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https://doi.org/10.1177/0146167220913694
Personality and Social
Psychology Bulletin
1 –22
© 2020 by the Society for Personality
and Social Psychology, Inc
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DOI: 10.1177/0146167220913694
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Empirical Research Paper
Humans are embedded in social relationships. Social
exchange theory, a prominent conceptual model, treats social
relationships as a series of transactions between two or more
parties (Cropanzano et al., 2017). According to this theory,
people’s transactions are shaped by the history of their inter-
actions. Importantly, each transaction casts a long shadow
over the future of the continued exchanges between individu-
als (Baron & Neuman, 1996; Burger, 1986; Charness et al.,
2007). Social exchange theory also posits that reciprocity
governs interpersonal exchanges, such that each individual
reciprocates the behaviors of another (e.g., Gouldner, 1960;
Helm et al., 1972).
Past research provides different perspectives on the role
of reciprocity in repeated social exchanges. One perspective,
homeomorphic reciprocity, holds that individuals reciprocate
actions in kind (Lyons & Scott, 2012). This view suggests
that the behavior that follows an action should be similar in
valence (i.e., positive or negative) and magnitude to the orig-
inal behavior that instigated the positive or negative reci-
procity (Cropanzano et al., 2017; Lyons & Scott, 2012). As a
result, reciprocity should remain relatively stable over time.
In contrast, an alternative perspective predicts that reciproc-
ity may escalate over time (e.g., Andersson & Pearson, 1999;
Hershcovis & Barling, 2010).
In this research, we reconcile these conflicting perspec-
tives by closely examining both positive and negative social
exchanges across different cultural contexts. We investigate
when and why, in repeated exchange relationships, culture
induces homeomorphic reciprocity in some contexts and the
escalation of reciprocity in other contexts. We propose that
individuals in different cultural settings may perceive equiv-
alent positively and negatively framed exchanges asymmet-
rically. Specifically, we suggest that, in positive exchanges,
individuals in North American settings will escalate reci-
procity, but individuals in East Asian settings will recipro-
cate in kind. Conversely, in negative exchanges, individuals
in East Asian settings will escalate their reciprocity, but indi-
viduals in North American settings will reciprocate in kind.
913694PSPXXX10.1177/0146167220913694Personality and Social Psychology BulletinDeng et al.
research-article2020
1Oklahoma State University, Stillwater, USA
2Northwestern University, Evanston, IL, USA
3City University of Hong Kong, Kowloon, Hong Kong
4London Business School, UK
Corresponding Author:
Cynthia S. Wang, Management & Organizations Department and the
Dispute Research Resolution Center, Northwestern University, 2211
Campus Drive, Evanston, IL 60208, USA.
Email: scynthia.wang@kellogg.northwestern.edu
Culture and Patterns of Reciprocity: The
Role of Exchange Type, Regulatory Focus,
and Emotions
Yingli Deng1, Cynthia S. Wang2, Federico Aime1, Long Wang3,
Niro Sivanathan4, and Yun Chung (Karina) Kim1
Abstract
Reciprocity is a fundamental mechanism for sustained social relationships. Escalation-based theories suggest that reciprocity
intensifies over time. In contrast, equity-based theories propose that people reciprocate behaviors in kind. We reconcile
these conflicting perspectives by examining social exchanges across different cultural contexts. Using three complementary
experiments, we investigate when, how, and why individuals in East Asian settings and those in North American settings
differentially reciprocate positive versus negative behaviors over time. Study 1 demonstrated that in positively framed
exchanges (i.e., giving) Americans escalated their reciprocity, but Singaporeans reciprocated in kind. However, in negatively
framed exchanges (i.e., taking), Singaporeans escalated their reciprocity, but Americans reciprocated in kind. Study 2
replicated the results using Hong Kongers and showed that cultural differences in regulatory focus were associated with
specific emotions (i.e., anxiety and happiness), which then escalated reciprocity. To establish causality, Study 3 manipulated
regulatory focus within one culture and replicated the pattern of results.
Keywords
reciprocity, social exchange, culture, regulatory focus, emotions
Received June 20, 2019; revision accepted February 19, 2020
2 Personality and Social Psychology Bulletin 00(0)
We also investigate whether these different escalation pat-
terns are driven by culturally induced regulatory focuses and
emotions. In particular, we propose that, because individuals
in East Asian settings tend to exhibit a prevention focus that
heightens anxiety, negative exchanges will likely escalate.
Conversely, because individuals in North American settings
tend to exhibit a promotion focus that heightens happiness,
positive exchanges will likely escalate.
Theoretical Development
Social Exchange
Social exchange theory suggests that human relationships
involve continuous exchanges between individuals (Andersson
& Pearson, 1999; Baron & Neuman, 1996; Burger, 1986;
Charness et al., 2007; Leymann, 1990; McCabe et al., 2003;
Rind & Strohmetz, 1999). Individuals calculate the worth of
their interpersonal exchanges by considering the rewards and
costs of these exchanges in terms of the positive value or nega-
tive value they bring (Homan, 1961). Based on these calcula-
tions, individuals decide how to act and respond to others
within these interpersonal exchanges.
In this article, we examine a specific aspect of social
exchange—reciprocity. Reciprocity is not only a taken-for-
granted assumption in humans, but it also reinforces other
social norms (Fehr & Gächter, 1998). The process of reci-
procity is when “one party tends to repay the good (or some-
times bad) deeds of another party” (Cropanzano et al., 2017,
p. 1). In essence, because reciprocity dictates that people
treat others as they would wish to be treated, it often occurs
as a reaction to others’ positive or negative actions (Heider,
2013). For example, Homan (1961) suggests that individuals
will take action to remedy a perceived injustice and Blau
(1964) argues that people consciously incur costs (e.g., do
someone a favor) with an expectation of receiving a reward
(e.g., returned favor) in the future.
Although homeomorphic reciprocity suggests that posi-
tive or negative behaviors trigger positive or negative reci-
procity of similar magnitudes, how individuals choose to
reciprocate is often less tidy (Keysar et al., 2008). For
instance, how a receiver reciprocates may be influenced by
social factors (e.g., assessments of the favor-giver; El-Alayli
& Messé, 2004), characteristics of the reciprocator (Bowles
& Gintis, 2003; Perugini et al., 2003), societal norms (Blau,
1968; Fehr et al., 2002; Whitson et al., 2015), or the receiv-
er’s own emotions (C. S. Wang et al., 2009). Therefore, indi-
viduals’ motivation to reciprocate is greatly shaped by these
social meanings rather than merely the cool cognitive calcu-
lus of the objective value of the resources exchanged (Brown,
1986).
As such, an alternative framework proposes that reciproca-
tion can intensify over time (e.g., Andersson & Pearson, 1999;
Baron & Neuman, 1996; Folger & Skarlicki, 1998; Hershcovis
& Barling, 2010; Zand, 1972) and research has found several
important factors that can explain the escalation of positive
and negative reciprocity. Researchers focusing on the escala-
tion of negative reciprocity have argued that relationships
build “interpersonal heat” (Folger & Skarlicki, 1998; Greco
et al., 2019) that progressively incites harsher retaliatory
behavior. For example, Keysar et al. (2008) demonstrate that,
in a four-round dictator game, people escalate negative actions
(i.e., in a “taking” game, leaving fewer resources to the target
over time) but not positive actions (i.e., in a “giving” game,
providing more resources to the target over time). Researchers
have also found that when group members differ in their ten-
dencies to trust (Ferguson & Peterson, 2015), or when indi-
viduals are viewed as strategic because they are inconsistent
with their return rates in a trust game (Bourgeois-Gironde &
Corcos, 2011), “downward trust spirals” occur. These findings
are consistent with the work that demonstrates negative events
influence emotions, cognitions, and behavior more than posi-
tive events (for reviews, see Baumeister et al., 2001; Rozin &
Royzman, 2001). They are also consistent with economic
studies, which demonstrate that individuals perceive and
reciprocate negative actions more aggressively than positive
actions (e.g., Abbink et al., 2000; Fehr & Gächter, 2000;
Keysar et al., 2008; Offerman, 2002).
At the same time, however, researchers have demon-
strated that the escalation of positive reciprocity can also
occur under certain circumstances. Bourgeois-Gironde and
Corcos (2011) find that consistent and high levels of return
rates in a trust game motivated trusting behaviors and the
escalation of positive reciprocity. Another factor that drives
the escalation of positive reciprocity is level of relational
capital—that is, the level of trust accumulated from repeated
social interactions (Elfenbein & Zenger, 2013). For example,
the seminal work on reciprocity by Berg et al. (1995) sug-
gested that positive reciprocity escalated in investment
games when participants who played the investor roles
exhibited trust.
In this article, we reconcile these conflicting perspectives
and propose that the cultural context and the type of exchange
are vital in determining the patterns of reciprocity that will
emerge over time. Specifically, we investigate how cultural
differences in regulatory focus (e.g., Lockwood et al., 2005;
Uskul et al., 2009) shape emotional experiences (e.g.,
Hochschild, 1983; Tsai et al., 2006), which may then subse-
quently influence whether positive and negative exchanges
are reciprocated in a homeomorphic or escalating manner.
By invoking both regulatory focus and emotions as two
underlying cultural mechanisms for our observed results, our
work helps reconcile opposing findings in the extant litera-
ture and offers a nuanced understanding of how the social
environment influences patterns of social exchange.
Cultural Differences in Regulatory Focus Drive
Emotional Experiences
Cultural differences in regulatory focus can have important
implications for our theorizing (e.g., Lockwood et al., 2005;
Uskul et al., 2009). Regulatory focus theory posits that
Deng et al. 3
humans operate via two distinct types of self-regulatory ori-
entations: those with a prevention focus and those with a pro-
motion focus (Higgins, 1997; Higgins et al., 1997). People
with a prevention focus pay more attention to losses than to
gains, attempt to align their actual self with their “ought self”
by fulfilling obligations, are guided by a need for security,
and are more likely to focus on negative aspects of the self
and situations to prevent future mishaps. In comparison,
individuals with a promotion focus are more gain oriented
rather than loss oriented, have aspirations to align their actual
self with their ideal self, are guided by the need for growth,
and are more likely to focus on positive aspects of the self
and situations to attain gains (Higgins, 2000; Higgins &
Spiegel, 2004).
East Asian settings and prevention focus. Cultural settings can
play a critical role in determining one’s self-regulatory orien-
tations, with individuals in East Asian settings often exhibit-
ing more prevention focus than individuals in North American
settings (e.g., Lee et al., 2000; Lockwood et al., 2005; Uskul
et al., 2009). Individuals in East Asian settings are embedded
in intricate webs of close-knit interpersonal relationships
(Heine et al., 1999; Kitayama et al., 1997; Markus & Kita-
yama, 1991) which emphasize the fulfillment of one’s obliga-
tion toward others, the maintenance of harmony, and a vigilant
outlook to maintain existing connections (Falk et al., 2009;
Heine et al., 1999). This careful consideration of social rela-
tionships is seen as necessary for the maintenance of every-
day well-being (Hamamura & Heine, 2008; Hashimoto &
Yamagishi, 2013; Oishi & Kesebir, 2012) and encourages a
more cautious undertaking of friendship (Adams & Plaut,
2003) as well as an alertness for attacks by enemies (Adams,
2005). As a result, individuals in East Asian settings often
take a more prevention-focused approach toward social rela-
tionships (Adams & Plaut, 2003). For example, compared
with individuals in North American settings, individuals in
East Asian settings are more punitive toward wrongdoers (C.
S. Wang & Leung, 2010; Whitson et al., 2015).
North American settings and promotion focus. In contrast to
the above, individuals in North American settings are more
promotion focused (Lee et al., 2000; Lockwood et al., 2005;
Uskul et al., 2009). Compared with individuals in East Asian
settings, individuals in North American settings perceive
their social networks to be more open and transient (Oishi &
Kisling, 2009) and their social world to be more malleable
(Chen et al., 2009). Hence, they have more opportunities to
meet new people and develop new social relationships
(Schug et al., 2009). These structural aspects encourage indi-
viduals in North American settings to focus less on vigilantly
maintaining existing connections and more on attaining posi-
tive achievements (Lee et al., 2000) and developing new
positive relationships. Thus, individuals in North American
settings are more likely to exhibit a “promotion-oriented
relationality” approach by placing an emphasis on finding
emotional satisfaction via new social connections (Li et al.,
2015). This approach allows for greater self-disclosure in
relationships (Schug et al., 2010), more positive behaviors
toward trustworthy strangers (C. S. Wang & Leung, 2010),
and disengagement from relationships that no longer provide
satisfaction (Adams & Plaut, 2003).
