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Conformity: Definitions, Types, and Evolutionary Grounding



Conformity research in social psychology spans a century, but researchers have only adopted an evolutionary perspective in the past 25 years. This change has been driven by gene-culture coevolutionary models and research on nonhuman animals. In this chapter, we outline why there is a credible basis for an evolutionary explanation for widespread behavioral conformity in humans. However, we caution that not all conformity in humans is the same because conforming in a perceptual judgment task in the laboratory (as per the Asch paradigm) is not equivalent to being an unwitting participant in a behavioral field study. Moreover, conformity has not been consistently defined across research disciplines, which hampers a valid assessment of its evolutionary origins. Theoretical models within social psychology and the study of gene-culture coevolution are valuable tools in the quest for evolutionary explanations of conformist behavior; they have utilized gained insights while inspiring simulations and empirical tests. We propose the idea of incorporating individuals’ habit adherence into the models to advance the study of conformity. Conformity is a powerful force in human decision making and is best understood from an evolutionary perspective.
Conformity: Denitions, Types,
and Evolutionary Grounding
Julie C. Coultas and Edwin J. C. van Leeuwen
J. C. Coultas ()
Centre for the study of Cultural Evolution, Stockholm
University, 106 91 Stockholm, Sweden
Department of Psychology, University of Sussex,
Falmer BN1 9QH, UK
E. J. C. van Leeuwen
Department of Developmental Psychology, University
of Jena, Am Steiger 3/1, 07743 Jena, Germany
Conformity is the act of tting in with the group.
As a group-living species, much of our behav-
ior is focused on preserving group cohesion. The
tendency to change one’s behavior to match the
responses of others is often adaptive (Cialdini and
Goldstein 2004). If we want to join a group, then
we monitor and copy the responses and actions
of those we observe. This copying behavior is not
always conscious (Chartrand and Bargh 1999),
but it is often functional. If we copy those around
us when we are unsure of ourselves, we will often
adopt successful behavior, especially when indi-
vidually acquired information is costly (Boyd
and Richerson 1985; Henrich and Boyd 1998).
In the past 25 years, there has been a burgeon-
ing interest in conformist behavior from diverse
disciplines including psychology, anthropology,
evolutionary biology, behavioral ecology, math-
ematics, and economics.
The grounding of conformist behavior in evo-
lutionary theory proved justified when nonhuman
species were similarly observed to be drawn to
majorities (e.g., Claidière and Whiten 2012). For
instance, chimpanzees behave as if they desire to
be like others (Hopper et al. 2011; Whiten et al.
2005), capuchin monkeys develop group-specific
foraging traditions (Perry 2009), and vervet mon-
keys acquiesce to local foraging techniques upon
entering a new group (van de Waal et al. 2013).
That these closely related species show behav-
ioral patterns that resemble crowd-following in
humans marked a starting point for exploring the
evolutionary roots of human conformity. When
even more distantly related species like rats
(Galef and Whiskin 2008; Jolles et al. 2011) and
fish (Day et al. 2001; Pike and Laland 2010) were
found to show conformity, it led to an interest in
the evolutionary roots of human conformity as
well as the robustness of conformity as a social
learning heuristic (Laland 2004).
Recent investigations into conformity, how-
ever, have exposed several issues that may distort
our understanding of conformist behavior, even
in humans. Notably, “conformity” has not been
defined unequivocally across disciplines (e.g.,
Haun et al. 2013). Whereas conformity in humans
has been defined in terms of forgoing personal
convictions in the face of a majority of peers ex-
pressing a different stance (e.g., Asch 1956; Sher-
if 1936), “conformity” has been used to describe
the process by which individual nonhumans ac-
quire the foraging strategy that becomes the most
common variant (e.g., Hopper et al. 2011; Perry
2009). Moreover, whereas some conformity stud-
ies have produced conclusions by investigating
the effects of one large group (i.e., the majority)
on the focal individuals in the absence of minori-
V. Zeigler-Hill et al. (eds.), Evolutionary Perspectives on Social Psychology, Evolutionary Psychology,
DOI 10.1007/978-3-319-12697-5_15, © Springer International Publishing Switzerland 2015
190 J. C. Coultas and E. J. C. van Leeuwen
ties (e.g., van de Waal et al. 2013), others have
investigated the effects of one conspecific on the
behavioral perseverance of the focal individuals
(e.g., Galef and Whiskin 2008). The plethora of
definitions used across these “conformity” stud-
ies has hampered assessment of the evolution-
ary roots of conformist behavior and thwarted
between-species comparisons (van Leeuwen and
Haun 2014). To clarify the study of conformity, a
proposal has been made for a streamlined set of
definitions (see Haun et al. 2013; van Leeuwen
and Haun 2014). In the following paragraphs,
we present this set of definitions and put the dis-
parate body of terms in line with this classifica-
tion. Another issue distorting understanding of
conformist behavior is that many “conformity”
findings can similarly be explained by (unbiased)
social influences (van Leeuwen and Haun 2014).
Social influence can be a potent force in shap-
ing individuals’ behavior, even in the absence of
majorities. In this chapter, however, we focus on
streamlining the study of conformity by delineat-
ing its definitions and arguing for a detailed con-
sideration of the type of influence that generates
the conformity effect.
First, it is important to consider that indi-
viduals can acquire the behavior of the majority
through mechanisms that do or do not concern
the meta-fact that it is “the majority” that is being
observed (as opposed to “a minority” or any
separate individual). The majority strategy could
be adopted for the reason that it is the majority
strategy, or for any other reason. Examples of
nonmajority targeted reasons are random copy-
ing, where individuals randomly copy a mem-
ber of their group, or the heuristic that guides
individuals to copy successful group members
(e.g., Laland 2004). Both these mechanisms
do not concern targeted majority copying, yet
likely cause the social learner to end up with the
majority strategy (see Haun et al. 2013). Since
both targeted and nontargeted majority copying
can produce similar behavioral signatures (i.e.,
within-group homogeneity; Boyd and Richerson
1985), it is important to distinguish their mecha-
nisms accordingly.
Another aspect to consider in labeling con-
formist behavior is whether the social learner had
preestablished convictions or behavior regarding
the observed phenomenon. Humans and many
other animals form routines or habits. These hab-
its may hinder the adoption of observed behavior
(van Leeuwen and Haun 2014). Compare this to
the situation in which individuals are ignorant to
the affordances (e.g., when people visit a new
city and want to find a good restaurant)—the im-
pact of observing the choice of the local majority
(i.e., the restaurant with the most customers on
a given square) would be larger than when the
visitors had acquired local preferences. A power-
ful situational incentive to adopt the behavior of
conspecifics seems to be naivety or uncertainty
(Kendal et al. 2009). Given the potential impact
of these different starting points (i.e., experi-
enced or naïve) on the tendency to use social in-
formation, it might improve accuracy to organize
conformity labels accordingly.
