain-relevant schemas of experts be trans-
ferred to automated information systems or to
other individuals? While we have identified the
conditions under which an individual can gain
complex, domain-relevant schemas, it is not
clear whether or how the content of these sche-
mas can be transferred from one individual to
another. Classic work on the transfer of exper-
tise, however, suggests that having experts
working together with novices may be critical to
this issue (Collins, 1982).
A related challenge for managers concerns
the transferability of intuitive skills across
fields and industries. Organizations, interested
in acquiring individuals with expert knowledge,
often hire managers and executives from other
firms and agencies. While such individuals are
pursued for their rich knowledge bases and de-
2007 49Dane and Pratt
cision-making abilities, our model proposes that
cognitive schemas must be domain relevant to
generate accurate intuitive judgments. For this
reason, an individual who possesses expert in-
tuition in one field or industry may not be as
effective in making intuitive decisions in a field
or industry that differs substantially from the
environment in which the individual’s cognitive
schemas were developed. This brings to mind
one of the key weaknesses ascribed to Carly
Fiorina in her very public and sudden ousting
from Hewlett-Packard in 2005: she did not have
the right “type” of experience to succeed at HP. If
true, this would suggest that her intuitive rea-
soning may not have been as effective as some-
one with more domain-relevant experience.
Thus, we consider the following question.
How different must context be before the cross-
situational relevance of cognitive schemas is
negated? While this question is, as yet, unan-
swered, we suggest that managers should be
slow to embrace intuitive judgments made by
organizational newcomers without relevant in-
dustry or occupational experience.
Conclusion
We have emphasized throughout this paper
how intuition is viewed as a potential means of
helping managers make both fast and accurate
decisions in organizations. In this regard, we
discussed how and why speed serves as one
characteristic of intuition and identified factors
that make intuitive judgments effective in deci-
sion making.
In closing, we suggest that further research on
intuition is important not only for building the-
ory on this particular construct but also for in-
creasing our field’s attention to nonconscious
processes more generally. We have emphasized
throughout this work that intuition arises
through nonconscious operations. In making
this point, we were informed by a growing body
of literature in psychology that has shown how a
large portion of cognitive thought occurs outside
of consciousness (Bargh, 1996; Bargh & Char-
trand, 1999; Jacoby, Lindsay, & Toth, 1992; Kihl-
strom, Barnhardt, & Tataryn, 1992; Reber, 1992).
Some psychologists have even referred to the
1990s as the “decade of automaticity” (Pizarro &
Bloom, 2003). Yet despite bourgeoning interest in
nonconscious and automatic processes among
psychologists, organizational scholars have yet
to focus extensively on these mechanisms and
how they may influence behavior in organiza-
tions. For this reason, we hope that our treat-
ment of intuition may help to put the “noncon-
scious” into organizational studies.
REFERENCES
Abernathy, C. M., & Hamm, R. M. 1995. Surgical intuition:
What it is and how to get it. Philadelphia: Hanley &
Belfus.
Agor, W. A. 1986. The logic of intuition: How top executives
make important decisions. Organizational Dynamics,
14(3): 5–18.
Agor, W. A. 1989. Intuition in organizations: Leading and
managing productively. Newbury Park, CA: Sage.
Bargh, J. A. 1996. Principles of automaticity. In E. T. Higgins
& A. Kruglanski (Eds.), Social psychology: Handbook of
basic principles: 169 –183. New York: Guilford Press.
Bargh, J. A., & Chartrand, T. L. 1999. The unbearable auto-
maticity of being. American Psychologist, 54: 462– 479.
Barnard, C. I. 1938. The functions of the executive. Cam-
bridge, MA: Harvard University Press.
Bastick, T. 1982. Intuition: How we think and act. New York:
Wiley.
Baylor, A. L. 2001. A U-shaped model for the development of
intuition by level of expertise. New Ideas in Psychology,
19: 237–244.
Bazerman, M. H. 1986. Judgment in managerial decision mak-
ing. New York: Wiley.
Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. 1997.
Deciding advantageously before knowing the advanta-
geous strategy. Science, 275: 1293–1295.
Behling, O., & Eckel, N. L. 1991. Making sense out of intuition.
Academy of Management Executive, 5(1): 46 –54.
Blattberg, R. C., & Hoch, S. J. 1990. Database models and
managerial intuition: 50% model 50% manager. Man-
agement Science, 36: 887– 899.
Bless, H., Bohner, G., Schwarz, N., & Strack, F. 1990. Mood and
persuasion: A cognitive response analysis. Personality
and Social Psychology Bulletin, 16: 331–345.
Bodenhausen, G. V. 1990. Stereotypes as judgmental heuris-
tics: Evidence of circadian variations in discrimination.
Psychological Science, 1: 319 –322.
Bowers, K. S., Regehr, G., Balthazard, C., & Parker, K. 1990.
Intuition in the context of discovery. Cognitive Psychol-
ogy, 22: 72–110.