Cultural differences in emotions. These cultural differences in
regulatory focus are particularly evident in emotional experi-
ences. Positive and negative emotions are managed by two par-
tially distinct self-regulatory systems: the behavioral activation
system and the behavioral inhibition system (Carver, 2006).
Regulatory focus theory contends that people are motivated to
adjust their feelings in a manner that aligns with their self-reg-
ulatory system so they can be “trait consistent.” Therefore, as
prevention-oriented individuals focus on the “potentially nega-
tive aspects of the self and situations in an attempt to avoid
future social mishap” (Lee et al., 2000, p. 1123; also see Sato
et al., 2014; Zhang & Mittal, 2007), their behavioral inhibition
system primarily motivates negative feelings (Carver &
Scheier, 1998; Gorman et al., 2012; Gray, 1981, 1990; Higgins,
1987), which help these individuals stay vigilant toward threats
in the environment (Friedman & Förster, 2008; Lee et al., 2000;
Li & Masuda, 2016). As a result, individuals’ prevention focus
in East Asian settings is more likely to motivate prevention-
focused emotions such as worry and anxiety.
In contrast, because promotion-focused individuals focus
primarily on personal achievement, potential gains, and posi-
tive relationships, their behavioral activation system often
motivates positive feelings such as happiness, joy, and opti-
mism (Gorman et al., 2012). These feelings allow them to
seek more opportunities to strengthen their social interac-
tions (Schug et al., 2010). Thus, individuals’ promotion focus
in North American settings (Lee et al., 2000) is more likely
to be associated with promotion-focused rather than preven-
tion-focused emotions (Friedman & Förster, 2008; Gorman
et al., 2012; Weber & Bauman, 2019).
Escalation of positive versus negative exchange. As the above
discussion outlines, cultural differences in regulatory focus
appear to be associated with positive (happiness) versus neg-
ative emotions (anxiety), which in turn explain different pat-
terns of reciprocity. Emotions influence the reciprocity
process (e.g., Lawler & Thye, 1999) by shaping people’s per-
ceptions and interpretations of others’ behaviors and of the
situation (Bower, 1991; Isen, 1987). Because positive or
negative emotions direct attention to different social mean-
ings (Barrett et al., 2016; Lawler & Thye, 1999), we expect
that individuals will be more sensitive to optimistic informa-
tion when they experience positive emotions and more sensi-
tive to pessimistic information when they experience
negative emotions (Fredrickson, 2001).
Indeed, research has found that individuals experiencing
positive emotions interpret and perceive neutral events more
positively than those experiencing negative emotions
4 Personality and Social Psychology Bulletin 00(0)
(Bower, 1981, 1991; Isen, 1987), overestimating the proba-
bility of positive events and underestimating the likelihood
of negative events (Wright & Bower, 1992). Because promo-
tion-focused individuals in North American settings are
more likely to experience happiness, they may be more
attuned to others’ positive actions (e.g., giving), prompting
the escalation of reciprocity in positive exchanges. On the
other hand, however, this attunement suggests that individu-
als in North American settings may be less attuned to others’
negative actions (e.g., taking), and, as a result, negative
exchanges will likely remain constant over time.
Meanwhile, extant research has demonstrated that people
experiencing negative emotions are likely to overestimate
the probability of negative events (Wright & Bower, 1992),
feel threatened, and perceive the environment as problematic
(Schwarz, 1990, 2000; Västfjäll et al., 2001). Consequently,
they are more likely to engage in negative reciprocity to
enhance their own safety and that of the people around them
(Ben-Ari et al., 1999; Keller et al., 2008; Leith & Baumeister,
1996). This logic suggests that because prevention-focused
individuals in East Asian settings experience anxiety, they
may be more attuned to others’ negative actions (e.g., taking)
and more likely to escalate reciprocity in negative exchanges.
At the same time, heightened anxiety may make individuals
in East Asian settings less attuned to others’ positive actions,
resulting in relatively consistent levels of reciprocity in posi-
tive exchanges over time.
Importantly, our model is congruent with regulatory fit
theory, which holds that an alignment between an individu-
al’s regulatory disposition and situational frame (i.e., regula-
tory fit; Higgins, 2000; see Johnson et al., 2015, for an
organizational review) results in the individual feeling
“right” (Camacho et al., 2003). These feelings of fit can have
perceptual ramifications, increasing the persuasiveness of
the messages that are congruent with a person’s predominant
motivational orientation (e.g., Elliot, 1997). Consistent with
this logic, Lee and Aaker (2004) demonstrate that gain-
framed appeals are more persuasive following promotion-
focused messages, but loss-framed appeals are more
persuasive following prevention-focused messages.
Regulatory fit theory suggests that individuals’ escalation
of reciprocity is influenced by the fit between their culturally
driven regulatory orientation and the situational framing. As
a novel addition to this theory, we argue that emotions play a
central role in the process. On one hand, as anxiety draws
attention to loss-related information and increases vigilance
over the course of repeated negatively framed exchanges
(Bradley et al., 1998), individuals’ feelings of fit in East
Asian settings may grow with increasing strength; hence, the
escalation of negatively framed exchanges may also increase
over time. However, because the feelings of fit do not align
the prevention-focused anxiety and the situational gain
frame, the escalation of positively framed exchanges may
not occur in East Asian settings. On the other hand, because
happiness draws attention to gain-related information
(Wright & Bower, 1992) and promotes eagerness
(Fredrickson, 2001; Klenk et al., 2011), feelings of fit may
grow over repeated positively framed exchanges. This
approach predicts that the escalation of positively framed
exchanges will emerge for individuals in North American
settings because the giving frame matches well with their
promotion-oriented happiness. However, given the lack of fit
between the promotion orientation and a situational loss
frame, the escalation of negatively framed exchanges will be
less likely to occur in North American settings.
Based on these reasonings, we hypothesize that, within
positive exchanges, individuals in North American settings
will escalate positive reciprocity, but the positive reciprocity
of individuals in East Asian settings will remain stable over
time. Conversely, because individuals in East Asian settings
are more prevention focused (and therefore more attentive to
negative actions), we hypothesize that, within negative
exchanges, they will escalate negative reciprocity, but the
negative reciprocity of individuals in North American set-
tings will remain stable over time (see Figure 1).
Alternative Theoretical Pathways
Our model proposes that cultural differences in regulatory
focus will lead to positive (happiness) versus negative emo-
tions (anxiety), which in turn explain different patterns of
reciprocity; however, it is important to note that other theo-
retical frameworks exist. For example, hedonic contingency
theory (Wegener & Petty, 1994) suggests that positive emo-
tions lead individuals to attend to positive events in an effort
to maintain and enhance their positive moods. Moreover,
those in negative moods “do not need to scrutinize hedonic
consequences to the same degree because there are many
more activities that will maintain or improve their mood”
(Hirt et al., 2008, p. 216). Our first prediction—that individu-
als in North American settings will escalate positive exchanges
and not negative exchanges—aligns with predictions from
hedonic contingency theory. However, our prediction that
individuals in East Asian settings will escalate negative
exchanges and not positive exchanges deviates from this the-
ory, which would predict that, because individuals in East
Asian settings are more anxious (a negative mood), they
would be less likely to escalate exchanges, regardless of
whether they were framed in a positive or negative manner.
Our anxiety-related theorizing also differs from another
prevalent theory, the negative state relief (NSR) model
(Cialdini et al., 1973, 1981). According to this model, negative
moods (e.g., sadness or depression) increase positive behav-
iors such as helping because doing so makes the helper feel
better. Thus, this theory would predict that individuals in East
Asian settings would de-escalate negative exchanges and
escalate positive exchanges. In sum, we consider these alter-
native theories as we empirically test our model as they pro-
vide different predictions about how individuals in East Asian
settings respond to negative versus positive reciprocity.
Deng et al. 5
Theoretical Contributions
Our work will contribute to the extant literature on culture
and social exchanges in a number of ways. First, by adopting
insights from recent theorizing (Morris et al., 2015), we view
culture as a critical factor that interacts with the social con-
text of negative versus positive exchanges. In particular, our
research helps explicate how and why people escalate versus
maintain their levels of reciprocity because of cultural differ-
ences; this stands in contrast to past theoretical assumptions
that culture produces “a broad tendency to prefer certain
states of affairs over others” (Hofstede, 1980, p. 19) and that
consistent cross-national differences in reciprocity should
emerge regardless of the social context in which these deci-
sions are made. Although some work has suggested that indi-
viduals in East Asian settings are generally more punitive
and less generous than individuals in North American set-
tings (C. S. Wang & Leung, 2010), our theorizing indicates
that people from different cultural settings may respond in
similar manners under different social circumstances (i.e.,
the reciprocity patterns of people in North American settings
[when exchange is framed negatively] and people in East
Asian settings [when exchange is framed positively] remain
constant and equivalent over time). Importantly, by theoriz-
ing and exploring regulatory focus and emotions as the
underlying cultural mechanisms, our research enhances our
understanding of how the social environment influences pat-
terns of social exchange.
Second, this work also contributes to the understanding of
social exchange processes. Unlike the normative approach of
past work, which extrapolates one-shot interactions to gener-
alized social behavior (Halevy et al., 2012), our research
examines behaviors over a longer temporal window. Doing
so affords us a dynamic assessment of social exchange over
time and sheds light on the temporal implications for how
social norms are activated and persist/escalate over time.
Moreover, in response to the call to consider emotions in the
social exchange process (Cropanzano et al., 2017; Gordon,
1981; Kemper, 1991; Scheff, 1983), we explore how emo-
tions can inform actors’ calculus of social exchange relation-
ships. In this way, our research surpasses the traditional view
of reciprocity as an economically calculative process (Lawler
& Thye, 1999) by providing an alternative lens through
which to view social exchange decisions.
Overview of Studies
We designed three complementary studies to investigate
whether individuals in North American settings and those in
East Asian settings demonstrate different escalation patterns
to negatively framed and positively framed actions because
of their differential regulatory focus and emotions. In Study
1, we recruited participants from the United States and
Singapore to examine the different escalation patterns using
a modified repeated dictator game (i.e., the taking vs. giving
game; Keysar et al., 2008). To test the robustness of our
effects as well as the cultural mechanism that we contend
drives these effects, in Study 2, we employed participants
from the United States and Hong Kong to measure their reg-
ulatory focus and associated emotions. Finally, to increase
our confidence in the underlying mechanism, in Study 3, we
manipulated regulatory focus within a single culture to estab-
lish causality.
Sample Size Sensitivity Analyses
For our studies, we used a general heuristic of collecting a
minimum of 30 data points per between-subject condition
(Cohen, 1988; VanVoorhis & Morgan, 2007; dyads in Studies
1 and 2, individuals in Study 3). Because we collected four
between-subject conditions, we aimed for at least 120 data
points per study. As we had access to a greater number of
participants than usual in Study 1, we took advantage of this
opportunity to enhance power.
We used the analysis of variance (ANOVA) repeated-
measures, within–between interaction function in G*Power
Figure 1. Theoretical model positing that individuals in North American settings (i.e., Americans) escalate positive exchanges because
they are more promotion focused and experience more happiness, whereas individuals in East Asian settings (i.e., Singaporeans and
Hong Kongers) escalate negative exchanges because they are more prevention focused and experience more anxiety.
Note. Cultural setting (0 = North American settings; 1 = East Asian settings); Exchange type (0 = Taking; 1 = Giving).