The term majority influence refers to any ef-
fect that the majority has on its observers (Haun
et al. 2013). This term includes targeted and
nontargeted majority copying, just like effects
on experienced and naïve observers. Under the
majority influence umbrella, we first identify ma-
jority-biased transmission as a general, nontar-
geted way in which majorities can affect its naïve
observers. In this case, the mere presence of a
majority increases the likelihood that the observ-
ers acquire the strategy of the majority compared
to the expectancy of acquiring this same strategy
in the absence of the majority (Haun et al. 2012;
also see Haun et al. 2013). Different strategies
could lead to majority-biased transmission, in-
cluding random copying or copying successful
individuals. Scholars across disciplines have
used different terms to capture processes that fall
under the term “majority-biased transmission.”
For instance, unbiased transmission refers to
random copying (Boyd and Richerson 1985), just
like linear transmission (e.g., Boyd 1988), linear
imitation (McElreath et al. 2005), and linear con-
formity (Claidière and Whiten 2012). Majority-
biased transmission was proposed to refer to the
process where naïve individuals face a majority.
This scrutiny of naïve individuals’ behavior
has been the trademark of scholars studying cul-
tural evolution (e.g., Boyd and Richerson 1985;
15 Conformity: Definitions, Types, and Evolutionary Grounding
Cavalli-Sforza and Feldman 1981; Henrich
and Boyd 1998; see Aoki avd Feldman 2013).
Moreover, the study of cultural evolution has
produced a more stringent version of majority-
biased transmission. In search of processes that
could change rather than perpetuate the distribu-
tion of cultural variants over generations, notably
towards (asymptotic) within-group homogeneity,
the hallmark of culture, it was found that within
the scope of majority influences only targeted
majority copying yielded the respective change,
not any form of majority-biased transmission
(e.g., Boyd and Richerson, 1985; Laland 2004).
This targeted majority copying was coined con-
formist bias (Boyd and Richerson 1985; Eriksson
and Coultas 2009; Eriksson et al. 2007), copy-
the-majority (Laland 2004), or hyper-conformity
(Claidière and Whiten 2012). The related change
in the distribution of cultural variants within pop-
ulations was referred to as conformist transmis-
sion, or conformity (Boyd and Richerson 1985).
Thus, the discovered impetus towards cultural
differentiation was described by a disproportion-
ate increase in the tendency to copy the majority
with increasing majority sizes (e.g., Henrich and
Boyd 1998). This version of conformity has been
central to studies of cultural evolution (Morgan
and Laland 2012; van Leeuwen and Haun 2014).
The term conformity has also been used in
the study of human psychology, defined as the
modification of an individual’s statements or be-
havior towards matching the majority (Kiesler
and Kiesler 1969). Psychologists have long been
interested in the extent to which humans are sus-
ceptible to group pressure, especially in scenarios
where people have good reasons to believe that
their group expresses an erroneous statement
(e.g., Asch 1956; Jenness 1932; Sherif 1936).
This version of conformity has become common
within popular culture. The human psychology
version of conformity differs from the cultural
evolution version in that individuals with pre-
established preferences, knowledge, or behavior
are being scrutinized, as opposed to naïve ones
(for more details, see van Leeuwen and Haun
2014). This aspect of forgoing personal strategies
in favor of the majority has led researchers to use
the equivalent term strong conformity (Haun and
Tomasello 2011). Most human psychology stud-
ies have not been accurate or explicit in their
analyses regarding targeted and nontargeted ma-
jority copying (Mesoudi 2009; van Leeuwen and
Haun 2014). Instead, different forms of majority
influences have been subsumed under the general
phenomenon of conformity, with the exception
of the distinction between two different motiva-
tions to conform: acquiring valuable informa-
tion ( informational conformity) and inducing
social approval ( normative conformity; Deutsch
and Gerard 1955; also see Claidière and Whiten
2012). The lack of scrutiny on the level of target-
ed and nontargeted majority copying has resulted
in a common usage of the term “conformity”
for instances in which humans (and nonhuman
animals) adopt another strategy without it being
clear whether the majority was responsible for
the strategy shift or any nonmajority influence
(see van Leeuwen and Haun 2014).
Another majority influence aspect that re-
mained incompletely assessed is its evolution-
ary framework. When the diversity of majority
influence definitions hampers cross-species com-
parisons, it remains unclear if there are any non-
human animal equivalents to human conformity
patterns. There is a fast-growing body of stud-
ies reporting cultural group differences in non-
human animals, which is indicative of majority
influences accordingly (reviewed in Galef 2012;
Hoppitt and Laland 2013). The study of cultural
evolution has shown that potent majority influ-
ences (specifically, conformist transmission) can
result in relative within-group homogeneity and
between-group heterogeneity, which in common
language amounts to “cultural differences” (re-
viewed in Aoki and Feldman 2013). Hence, it
could be inferred that nonhuman animal culture
arises through similar majority influence princi-
ples. Although this hypothesis is currently under
investigation (e.g., van Leeuwen et al. 2013;
Luncz and Boesch 2013; van de Waal et al. 2013),
the impetus to view majority influences from an
evolutionary perspective seems plausibly justi-
fied (see also Richerson and Boyd 2005). It was
the seminal work on modeling the evolution of
culture by anthropologists Boyd and Richerson
(1985) that highlighted the importance of placing
192 J. C. Coultas and E. J. C. van Leeuwen
conformity in an evolutionary framework. Their
work not only showed that the targeted form of
majority influence (i.e., conformist transmission)
could lead to cultural group differences, but was
able to explain phenomena that had been evo-
lutionary puzzles until then, most prominently
large-scale human cooperation (Boyd and Rich-
erson 1991). To streamline the proximate forms
of conformity, however, and provide the data-
driven tools to advance the current models of
gene-culture coevolution, we focus on clarifying
the plethora of conformity definitions and prog-
ress in the next section by delineating different
types of conformity and reviewing the existing
evidence accordingly.
Types of Conformity
Early conformity experiments within social psy-
chology (e.g., Asch 1951, 1956; Gerard et al.
1968; Milgram et al. 1969; Sherif 1935) and
theory (e.g., Deutsch and Gerard 1955; Latané
1981; Tanford and Penrod 1984) are still impor-
tant in our thinking about conformity, but more
recent accounts informed by evolutionary theory
challenge us to take another look at the phenom-
enon (e.g., Boyd and Richerson 1985; Cladière
and Whiten 2012; Henrich and Boyd 1998; Rich-
erson and Boyd 2005) and empirical work (e.g.,
Coultas 2004; Efferson et al. 2008; Eriksson and
Coultas 2009; Griskevicius et al. 2006; McEl-
reath et al. 2005).