Briggs, K. C., & Myers, I. B. 1976. Myers-Briggs type indicator.
Palo Alto, CA: Consulting Psychologists Press.
Bruner, J. S. 1962. On knowing. Cambridge, MA: Harvard
University Press.
Burke, L. A., & Miller, M. K. 1999. Taking the mystery out of
intuitive decision making. Academy of Management Ex-
ecutive, 13(4): 91–99.
50 JanuaryAcademy of Management Review
Carlson, R. A., & Dulany, D. E. 1985. Conscious attention and
abstraction in concept learning. Journal of Experimental
Psychology: Learning, Memory, and Cognition, 11: 45–58.
Chen, S., & Chaiken, S. 1999. The heuristic-systematic model
in its broader context. In S. Chaiken & Y. Trope (Eds.),
Dual-process theories in social psychology: 73–96. New
York: Guilford Press.
Chi, M. T. H., Glaser, R., & Farr, M. J. 1998. The nature of
expertise. Hillsdale, NJ: Lawrence Erlbaum Associates.
Claxton, G. 1998. Knowing without knowing why. Psycholo-
gist, 11(5): 217–220.
Collins, H. M. 1982. The replication of experiments in phys-
ics. In B. Barnes & D. Edge (Eds.), Science in context:
94 –116. Cambridge, MA: MIT Press.
Cyert, R. M., & March, J. G. 1963. A behavioral theory of the
firm. Englewood Cliffs, NJ: Prentice-Hall.
Dawes, R. M., Faust, D., & Meehl, P. E. 1989. Clinical versus
actuarial judgment. Science, 31: 1668 –1674.
De Dreu, C. K. W. 2003. Time pressure and closing of the mind
in negotiation. Organizational Behavior and Human De-
cision Processes, 91: 280 –295.
Denes-Raj, V., & Epstein, S. 1994. Conflict between intuitive
and rational processing: When people behave against
their better judgment. Journal of Personality and Social
Psychology, 66: 819 829.
Donaldson, T. 2003. Editor’s comments: Taking ethics seri-
ously—A mission now more possible. Academy of Man-
agement Review, 28: 363–366.
Dreyfus, H. L., & Dreyfus, S. E. 1986. Mind over machine: The
power of human intuition and expertise in the era of the
computer. New York: Free Press.
Edland, A., & Svenson, O. 1993. Judgment and decision mak-
ing under time pressure. In O. Svenson & A. J. Maule
(Eds.), Time pressure and stress in human judgment and
decision making: 27– 40. New York: Plenum Press.
Eisenhardt, K. 1989. Making fast strategic decisions in high-
velocity environments. Academy of Management Jour-
nal, 32: 543–576.
Elsbach, K. D., & Barr, P. S. 1999. The effects of mood on
individuals’ use of structured decision protocols. Orga-
nization Science, 10: 181–198.
Epstein, S. 1990. Cognitive-experiential self-theory. In L. Per-
vin (Ed.), Handbook of personality: Theory and research:
165–192. New York: Guilford Press.
Epstein, S. 1994. Integration of the cognitive and psychody-
namic unconscious. American Psychologist, 49: 709 –724.
Epstein, S. 2002. Cognitive-experiential self-theory of per-
sonality. In T. Millon & M. J. Lerner (Eds.), Comprehen-
sive handbook of psychology. Volume 5: Personality and
social psychology: 159 –184. Hoboken, NJ: Wiley.
Epstein, S., & Pacini, R. 1999. Some basic issues regarding
dual-process theories from the perspective of cognitive-
experiential self-theory. In S. Chaiken & Y. Trope (Eds.),
Dual-process theories in social psychology: 462–482. New
York: Guilford Press.
Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. 1996. Individual
differences in intuitive-experiential and analytical-
rational thinking styles. Journal of Personality and Social
Psychology, 71: 390 405.
Ericsson, K. A., & Charness, N. 1994. Expert performance: Its
structures and acquisition. American Psychologist, 49:
725–747.
Ericsson, K. A., Krampe, R. T., & Tesch-Ro¨mer, C. 1993. The
role of deliberate practice in the acquisition of expert
performance. Psychological Review, 100: 363– 406.
Ericsson, K. A., & Lehmann, A. C. 1996. Experts and excep-
tional performance: Evidence of maximal adaptation to
task constraints. Annual Review of Psychology, 47: 273–
305.
Ericsson, K. A., & Smith, J. 1991. Prospects and limits of the
empirical study of expertise: An introduction. In K. A.
Ericsson & J. Smith (Eds.), Toward a general theory of
expertise: 1–38. New York: Cambridge University Press.
Ferguson, G. 1999. Cracking the intuition code. Chicago:
Contemporary Books.
Fiske, S. T., & Taylor, S. E. 1991. Social cognition (2nd ed.).
New York: McGraw-Hill.
Franquemont, S. 1999. You already know what to do. New
York: Jeremy P. Tarcher/Putnam.