6 Personality and Social Psychology Bulletin 00(0)
to perform sensitivity analyses for the studies (Faul et al.,
2007). In Studies 1 to 3, we entered four “groups” because
we had four between-subject conditions (Studies 1 and 2:
Cultural setting × Exchange type; Study 3: Regulatory focus
× Exchange type). In Studies 1 and 3, we entered four “mea-
surements” because the within-subject factor included four
rounds. In Study 2, we entered eight “measurements” (eight
rounds). Using the standard criteria (X. Wang et al., 2018; α
= .05 two-tailed, β = 0.80), the results showed that our sam-
ple sizes could detect the minimal effect sizes of f = 0.08 for
Study 1 (N = 232 dyads, correlation among repeated mea-
sures = .63), f = 0.08 in Study 2 (N = 141 dyads, correlation
among repeated measures = .63), and f = 0.09 for Study 3
(N = 159 individuals, correlation among repeated measures
= .71).
Study 1
Method
Study 1 had a 2 (Cultural setting: American vs. Singaporean)
× 2 (Exchange type: Give vs. Take) × 2 (Player: A vs. B) × 4
(Round: 1–4) mixed design, with the last factor within sub-
jects to track the escalation of reciprocity.
Participants and Procedure
Two hundred and sixty students from a U.S. southwestern
university (132 males, 123 females, and five did not report;1
mean age = 21.07 years, SD = 2.722) and 204 students from
a Singaporean university (82 males, 120 females, and two
did not report; mean age = 20.70 years, SD = 1.53) com-
pleted the study. In both samples, participants earned extra
credit and were compensated in money based on their study
responses. American participants were compensated in U.S.
dollars (US$), and Singaporean participants were compen-
sated in Singapore dollars (SG$). At the time of the study,
US$1 was worth approximately SG$1.30. All instructions
were given and written in English.
Upon arrival, participants were randomly assigned to be
either Player A or Player B, and these two players were
seated in two different rooms. Player As and Player Bs were
randomly paired and instructed to complete an interactive
game over multiple rounds. Participants were also told that
they would be compensated based on their final point alloca-
tions at the end of the study.
Depending on their random assignment, each pair of play-
ers played either the giving or the taking game (Keysar et al.,
2008). In the giving game, Player As were first allocated 100
points (equivalent to $2.00 in the relevant currency) and they
decided how many points they would give to Player Bs.
Then, the roles were reversed, such that Player Bs were allo-
cated a new set of 100 points and decided how many points
to give to Player As. In the taking game, Player Bs were allo-
cated 100 points and Player As decided how many points
they would take from Player Bs’ allocation. Player Bs then
decided how many points to take from Player As’ allocated
100 points. In both the taking and giving games, these two
decisions constituted one round. Each pair of players com-
pleted four rounds, with eight individual decisions made in
total.
Participants were not informed of the number of rounds to
prevent any preplanning to defect on the final round. After
completing all four rounds, participants completed a demo-
graphic questionnaire. Participants then received both the
extra credit and the cash compensation based on their alloca-
tion decisions (from $0 to $16, i.e., $4 per round) and were
debriefed on the study.
Dependent Measure
Allocation decisions. We measured the amounts Player A and
Player B gave (in the giving game) or took (in the taking
game) in each round. As higher numbers in the taking game
equated to participants removing more resources from the
other participant, higher numbers reflected greater negative
reciprocity. Similarly, as higher numbers in the giving game
translated to participants giving more resources to the other
side, higher numbers reflected greater positive reciprocity.
Results
Table 1 outlines the descriptive statistics and correlations. As
Player A and Player B came from the same cultural setting in
each pairing, we expected that they would have similar psy-
chological experiences based on our theorizing and would
therefore exhibit similar escalation patterns. For example,
we did not expect an American Player A to escalate their
reciprocity in the giving game in a different manner than his
or her partner (i.e., an American Player B). To test our
assumption, we first conducted a Cultural setting × Exchange
type × Player × Round mixed-methods ANOVA, with
Allocation decisions as the dependent variable. We entered
Round (1–4) as the within-subject factor and Cultural set-
ting, Exchange type, and Player (A or B) as the between-
subject factors. A main effect for Round emerged, F(3, 1368)
= 17.45, p < .001. A main effect did not emerge for the
Cultural setting, F(1, 456) = 0.002, p = .969. Moreover, nei-
ther a main effect for the Player factor, F(1, 456) = 0.43, p =
.510, nor any interactions with the Player factor emerged
(Round × Player, Cultural setting × Round × Player,
Cultural setting × Exchange type × Player, Cultural setting
× Exchange type × Round × Player), all Fs < 0.001, all
ps > .50. These results suggest that the allocation decisions for
Player A did not substantively differ from those of Player B.
Therefore, in line with past research (Humphrey et al.,
2017; Keysar et al., 2008; Loyd et al., 2013), we used dyads
as our unit of analysis for the subsequent analyses by calcu-
lating the average amount that each Player A and Player B
gave (giving game) or took (taking game) in each round.3 We
Deng et al. 7
further tested the validity of aggregation, all ICC(1) values
> .68, all rWG values > .83: The ICC values were acceptable
according to the conventionally accepted values (Bliese,
2000; LeBreton & Senter, 2008).4
We then conducted a Cultural setting × Exchange type ×
Round mixed-methods ANOVA, with Round as the repeated
measure and Allocation decisions as the dependent variable.
A significant Cultural setting × Exchange type × Round
three-way interaction on Allocation decisions emerged,
F(3, 684) = 3.90, p = .009, η2 = .02.
In the giving game, American dyads were more generous
over time, F(1, 79) = 33.12, p < .001, η2 = .30, but
Singaporean dyads’ reciprocity remained stable over time,
F(1, 50) = 2.33, p = .133, η2 = .05. In contrast, in the taking
game, Singaporean dyads became more punitive over time,
F(1, 50) = 11.91, p = .001, η2 = .19, but American dyads’
reciprocity remained stable over time, F(1, 49) = .00, p =
.996, η2 = .00. Taken together, these results suggest that
Singaporean dyads escalated their negative exchanges more
than American dyads did, whereas American dyads escalated
their positive exchanges more than Singaporean dyads did
(see Figure 2).
Discussion
Study 1 provided a clear pattern of results: individuals in
North American settings escalated positive reciprocity,
whereas individuals in East Asian settings escalated negative
reciprocity over time. Although Study 1 provides support for
our hypotheses, it does not test the mechanisms driving these
results. Thus, we designed Study 2 to test the role of regula-
tory focus and emotions in the escalation of reciprocity.
Furthermore, we tested the cultural generalizability of our
findings by comparing American participants with another
East Asian sample—participants from Hong Kong.
Study 2
Study 2 used similar giving and taking games to replicate the
results of Study 1 and to test the underlying mechanisms
behind the cultural differences in positive versus negative
reciprocity. We predicted that the type of exchange would
moderate the relationship between cultural setting and the
escalation of reciprocity via regulatory focus and emotions.
In the giving game, we predicted that Americans would esca-
late their generosity because they are more promotion
focused and experience greater happiness than Hong
Kongers. In contrast, in the taking game, we predicted that
Hong Kongers would escalate their punitive actions because
they are more prevention focused and experience greater
anxiety than Americans. Accordingly, in our analysis, we
tested a second-stage serial mediated moderation model to
examine whether regulatory focus and emotions can explain
the cultural differences in escalation.
Participants and Procedure
A total of 282 students participated in the study. Among
them, 154 students were from a U.S. southwestern university
(80 men and 74 women; mean age = 21.52, SD = 2.77) and
the rest of the 128 students were from a Hong Kong univer-
sity (36 men and 92 women; mean age = 20.63, SD = 2.30).
As in Study 1, participants in both cultures followed
exactly the same procedure and instructions, all of which
were given and written in English. Upon arrival, participants
were randomly assigned to one of two rooms (Room A or B).
Participants completed an 18-item regulatory focus scale,
consisting of promotion focus (nine items) and prevention
focus (nine items) subscales (Lockwood et al., 2002) that
asked them to indicate how well each statement described
them (1 = not at all true of me to 9 = very true of me). The
sample items were as follows: “Overall, I am more oriented
toward achieving success than preventing failure” (promo-
tion focus item; αUS = .90, αHK = .86) and “I am more ori-
ented toward preventing losses than I am toward achieving
gains” (prevention focus item; αUS = .86, αHK = .77).
After completing the regulatory focus questions, each
participant was randomly assigned to be one of two players
(Player A vs. Player B) in one of the two games (giving vs.
taking game), and in each round each player was allocated
100 points (equivalent to US$1.00). Each pair of players
played the game for eight rounds.
Table 1. Descriptive Statistics and Variable Intercorrelations—Study 1.
Variables M SD 1 2 3 4 5
1. Cultural setting — — —
2. Exchange type — — −.12 —
3. Round 1 allocation 51.52 26.73 −.04 −.03 —
4. Round 2 allocation 56.26 31.51 .01 −.01 .69** —
5. Round 3 allocation 58.33 34.18 −.002 −.004 .58** .72** —
6. Round 4 allocation 61.32 34.41 −.04 .09 .50** .61** .70**
Note. N = 232 dyads. Cultural setting (0 = U.S. Southwest; 1 = Singapore); Exchange type (0 = Taking; 1 = Giving). Allocation for each round is the
points exchanged within a dyad for each round, averaged.
*Correlation is significant at p ≤ .05. **Correlation is significant at p ≤ .01.
8 Personality and Social Psychology Bulletin 00(0)
After participants finished the game, they were asked to
indicate how much they felt certain emotions on a five-point
Likert-type scale (1 = not at all to 5 = extremely). Four
questions assessed their feelings of happiness (Lee et al.,
2000; e.g., “happy”; αUS = .90, αHK = .91) and five items
assessed their anxiety (“nervous”; αUS = .91, αHK = .91).
Finally, participants completed the demographic ques-
tions and were debriefed about the study. Both the Hong
Kong and American participants were compensated for their
game decisions; American participants also received an extra
course credit.
Dependent Measure
Allocation decisions. As in Study 1, the amounts that Player
As and Player Bs gave or took in each round were averaged
to form a scale of allocation, with higher numbers reflecting
either more positive (giving game) or negative (taking game)
reciprocity.
Results
Table 2 outlines the descriptive statistics and correlations for
the variables. Table 3 outlines the means and standard devia-
tions of Promotion focus, Prevention focus, Happiness, and
Anxiety by condition. As in Study 1, we first conducted a
Cultural setting × Exchange type × Player × Round mixed-
methods ANOVA. We entered Round (1–8) as the within-
subject factor and Cultural setting, Exchange type, and
Player (A or B) as the between-subject factors. A main effect
emerged for Round, F(7, 1918) = 4.66, p < .001, but not for
Cultural setting, F(1, 274) = 3.41, p = .066, or for Player,
F(1, 274) = 0.01, p = .916. As in Study 1, no significant
interactions with the Player factor emerged, all Fs < 0.70,
Figure 2. Study 1 allocation decisions as a function of Cultural setting, Exchange type, and Round.
9
Table 2. Descriptive Statistics and Variable Intercorrelations—Study 2.
Variables M SD 1 2 3 4 5 6 7 8 9 10 11 12 13
1. Cultural setting — — —
2. Exchange type — — −.06 —
3. Round 1 allocation 50.76 29.78 −.07 .03 —
4. Round 2 allocation 52.62 32.85 −.09 .02 .73** —
5. Round 3 allocation 55.58 37.47 −.14 .002 .55** .69** —
6. Round 4 allocation 59.34 37.58 −.14 −.02 .54** .58** .77** —
7. Round 5 allocation 59.51 39.40 −.06 −.02 .42** .52** .70** .74** —
8. Round 6 allocation 58.82 40.20 −.04 −.03 .40** .53** .63** .66** .80** —
9. Round 7 allocation 58.25 40.69 −.03 −.01 .35** .52** .58** .63** .75** .84** —
10. Round 8 allocation 55.89 40.43 −.12 −.06 .39** .50** .61** .70** .76** .83** .81** —
11. Promotion focus 7.23 0.78 −.34** −.01 .20* .16 .12 .12 .13 .04 .03 .06 —
12. Prevention focus 5.63 1.00 .21* .06 −.16 −.09 −.22** −.21* −.22* −.19* −.22* −.24** .01 —
13. Happiness 2.59 0.79 −.32** .03 .25** .20* .28** .23** .24** .25** .20* .26** .22** −.32** —
14. Anxiety 1.53 0.56 .31** −.01 −.08 .02 −.09 −.15 −.02 .004 −.02 .01 −.07 .17* −.11
Note. N = 141 dyads. Cultural setting (0 = U.S. Southwest; 1 = Hong Kong); Exchange type (0 = Taking; 1 = Giving). Allocation, Promotion focus, Prevention focus, Happiness, and Anxiety are all
aggregated to the dyadic level.