Because most studies of human psychology
have focused on the “conformity” operationaliza-
tion as outlined in the previous section, we focus
on research shedding light on this phenomenon,
with an occasional excursion to the “conform-
ist transmission” operationalization when stud-
ies are of particular relevance. There has been a
recent proposal to separate conformity research
into two categories: studies where information-
al social influence comes into play and studies
where the influence is normative (Campbell and
Fairey 1989; Cladière and Whiten 2012; Deutsch
and Gerard 1955). There is utility in thinking
about different types of social influence, but in-
formational and normative influences can often
be theoretically and empirically intertwined
(Cialdini and Goldstein 2004; David and Turner
2001). To tease apart the social influences on
conformist behavior, we first consider Deutsch
and Gerard’s (1955) informational and normative
social influence, then review relevant conformity
experiments focusing on three types: conformity
in perceptual judgment, behavioral conformity,
and conformity in opinions and attitudes. The
foundational contribution of conformity research
to both early theoretical models in social psychol-
ogy (Social Impact Theory, Latané 1981; Social
Influence Model, Tanford and Penrod 1984) and
a later gene-culture coevolutionary model (Con-
formist Transmission Model; Boyd and Richer-
son 1985) is acknowledged. However, the con-
text of the experiment (e.g., field or laboratory)
and the prior “habits” and self-perceptions of the
participants (self-categorization theory; Turner
1991) need to be taken into account.
In a recent review of conformity, Cialdini and
Goldstein (2004) focus on Deutsch and Gerard’s
(1955) concept of informational and normative
social influence. This approach to conformity
has been influential, as it draws attention to the
fact that different processes of influence could
be present in different situations. Deutsch and
Gerard describe normative social influence as
an influence to conform to the positive expecta-
tions of another person or group, which can lead
to solidarity and informational social influence
(i.e., to accept information obtained from another
person or group as evidence about reality). They
recognize that these two types of influence often
emerge together, but that it is possible to conform
behaviorally by agreeing publically with the be-
liefs of others even though they are counter to
one’s own beliefs (normative influence; see also
Kelman 1961; Mann 1969). In addition, it is pos-
sible to accept an opponent’s belief as evidence
about a particular aspect of reality (informational
influence) even though there may be no intention
of accepting all the opponent’s beliefs (Deutsch
and Gerard 1955).
Festinger’s (1950, 1954) social comparison
theory encourages us to be cautious in accepting
the distinction between normative and informa-
tional influence without acknowledging some ad-
15 Conformity: Definitions, Types, and Evolutionary Grounding
ditional factors. People tend not to evaluate their
opinions or abilities by comparing themselves
to others who are divergent from themselves
(Festinger 1950). We are more strongly influ-
enced by people who are similar to us. Turner
(1991) also argues that the processes of normal-
ization, conformity, and innovation are intercon-
nected with the formation, maintenance, and
change of in-group norms. Conversely, Campbell
and Fairey (1989) argue for the relative impor-
tance of normative and informational influences
in conformity experiments where they manipulate
public and private agreement using an Asch-type
paradigm. Cladière and Whiten (2012) base their
argument for dissecting conformity research into
these two categories on Campbell and Fairey’s
(1989) work. However, although normative and
informational influences are important notions,
we argue for an explicit appraisal of the type of
conformity experiment in which the respective
behavior is elicited.
Conformity experiments are not homoge-
neous; some studies take place in laboratories
(e.g., Allport 1924; Asch 1951 1956; Sherif
1935), others in natural environments where par-
ticipants are unaware that they are in an experi-
ment (e.g., Allport 1934; Coultas and Eriksson
2014; Mann 1977; Milgram et al. 1969), oth-
ers use naturalistic methods in a formal setting
(e.g., Coultas 2004), whereas other studies influ-
ence people’s opinion in the laboratory or in the
natural environment (Crutchfield 1955; Eriksson
and Coultas 2009; Latané and Davis 1974). This
methodological variation creates problems for
making comparisons across conformity studies.
For instance, group size needs to be greater than
three for naturalistic experiments when people
are unaware that they are taking part in a study;
both Mann (1977) and Coultas (2004) found that
there needed to be at least five or six models of
the target behavior before any conformist behav-
ior was observed.1 Similarly, most behavioral
conformity experiments take place in the field,
whereas perceptual judgment experiments focus-
ing on conformity take place in the laboratory.
1 Asch proposed that conformity leveled off at a group
size of three in perceptual judgment experiments.
The flexible nature of conformity studies on at-
titudes and opinions means that they can take
place in the laboratory or in naturalistic environ-
ments. Next, we address the evidence for confor-
mity classified by the type of experiment, both
regarding task features and the context in which
the study takes place.
Conformity in Perceptual Judgment
Earlier conformity studies (e.g., Asch 1951, 1956;
Crutchfield 1955; Sherif 1935) were explorations
of situational uncertainty where people some-
times denied the evidence of their own senses
and accepted others’ perceptual judgments. The
effect of different group sizes on people’s con-
formist tendencies was measured in these ex-
periments, but not always systematically (Bond
2005). Additionally, the proportion of people
producing the target behavior (majority) com-
pared to those who were producing the minority
behavior was not always clearly reported (e.g.,
Moscovici et al. 1969; Nemeth et al. 1977). One
earlier perceptual judgment study did systemati-
cally manipulate unanimous and nonunanimous
majorities to measure the level of conformist
behavior (Jacobs and Campbell 1961), but it is
only in the past decade, inspired by gene-culture
coevolutionary models, that conformity experi-
ments have begun to systematically manipulate
both group size and proportion.
Perceptual judgment experiments have a spe-
cial place in social psychology, where Asch’s
work on perceptual judgment is most frequently
reported. However, in an earlier experiment, All-
port (1924) had participants judge—both alone
and in groups—the pleasantness or unpleasant-
ness of odors, ranging from putrid to perfumes.
Participants judged the putrid odors as less un-
pleasant when they were in a group than when
they were on their own and the pleasant smells as
less pleasant when they made their judgment in
the group rather than on their own. People modi-
fied their opinion about the odors when work-
ing in a group and avoided extreme judgments.
The reported olfactory experiences changed
depending on whether they were in a group or
194 J. C. Coultas and E. J. C. van Leeuwen
on their own which indicates that a group norm
was formed. Sherif’s (1935) perceptual judg-
ment experiments using the “autokinetic” effect
also demonstrated that artificially created norms
or judgments in groups could alter the judgment
of an individual. He presented a stationary point
of light at a distance of about 5 m from partici-
pants in a darkened room and asked them (both
in groups and alone) to make oral estimations
about the movement of the light. The participants
in groups were influenced by the overestimation
of confederates.
Utilizing the situational ambiguity of Sherif’s
(1935) autokinetic effect, Jacobs and Campbell
(1961) asked groups of two, three, or four partici-
pants to make judgments on how far the light had
moved. In the first set of 30 trials, all but one of
the participants were confederates and gave wide-
ly discrepant judgments compared to that of the
one naïve participant. In subsequent blocks of 30
trials (generations), a confederate was removed
and another naïve participant was included in
the group. By the second, third, or fourth genera-
tion, there were no confederates left in the group.