Gollwitzer, P., & Bayer, U. 1999. Deliberative versus imple-
mental mindsets in the control of action. In S. Chaiken &
Y. Trope (Eds.), Dual-process theories in social psychol-
ogy: 403– 422. New York: Guilford Press.
Guenther, H. V. 1958. The levels of understanding in Bud-
dhism. Journal of the American Oriental Society, 78:
19 –28.
Haidt, J. 2001. The emotional dog and its rational tail: A
social intuitionist approach to moral judgment. Psycho-
logical Review, 108: 814 834.
Hammer, M., Leonard, D., & Davenport, T. 2004. Why don’t we
know more about knowledge? MIT Sloan Management
Review, 45(4): 14 –18.
Hammond, K. R., Hamm, R. M., Grassia, J., & Pearson, T. 1987.
Direct comparison of the efficacy of intuitive and ana-
lytical cognition in expert judgment. IEEE Transactions
on Systems, Man, and Cybernetics, 17: 753–770.
Harper, S. C. 1989. Intuition: What separates executives from
managers. In W. H. Agor (Ed.), Intuition in organizations:
Leading and managing productively: 111–124. Newbury
Park, CA: Sage.
Hayashi, A. M. 2001. When to trust your gut. Harvard Business
Review, 79(2): 59 65.
Hitt, M. A., Keats, B., & DeMarie, S. M. 1998. Navigating in the
new competitive landscape: Building strategic flexibil-
ity and competitive advantage in the 21
st
century. Acad
-
emy of Management Executive, 12(4): 22– 42.
Hodgkinson, G., & Sadler-Smith, E. 2003. Complex or unitary?
A critique and empirical reassessment of the Allinson-
Hayes Cognitive Style Index. Journal of Occupational
and Organizational Psychology, 76: 243–268.
Hofstede, G. 2001. Culture’s consequences (2nd ed.). Thou-
sand Oaks, CA: Sage.
2007 51Dane and Pratt
Hogarth, R. M. 2001. Educating intuition. Chicago: University
of Chicago Press.
Isaack, T. S. 1978. Intuition: An ignored dimension of man-
agement. Academy of Management Review, 3: 917–922.
Isen, A. M., Means, B., Patrick, R., & Nowicki, G. 1982. Some
factors influencing decision-making strategy and risk
taking. In M. S. Clarke & S. T. Fiske (Eds.), Affect and
cognition: 243–261. Hillsdale, NJ: Lawrence Erlbaum As-
sociates.
Isenberg, D. J. 1984. How senior managers think. Harvard
Business Review, 62(6): 81–90.
Jacoby, L. L., Lindsay, D. S., & Toth, J. P. 1992. Unconscious
influences revealed. American Psychologist, 47: 802– 809.
Janis, I. L., & Mann, L. 1977. Decision making: A psychological
analysis of conflict, choice, and commitment. New York:
Free Press.
Jung, C. G. 1933. (First published in 1921.) Psychological
types. New York: Harcourt, Brace, and Company.
Kaempf, G. L., Klein, G., Thordsen, M. L., & Wolf, S. 1996.
Decision making in complex naval command-and-
control environments. Human Factors, 38: 220 –231.
Kahneman, D. 2003. A perspective on judgment and choice.
American Psychologist, 58: 697–720.
Kahneman, D., Slovic, P., & Tversky, A. 1982. Judgment under
uncertainty: Heuristics and biases. Cambridge: Cam-
bridge University Press.
Kahneman, D., & Tversky, A. 2000. Choices, values, and
frames. Cambridge: Cambridge University Press.
Kaplan, M. F., Wanshula, L. T., & Zanna, M. P. 1993. Time
pressure and information integration in social judg-
ment. In O. Svenson & A. J. Maule (Eds.), Time pressure
and stress in human judgment and decision making:
255–267. New York: Plenum Press.
Khatri, N., & Ng, H. A. 2000. The role of intuition in strategic
decision making. Human Relations, 53: 57– 86.
Kihlstrom, J. F. 1987. The cognitive unconscious. Science, 237:
1445–1452.
Kihlstrom, J. F., Barnhardt, T. M., & Tataryn, D. T. 1992. The
psychological unconscious. American Psychologist, 47:
788 –791.
Klein, G. 1998. Sources of power: How people make decisions.
Cambridge, MA: MIT Press.
Klein, G. 2003. Intuition at work. New York: Doubleday.
Kruger, J., & Dunning, D. 1999. Unskilled and unaware of it:
How difficulties in recognizing one’s own incompetence
lead to inflated self-assessments. Journal of Personality
and Social Psychology, 77: 1121–1134.
Kruglanski, A. W., & Freund, T. 1983. The freezing and un-
freezing of lay-inference: Effects on impressional pri-
macy, ethnic stereotyping, and numerical anchoring.
Journal of Experimental Social Psychology, 19: 448 468.
Langer, E. J. 1989. Mindfulness. Reading, MA: Addison-
Wesley.