*Correlation is significant at p ≤ .05. **Correlation is significant at p ≤ .01.
10 Personality and Social Psychology Bulletin 00(0)
ps > .40. We further tested the validity of aggregation and
the results supported aggregating to the dyadic level, all
ICC(1) values > .80, all rWG values > .80. The ICC values
were acceptable according to the conventionally accepted
values (Bliese, 2000; LeBreton & Senter, 2008). Thus, as in
Study 1, we used dyads as our unit of analysis by calculating
the average amount that each Player A and Player B gave
(giving game) or took (taking game) in each round. We
dropped the Player factor and conducted a three-way mixed-
methods ANOVA to understand the effects of Cultural set-
ting, Exchange type, and Round on dyad Allocation
decisions. A significant Cultural setting × Exchange type ×
Round three-way interaction emerged for Allocation deci-
sions, F(7, 959) = 3.57, p = .001, η2 = .03.5
In the taking game, Hong Kong dyads became marginally
more punitive over time, F(1, 33) = 3.84, p = .059, η2 =
.10, but American dyads’ allocations remained stable,
F(1, 35) = 0.05, p = .829, η2 = .001. In contrast, in the giv-
ing game, American dyads became more generous over time,
F(1, 40) = 5.43, p = .025, η2 = .12, whereas Hong Kong
dyads’ allocations remained stable, F(1, 29) = 0.66, p =
.425, η2 = .02. In summary, Study 2 replicated the results of
Study 1 by demonstrating that Hong Kong dyads escalated
negative behaviors more than American dyads did, whereas
American dyads escalated positive behaviors more than
Hong Kong dyads did (see Figure 3).6
Moderated serial mediation growth model analyses. To test the
underlying mechanisms of regulatory focus and emotions,
we also tested whether the nature of exchange (i.e., giving
vs. taking) would moderate the indirect effect of culture on
escalation through regulatory focus and emotions. First, we
hypothesized that American dyads would be more promotion
focused than Hong Kong dyads and that their promotion
focus would be associated with stronger happiness. In turn,
we predicted that happiness would help escalate positive
reciprocity in the giving game but would not escalate nega-
tive reciprocity in the taking game.
Second, we hypothesized that Hong Kong dyads would
be more prevention focused than American dyads and that
their prevention focus would be associated with stronger
anxiety. In turn, anxiety would help escalate negative reci-
procity in the taking game but would not escalate positive
reciprocity in the giving game.
To test these predictions, we followed the procedure of
Chan (1998) to combine lower-level measures into collective
constructs and aggregate participants’ regulatory focus and
emotions to the dyadic level by calculating the average
amount that each of Player A and Player B (Humphrey et al.,
2017; Loyd et al., 2013). We also tested the validity of aggre-
gation, Promotion focus: ICC(1) = .12, rWG = .90; Prevention
focus: ICC(1) = .10, rWG = .89; Happiness: ICC(1) = .08,
rWG = .70; Anxiety: ICC(1) = .15, rWG = .71, and the results
supported aggregating to the dyadic level (LeBreton &
Senter, 2008).
We then ran a two-factor latent growth model to estimate
a latent intercept (i) and a latent slope (s), and followed the
path-analytic approach (Preacher et al., 2007; with 5,000
bootstrapped samples and 95% confidence intervals [CIs]) to
test the indirect effects of cultural setting on the latent slope
through regulatory focus and emotions in each game (taking
vs. giving).
Cultural differences in regulatory focus. Americans dyads
(M = 7.47, SD = 0.77) were more promotion focused than
Hong Kong dyads (M = 6.95, SD = 0.69), t(139) = 4.22,
p < .001, d = 0.72, 95% CI = [0.28, 0.77], and Hong Kong
dyads (M = 5.86, SD = 0.85) were more prevention focused
than American dyads (M = 5.44, SD = 1.07), t(139) = 2.56,
p = .012, d = 0.43, 95% CI = [−0.75, −0.09].
Regulatory focus and emotions. Promotion focus was posi-
tively associated with happiness (b = 0.23, SE = 0.09, p =
.013) and prevention focus was positively associated with
anxiety (b = 0.10, SE = 0.04, p = .017).
Latent growth modeling. Latent growth modeling (LGM)
enabled us to model mean-level changes in allocations
across eight rounds, as well as the differences in changes,
while controlling for the effects of measurement error. We
constructed a model with two growth factor components:
the latent intercept and the latent slope. The latent intercept
reflects the average of Round 1 allocation; the latent slope
Table 3. Means (Standard Deviations in Parentheses) of Promotion Focus, Prevention Focus, Happiness, and Anxiety by Condition—
Study 2.
Giving Taking Giving Taking
Countries
Promotion
focus
Prevention
focus
Promotion
focus
Prevention
focus Happiness Anxiety Happiness Anxiety
United States 7.41
(0.79)
5.38
(1.11)
7.53
(0.75)
5.51
(1.04)
2.87
(0.82)
1.38
(0.55)
2.76
(0.81)
1.36
(0.37)
Hong Kong 6.97
(0.59)
6.13
(0.67)
6.92
(0.78)
5.63
(0.93)
2.26
(0.79)
1.73
(0.61)
2.35
(0.56)
1.72
(0.62)
Note. N = 141 dyads.
Deng et al. 11
estimates a linear growth trajectory over eight rounds. The
variance in the latent intercept reflects differences in the
Round 1 allocation; the variance in the slope represents dif-
ferences in mean-level changes over time. We constructed
the model by defining the intercept factor as the Round 1
allocation and setting the loadings of allocations from Round
1 to Round 8 to 1 on the intercept factor and to 0 to 7 on the
slope factor. In addition, we correlated residual variables for
the allocations over time because the error variances were
homoscedastic over time for repeated latent variables (Lance
et al., 2000).
To examine whether the Exchange type (taking vs. giving)
moderated the indirect effect of Cultural setting on Escalation
(slope factor) through Regulatory focus and Emotions, we
tested whether (a) a Happiness × Exchange type interaction
on Escalation (slope factor) emerged; (b) Promotion focus
and Happiness mediated the relationship between Culture and
Escalation (slope factor) in the giving game, but not in the
taking game; (c) an Anxiety × Exchange type interaction on
Escalation (slope factor) emerged; and (d) Prevention focus
and Anxiety mediated the relationship between Culture and
Escalation (slope factor) in the taking game but not in the giv-
ing game. Figure 4 shows the two-factor latent growth model
for allocations and the paths between the studied variables
(e.g., Culture, Regulatory focus, Emotions, and Exchange
type). To test the underlying mechanisms of Regulatory focus
and Emotions, we conducted a path analysis using Mplus and
a maximum likelihood estimation.
Promotion focus and happiness. We found a significant
Happiness × Exchange type effect on Escalation (slope fac-
tor) (b = 2.52, SE = 1.12, p = .024). We also found that
Exchange type moderated the indirect effect of Culture on
Escalation (slope factor) via Promotion focus and Happi-
ness. In the giving game, an indirect effect emerged for the
serial mediation (b = −0.15, SE = 0.13, 95% CI = [−0.61,
−0.01]), suggesting that the escalation of giving was greater
for American dyads than Hong Kong dyads over the eight
rounds because Americans were more promotion focused
and experienced higher levels of happiness. In contrast,
the indirect effect was not significant in the taking game
(b = 0.16, SE = 0.16, 95% CI = [−0.03, 0.68]).
Figure 3. Study 2 allocation decisions as a function of the Cultural setting, Exchange type, and Round.
12 Personality and Social Psychology Bulletin 00(0)
Prevention focus and anxiety. Following the same proce-
dures as above and using Prevention focus and Anxiety as
the mediators, we found an Anxiety × Exchange type inter-
action effect on Escalation (slope factor) (b = −3.29, SE =
1.50, p = .028). We also observed that the Exchange type
moderated the indirect effect of Culture on the Escalation
(slope factor) via Prevention focus and Anxiety. In the tak-
ing game, the indirect effect was positive and significant for
the serial mediation (b = 0.12, SE = 0.09, 95% CI = [0.02,
0.41]), suggesting that the escalation of taking was greater
for Hong Kong dyads than those for American dyads over
the eight rounds because Hong Kongers were more preven-
tion focused and experienced higher levels of anxiety. In the
giving game, however, the indirect effect was not significant
(b = −0.01, SE = 0.05, 95% CI = [−0.15, 0.06]) (see Table 4
for detailed results).7
Discussion
Study 2 replicated the findings of Study 1: Individuals in the
North American settings escalated their positive exchange, but
positive reciprocity remained stable for individuals in the East
Asian settings. Conversely, individuals in the East Asian
settings escalated negative exchanges, whereas negative
reciprocity remained constant in the North American settings.
In addition, Study 2 showed that regulatory focus and emo-
tions were the underlying mechanisms behind these findings.
Study 3
The relationships between regulatory focus and the other
measures in Study 2 were correlational, leaving the possibil-
ity that an unknown variable may account for the observed
effects (Spencer et al., 2005). To establish regulatory focus
as a causal mechanism, we followed the past research on
cross-cultural studies by manipulating regulatory focus
within a single culture to more robustly test the causal effect
of regulatory focus in Study 3 (San Martin et al., 2019; C. S.
Wang et al., 2011).
Method
Study 3 employed a 2 (Regulatory focus: Prevention vs.
Promotion focus) × 2 (Exchange type: Give vs. Take) × 4
(Round: 1–4) mixed design, with the last factor serving as a
within-subject factor tracking escalation of behaviors.
Participants ostensibly interacted with other participants in the
game, but in reality the other “participant” was preprogrammed
Figure 4. Study 2 path diagram of a two-factor latent growth model for Allocation decisions.
Note. Cultural setting (0 = North American settings; 1 = East Asian settings); Exchange type (0 = Taking; 1 = Giving). Interaction 1 = Exchange type ×
Happiness; Interaction 2 = Exchange type × Anxiety. R1 to R8 represents the allocation for each round. Covariances between same-item residuals were
omitted for clarity. Control variables and paths are shown in gray. Hypothesized variables and paths are in black; nonsignificant paths are denoted with
dashed lines.
Deng et al. 13
to make an offer of 50 points (out of 100 points) in the first
round. This manipulation ensured that the first move was con-
sistent across conditions, allowing us to measure how our
manipulations influenced patterns of reciprocity over time.
Moreover, we deliberately ensured that the first move was a
50–50 split (Pillutla & Murnighan, 1996)—that is, an objec-
tively “fair” split. Even with this fair split in place, we pre-
dicted that regulatory focus and exchange type would shape the
interpretations of the first move and that promotion-manipu-
lated individuals would escalate reciprocity in the giving game,
but not in the taking game. We also predicted that prevention-
manipulated individuals would escalate reciprocity in the tak-
ing game, but not in the giving game.
Participants and Procedure
One hundred and fifty-nine U.S. participants (71 males and
88 females; mean age = 34.00 years, SD = 10.51) were
recruited from Amazon Mechanical Turk (MTurk) in
exchange for payment. Participants were randomly assigned
to a word fragment task (Gilbert & Hixon, 1991; Whitson
et al., 2019) to prime regulatory focus (Prevention vs.
Promotion focus). In each condition, participants were
shown four words with one or two missing letters and asked
to write in the missing letters to form the word. For example,
the fragment “gro_th” needed a “w” to form the word
“growth.” The four words in the promotion focus prime were
“growth,” “active,” “eager,” and “accomplish,” whereas
those in the prevention focus prime were “calm,” “vigilant,”
“safe,” and “secure.”
Upon completion, participants were randomly assigned to
either the giving or the taking game. All participants were
told that they were assigned as Player B to play against
another participant (Player A) who was networked through
the internet. As noted, in actuality, Player A’s actions were
computer programmed.
Table 4. Path Analysis Results for Two-Factor Latent Growth Model for Allocations—Study 2.