Jacobs and Campbell (1961) continued their
experiment by replacing the most experienced
naïve participant with another naïve participant
up to the 11th generation. They found that control
groups estimated the light movement around the
4-inch mark, but naïve participants in the presence
of confederates who were radically overestimat-
ing the light movement (e.g., 16 inches) would
provide much greater estimates than those in the
control condition (e.g., 14 inches). Even when all
the confederates had been replaced, the influence
of the confederates remained, with naïve partici-
pants estimating the light movement at around
the 10-inch mark. Jacobs and Campbell’s results
indicate that the majority can have a significant
effect on how others make perceptual judgments
even after those who made up the majority are
no longer present. The experimental procedures
used by Jacobs and Campbell (1961) suggest the
existence of conformist transmission (Boyd and
Richerson 1985; Henrich and Boyd 1998).
Asch (1951) wanted to test conformity in a
situation where, unlike Sherif’s autokinetic ef-
fect, there was a right or wrong answer. He asked
participants to match the length of a line on one
card with one line out of three lines of unequal
length on another card. In a control group, Asch
found that the error rate was very small. In the
main study, confederates made unanimously in-
correct line judgments two thirds of the time (on
12 out of 18 trials). Naïve participants were then
asked to give their answer. Three quarters of par-
ticipants were influenced by the incorrect major-
ity some of the time. In total, just over two thirds
of the choices made by the real participants were
correct despite the pressure of the majority. Asch
used unanimous groups of various sizes (1, 2, 3,
4, 8, 16) and found that when there was one con-
federate and one naïve participant the majority
effect all but disappeared. Asch was convinced
that the effect was present in full force when
there was a majority of three (though it is impor-
tant to note that Asch’s assertion was based on a
sample of ten participants). The larger majorities
of four, eight, and sixteen did not produce effects
that were substantially greater than a majority of
three. He therefore predicted a nonlinear effect
of conformity. It would be judicious to accept
these results with a note of caution due to the
small sample size and concerns about consisten-
cy across Asch’s studies (Bond 2005). Another
reason for caution is that an early Asch replica-
tion (Gerard et al. 1968) found that conformity
increased linearly with group size, although the
first few models of the behavior had the most im-
One of the defining characteristics of percep-
tual judgment tasks is that there is often scope
for situational ambiguity. In Sherif’s autokinetic
technique, even the control participants believed
that the stationary light had moved a short dis-
tance. Recently, there have been critical assess-
ments of Asch’s studies in a meta-analysis of
Asch-type perceptual judgment task studies
(Bond and Smith 1996). Bond and Smith also
note that conformist behavior as defined by per-
formance on the Asch perceptual judgment task
has declined in the USA since the 1950s. Bond
(2005) comments that “given the pre-eminent
status of Asch’s (1951,1955, 1956) conformity
experiments, it is surprising to find inconsisten-
cies in the reports of what size of majority was
15 Conformity: Definitions, Types, and Evolutionary Grounding
employed” (p. 338). A large number of percep-
tual judgment experiments have used nonunani-
mous majorities, but have not systematically test-
ed proportion (e.g., Asch 1951, 1956; Moscovici
et al. 1969; Nemeth et al. 1977). The predictions
made by theoretical models (Boyd and Richerson
1985; Latané 1981; Tanford and Penrod 1984)
encourage researchers to carefully plan studies
where both group size and proportion are varied
Behavioral Conformity
A key aspect of many behavioral conformity ex-
periments is that participants are unaware that
they are taking part in a study. Bargh and Char-
trand’s (1999) work on automatic imitation, in
which people adopt the behavior of those around
them without being aware, has made a contri-
bution to our thinking about conformity experi-
ments in naturalistic environments. Our predis-
position for affiliative (Cialdini and Goldstein
2004) or docile (Simon 1990) behavior means
we often copy those around us without any con-
scious intent. This form of behavioral conformity
would fall under the heading of the ethological
approach to human behavior—observing hu-
mans in their natural habitat (Hinde 1982). Many
years before Asch’s studies, Allport (1934) had
developed his J-curve conformity hypothesis
by observing people stopping their cars at street
crossings, people parking their cars, the degree of
kneeling in two Catholic churches, and participa-
tion in congregational singing. He argued that in
order for conformity to occur there had to be a
purpose for the behavior, there had to be some
rule in society related to it, and over half the pop-
ulation needed to be behaving in that particular
way. Allport’s main conformity hypothesis was
that if over half the population were producing a
particular behavior then that behavior was likely
to be adopted. This is similar to the predictions
made by Boyd and Richerson’s (1985) conform-
ist transmission model.
Following the tradition of naturalistic obser-
vation, Milgram et al. (1969) sent out groups
of stooges (group sizes 1, 2, 3, 5, 10, and 15) to
stare up at a building in New York and counted
how many people looked up as they walked
past or stopped and stared alongside the group.
They found that the size of the stimulus group
significantly affected the proportion of passersby
who looked up or stopped alongside the group.
The larger the stimulus crowd staring up at the
building, the greater the effect.2 More recently,
this field study has been replicated in the UK
and Sweden (Coultas and Eriksson 2014; Gallup
et al. 2012) producing a similar linear pattern of
influence with increase in group size. However,
far fewer people were influenced to stare up at
a building in the UK and Sweden compared to
the earlier New York study, leading to the ques-
tion of whether these differences in conformity
are situational. Potential influences on behavioral
conformity include location (e.g., city size; Mil-
gram 1970; Newman and McCauley 1977; Mul-
len et al. 1990), change in conformist behavior
across time (Bond and Smith 1996), and different
types of groups or entities. Knowles and Bassett
(1976) manipulated the type of stimulus groups
in a similar field experiment to Milgram et al.
and found that those standing silently while star-
ing up had greater influence on passersby com-
pared to groups who interacted with one another.
Coultas and Eriksson’s (2014) replication of Mil-
gram et al.’s (1969) study, which ran in three dif-
ferent locations in the UK and one in Sweden,
also established that the type of stimulus group is
an important factor.
The fundamental difference between conformi-
ty field studies and laboratory experiments is that
participants in the laboratory know that they are tak-
ing part in an experiment. The ethological method
focuses on humans in their natural habitat—walk-
ing along the street, sometimes making decisions
consciously, while at other times automatically fol-
lowing the crowd. Mann (1977) looked at the in-
fluence of stimulus groups on people’s queue-join-
ing behavior in Jerusalem where this was not the
social norm. Mann observed the effect of stimulus
queues of two, four, six, and eight confederates on
569 commuters waiting at a bus stop. Congruent
2 Lumsden and Wilson (1981) used these findings when
constructing their trend-watcher curve.
196 J. C. Coultas and E. J. C. van Leeuwen
with findings by Milgram et al., Mann found that
a larger stimulus queue had a greater influence on
commuters. However, unlike in Milgram et al.’s
study, Mann found that a six-person queue was re-
quired to induce a reliable level of queue-joining
behavior. These findings reinforce the need to take
the situation into account when designing experi-
ments and manipulating group size.