Laughlin, P. 1980. Social combination processes of coopera-
tive problem-solving groups on verbal intellective tasks.
In M. Fishbein (Ed.), Progress in social psychology, vol. 1:
127–155. Hillsdale, NJ: Lawrence Erlbaum Associates.
Laughlin, P. R., & Ellis, A. L. 1986. Demonstrability and social
combination processes on mathematical intellective tasks.
Journal of Experimental Social Psychology, 22: 177–189.
Lewicki, P., Hill, T., & Bizot, E. 1988. Acquisition of procedural
knowledge about a pattern of stimuli that cannot be
articulated. Cognitive Psychology, 20: 24 –37.
Lieberman, M. D. 2000. Intuition: A social cognitive neuro-
science approach. Psychological Bulletin, 126: 109 –137.
Lovett, M. C. 2002. Problem solving. In H. Pashler & D. Medin
(Eds.), Stevens’ handbook of experimental psychology.
Volume 2: Memory and cognitive processes: 317–362.
New York: Wiley.
MacGregor, D., Lichtenstein, S., & Slovic, P. 1988. Structuring
knowledge retrieval: An analysis of decomposed quan-
titative judgments. Organizational Behavior and Human
Decision Processes, 42: 303–323.
March, J., & Simon, H. 1993. Organizations (2nd ed.). Cam-
bridge, MA: Blackwell.
Matusik, S. F., & Hill, C. W. L. 1998. The utilization of contin-
gent work, knowledge creation, and competitive advan-
tage. Academy of Management Review, 23: 680 697.
Maule, A. J., Hockey, G. R. J., & Bdzola, L. 2000. Effects of
time-pressure on decision-making under uncertainty:
Changes in affective state and information processing
strategy. Acta Psychologica, 104: 283–301.
McGrath, J. E. 1984. Groups: Interaction and performance.
Englewood Cliffs, NJ: Prentice-Hall.
McMackin, J., & Slovic, P. 2000. When does explicit justifica-
tion impair decision making? Applied Cognitive Psy-
chology, 14: 527–541.
Meehl, P. E. 1954. Clinical versus statistical prediction. Min-
neapolis: University of Minnesota Press.
Myers, D. G. 2002. Intuition: Its powers and perils. New Ha-
ven, CT: Yale University Press.
Nissen, M. J., & Bullemer, P. 1987. Attentional requirements of
learning: Evidence from performance measures. Cogni-
tive Psychology, 19: 1–32.
Osbeck, L. M. 1999. Conceptual problems in the development
of a psychological notion of “intuition.” Journal for the
Theory of Social Behaviour, 29: 229 –250.
Osbeck, L. M. 2001. Direct apprehension and social construc-
tion: Revisiting the concept of intuition. Journal of The-
oretical and Philosophical Psychology, 21: 118 –131.
Osterloh, M., & Frey, B. 2000. Motivation, knowledge transfer,
and organizational forms. Organization Science, 11:
538 –550.
Pacini, R., & Epstein, S. 1999. The relation of rational and
experiential information processing styles to personal-
ity, basic beliefs, and the ratio-bias problem. Journal of
Personality and Social Psychology, 76: 972–987.
Perlow, L. A., Okhuysen, G. A., & Repenning, N. P. 2002. The
speed trap: Exploring the relationship between decision
making and temporal context. Academy of Management
Journal, 45: 931–955.
52 JanuaryAcademy of Management Review
Peters, J. T., Hammond, K. R., & Summers, D. A. 1974. A note
on intuitive vs. analytic thinking. Organizational Behav-
ior and Human Performance, 12: 125–131.
Pirsig, R. M. 1974. Zen and the art of motorcycle maintenance:
An inquiry into values. New York: Morrow.
Poincare´, H. 1969. Intuition and logic mathematics. Mathe-
matics Teacher, 62: 205–212.
Policastro, E. 1999. Intuition. In M. A. Runco & S. R. Pritzker
(Eds.), Encyclopedia of creativity, vol. 2: 89 –93. San Di-
ego: Academic Press.
Pizarro, D. A., & Bloom, P. 2003. The intelligence of the moral
intuitions: Comment on Haidt (2001). Psychological Re-
view, 110: 193–196.
Prietula, M. J., & Simon, H. A. 1989. The experts in your midst.
Harvard Business Review, 67(1): 120 –124.
Raidl, M. H., & Lubart, T. I. 2000-2001. An empirical study of
intuition and creativity. Imagination, Cognition and Per-
sonality, 20: 217–230.
Raiffa, H. 1968. Decision analysis: Introductory lectures on
choices under uncertainty. Reading, MA: Addison-
Wesley.
Reber, A. S. 1976. Implicit learning of synthetic languages:
The role of instructional set. Journal of Experimental
Psychology: Human Learning and Memory, 2: 88 –94.
Reber, A. S. 1989. Implicit learning and tacit knowledge. Journal
of Experimental Psychology: General, 118: 219 –235.