Model b SE p R2
Outcome variable: Promotion focus .11
Constant 7.47 0.09 <.001
Cultural setting −0.53 0.12 <.001
Outcome variable: Prevention focus .05
Constant 5.44 0.12 <.001
Cultural setting 0.42 0.16 .008
Outcome variable: Happiness .15
Constant 2.38 0.87 .006
Promotion focus 0.23 0.09 .013
Prevention focus −0.26 0.07 <.001
Outcome variable: Anxiety .03
Constant 1.37 0.48 .004
Prevention focus 0.10 0.04 .017
Promotion focus −0.05 0.06 .343
Outcome variable: Escalation (slope factor) .10
Constant 6.84 6.25 .274
Cultural setting −0.95 1.07 .374
Exchange type −2.23 3.87 .564
Promotion focus −0.71 0.65 .274
Happiness −1.31 1.10 .234
Happiness × Exchange type 2.52 1.12 .024
Prevention focus −0.27 0.56 .630
Anxiety 2.94 1.19 .014
Anxiety × Exchange type −3.29 1.50 .028
Boot effect SE 95% CI
Conditional indirect effects via promotion focus and happiness
Taking 0.16 0.16 [−0.03, 0.68]
Giving −0.15 0.13 [−0.61, −0.01]
Conditional indirect effects via prevention focus and anxiety
Taking 0.12 0.09 [0.02, 0.41]
Giving −0.01 0.05 [−0.15, 0.06]
Note. N = 141 dyads. Bootstrap sample size = 5,000. Cultural setting (0 = U.S. Southwest; 1 = Hong Kong); Exchange type (0 = Taking; 1 = Giving).
Allocation, Promotion focus, Prevention focus, Happiness, and Anxiety are all aggregated to the dyadic level. CI = confidence interval.
14 Personality and Social Psychology Bulletin 00(0)
In the giving game, the participant (Player B) and the
other player (Player A) were each allocated a set of 100
points, and Player A first decided how many points to give to
Player B.
Player A was preprogrammed to make an offer of 50
points in the first round. The participant then chose how
many points out of their 100-point allocation to give to
Player A. These two moves constituted Round 1.
In the subsequent three rounds, Player As move mirrored
the participant’s move in the previous round. For example, if
the participant gave Player A 60 points in the first round,
Player A gave the same amount (60 points) back to the par-
ticipant in the second round. Participants continued to make
giving decisions until they completed four rounds.
In the taking game, the paradigm remained the same as
in the giving game except that decisions were described as
taking instead of giving. The instructions did not outline
the number of rounds that would be played. Participants
then completed the demographic questionnaire and were
debriefed.
Dependent Measure
Allocation decisions. For each round, we recorded how many
points participants gave in the giving game (or took in the
taking game) to (or from) Player A, from 0 to 100, with
higher numbers reflecting either more generous (giving
game) or punitive (taking game) decisions.
Results
Table 5 includes descriptive statistics and correlations for the
variables. A Regulatory focus × Exchange type × Round
mixed-methods ANOVA, with Round serving as a within-
subject factor demonstrated a significant Regulatory focus ×
Exchange type × Round three-way interaction on Allocation
decisions, F(3, 465) = 2.93, p = .033, η2 = .02.
In the taking game, exchanges in the prevention focus
condition became more punitive over time, F(1, 41) = 7.20,
p = .010, η2 = .15, but the exchanges in the promotion focus
condition remained stable over time, F(1, 38) = 0.07, p =
.793, η2 = .002. In contrast, in the giving game, exchanges
in the promotion focus condition were more generous over
time, F(1, 39) = 5.75, p = .021, η2 = .13, but the exchanges
in the prevention focus condition remained stable over time,
F(1, 37) = 0.34, p = .562, η2 = .01 (see Figure 5).
Overall, Study 3 supported our argument that cultural dif-
ferences in regulatory focus may explain patterns of reci-
procity by showing that even state-level regulatory focus
manipulations shape the escalation of reciprocity. In positive
exchanges, individuals in a promotion-oriented state esca-
lated reciprocity, but this escalation did not occur for indi-
viduals in a prevention-oriented state. Conversely, in negative
exchanges, individuals in a prevention-oriented state esca-
lated reciprocity, but this escalation did not occur for indi-
viduals in a promotion-oriented state.
General Discussion
Reciprocity is a basic governing mechanism for sustained
social relationships (Fehr & Gächter, 2000). Our research
investigated how people escalated different types of reci-
procity in different cultures. Study 1 demonstrated that indi-
viduals in a North American setting escalated positive and
not negative exchanges, whereas individuals in an East Asian
setting escalated negative and not positive exchanges. Study
2 conceptually replicated these findings and showed that
regulatory focus and emotions were the driving mechanisms
behind these cultural differences. Study 3 manipulated regu-
latory focus and showed that individuals in a promotion-ori-
ented state escalated reciprocity when exchanges were
positive (but not negative), whereas individuals in a preven-
tion-oriented state escalated reciprocity when exchanges
were negative (but not positive).
Theoretical Implications
Our research contributes to the social exchange theory by
exploring how culture influences reciprocity over time.
Escalation-based theories suggest that reciprocity may inten-
sify over time, but equity-based theories propose that people
reciprocate behaviors in kind. Our work provides evidence
for both theoretical perspectives, with the cultural background
of reciprocators and the type of the exchange determining
Table 5. Descriptive Statistics and Variable Intercorrelations—Study 3.
Variables M SD 1 2 3 4 5 6
1. Regulatory focus — — —
2. Exchange type — — .03 —
3. Round 1 allocation 52.28 20.33 .01 −.33** —
4. Round 2 allocation 53.93 23.57 −.09 −.34** .83** —
5. Round 3 allocation 55.77 24.98 −.03 −.34** .65** .79** —
6. Round 4 allocation 56.78 26.38 −.10 −.27** .52** .66** .79** —
Note. N = 159 individuals. Regulatory focus (0 = Prevention focus; 1 = Promotion focus); Exchange type (0 = Taking; 1 = Giving).
*Correlation is significant at p ≤ .05. **Correlation is significant at p ≤ .01.
Deng et al. 15
patterns of reciprocity. Moreover, our research further dem-
onstrates the meaningful impact of subjective components in
individuals’ calculus of reciprocity in social exchanges. In
particular, regulatory focus and emotions can color people’s
cultural perceptions of social exchange and in turn influence
their behaviors. Importantly, cultural differences in regulatory
focus and their specific emotional signatures (i.e., promotion
focus engenders happiness and prevention focus engenders
anxiety) drive patterns of reciprocity. This work begins to
answer the recent calls to bring emotions to the foreground
when studying social exchange (e.g., Cropanzano et al., 2017;
Lawler & Thye, 1999).
By examining a series of exchanges, our study provides a
dynamic and realistic lens that allows for a better understand-
ing of how reciprocity works. Although theories of social
exchange often assume continuous interactions (Cropanzano
et al., 2017; Greco et al., 2019), empirical research almost
exclusively employs one-shot decisions (e.g., Aryee et al.,
2002; Bishop & Scott, 2000; Cortina & Magley, 2003;
Eisenberger et al., 2001; Glomb & Liao, 2003), providing a
limited understanding of how people reciprocate over time.
By focusing on the dynamic escalation of reciprocity rather
than examining one-shot interactions (Halevy et al., 2012), our
research gives insight into how and why cultural orientations
and societal norms are formed and become reified over time.
Alternative theoretical pathways. We tested our model based
on the alternate theories described in the introduction.
Hedonic contingency theory suggests that because individu-
als in East Asian settings are more anxious, they are unlikely
to be influenced by whether the exchanges are framed in a
positive versus negative manner. Yet we find that, because of
this anxiety, individuals in East Asian settings escalated neg-
atively framed exchanges, but not positively framed
exchanges. Similarly, our anxiety-related findings were not
consistent with the NSR model (Cialdini et al., 1973, 1981),
which suggests that negative moods increase positive behav-
iors such as helping because doing so makes the helper feel
better; if this were true, anxiety should have increased giv-
ing, which we did not observe in our studies (as shown in the
correlation table in Table 2, there is not a positive correlation
between anxiety and allocation amounts).
One reason for these different results could be that previ-
ous empirical work on both the hedonic contingency
Figure 5. Study 3 allocation decisions as a function of Regulatory focus, Exchange type, and Round.
16 Personality and Social Psychology Bulletin 00(0)
(Wegener & Petty, 1994) and NSR (Bless et al., 1992; M. M.
Mitchell, 2000; Tiedens & Linton, 2001) theories has focused
on sadness rather than on anxiety, the negative emotion we
examined. We did not measure sadness because it is associ-
ated with withdrawal behavior (Dawson et al., 1992;
Harmon-Jones et al., 2009) and is not an emotion associated
with prevention focus (which is essential to our cultural theo-
rizing). Nonetheless, it is worth considering how different
types of negative emotions may be related to decisions to
escalate reciprocity. Therefore, future work might compare
sadness and anxiety as precursors to the escalation (or de-
escalation) of reciprocity.
Future Directions and Limitations
Interestingly, in Study 2, prevention focus was more strongly
related to happiness (negatively) than to anxiety (see Table 2).
Although past work provides support for the relationship
between prevention focus and both happiness (negative) and
anxiety (positive), some authors have suggested that preven-
tion focus has a stronger relationship with anxiety than with
happiness (Faddegon et al., 2008; Shah & Higgins, 2001).
For example, prevention-focused people become more agi-
tated and anxious after experiencing failure (Higgins et al.,
1997), and there is evidence that prevention-focused indi-
viduals may be less happy because their vigilance causes
them to “forego many momentary pleasures for the sake of
achieving higher order long-term goals” (Cheung et al.,
2014, p. 2). Future research could investigate this possibility
by more deeply examining the nuances of emotions.
In the current studies, we focused on how individuals
from the same culture made sequential economic decisions.
However, not all interpersonal interactions occur within the
same culture (Henderson et al., 2018; Molinsky, 2007; Ott &
Michailova, 2018), which could introduce complications.
Levitt (2015), for example, outlines how prejudice and
ethnocentrism can challenge international team dynamics.
Negatively framed exchanges may escalate more quickly
when the interactions are cross-cultural because of these
underlying prejudices. Future studies might further investi-
gate reciprocity and reciprocal escalation patterns in cross-
cultural interactions in an effort to improve these interactions
by reducing prejudice and ethnocentrism.
Future work could also explore how repeated interactions
within cultures may strengthen norms and social perceptions.
The social radar account posited by Morris et al. (2015) sug-
gests that behaving in line with injunctive norms (i.e., per-
ceptions of behaviors that evoke social approval or
disapproval) increases social approval and signals to actors
that their positions are validated (Belk et al., 1982; Goffman,
1959; Strauss, 1977). In our case, the escalation of the type
of reciprocity that fits one’s injunctive norms elucidates the
process of cultural transmission and change, suggesting that
this may be at least one part of the learning process from
which cultural norms are derived. For instance, our findings
that culture and the type of exchange interact to trigger esca-
lation may help explain why individuals in East Asian set-
tings are generally more punitive and less rewarding than
individuals in North American settings in one-shot interac-
tions (Leung et al., 2011; Singh et al., 2011).
Moreover, the escalation of negative actions (and the lack
of escalation of positive actions) by individuals who are
more prevention focused may reinforce their vigilance in
certain social situations. In contrast, the escalation of posi-
tive actions (and the lack of escalation of negative actions)
by individuals who are more promotion focused may rein-
force their beliefs that people are supportive and dependable,
further encouraging the pursuit of positive relationships.
Future work should continue to explore how repeated social
exchanges may shape cultural norms.
Our work also provides a potential opportunity to dimin-
ish—and perhaps even reverse—cycles of harmful retribution.
Table 6. Ethnicity Information for Studies 1 to 3.
Study 1 Study 2 Study 3
U.S. Singapore U.S. Hong Kong U.S.