Field studies are used extensively to demon-
strate how humans behave in everyday life. In
their naturalistic study of environmental conser-
vation, Aronson and O’Leary (1983) found that
a sign instructing students to save water by turn-
ing off the shower while they soaped up had little
effect, whereas two thirds turned off the shower
with two models of the behavior. Similarly, two
field experiments by Goldstein et al. (2008)
found that hotel guests were not influenced by
a sign in their room encouraging environmental
conservation (e.g., reuse their towels), but were
influenced by the information that the majority
of hotel guests reuse their towels. Situational
influence was also present, as hotel guests who
were informed that the majority of guests who
had stayed in their current room had reused their
towels were more likely to produce the same be-
havior than those guests who only saw the sign
encouraging environmental conservation.
Goldstein et al. (2008) report a study of con-
formity to the unseen and anonymous majority.
Inevitably, there will be studies of conformist be-
havior that do not fall easily into the categories
of behavioral conformity, perceptual judgment,
or attitudes. An unpublished study by Latané
and Davis (1974 cited in Latané and Wolf 1981)
is an example of conformity to the anonymous
majority’s opinion. In this field experiment, col-
lege students were approached and asked to sign
a questionnaire concerning the adequacy of local
newspapers. Each page of the questionnaire had
one question at the top and two columns labeled
“yes” and “no” below. This dichotomous choice
was a constrained behavior with little commit-
ment required other than to sign one’s name in
a column. The questionnaires already contained
a varying number of signatures before being pre-
sented to the respondent. These signatures were
either all in the “yes” column or all in the “no”
column and were counterbalanced so that they
appeared in both columns an equal number of
times. Even though a proper baseline measure
was absent in their study (i.e., how people would
behave if there were no signatures), they found
that conformity increased systematically with the
number of signatures up to a majority of 12.
Importantly, individuals’ habitual behavior
will influence how they respond to a novel behav-
ior. In a study of behavior in a computer labora-
tory, participants—unaware that they were taking
part in an experiment—were influenced to place
their keyboard covers in an unusual position (on
top of their computers) by the presence of models
of that behavior (Coultas 2004). However, con-
trary to Asch’s findings, group size needed to be
greater than three before anyone copied the novel
behavior and conformed to the majority which
demonstrated that the strongest predictor of con-
formity, once group size was greater than five,
was the proportion of individuals who were al-
ready producing the behavior. In a subsequent ex-
periment, participants who had signed up for clin-
ical psychology experiments also (unknowingly)
took part in a conformist transmission study in
which they were influenced to change the way
they wrote the date by those who had filled in the
sheets and signed the date before them (a com-
mon method, e.g., “14/5/96,”3 and a rare meth-
od, e.g., “14th May 1996”; Coultas 2004). The
relative size of the majority (i.e., proportion) was
shown to be a significant predictor of conformity
and participants were more likely to be influ-
enced by the majority if their behavior was rare
(e.g., 14th May 1996) and the majority behavior
was the common behavior (e.g., 14/5/96). In this
case, the data fitted the conformist transmission
curve. However, when an individual who wrote
the date in the most common form (14/5/96)
was presented with a sheet where the majority of
people (forged) had written the date analogically
(14th May 1996), conformity occurred only when
approximately three quarters of the forged dates
were written analogically. People were less likely
to adopt a rare behavior even if that behavior was
common in the context of the experiment.
3 Note that this is the UK numerical version of the date.
US version would be 5/14/96. The difference in US/UK
date-signing was used as a variable in an unpublished
study by Moore and Coultas (2010).
15 Conformity: Definitions, Types, and Evolutionary Grounding
The two studies by Coultas (2004) were a di-
rect test of the conformist transmission model
(Boyd and Richerson 1985), as both the influ-
ence of group size and proportion was measured
for each individual. Recapitulating, conformist
transmission is the disproportionately increasing
tendency to adopt the majority strategy with in-
creasing relative majority size and can thus only
be measured when group size and majority pro-
portion are varied. Its importance follows from
the fact that only this disproportionate tendency
to copy the majority will yield behavioral patterns
typical of what we consider to be “culture” (i.e.,
relative within-group homogeneity and between-
group heterogeneity; see also Richerson and
Boyd 2005). The computer laboratory and date-
signing studies also illustrate that the conformist
transmission model needs to be modified on the
basis of the “habits” that people bring with them
to naturalistic experiments. Our predispositions
to behave in certain ways can override the influ-
ence of the majority if we are strongly attached
to our personal strategy (van Leeuwen and Haun
2014) or the specific behavior that is being stud-
ied is not a social norm. In their review, Cialdini
and Goldstein (2004) also acknowledge that pre-
existing attitudes, prior behaviors, and commit-
ments will influence our behavior towards novel
stimuli. These habits or predispositions that peo-
ple bring to a situation are related to the concept
of social identity (Tajfel and Turner 1979; Turner
et al. 1987); the phenomenon that describes how
people’s perception of who they are is based on
their identifying with certain groups (see also
the concept of self-categorization (Turner 1991)
and the drive to maintain a favorable self-con-
cept (Cialdini and Goldstein 2004). However,
the adoption of a group norm may not always be
a conscious action (Bargh and Chartrand 1999;
Chartrand and Bargh 1999; Nisbett and Wilson
Conformity in Opinion and Attitude
The terms opinions and attitudes are sometimes
incorrectly used interchangeably (e.g., Nowak
et al. 1990; Haddock and Maio 2008). Attitudes
have affective, cognitive, and behavioral compo-
nents and involve favoring or disfavoring some
particular entity (e.g., Eagly and Chaiken 1993).
Moreover, attitudes are relatively deep-rooted
and change only gradually over time. Opinions
are more flexible and prone to change and there-
fore are the most relevant in a review of confor-
mity research. However, there is empirical evi-
dence that both people’s opinions and attitudes
are influenced by those around them (Crutchfield
1955; Eriksson and Coultas 2009; Newcomb
et al. 1967; Wolf and Latané 1983).
Most of the studies in this section focus on
participants changing their opinion about a par-
ticular aspect within an experiment. However, in
a longitudinal study begun in 1935, Newcomb
(1943) studied attitude change across time at a
college with predominantly conservative stu-
dents and liberal professors. Over time, students
increasingly adopted the liberal attitudes of their
new reference group, the professors. When New-
comb et al. (1967) interviewed the students 25
years later, they found that the adopted attitudes
persisted. Indeed, opinion change has been a topic
within social psychology for many years (e.g.,
Allport 1924; reviewed in Cialdini and Gold-
stein 2004). Opinions can be manipulated both
in the laboratory (e.g., Crutchfield 1955) and in
the field (e.g., Eriksson and Coultas 2009; Latané
and Davis 1974; Stang 1976; White 1975). For
instance, in Crutchfield’s (1955) study, where
participants agreed or disagreed with particular
statements, there was a shift to change opinion
and agree with the unanimous majority, but when
participants provided a subjective judgment
(preference) about two simple line drawings they
were not influenced by the majority.