Reber, A. S. 1992. An evolutionary context for the cognitive
unconscious. Philosophical Psychology, 5: 33–51.
Reber, A. S., Kassin, S. M., Lewis, S., & Cantor, G. 1980. On the
relationship between implicit and explicit modes in
learning of complex rule structure. Journal of Experi-
mental Psychology: Human Learning and Memory, 6:
492–502.
Reber, A. S., Walkenfeld, F. F., & Hernstadt, R. 1991. Implicit
and explicit learning: Individual differences and IQ.
Journal of Experimental Psychology: Learning, Memory,
and Cognition, 17: 888 896.
Rorty, R. 1967. Intuition. In P. Edwards (Ed.), Encyclopedia of
philosophy: 204 –212. New York: Macmillan.
Rowan, R. 1989. What it is. In W. H. Agor (Ed.), Intuition in
organizations: Leading and managing productively: 78
88. Newbury Park, CA: Sage.
Ruder, M., & Bless, H. 2003. Mood and the reliance on the
ease of retrieval heuristic. Journal of Personality and
Social Psychology, 85: 20 –32.
Schoemaker, J. H., & Russo, J. E. 1993. A pyramid of decision
approaches. California Management Review, 36(1): 9 –31.
Schwarz, N., Bless, H., & Bohner, G. 1991. Mood and persua-
sion: Affective states influence the processing of persua-
sive communications. Advances in Experimental Social
Psychology, 24: 161–199.
Seger, C. A. 1994. Implicit learning. Psychological Bulletin,
115: 163–196.
Shanteau, J., & Stewart, T. R. 1992. Why study expert decision
making? Some historical perspectives and comments.
Organizational Behavior and Human Decision Pro-
cesses, 53: 95–106.
Shapiro, S., & Spence, M. T. 1997. Managerial intuition: A
conceptual and operational framework. Business Hori-
zons, 40(1): 63– 68.
Shirley, D. A., & Langan-Fox, J. 1996. Intuition: A review of the
literature. Psychological Reports, 79: 563–584.
Simon, H. A. 1987. Making management decisions: The role
of intuition and emotion. Academy of Management Ex-
ecutive, 1(1): 57– 64.
Simon, H. A. 1992. What is an “explanation” of behavior?
Psychological Science, 3: 150 –161.
Simon, H. A. 1996. The sciences of the artificial (3rd ed.).
Cambridge, MA: MIT Press.
Simon, H. A., & Chase, W. G. 1973. Skill in chess. American
Scientist, 61: 394 403.
Sinclair, M., Ashkanasy, N. M., Chattopadhyay, P., & Boyle,
M. V. 2002. Determinants of intuitive decision-making in
management: The moderating role of affect. In N. M. Ash-
kanasy, W. Zerbe, & C. E. J. Ha¨ rtel (Eds.), Managing emo-
tions in the workplace: 143–163. Armonk, NY: M. E. Sharpe.
Sloman, S. A. 1996. The empirical case for two systems of
reasoning. Psychological Bulletin, 119: 3–22.
Stadler, M. A., & Frensch, P. A. 1998. Handbook of implicit
learning. Thousand Oaks, CA: Sage.
Stanovich, K. E., & West, R. F. 2000. Individual differences in
reasoning: Implications for the rationality debate? Be-
havioral and Brain Sciences, 23: 645– 665.
Sternberg, R. J., & Davidson, J. E. 1995. The nature of insight.
Cambridge, MA: MIT Press.
Suri, R., & Monroe, K. B. 2003. The effects of time constraints
on consumers’ judgments of prices and products. Journal
of Consumer Research, 30: 92–104.
Tiedens, L., & Linton, S. 2001. Judgment under emotional
certainty and uncertainty: The effects of specific emo-
tions on information processing. Journal of Personality
and Social Psychology, 81: 1–16.
Tversky, A., & Kahneman, D. 1974. Judgment under uncer-
tainty: Heuristics and biases. Science, 185: 1124 –1131.
Tversky, A., & Kahneman, D. 1983. Extensional versus intui-
tive reasoning: The conjunction fallacy in probability
judgment. Psychological Review, 90: 293–315.
Vaughan, F. E. 1979. Awakening intuition. New York: Double-
day.
Weick, K. 1995. Sensemaking in organizations. Thousand
Oaks, CA: Sage.
Weiss, H. M., & Cropanzano, R. 1996. Affective events theory:
A theoretical discussion of the structure, causes and
consequences of affective experiences at work. Re-
search in Organizational Behavior, 18: 1–74.
Westcott, M. R., & Ranzoni, J. H. 1963. Correlates of intuitive
thinking. Psychological Reports, 12: 595– 613.
Wild, K. W. 1938. Intuition. Cambridge: Cambridge Univer-
sity Press.
2007 53Dane and Pratt
Wilson, T. D., & Schooler, J. W. 1991. Thinking too much:
Introspection can reduce the quality of preferences and
decisions. Journal of Personality and Social Psychology,
60: 181–192.