Caucasian: 158 Chinese: 173 Caucasian: 100 Chinese: 120 Caucasian: 117
African American: 23 Indian: 11 African American:12 Indian: 4 African American: 16
Hispanic: 18 Malaysian: 8 Hispanic: 12 Indonesian: 1 Asian: 12
Chinese: 13 Vietnamese: 3 Native American: 8 Caucasian: 1 Hispanic: 7
Native American: 11 Filipino: 2 Chinese: 5 Other ethnicity: 2 Native American: 2
Vietnamese: 3 Other Asian: 4 Korean: 4 Other Ethnicity: 5
Indian: 3 Did not report: 3 Filipino: 2
Korean: 3 Vietnamese: 2
Filipino: 1 Indian: 1
Other Asian: 3 Japanese: 1
Other ethnicity: 7 Other Asian: 6
Did not report: 17 Other ethnicity: 1
Total: 260 Total: 204 Total: 154 Total: 128 Total: 159
Deng et al. 17
Previous research has discussed how negative forms of reci-
procity can be harmful to those within and outside of the social
exchange (e.g., Harris et al., 2007; M. S. Mitchell & Ambrose,
2007). For example, negative reciprocity decreases organiza-
tional commitment, thereby leading to increased turnover
(Porter et al., 1974), decreased motivation (Farrell & Rusbult,
1981), reduced perceived organizational support (Settoon
et al., 1996), and fewer organizational citizenship behaviors
(Williams & Anderson, 1991). Likewise, retaliation can result
in spiraling acts of vengeance, a precursor to violence in soci-
eties and, in extreme cases, geopolitical conflict (Davie, 1929;
Nisbett & Cohen, 1996; Otterbein, 1970; Tumey-High, 1971).
Findings of Study 3 suggest that intervention may be possi-
ble—by engendering a promotion orientation among key deci-
sion-makers to curtail negative escalation spirals.
At the same time, negative reciprocity is not always detri-
mental; it may help prevent opportunistic behaviors, sustain
social norms (Fehr & Gächter, 1998), and increase coopera-
tion in groups (Rockenbach & Milinski, 2006). For instance,
harsh sanctioning increases coordination between members,
which helps protect members during times of threat (Gelfand
et al., 2011). Future research may benefit from considering
the conditions under which the escalation of negative actions
can result in positive (vs. destructive) consequences.
Conclusion
Although reciprocity is a universal norm in social relation-
ships (Fehr & Gächter, 2000), people display different pat-
terns of reciprocity in different cultures (Buchan et al., 2002;
Cosmides & Tooby, 2005). Our research provides a nuanced
understanding of social exchanges by examining how and
why individuals in East Asian settings reciprocate negative
and positive actions differently from individuals in North
American settings. Classic adages and sayings, such as “An
eye for an eye” and “If you cooperate with others, others will
cooperate with you,” suggest that people generally recipro-
cate in kind. Our research supports these traditional perspec-
tives but also illustrates when and why they may be limited,
thereby taking an initial step toward a more comprehensive
understanding of how cultural systems shape reciprocity.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article: The
work described in this paper was partially supported by a grant from
the Research Grants Council of the Hong Kong Special
Administrative Region, China (Project No. CityU 11529116).
ORCID iD
Cynthia S. Wang https://orcid.org/0000-0003-3880-8753
Supplemental Material
Supplemental material is available online with this article.
Notes
1. In Studies 1 and 2, the East Asian samples had a higher propor-
tion of women than did the North American samples. Therefore,
we controlled for the gender composition of the dyads in all three
studies (0 = mixed dyad, 1 = male dyad, 2 = female dyad). Our
results remained significant, suggesting that the gender compo-
sition of dyads did not influence our effects.
2. The ethnicities of participants within each cultural setting are
included in Table 6. In addition, as a robustness check, we
dropped those of East Asian descent from our North American
sample and those of North American descent from our East
Asian sample in Studies 1 and 2, and our results remained sig-
nificant. We report these analyses in Supplementary Material.
3. There are potential limitations of averaging scores. First, aver-
aging two participants’ scores eliminates the ability to take into
account variability in responses of the two participants. For
example, a scenario in which Player A allocates 10 points and
Player B allocates 90 points in one round is very different from
one in which Player A allocates 50 points and Player B allo-
cates 50 points, although the average score for both scenarios is
50 points. However, we theoretically do not expect these play-
ers from the same culture and exchange type condition to dif-
fer in their allocation decisions. Consistent with our theoretical
predictions, we did not find the main effect of Player in either
Study 1 or Study 2, indicating that Player A and Player B did
not significantly differ in their allocation patterns. The second
limitation of averaging scores within dyads is the power of the
hypothesis tests (Krull & MacKinnon, 2001). To eliminate this
concern, we ran a sensitivity analysis, which suggests that we
have sufficient power to detect a small effect size.
4. The repeated-measures actor–partner interdependence model
(RM-APIM; Cook & Kenny, 2005; Perry et al., 2017) is a good
approach to examine how Player A’s actions affect Player B’s
actions. However, one of the most important assumptions of the
RM-APIM is that dyad members are distinguishable (Kenny
et al., 2006; Perry et al., 2017). Theoretically, Player A and
Player B are indistinguishable as both players come from the
same cultural setting and engage in the same type of game.
Therefore, we designed our study to randomly assign partici-
pants into these indistinguishable dyads. Empirically, we did not
find any main or interaction effects of the Player factor on the
allocation decisions, which suggests that there was no difference
between Player A and Player B in their allocation decisions.
Taken together, we conclude that dyad members are indistin-
guishable, and thus we did not use the RM-APIMs to analyze
our results.
5. Based on the allocation patterns in the first round, it is possible
that Hong Kong participants escalated their taking because they
took more than American participants did in the first round and
that Americans escalated their giving because they gave more
than Hong Kong participants in the first round. We performed
several analyses to rule out the possibility that the initial move
motivates escalation. We report these results in Supplementary
Material.
6. Based on the escalation patterns shown in Figure 3, it is possible
that American participants gave and Hong Kong participants
18 Personality and Social Psychology Bulletin 00(0)
took over the eight rounds in a curvilinear pattern. Indeed,
Americans gave over the eight rounds in a curvilinear pattern,
F(1, 40) = 18.07, p < .001, η2 = .31, and Hong Kong partici-
pants took over the eight rounds in a similar curvilinear pattern,
F(1, 33) = 7.04, p = .01, η2 = .18. We discuss these findings in
more detail in Supplementary Material.
7. Because emotions were measured after the games, an alterna-
tive explanation remains. Specifically, the experience of the
game could have shaped the participant’s pattern of emotions.
However, statistically, we did not find support for this alterna-
tive moderated mediation. In addition, we ran alternative models
that support the dispositional nature of the emotions. We report
these results in Supplementary Material.
References
Abbink, K., Irlenbusch, B., & Renner, E. (2000). The moonlight-
ing game: An experimental study on reciprocity and retribu-
tion. Journal of Economic Behavior & Organization, 42(2),
265–277.
Adams, G. (2005). The cultural grounding of personal relation-
ship: Enemyship in North American and West African worlds.
Journal of Personality and Social Psychology, 88(6), 948–968.
Adams, G., & Plaut, V. C. (2003). The cultural grounding of per-
sonal relationship: Friendship in North American and West
African worlds. Personal Relationships, 10(3), 333–347.
Andersson, L. M., & Pearson, C. M. (1999). Tit for tat? The spiraling
effect of incivility in the workplace. Academy of Management
Review, 24(3), 452–471.
Aryee, S., Budhwar, P. S., & Chen, Z. X. (2002). Trust as a media-
tor of the relationship between organizational justice and
work outcomes: Test of a social exchange model. Journal of
Organizational Behavior, 23(3), 267–285.
Baron, R. A., & Neuman, J. H. (1996). Workplace violence and
workplace aggression: Evidence on their relative frequency
and potential causes. Aggressive Behavior, 22(3), 161–173.
Barrett, L. F., Lewis, M., & Haviland-Jones, J. M. (2016). Handbook
of emotions. Guilford Press.
Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K.
D. (2001). Bad is stronger than good. Review of General
Psychology, 5(4), 323–370.
Belk, R. W., Bahn, K. D., & Mayer, R. N. (1982). Developmental
recognition of consumption symbolism. Journal of Consumer
Research, 9, 4–17.
Ben-Ari, O. T., Florian, V., & Mikulincer, M. (1999). The impact
of mortality salience on reckless driving: A test of terror
management mechanisms. Journal of Personality and Social
Psychology, 76(1), 35–45.
Berg, J., Dickhaut, J., & McCabe, K. (1995). Trust, reciprocity, and
social history. Games and Economic Behavior, 10(1), 122–142.
Bishop, J. W., & Scott, K. D. (2000). An examination of organiza-
tional and team commitment in a self-directed team environ-
ment. Journal of Applied Psychology, 85(3), 439–450.
Blau, P. M. (1964). Social exchange theory. Wiley.
Blau, P. M. (1968). Interaction: Social exchange. In P. M. Blau
(Ed.), International encyclopedia of the social sciences (Vol.
7, pp. 452–458). Macmillan.
Bless, H., Mackie, D. H., & Schwartz, N. (1992). Mood effects on
attitude judgments: Independent effects of mood before and
after message elaboration. Journal of Personality and Social
Psychology, 63, 585–595.
Bliese, P. D. (2000). Within-group agreement, non-independence,
and reliability. In K. J. Klein & S. W. J. Kozlowski (Eds.),
Multilevel theory, research, and methods in organizations (pp.
349–381). Jossey-Bass.
Bourgeois-Gironde, S., & Corcos, A. (2011). Discriminating stra-
tegic reciprocity and acquired trust in the repeated trust-game.
Economics Bulletin, 31(1), 177–188.
Bower, G. H. (1981). Mood and memory. American Psychologist,
36(2), 129–148.
Bower, G. H. (1991). Mood congruity of social judgments. In J.
P. Forgas (Ed.), Emotion and social judgments (pp. 31–53).
Psychology Press.
Bowles, S., & Gintis, H. (2003). Origins of human cooperation. In
P. Hammerstein (Ed.), Genetic and cultural evolution of coop-
eration (pp. 429–443). MIT Press.
Bradley, B. P., Mogg, K., Falla, S. J., & Hamilton, L. R. (1998).
Attentional bias for threatening facial expressions in anxiety:
Manipulation of stimulus duration. Cognition and Emotion,
12(6), 737–753.
Brown, R. (1986). Social psychology. Free Press.
Buchan, N. R., Croson, R. T., & Dawes, R. M. (2002). Swift neigh-
bors and persistent strangers: A cross-cultural investigation of
trust and reciprocity in social exchange. American Journal of
Sociology, 108(1), 168–206.
Burger, J. M. (1986). Increasing compliance by improving the deal:
The that’s-not-all technique. Journal of Personality and Social
Psychology, 51(2), 277–283.
Camacho, C. J., Higgins, E. T., & Luger, L. (2003). Moral value
transfer from regulatory fit: What feels right is right and
what feels wrong is wrong. Journal of Personality and Social
Psychology, 84(3), 498–510.
Carver, C. S. (2006). Approach, avoidance, and the self-regulation
of affect and action. Motivation and Emotion, 30(2), 105–110.
Carver, C. S., & Scheier, M. F. (1998). On the self-regulation of
behavior. Cambridge University Press.
Chan, D. (1998). Functional relations among constructs in the same
content domain at different levels of analysis: A typology of
composition models. Journal of Applied Psychology, 83(2),
234–246.
Charness, G., Haruvy, E., & Sonsino, D. (2007). Social distance
and reciprocity: An Internet experiment. Journal of Economic
Behavior & Organization, 63, 88–103.
Chen, J., Chiu, C.-y., & Chan, S. F. (2009). The cultural effects
of job mobility and the belief in a fixed world: Evidence
from performance forecast. Journal of Personality and Social
Psychology, 97(5), 851–865.
Cheung, T. T., Gillebaart, M., Kroese, F., & De Ridder, D. (2014).
Why are people with high self-control happier? The effect of
trait self-control on happiness as mediated by regulatory focus.
Frontiers in Psychology, 5, Article 722.
Cialdini, R. B., Baumann, D. J., & Kenrick, D. T. (1981). Insights
from sadness: A three step model of the development of altru-
ism as hedonism. Developmental Review, 1, 207–223.
Cialdini, R. B., Darby, B., & Vincent, J. (1973). Transgression and
altruism: A case for hedonism. Journal of Experimental Social
Psychology, 9, 502–516.