The study of the effects of different motiva-
tions on tendencies to conform has been extended
beyond the distinction between informational and
normative influences. In a coherent set of experi-
ments, two motives pivotal to evolutionary success
were studied in the context of conformity: self-pro-
tection (survival) and mate attraction (reproduc-
tion; Griskevicius et al. 2006). By theorizing about
the possible ramifications of conformity in light
of these two motives, these scholars were able to
predict the existence of (sex-specific) behavioral
198 J. C. Coultas and E. J. C. van Leeuwen
patterns likely shaped by evolutionary processes.
In line with these predictions, being primed with a
self-protective mindset caused both males and fe-
males to increase their conformist responses. This
finding was interpreted to be evolutionarily ad-
vantageous in the sense that avoiding standing out
from the crowd lowers predation risk (Griskevi-
cius et al. 2006). Additionally, the activation of
mate attraction motives resulted in sex-specific
conformity responses, congruent with predictions
based on sex-specific mating strategies where men
chose to stand out of the crowd to highlight the
qualities generally preferred by women (assertive-
ness, independence, leadership; see Buss 2003)
and women preferred to emphasize the qualities
generally liked by men (agreeableness, facilitating
group cohesion; see Campbell 2002) by conform-
ing to the majority (Griskevicius et al. 2006).This
study nicely illustrates how evolutionary theory
could be used to set up specific empirical studies
revolving around conformist tendencies.
A useful approach to understanding different
types of influence is to examine the situations in
which conformist behavior occurs. Why would
conformist behavior have been useful in our evo-
lutionary past? In situations where there is uncer-
tainty about the correct behavior, the best strat-
egy is often to adopt the most common behavior
(Boyd and Richerson 1985). From this perspec-
tive, both group size and proportion are important
factors in conformity research. Two theoretical
models in social psychology sought to formal-
ize predictions of conformist behavior, using
both group size and proportion; whereas Latané
(1981) used the findings from Asch (1951) and
Milgram et al. (1969) as the foundations of social
impact theory (SIT), Tanford and Penrod (1984)
used jury decision making in the development of
their social influence model (SIM).4 This means
that SIT used both laboratory (e.g., Asch) and
field studies (e.g., Milgram et al.) synonymously,
whereas social influence theory used jury deci-
sion making to represent social influence in gen-
eral. In an alternative approach, Boyd and Richer-
son (1985) used the gene-culture coevolutionary
4 The SIM equation in Tanford and Penrod (1984) is
incorrect (see Coultas, 2004; MacCoun, 2012).
theory, inspired by population genetics and past
research within social psychology, to develop
their conformist transmission model. This evo-
lutionary model of conformity made predictions
about behavior which had echoes of an earlier
model of conformity within social psychology
(Allport 1934). Boyd and Richerson’s conformist
transmission model emphasized the importance
of proportion (frequency) in conformity research
and enabled researchers to formalize their empiri-
cal work in order to test the model both in simula-
tions (Henrich and Boyd 1998) and in the field
(Coultas 2004; Eriksson and Coultas 2009). How-
ever, for reasons of direct relevance to the evolu-
tion of culture, their theoretical focus has not been
on the aspect of changing perceptions, behavior,
or opinions, but rather on the more pronounced
form of conformist behavior (i.e., “conformist
transmission”) in which typically naïve individu-
als are under investigation. At the intersection of
social psychology’s focus on “conformity” and
the conformist variant central to analyses of cul-
tural evolution (“conformist transmission”), we
would envision fruitful cross-fostering leading to
the incorporation of individuals’ habits or predis-
positions, and the evidenced circumstances under
which they would be abandoned, into models of
cultural evolution (cf. Strimling et al. 2009; see
also van Leeuwen and Haun 2014).
This section has aimed to emphasize the im-
portance of taking into account the type (percep-
tion, behavior, or opinion) and context (laboratory,
field) of conformity, while at the same time ad-
vancing the idea that individuals’ current habits or
mind-sets need to be factored in when interpreting
any kind of conformist or nonconformist behavior.
Concluding Remarks
In this chapter, we hope to have conveyed how
evolutionary theory can elucidate the study of
conformity. By taking seriously the predictions
and ramifications of the early gene-culture co-
evolution models (Boyd and Richerson 1985;
Henrich and Boyd 1998) and by appreciating
the conformity evidence from nonhuman animal
studies, our understanding of conformist behavior
15 Conformity: Definitions, Types, and Evolutionary Grounding
can transcend the unfounded sphere of plausible
evolutionary scenarios to become a substantiated
research endeavor including testable hypotheses
stemming from evolutionary theory. However,
we have identified several proximate issues that
cloud our current appreciation of the scope of
conformity. In order to achieve a coherent field
of conformity research in the future, we have
three simple pieces of advice for researchers.
Firstly, define conformity in the context of your
experimental manipulation. Social psychology
typically focuses on another form of conformity
than scholars investigating cultural evolution, and
even within social psychology, there are several
different definitions; only by specifying the oper-
ationalization of conformity will we be able to in-
terpret and compare the phenomena validly. Sec-
ondly, make sure that different types of confor-
mity are not subsumed under the same heading.
Different patterns are expected based on whether
the conformity scenario entails perceptual, behav-
ioral, or opinion features. Moreover, field studies
and laboratory studies yield very different results.
In general, group size needs to be larger in field
studies than in the laboratory before conformist
behavior is elicited. Furthermore, it would be
fruitful to formally acknowledge that participants’
preestablished views and habits will inevitably in-
fluence the outcome of any conformity study. By
operationalizing this idiosyncratic aspect and in-
corporating this measure into conformity models,
in both social psychology and the study of cul-
tural evolution, we will gain a more fine-grained
understanding of the effects of majorities. Finally,
taking an evolutionary perspective on conformity
is an exciting proposition, but take care not to
overestimate the presence of conformity based on
models and simulations. It makes good sense to
conform to the group in some situations, but non-
conformity and independence are also adaptive
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... One of the important holistic concepts of the social sciences which are very similar in the context of subject-object-environment interaction is social conformity in social psychology. Social conformity is a type of social influence that results in a change of behavior or belief to fit in with a group (Coultas, & van Leeuwen, 2015). Social conformity can occur in the form of obedience, compliance, identification, and internalization. ...
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In the book Two Cultures, two cultures and the Scientific Revolution, C. P. Snow's (1959) is the first episode of the popular speech conference. He argued that sciences and humanities had been separated into "two cultures" in "the intellectual history of Western civilization‖ and that this separation became a significant handicap both in addressing the problems of today's World. This criticism can be understood in the context of mechanistic view and cartesian philosophy. The idea had found a very strong foundation for finding a position for itself, not only in the natural sciences, but also in the Social Sciences. For instance, in the early 1800s, philosopher Auguste Comte formulated the name 'Social Physics' with the hope that a mechanistic science could help to break down the complexities of society. Curriculum theory was also begun by such views based on the principles of the Fordist production system. However, scientists find that the rules of classical physics and mechanistic view do not necessarily extend to the beginning of the 20th century. Today, we confront a similar paradigm shift in the curriculum theory from the cartesian perspective toward a more holistic view in curriculum theory combining two cultures. Therefore, the main aim of this article is to discuss curriculum theory in the context of such a paradigm shift. In this respect, curriculum theory is taken as the transdisciplinary study of educational experience in which the main focus is ideas.