Woolhouse, L. S., & Bayne, R. 2000. Personality and the use of
intuition: Individual differences in strategy and perfor-
mance on an implicit learning task. European Journal of
Personality, 14: 157–169.
Erik Dane (erikdane@uiuc.edu) is a doctoral candidate in organizational behavior at
the University of Illinois at Urbana-Champaign. His current research explores how
professionals leverage their experience and intuition to respond effectively to job-
related challenges.
Michael G. Pratt (mpratt@uiuc.edu) is a James F. Towey Fellow and associate profes-
sor of organizational behavior at the University of Illinois at Urbana-Champaign. He
earned his Ph.D. in organizational psychology from the University of Michigan. His
current research explores intuition, meaning, and identity dynamics among profes-
sionals.
54 JanuaryAcademy of Management Review
... Pour le modèle naturaliste, et à un degré moindre pour celui de la rationalité limitée, l'expérience et l'intuition jouent un rôle crucial dans la prise de décision (Fredrickson, 1985;Zsambock et Klein, 1997;Dane et Pratt, 2007;Klein, 2008). La veille stratégique soutient la prise de décision fondée sur l'expérience et l'intuition parce qu'elle permet de détecter des signaux faibles dans l'environnement externe (Ansoff, 1975;Hambrick, 1982;Lesca, 1994), et donc d'acquérir des connaissances issues de stimuli de l'environnement (implicit learning). ...
... Dans nos résultats, le type de soutien Alimenter la réflexion rassemble les expressions « ouvrir les horizons » [IIBG02], « forger sa pensée » [IAG15], « susciter des idées » [IAG03], « stimuler l'intérêt et l'éveil »Des répondants gestionnaires ont mentionné qu'ils prenaient leurs décisions stratégiques par intuition. Pour rappel, l'intuition consiste en un processus non conscient de traitement de l'information, qui relie, de manière holistique, des éléments d'information épars, rapidement et immédiatement, et qui implique des jugements émotionnels(Dane et Pratt, 2007). La prise de décision par intuition passerait par l'acquisition de connaissances issues de stimuli dans l'environnement (Zambock etKlein, 1997). ...
Thesis
Dans l’ensemble des pays de l’Organisation de coopération et de développement économiques (OCDE), le secteur public de la santé fait face à un environnement complexe qui se caractérise par la rapidité des changements technologiques et scientifiques. Face à une demande accrue des citoyens pour des services fiables, accessibles et efficaces, les organisations publiques de santé se voient aussi contraintes par la rareté des ressources, notamment financières et budgétaires. Pour répondre à la mission publique qui leur est confiée, elles se tournent de plus en plus vers les outils et principes du management stratégique, dont la veille stratégique. Au Québec, la veille stratégique a fait son apparition dans le plan stratégique d’organisations publiques de santé dans le milieu des années 2000. Des initiatives de veille ont également vu le jour, comme en témoigne la Communauté de pratique de veille en santé et services sociaux créée en 2009. Notre thèse a pour but d’explorer ce qu’est la veille stratégique dans le secteur public de la santé au Québec. La recherche a pour objectifs de (1) décrire les caractéristiques de la veille telle qu’elle est implantée dans des organisations publiques de santé du Québec; (2) décrire les finalités de la veille dans les organisations publiques de santé du Québec : (a) décrire les types de soutien qu’apporte la veille à la stratégie des organisations publiques de santé du Québec; (b) décrire les types de soutien qu’apporte la veille à la prise de décision des gestionnaires publics de santé du Québec; (c) décrire, s’il y en a, les autres types de soutien qu’apporte la veille aux organisations publiques de santé du Québec; (3) identifier les caractéristiques d’une veille stratégique dans le secteur public de la santé. Au travers d’une étude de cas multiples, la recherche examine trois projets de veille (cas) autour de quatre composantes, soit le produit de veille, les acteurs de la veille, le processus de veille et les finalités de la veille. En tout, 5 veilleurs et 16 gestionnaires clients de la veille (11 cadres supérieurs et cinq cadres intermédiaires) ont été interrogés, en suivant les principes de la théorie ancrée. D’après nos résultats, une veille serait stratégique si elle est centrée sur les besoins informationnels des gestionnaires clients de la veille et selon l’utilisation que ces derniers font du produit de veille. Un produit de veille stratégique devrait être fortement personnalisé, dynamique et évolutif, concis et attrayant. De plus, il devrait reposer sur des critères de qualité de l’information et sur une analyse et une interprétation de l’information. Le fait d’intégrer un veilleur aux équipes de gestion pourrait contribuer à développer un tel produit de veille stratégique. Le processus de veille stratégique devrait comprendre des étapes d’évaluation / réévaluation des besoins informationnels, identification des sources d’information, traitement, analyse et interprétation de l’information, et diffusion et utilisation du produit de veille. Enfin, la veille stratégique poursuit des finalités de soutien à la prise de décision et de soutien à la planification stratégique. Ces soutiens ont été regroupés en utilités d’apprentissage, d’exploration, d’analyse, symbolique, de comparaison et stratégique.