Cohen, J. (1988). Statistical power analysis for the behavioral sci-
ences. Academic Press.
Cook, W. L., & Kenny, D. A. (2005). The actor–partner interdepen-
dence model: A model of bidirectional effects in developmental
Deng et al. 19
studies. International Journal of Behavioral Development,
29(2), 101–109.
Cortina, L. M., & Magley, V. J. (2003). Raising voice, risking
retaliation: Events following interpersonal mistreatment in the
workplace. Journal of Occupational Health Psychology, 8(4),
247–265.
Cosmides, L., & Tooby, J. (2005). Neurocognitive adaptations
designed for social exchange. In D. M. Buss (Ed.), The hand-
book of evolutionary psychology (pp. 584–627). John Wiley.
Cropanzano, R., Anthony, E. L., Daniels, S. R., & Hall, A. V.
(2017). Social exchange theory: A critical review with theo-
retical remedies. Academy of Management Annals, 11(1),
479–516.
Davie, M. (1929). The evolution of warfare. Yale University Press.
Dawson, G., Panagiotides, H., Klinger, L. G., & Hill, D. (1992).
The role of frontal lobe functioning in the development of
infant self-regulatory behavior. Brain and Cognition, 20(1),
152–175.
Eisenberger, R., Armeli, S., Rexwinkel, B., Lynch, P. D., &
Rhoades, L. (2001). Reciprocation of perceived organizational
support. Journal of Applied Psychology, 86(1), 42–51.
El-Alayli, A., & Messé, L. A. (2004). Reactions toward an unex-
pected or counternormative favor-giver: Does it matter if we
think we can reciprocate? Journal of Experimental Social
Psychology, 40(5), 633–641.
Elfenbein, D. W., & Zenger, T. R. (2013). What is a relationship
worth? Repeated exchange and the development and deployment
of relational capital. Organization Science, 25(1), 222–244.
Elliot, A. J. (1997). Integrating the “classic” and “contemporary”
approaches to achievement motivation: A hierarchical model
of approach and avoidance achievement motivation. Advances
in Motivation and Achievement, 10(7), 143–179.
Faddegon, K., Scheepers, D., & Ellemers, N. (2008). If we have the
will, there will be a way: Regulatory focus as a group identity.
European Journal of Social Psychology, 38(5), 880–895.
Falk, C. F., Heine, S. J., Yuki, M., & Takemura, K. (2009). Why
do Westerners self-enhance more than East Asians? European
Journal of Personality, 23(3), 183–203.
Farrell, D., & Rusbult, C. E. (1981). Exchange variables as pre-
dictors of job satisfaction, job commitment, and turnover:
The impact of rewards, costs, alternatives, and investments.
Organizational Behavior and Human Performance, 28(1),
78–95.
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power
3: A flexible statistical power analysis program for the social,
behavioral, and biomedical sciences. Behavior Research
Methods, 39(2), 175–191.
Fehr, E., Fischbacher, U., & Gächter, S. (2002). Strong reciproc-
ity, human cooperation, and the enforcement of social norms.
Human Nature, 13(1), 1–25.
Fehr, E., & Gächter, S. (1998). Reciprocity and economics: The
economic implications of Homo Reciprocans1. European
Economic Review, 42(3–5), 845–859.
Fehr, E., & Gächter, S. (2000). Fairness and retaliation: The eco-
nomics of reciprocity. The Journal of Economic Perspectives,
14, 159–181.
Ferguson, A. J., & Peterson, R. S. (2015). Sinking slowly: Diversity
in propensity to trust predicts downward trust spirals in small
groups. Journal of Applied Psychology, 100(4), 1012–1024.
Folger, R., & Skarlicki, D. P. (1998). When tough times make tough
bosses: Managerial distancing as a function of layoff blame.
Academy of Management Journal, 41(1), 79–87.
Fredrickson, B. L. (2001). The role of positive emotions in positive
psychology: The broaden-and-build theory of positive emo-
tions. American Psychologist, 56(3), 218–226.
Friedman, R. S., & Förster, F. (2008). Activation and measure-
ment of motivational states. In A. J. Elliot (Ed.), Handbook
of approach and avoidance motivation (pp. 235–246).
Psychology Press.
Gelfand, M. J., Raver, J. L., Nishii, L., Leslie, L. M., Lun, J.,
Lim, B. C., Duan, L., Almaliach, A., Ang, S., & Arnadottir,
J. (2011). Differences between tight and loose cultures: A
33-nation study. Science, 332(6033), 1100–1104.
Gilbert, D. T., & Hixon, J. G. (1991). The trouble of thinking:
Activation and application of stereotypic beliefs. Journal of
Personality and Social Psychology, 60(4), 509–517.
Glomb, T. M., & Liao, H. (2003). Interpersonal aggression in work
groups: Social influence, reciprocal, and individual effects.
Academy of Management Journal, 46(4), 486–496.
Goffman, E. (1959). The presentation of self in everyday life.
Penguin Books.
Gordon, S. L. (1981). The sociology of sentiments and emotion.
Basic Books.
Gorman, C. A., Meriac, J. P., Overstreet, B. L., Apodaca, S.,
McIntyre, A. L., Park, P., & Godbey, J. N. (2012). A meta-
analysis of the regulatory focus nomological network: Work-
related antecedents and consequences. Journal of Vocational
Behavior, 80(1), 160–172.
Gouldner, A. W. (1960). The norm of reciprocity: A preliminary
statement. American Sociological Review, 25, 161–178.
Gray, J. A. (1981). A critique of Eysenck’s theory of personality.
In H. J. Eysenck (Ed.), A model for personality (pp. 246–276).
Springer.
Gray, J. A. (1990). Brain systems that mediate both emotion and
cognition. Cognition and Emotion, 4, 269–288.
Greco, L. M., Whitson, J. A., O’Boyle, E. H., Wang, C. S., & Kim,
J. (2019). An eye for an eye? A meta-analysis of negative
reciprocity in organizations. Journal of Applied Psychology,
104(9), 1117–1143.
Halevy, N., Weisel, O., & Bornstein, G. (2012). “In-group love”
and “out-group hate” in repeated interaction between groups.
Journal of Behavioral Decision Making, 25(2), 188–195.
Hamamura, T., & Heine, S. J. (2008). The role of self-criticism in
self-improvement and face maintenance among Japanese. In E.
C. Chang (Ed.), Self-criticism and self-enhancement: Theory,
research, and clinical implication (pp. 105–122). American
Psychological Association.
Harmon-Jones, E., Harmon-Jones, C., Abramson, L., & Peterson,
C. K. (2009). PANAS positive activation is associated with
anger. Emotion, 9(2), 183–196.
Harris, K. J., Kacmar, K. M., & Zivnuska, S. (2007). An investiga-
tion of abusive supervision as a predictor of performance and
the meaning of work as a moderator of the relationship. The
Leadership Quarterly, 18(3), 252–263.
Hashimoto, H., & Yamagishi, T. (2013). Two faces of interde-
pendence: Harmony seeking and rejection avoidance. Asian
Journal of Social Psychology, 16(2), 142–151.
20 Personality and Social Psychology Bulletin 00(0)
Heider, F. (2013). The psychology of interpersonal relations.
Psychology Press.
Heine, S. J., Lehman, D. R., Markus, H. R., & Kitayama, S. (1999).
Is there a universal need for positive self-regard? Psychological
Review, 106(4), 766–794.
Helm, B., Bonoma, T. V., & Tedeschi, J. T. (1972). Reciprocity for
harm done. The Journal of Social Psychology, 87(1), 89–98.
Henderson, L. S., Stackman, R. W., & Lindekilde, R. (2018).
Why cultural intelligence matters on global project teams.
International Journal of Project Management, 36(7), 954–967.
Hershcovis, M. S., & Barling, J. (2010). Comparing victim attri-
butions and outcomes for workplace aggression and sexual
harassment. Journal of Applied Psychology, 95(5), 874–888.
Higgins, E. T. (1987). Self-discrepancy: A theory relating self and
affect. Psychological Review, 94(3), 319–340.
Higgins, E. T. (1997). Beyond pleasure and pain. American
Psychologist, 52(12), 1280–1300.
Higgins, E. T. (2000). Making a good decision: Value from fit.
American Psychologist, 55(11), 1217–1230.
Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses
to goal attainment: Strength of regulatory focus as moderator.
Journal of Personality and Social Psychology, 72(3), 515–525.
Higgins, E. T., & Spiegel, S. (2004). Promotion and prevention
strategies for self-regulation: A motivated cognition perspec-
tive. In R. F. Baumeister & K. D. Vohs (Eds.), Handbook of
self-regulation: Research, theory, and applications (Vol. 15,
pp. 171–187). Guilford Press.
Hirt, E. R., Devers, E. E., & McCrea, S. M. (2008). I want to be cre-
ative: Exploring the role of hedonic contingency theory in the
positive mood-cognitive flexibility link. Journal of Personality
and Social Psychology, 94(2), 214–230.
Hochschild, A. (1983). Comment on Kemper’s “Social construc-
tionist and positivist approaches to the sociology of emotions.”
University of Chicago Press.
Hofstede, G. (1980). Culture and organizations. International
Studies of Management & Organization, 10(4), 15–41.
Homan, G. C. (1961). Social behavior: Its elementary forms.
Harcourt, Brace & World.
Humphrey, S. E., Aime, F., Cushenbery, L., Hill, A. D., &
Fairchild, J. (2017). Team conflict dynamics: Implications of a
dyadic view of conflict for team performance. Organizational
Behavior and Human Decision Processes, 142, 58–70.
Isen, A. M. (1987). Positive affect, cognitive processes, and social
behavior. In L. Berkowitz (Ed.), Advances in experimental
social psychology (Vol. 20, pp. 203–253). Elsevier.
Johnson, P. D., Smith, M. B., Wallace, J. C., Hill, A. D., & Baron,
R. A. (2015). A review of multilevel regulatory focus in orga-
nizations. Journal of Management, 41(5), 1501–1529.
Keller, J., Hurst, M., & Uskul, A. (2008). Prevention-focused
self-regulation and aggressiveness. Journal of Research in
Personality, 42(4), 800–820.
Kemper, T. D. (1991). Predicting emotions from social relations.
Social Psychology Quarterly, 54, 330–342.
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data
analysis. Guilford Press.
Keysar, B., Converse, B. A., Wang, J., & Epley, N. (2008).
Reciprocity is not give and take asymmetric reciprocity to
positive and negative acts. Psychological Science, 19(12),
1280–1286.
Kitayama, S., Markus, H. R., Matsumoto, H., & Norasakkunkit, V.
(1997). Individual and collective processes in the construction
of the self: Self-enhancement in the United States and self-crit-
icism in Japan. Journal of Personality and Social Psychology,
72(6), 1245–1267.
Klenk, M. M., Strauman, T. J., & Higgins, E. T. (2011). Regulatory
focus and anxiety: A self-regulatory model of GAD-depression
comorbidity. Personality and Individual Differences, 50(7),
935–943.
Krull, J. L., & MacKinnon, D. P. (2001). Multilevel modeling of
individual and group level mediated effects. Multivariate
Behavioral Research, 36(2), 249–277.
Lance, C. E., Vandenberg, R. J., & Self, R. M. (2000). Latent
growth models of individual change: The case of newcomer
adjustment. Organizational Behavior and Human Decision
Processes, 83(1), 107–140.
Lawler, E. J., & Thye, S. R. (1999). Bringing emotions into social
exchange theory. Annual Review of Sociology, 25(1), 217–244.
LeBreton, J. M., & Senter, J. L. (2008). Answers to 20 ques-
tions about interrater reliability and interrater agreement.
Organizational Research Methods, 11(4), 815–852.
Lee, A. Y., & Aaker, J. L. (2004). Bringing the frame into focus:
The influence of regulatory fit on processing fluency and per-
suasion. Journal of Personality and Social Psychology, 86(2),
205–218.
Lee, A. Y., Aaker, J. L., & Gardner, W. L. (2000). The pleasures
and pains of distinct self-construals: The role of interdepen-
dence in regulatory focus. Journal of Personality and Social
Psychology, 78(6), 1122–1134.