... Conformity is the act of adjusting to the group. As creatures that live in groups, most of our behavior is focused on maintaining relationships with groups (Coultas & Van Leeuwen, 2015;Wijenayake et al., 2020). According to Myers (2015), conformity is a change in behavior or action caused by pressure from a group. ...
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The research aimed to investigate the relationship between conformity and consumptive behavior in female adolescents. It applied a quantitative method with ex-post facto design. The sample was 97 female adolescents in Yogyakarta and was determined using a convenience sampling technique. They completed two questionnaires of conformity and consumptive behavior. The instrument validation technique used content validity, and the validity of the instruments was measured by psychology measurement experts. The instruments' reliability was analyzed using Cronbach Alpha with coefficients of 0,914 (consumptive behavior) and 0,790 (conformity). Data analysis techniques used Pearson product-moment correlation analysis. The result of the research shows that there is a significant positive relationship between conformity and consumptive behavior in female adolescents. In other words, conformity can be a strong predictor of consumptive behavior in female adolescents.
... Although this might be good in hindsight, it is actually bad since you have to conform to the wants of the group even if it compromises what you want to do. Conformity is a powerful force in human decision making and is best understood from an evolutionary perspective (Coultas, & Leeuwen, 2015). ...
... and Richerson's (1985, chapter 7) conformist transmission has been debated (see, e.g.,Coultas and van Leeuwen, 2015). However, from a theoretical standpoint, it is reasonable to regard conformist cultural transmission as a particular case of frequency-dependent transmission. ...
In a model of vertical and oblique cultural transmission of a dichotomous trait, the rates of transmission of each form of the trait are functions of the trait frequency in the population. Sufficient conditions on these functions are derived for a stable trait polymorphism to exist. If the vertical transmission rates are monotone decreasing functions of the trait frequency, a complete global stability analysis is presented. It is also shown that a unique protected polymorphism can be globally stable even though the sufficient conditions are not met. The evolution of frequency-dependent transmission is modeled using modifier theory, and exact conditions are derived for a transmission modifier to invade a population at a stable polymorphism. Finally, the interaction between frequency-dependent selection and frequency-dependent transmission is explored.
... As a final terminological note, the influence of majority rules has chiefly been studied by social psychologists under the label of conformity, distinguishing between normative conformity -aiming at ingratiation with the group one conforms to -and informational conformity -aiming at accuracy (Deutsch and Gerard 1955; for an attempt to experimentally disentangle the effects of both types of conformity, see Sowden et al. 2018). It is often difficult to tell exactly how much these two types of conformity are engaged in a given task -a difficulty linked to the fact that the theoretical distinction is itself not entirely clear-cut (see Cialdini and Goldstein 2004;Coultas and van Leeuwen 2015;Deutsch and Gerard 1955;Hodges 2015). The difficulty in distinguishing informational and normative conformity is even more acute in the case of non-experimental studies, which is the main reason why we have chosen to exclude them from the present review. ...
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Mathematical models and simulations demonstrate the power of majority rules, i.e. following an opinion shared by a majority of group members. Majority opinion should be followed more when (a) the relative and absolute size of the majority grow, the members of the majority are (b) competent, and (c) benevolent, (d) the majority opinion conflicts less with our prior beliefs and (e) the members of the majority formed their opinions independently. We review the experimental literature bearing on these points. The few experiments bearing on (b) and (c) suggest that both factors are adequately taken into account. Many experiments show that (d) is also followed, with participants usually putting too much weight on their own opinion relative to that of the majority. Regarding factors (a) and (e), in contrast, the evidence is mixed: participants sometimes take into account optimally the absolute and relative size of the majority, as well as the presence of informational dependencies. In other circumstances, these factors are ignored. We suggest that an evolutionary framework can help make sense of these conflicting results by distinguishing between evolutionarily valid cues-that are readily taken into account-and non-evolu-tionarily valid cues-that are ignored by default. Social Media Summary: People are good at taking majority opinions into account, when the information is presented naturally. Humans rely enormously on others to obtain information. In many cases, we rely not on a single individual, but on several informants-we seek advice from our colleagues, read different newspapers, ask for a second medical opinion. Sometimes these informants provide divergent advice, sometimes they concur. When several people agree, how much weight should we put on their opinion? We have known at least since Condorcet (1785) that following majority rules-adopting the opinion of the majority of the relevant group-can be a powerful heuristic. However, this heuristic should be used with caution, as it only applies under specific circumstances. The present article reviews the literature on how, and how well, humans use majority rules. Our review does not bear on how groups make collective decisions, but on how individuals take into account majority opinions. Although these two domains are linked, they are distinct: groups can make collective decisions without using majority rules, and individuals can use majority rules without any group decision having to be made, or without even belonging to any group. How individuals take into account the decisions made by others will often influence the group's collective capacity to arrive at the right decision. The rules an individual uses to aggregate the decisions of other individuals may thus be seen as an element of collective decision-making, itself an aspect of group cognition (Hutchins 1996). Here, however, the important
... Prochazkova & Kret, 2017) and cognitive alignment (e.g. conformity and consensus Coultas & van Leeuwen, 2015). Importantly, they proposed that these three levels of social alignment (motion, emotion, and cognition) represent a core mechanism of connectedness and rely on shared neural networks; therefore, triggering one behaviour activates all other behaviours and encourages likability, closeness and connectedness. ...
... Social conformity is the act of fitting in with the group, manifested in the tendency of people to modify their opinions or judgments according to those of the group [15]. This form of 'cognitive' alignment with the group can appear in various domains such as food preference [16], longterm memory [17], visual perception [18], and moral judgments [19]. ...
When we clap our hands in synchrony, feel the sadness of a friend, or match our attitudes to peer norms, we align our behavior with others. We propose here a model that views synchronized movement, emotional contagion, and social conformity as interrelated processes that rely on shared neural networks. Building on the predictive coding framework, we suggest that social alignment is mediated by a three-component feedback loop – an error-monitoring system that reacts to misalignment, an alignment system, and a reward system that is activated when alignment is achieved. We describe herding-related syndromes (autism, loneliness) and call for innovative research to investigate the links between the levels of alignment.
Children’s engagement is identified at four main levels: solitary, onlooking, parallel-aware and cooperative. These levels differ in the degree of shared attention, contingency, control and shared understanding involved. Design influences how children transition between different levels. Initial engagement involves creating potential entry points to draw children in. Augmented objects can increase the likelihood of transition to more collaborative interaction through sound and vision, yet technology may also interfere with engagement. Tabletops and digitally-augmented objects can work well for collaboration through supporting shared awareness. The same factors in engagement can be considered for using technologies that are more widely available.