... Although organizational decisions often are made by teams rather than individuals (Zhu et al., 2020), individual decision makers exert influence and control (Van Riel et al., 2004), so their attitudes determine how group-level decisions emerge (Dane and Pratt, 2007). In other words, individual-, project-, and team-level aspects of decision making are intertwined and interact recursively (Lichtenthaler, 2011). ...
Article
Affordable innovations, which serve consumers with a low willingness or ability to pay, are a means to address grand challenges while also generating economic value. However, less is known about how managers’ and decision makers’ individual-level preferences and attitudes for or against affordable innovation hinder their development. Hence, in addition to identifying and conceptualizing the affordable innovation rejection (AIR) attitudes of decision makers as a major obstacle, this study proposes a scale to measure them. Specifically, with a series of qualitative and quantitative studies, this research develops and validates a parsimonious psychometric scale that can measure decision makers’ affordable innovation rejection attitudes. The resulting six-item scale is based on a tripartite AIR conceptualization, which proves valid in terms of convergent, discriminant, experimental, nomological, predictive, and test–retest reliability. The proposed research agenda in turn details some possible applications of this scale.
... Individual decision styles, as a facet of cognitive styles, capture tendencies for specific decision-making processes (Hamilton et al., 2016;Kozhevnikov, 2007). A rational decision style in general covers thorough evaluation, collecting information, and thinking about alternatives, while an intuitive decision-making style encompasses quick and shortsighted decisions and the involvement of feelings (Dane & Pratt, 2007;Hamilton et al., 2016;Shafir & LeBoeuf, 2002). The individual decision-making style is assumed to influence the likelihood for the impulsive or reflective system being triggered as the leading processing mode (Schiebener & Brand, 2015). ...
Article
Full-text available
Although consequences of sharing personal information can be negative and severe (e.g., identity theft), individuals still engage in extensive self-disclosures on social networks. One commonly applied explanatory approach is the privacy calculus. Following this, self-disclosures can be conceptualized as rational choices resulting from a weighing of risks and benefits. However, this view misses the additional impulsive nature of decisions. The current study therefore takes the lens of dual-process theories and highlights that self-disclosure decisions can also be guided by an impulsive system. To test for the impact of descriptive social norms, a warning message, privacy-related decision-making styles, and perceived benefits and risks on individuals’ self-disclosure decisions, the fictitious social network “AHOY!” was created. It enabled the measurement of participants’ (N = 551; Mage = 40.77, SDage = 13.93) actual self-disclosures on two decision stages: 1) whether or not a post was created, 2) how much information (on a psychological and informational dimension) was provided. Further, descriptive social norms (i.e., the extent of other users’ self-disclosures) and the presence/absence of a warning message were varied. The remaining factors were measured using questionnaires. The results imply that cognitive and affective processes (expected to be triggered by the investigated factors) are involved differently in the two decision stages. While both the reflective and impulsive system may be involved in the first stage, with the reflective system also potentially taking a predominant role, the impulsive system may be predominant when deciding how much to disclose. This highlights the importance of exceeding common assumptions of rationality to better understand and support individuals’ self-disclosure decisions.
... The common concepts presented so far cannot handle all phenomena of intuitive decision-making [26] we know from everyday practice [27]. Affective intuition may need deeper explanation differentiating feelings and emotions [28] based on neuroscience [29]. ...
Preprint
Full-text available
This article reports on a pilot study to develop a new measuring instrument for intuitive decision making (intuition). This is important to better describe intuition for different occupations. Current intuition measures inadequately assess job related intuition types. Intuitive decision making hardly made into business administration science. A new description on intuition is needed to relate it to decision making at the workplace. Therefore, new items of a potential measurement tool were tested to measure different types of intuition. Based on existing scales from Pretz et al, Epstein New categories of intuition were explored based theories on emotions and feelings (Craig, Damasio), Heuristics (Gigerenzer), Unconscious Thought (Dijksterhuis), and Anticipation (Radin, Bem, Thalbourne). This will lead to a multidimensional domain-specific model on intuition-short RHIA. We report on 4 validity studies based on an multinational sample form over 30 countries (n=5570). Study 1 reports the reliability and factor structure of the RHIA and correlations with extant intuition and personality measures. Study 2 presents a confirmatory factor analysis. Studies 3 and 4 examine the predictive validity of the RHIA with respect to clinical decision-making. The scales developed were valid, consistent, and reliable. The scales were internally consistent and stable over time, and factor analyses supported the predicted distinctions among them. The scales were positively tested according to different studies on intuition. Correlations with existing scales showed that the RIEHUA is unique in its assessment of all types of intuition in one measure. This analysis is the basis for developing a comprehensive tool with more items to measure different types of intuition in a multidimensional domain-specific approach in the future.