Leith, K. P., & Baumeister, R. F. (1996). Why do bad moods
increase self-defeating behavior? Emotion, risk tasking, and
self-regulation. Journal of Personality and Social Psychology,
71(6), 1250–1267.
Leung, A. K.-y., Chiu, C.-y., & Hong, Y.-y. (2011). Cultural
processes: A social psychological perspective. Cambridge
University Press.
Levitt, S. R. (2015). Cultural factors affecting international team-
work dynamics. International Journal of Knowledge, Culture
and Change in Organizations: Annual Review, 13, 9–23.
Leymann, H. (1990). Mobbing and psychological terror at work-
places. Violence & Victims, 5(2), 119–126.
Li, L. M. W., Adams, G., Kurtiş, T., & Hamamura, T. (2015).
Beware of friends: The cultural psychology of relational mobil-
ity and cautious intimacy. Asian Journal of Social Psychology,
18(2), 124–133.
Li, L. M. W., & Masuda, T. (2016). The role of regulatory focus
in how much we care about enemies: Cross-cultural compari-
son between European Canadians and Hong Kong Chinese.
Journal of Cross-Cultural Psychology, 47(1), 131–148.
Lockwood, P., Jordan, C. H., & Kunda, Z. (2002). Motivation by
positive or negative role models: Regulatory focus determines
who will best inspire us. Journal of Personality and Social
Psychology, 83(4), 854–864.
Lockwood, P., Marshall, T. C., & Sadler, P. (2005). Promoting suc-
cess or preventing failure: Cultural differences in motivation
by positive and negative role models. Personality and Social
Psychology Bulletin, 31(3), 379–392.
Loyd, D. L., Wang, C. S., Phillips, K. W., & Lount, R. B. (2013).
Social category diversity promotes pre-meeting elaboration:
Deng et al. 21
The role of relationship focus. Organization Science, 24, 757–
772.
Lyons, B. J., & Scott, B. A. (2012). Integrating social exchange
and affective explanations for the receipt of help and harm: A
social network approach. Organizational Behavior and Human
Decision Processes, 117(1), 66–79.
Markus, H. R., & Kitayama, S. (1991). Culture and the self:
Implications for cognition, emotion, and motivation.
Psychological Review, 98(2), 224–253.
McCabe, K. A., Rigdon, M. L., & Smith, V. L. (2003). Positive
reciprocity and intentions in trust games. Journal of Economic
Behavior & Organization, 52(2), 267–275.
Mitchell, M. M. (2000). Able but not motivated? The relative
effects of happy and sad mood on persuasive message process-
ing. Communication Monographs, 67, 215–226.
Mitchell, M. S., & Ambrose, M. L. (2007). Abusive supervision
and workplace deviance and the moderating effects of nega-
tive reciprocity beliefs. Journal of Applied Psychology, 92(4),
1159–1168.
Molinsky, A. (2007). Cross-cultural code-switching: The psycho-
logical challenges of adapting behavior in foreign cultural
interactions. Academy of Management Review, 32(2), 622–640.
Morris, M. W., Hong, Y.-y., Chiu, C.-y., & Liu, Z. (2015).
Normology: Integrating insights about social norms to under-
stand cultural dynamics. Organizational Behavior and Human
Decision Processes, 129, 1–13.
Nisbett, R. E., & Cohen, D. (1996). Culture of honor. Westview
Press.
Offerman, T. (2002). Hurting hurts more than helping helps.
European Economic Review, 46(8), 1423–1437.
Oishi, S., & Kesebir, S. (2012). Optimal social-networking strat-
egy is a function of socioeconomic conditions. Psychological
Science, 23(12), 1542–1548.
Oishi, S., & Kisling, J. (2009). The mutual constitution of residen-
tial mobility and individualism. In R. S. Wyer, C.-y. Chiu, &
Y.-y. Hong (Eds.), Understanding culture: Theory, research,
and application (pp. 223–238). Psychology Press.
Ott, D. L., & Michailova, S. (2018). Cultural intelligence: A
review and new research avenues. International Journal of
Management Reviews, 20(1), 99–119.
Otterbein, K. (1970). The evolution of war. HRAF Press.
Perry, N. S., Baucom, K. J., Bourne, S., Butner, J., Crenshaw, A.
O., Hogan, J. N., Imel, Z. E., Wiltshire, T., & Baucom, B. R.
(2017). Graphic methods for interpreting longitudinal dyadic
patterns from repeated-measures actor–partner interdepen-
dence models. Journal of Family Psychology, 31(5), 592–603.
Perugini, M., Gallucci, M., Presaghi, F., & Ercolani, A. P. (2003).
The personal norm of reciprocity. European Journal of
Personality, 17(4), 251–283.
Pillutla, M. M., & Murnighan, J. K. (1996). Unfairness, anger, and
spite: Emotional rejections of ultimatum offers. Organizational
Behavior and Human Decision Processes, 68(3), 208–224.
Porter, L. W., Steers, R. M., Mowday, R. T., & Boulian, P. V.
(1974). Organizational commitment, job satisfaction, and
turnover among psychiatric technicians. Journal of Applied
Psychology, 59(5), 603–609.
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing
moderated mediation hypotheses: Theory, methods, and pre-
scriptions. Multivariate Behavioral Research, 42(1), 185–227.
Rind, B., & Strohmetz, D. (1999). Effect on restaurant tipping of
a helpful message written on the back of customers’ checks.
Journal of Applied Social Psychology, 29(1), 139–144.
Rockenbach, B., & Milinski, M. (2006). The efficient interaction of
indirect reciprocity and costly punishment. Nature, 444(7120),
718–723.
Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity
dominance, and contagion. Personality and Social Psychology
Review, 5(4), 296–320.
San Martin, A., Schug, J., & Maddux, W. (2019). Relational mobil-
ity and cultural differences in analytic and holistic thinking.
Journal of Personality and Social Psychology, 116(4), 495–
518.
Sato, K., Yuki, M., & Norasakkunkit, V. (2014). A socio-ecological
approach to cross-cultural differences in the sensitivity to social
rejection: The partially mediating role of relational mobility.
Journal of Cross-Cultural Psychology, 45(10), 1549–1560.
Scheff, T. J. (1983). Toward integration in the social psychology of
emotions. Annual Review of Sociology, 9(1), 333–354.
Schug, J., Yuki, M., Horikawa, H., & Takemura, K. (2009).
Similarity attraction and actually selecting similar others: How
cross-societal differences in relational mobility affect interper-
sonal similarity in Japan and the USA. Asian Journal of Social
Psychology, 12(2), 95–103.
Schug, J., Yuki, M., & Maddux, W. (2010). Relational mobil-
ity explains between-and within-culture differences in self-
disclosure to close friends. Psychological Science, 21(10),
1471–1478.
Schwarz, N. (1990). Feelings as information: Informational and
motivational functions of affective states. In E. T. Higgins &
R. M. Sorrentino (Eds.), Handbook of motivation and cognition
(pp. 527–561). Guilford Press.
Schwarz, N. (2000). Emotion, cognition, and decision making.
Cognition and Emotion, 14(4), 433–440.
Settoon, R. P., Bennett, N., & Liden, R. C. (1996). Social exchange
in organizations: Perceived organizational support, leader–
member exchange, and employee reciprocity. Journal of
Applied Psychology, 81(3), 219–227.
Shah, J., & Higgins, E. T. (2001). Regulatory concerns and appraisal
efficiency: The general impact of promotion and prevention.
Journal of Personality and Social Psychology, 80(5), 693–705.
Singh, R., Simons, J., Self, W., Tetlock, P., Bell, P., Ong, P., &
Kaur, S. (2011). Cultural and developmental differences in
norm and meta-norm enforcement: Does collective blame
compensate for individual blame? In P. Singh, P. Bain, C. H.
Leong, G. Misra, & Y. Ohtsubo (Eds.), Psychological, group,
and cultural processes in changing societies: Progress in Asian
social psychology (Vol. 8, pp. 109–122). Macmillan.
Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a
causal chain: Why experiments are often more effective than
mediational analyses in examining psychological processes.
Journal of Personality and Social Psychology, 89(6), 845–851.
Strauss, W. A. (1977). Existence of solitary waves in higher dimen-
sions. Communications in Mathematical Physics, 55(2),
149–162.
Tiedens, L. Z., & Linton, S. (2001). Judgment under emotional
certainty and uncertainty: The effects of specific emotions
on information processing. Journal of Personality and Social
Psychology, 81(6), 973–988.
22 Personality and Social Psychology Bulletin 00(0)
Tsai, J. L., Knutson, B., & Fung, H. H. (2006). Cultural variation in
affect valuation. Journal of Personality and Social Psychology,
90(2), 288–307.
Tumey-High, H. H. (1971). Primitive war: Its practice and con-
cepts. University of South Carolina Press.
Uskul, A. K., Sherman, D. K., & Fitzgibbon, J. (2009). The cultural
congruency effect: Culture, regulatory focus, and the effec-
tiveness of gain- vs. loss-framed health messages. Journal of
Experimental Social Psychology, 45(3), 535–541.
VanVoorhis, C. W., & Morgan, B. L. (2007). Understanding power
and rules of thumb for determining sample sizes. Tutorials in
Quantitative Methods for Psychology, 3(2), 43–50.
Västfjäll, D., Gärling, T., & Kleiner, M. (2001). Does it make you
happy feeling this way? A core affect account of preference for
current mood. Journal of Happiness Studies, 2(4), 337–354.
Wang, C. S., Galinsky, A. D., & Murnighan, J. K. (2009). Bad drives
psychological reactions but good propels behavior: Reactions
to honesty and deception. Psychological Science, 20, 634–644.
Wang, C. S., & Leung, A. K.-y. (2010). The cultural dynamics of
rewarding honesty and punishing deception. Personality and
Social Psychology Bulletin, 36(11), 1529–1542.
Wang, C. S., Sivanathan, N., Narayanan, J., Ganegoda, D.,
Bauer, M., Bodenhausen, G. V., & Murnighan, J. K. (2011).
Retribution and emotional regulation: The effect of time delay
in angry economic interactions. Organizational Behavior and
Human Decision Processes, 116, 46–54.
Wang, X., Guinote, A., & Krumhuber, E. G. (2018). Dominance
biases in the perception and memory for the faces of power-
holders, with consequences for social inferences. Journal of
Experimental Social Psychology, 78, 23–33.
Weber, L., & Bauman, C. W. (2019). The cognitive and behav-
ioral impact of promotion and prevention contracts on trust in
repeated exchanges. Academy of Management Journal, 62(2),
361–382.
Wegener, D. T., & Petty, R. E. (1994). Mood management across
affective states: The hedonic contingency hypothesis. Journal
of Personality and Social Psychology, 66(6), 1034–1048.
Whitson, J. A., Kim, J., Wang, C. S., Menon, T., & Webster, B.
D. (2019). Regulatory focus and conspiratorial perceptions:
The importance of personal control. Personality and Social
Psychology Bulletin, 45(1), 3–15.
Whitson, J. A., Wang, C. S., Kim, J., Cao, J., & Scrimpshire, A.
(2015). Responses to normative and norm-violating behav-
ior: Culture, job mobility, and social inclusion and exclusion.
Organizational Behavior and Human Decision Processes, 129,
24–35.
Whitson, J. A., Wang, C. S., See, Y.-H. M., Baker, W., & Murnighan,
J. K. (2015). How, when, and why recipients and observers
reward good deeds and punish bad deeds. Organizational
Behavior and Human Decision Processes, 128, 84–95.
Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and
organizational commitment as predictors of organizational citi-
zenship and in-role behaviors. Journal of Management, 17(3),
601–617.
Wright, W. F., & Bower, G. H. (1992). Mood effects on subjective
probability assessment. Organizational Behavior and Human
Decision Processes, 52(2), 276–291.
Zand, D. E. (1972). Trust and managerial problem solving.
Administrative Science Quarterly, 17(2), 229–239.
Zhang, Y., & Mittal, V. (2007). The attractiveness of enriched and
impoverished options: Culture, self-construal, and regulatory
focus. Personality and Social Psychology Bulletin, 33(4),
588–598.