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ÖZ: Tüketiciler için lüks ürün satın almanın, mutluluğu yakalamada önemli bir bireysel motivasyon unsuru olduğu ileri sürülmektedir. Tüketiciler satın alma kararı verirken çevresindeki insanlardan etkilenebilir. Bu davranışsal etkinin altında yatan temel neden tüketici sosyal uyumu olarak tanımlanmaktadır. Tüketici sosyal uyumunun şiddeti cinsiyet açısından farklılık gösterebilir. Araştırmanın amacı, lüks üründe mutluluk arama motivasyonu ile lüks ürün satın alma niyeti arasındaki ilişkide, tüketici sosyal uyumu ve cinsiyetin düzenleyici rolünün belirlenmesidir. Oluşturulan anket 422 katılımcıya uygulanmıştır. Araştırmada, SPSS programına yüklenerek kullanılan, PROCESS Makro yazılımı düzenleyici analizi yapılmasına yardımcı olmuştur. Sonuçlara göre lüks üründe mutluluk arama motivasyonunun lüks ürün satın alma niyeti üzerindeki etkisi sosyal uyumu yüksek olan tüketicilerde daha fazla etkilidir. Bu etkinin, sosyal uyumu yüksek olan kadın tüketicilerde daha güçlü olduğu anlaşılmıştır. Anahtar Kelimeler: Lüks Üründe Mutluluk Arama Motivasyonu, Lüks Ürün Satın Alma Niyeti, Tüketicinin Sosyal Uyumu, PROCESS Makro Model ABSTRACT: For consumers, it has been argued that purchasing luxury products is an important individual motivation in having pleasure. Consumer may be affected by people around them when making purchasing decisions. The main reason underlying this behavioral effect is defined as consumer social conformity. The force of consumer social conformity may differ in terms of gender. The aim of the study is to reveal the moderating role of consumer social conformity and gender in the relationship between pleasure seeking motivation in luxury product and luxury product purchase intention. The questionnaire was conducted to 422 participants. To perform moderating analysis, PROCESS Macro software was used by installing SPSS program. It is revealed that the effect of pleasure seeking motivation in luxury product on the luxury product purchase intention is more effective for consumers with high social conformity. This effect is more powerful for women with high consumer social conformity. Keywords: Pleasure Seeking Motivation in Luxury Product, Luxury Product Purchase Intention, Consumer Social Conformity, PROCESS Macro Model
One characteristic of human nature is the ability to align our behavior with others. Previous research has linked poor communication skills to alexithymia. This may suggest the possibility that individuals with high alexithymia do not adhere to the principles of social alignment. One form of cognitive alignment is consensus with a group. So far, little research attention has been given to the possible link between alexithymia and this form of cognitive social alignment. In this study, we address this gap by investigating the association between consensus-reaching abilities and alexithymia. A sample comprising of 122 participants completed the Toronto Alexithymia Scale and then played a specially designed game called “Consensus under a deadline”. In each game, a participant played with either seven bots designed to act rationally and always seek a consensus, or with seven other participants. The participants were unaware who they were playing with. The results of the study confirm the link between alexithymia and impaired cognitive social alignment, showing that the alexithymia cognitive component (EOT) is associated with a deficit in reaching a consensus with humans (that sometimes act irrationally). However, this association was not evident when group members were bots (that always act rationally).
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Evidence is reviewed which suggests that there may be little or no direct introspective access to higher order cognitive processes. Subjects are sometimes (a) unaware of the existence of a stimulus that importantly influenced a response, (b) unaware of the existence of the response, and (c) unaware that the stimulus has affected the response. It is proposed that when people attempt to report on their cognitive processes, that is, on the processes mediating the effects of a stimulus on a response, they do not do so on the basis of any true introspection. Instead, their reports are based on a priori, implicit causal theories, or judgments about the extent to which a particular stimulus is a plausible cause of a given response. This suggests that though people may not be able to observe directly their cognitive processes, they will sometimes be able to report accurately about them. Accurate reports will occur when influential stimuli are salient and are plausible causes of the responses they produce, and will not occur when stimuli are not salient or are not plausible causes.
Long considered one of the most provocative and demanding major works on human sociobiology, Genes, Mind, and Culture introduces the concept of gene-culture coevolution. It has been out of print for several years, and in this volume Lumsden and Wilson provide a much needed facsimile edition of their original work, together with a major review of progress in the discipline during the ensuing quarter century. They argue compellingly that human nature is neither arbitrary nor predetermined, and identify mechanisms that energize the upward translation from genes to culture. The authors also assess the properties of genetic evolution of mind within emergent cultural patterns. Lumsden and Wilson explore the rich and sophisticated data of developmental psychology and cognitive science in a fashion that, for the first time, aligns these disciplines with human sociobiology. The authors also draw on population genetics, cultural anthropology, and mathematical physics to set human sociobiology on a predictive base, and so trace the main steps that lead from the genes through human consciousness to culture. © 2005 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.
Attitude and opinion data provide a basis for inferring the meaning of opinions held by individuals and groups and also for predictions about their future behavior. Such inferences and predictions, if they are to be made effectively, require a theoretical foundation which explains the processes by which people adopt and express particular opinions. Here is a theory of three processes by which persons respond to social influence.
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What was noted by E. J. Langer (1978) remains true today; that much of contemporary psychological research is based on the assumption that people are consciously and systematically processing incoming information in order to construe and interpret their world and to plan and engage in courses of action. As did E. J. Langer, the authors question this assumption. First, they review evidence that the ability to exercise such conscious, intentional control is actually quite limited, so that most of moment-to-moment psychological life must occur through nonconscious means if it is to occur at all. The authors then describe the different possible mechanisms that produce automatic, environmental control over these various phenomena and review evidence establishing both the existence of these mechanisms as well as their consequences for judgments, emotions, and behavior. Three major forms of automatic self-regulation are identified: an automatic effect of perception on action, automatic goal pursuit, and a continual automatic evaluation of one's experience. From the accumulating evidence, the authors conclude that these various nonconscious mental systems perform the lion's share of the self-regulatory burden, beneficently keeping the individual grounded in his or her current environment.
The chameleon effect refers to nonconscious mimicry of the postures, mannerisms, facial expressions, and other behaviors of one's interaction partners, such that one's behavior passively rind unintentionally changes to match that of others in one's current social environment. The authors suggest that the mechanism involved is the perception-behavior link, the recently documented finding (e.g., J. A. Bargh, M. Chen, & L. Burrows, 1996) that the mere perception of another' s behavior automatically increases the likelihood of engaging in that behavior oneself Experiment 1 showed that the motor behavior of participants unintentionally matched that of strangers with whom they worked on a task. Experiment 2 had confederates mimic the posture and movements of participants and showed that mimicry facilitates the smoothness of interactions and increases liking between interaction partners. Experiment 3 showed that dispositionally empathic individuals exhibit the chameleon effect to a greater extent than do other people.