Article
This paper serves to deepen the understanding of how inconsistencies between feeling, thinking, and doing are managed by decision-makers in emergency settings. We use a practice approach and investigate the emergency physicians in an Emergency Department (ED), by means of 200 h of observations, 12 in-depth interviews, and organizational documentation. Data are analyzed using an abductive template-based approach. The configuration of three different decision-making modes, namely an experiential-based mode, an ostensive-based mode, and an action-based mode, provide an eight-fold typology of emergency physicians' decision-making praxis. “Weak” signals are the starting point for clinical assessment, and inconsistencies among the modes are strategically used and surprisingly often associated with positive treatment outcomes. The praxis perspective used in this article bridges literature on choice and interpretation—processes usually separated in organizational and decision-making literature. Inconsistency between the modes allow physicians to create an action space where decision-making is about more than providing the “right” answer. Making use of the eight-fold typology helps physicians identify “blind spots”, improve practice in both mundane and medically rare cases, as well as aid in revision of existing routines. This awareness also provides for high-quality care, an increased acceptance of inconsistencies by the public, with a potential to reduce litigation issues.
Article
In the present society, people have become cautious about their online presence. By adopting a qualitative methodological approach, the study investigates consumers’ approach to SMEB (Social Media Engagement Behaviour). Through the lens of the personal branding construct, it is understood that people seek to create a satisfying presentation of the desired self. A further concern is to maintain the public’s perception of such an identity. Psychological experiences include the negative impact of self-disclosure, social phobia, and concerns for the brand of ‘me’. The fear is not being perceived correctly or being associated with controversial opinions in the eye of the target audience that they regard as important. Going beyond career advancement, the study contributes to understand how concerns for personal brand impact Gen Y’s SMEB. The findings assist commercial brands in gaining more knowledge of such consumer groups in terms of the future engagement process.
Chapter
Strategy research has been focused on rational and detached ways of thinking, which has led strategists to perform formulation and implementation in a one-dimensional manner. In other words, the work is performed in an emotionless manner, as if procedural instead of developmental in nature, and in isolation from the people who contribute. In order to make sense of this for the practicing manager, I review approximately 60 articles on strategic thinking (cognition) focusing on emotions, the contributors to strategy work and the nature of the work. Fascinatingly, the literature conceives of strategic cognition as overwhelmingly controlled by our historical form of cognition from when we lived in the forest. Additionally, strategists and their team members are described as highly emotional, emotionally contagious, intuitive and interactive Homo sapiens—NOT as calm rational managers! This review demonstrates that the focus on rationality and detachment actually promotes negative and damaging ways of thinking, which is experienced by the strategy team as debilitating psychological harm. However, strategists can use emotional contagion in order to spread positive ways of thinking that are experienced by the team as psychological pleasure. Such pleasure actually enhances passion and creativity, suggested to produce more unique and valuable products. This is what strategists need to know about strategy! This expanded view of strategic cognition provides new implications and questions for strategy research and education.
Article
Research on work as a calling is gaining momentum, and work-as-a-calling theory is providing a helpful deductive structure to the consistent evidence that people who view their work as a calling and can actively live out that calling usually experience both career-related and general well-being. What is less clear are the key processes that may lead people to perceive a calling in the first place. By bringing work identity into sharper focus, we propose an especially promising framework for constructing a sense of calling, one that uses a cognitive approach. This cognitive approach to eliciting a sense of calling builds on four key work-identity precursors: effort calculation, reflection, appraisal, and fusion. These forward-looking processes are supported by extant research and are promising areas for future research that can illuminate how people may come to perceive a calling.
Chapter
In their 1963 seminal book, Donald Campbell and Julian Stanley introduced what they called quasi-experimental designs for research. They argued that in the managerial and organizational sciences—unlike in the exact sciences—true experiments like those conducted in a laboratory, are not feasible.
Article
Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent than rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology.
Book
Arguably one of the most profoundly important essays ever written on the nature and significance of "quality" and definitely a necessary anodyne to the consequences of a modern world pathologically obsessed with quantity. Although set as a story of a cross-country trip on a motorcycle by a father and son, it is more nearly a journey through 2,000 years of Western philosophy. For some people, this has been a truly life-changing book.
Article
This paper presents the findings of a study on how experienced naval officers make decisions in a complex, time-pressured command and control setting, the Combat Information Center of AEGIS cruisers. The decision processes invoked by the officers were consistent with the recognition-primed decision model. The majority of decisions concerned situation awareness and diagnosis in which the decision makers used feature-matching and story generation strategies to build situation awareness. Furthermore, awareness of the situation enabled the officers to recognize appropriate actions from published procedures or past experience. A recognitional strategy was used to identify 95% of the actions taken; decision makers compared multiple options in only 4% of the cases. These findings are discussed in terms of their implications for framing command-and-control problems, for emphasizing situation awareness, for a descriptive model of decision making, and for designing decision supports.