Article Review
Spread of Unethical Behavior in Organizations: A Dynamic Social Network Perspective
Franziska Zuber
Received: 19 June 2013 / Accepted: 20 June 2014 / Published online: 10 July 2014
� Springer Science+Business Media Dordrecht 2014
Abstract The spread of unethical behavior in organiza-
tions has mainly been studied in terms of processes
occurring in a general social context, rather than in terms of
actors’ reactions in the context of their specific social
relationships. This paper introduces a dynamic social net-
work analysis framework in which this spread is concep-
tualized as the result of the reactions of perpetrators,
victims, and observers to an initial act of unethical
behavior. This theoretical framework shows that the social
relationships of the actors involved in an initial act impact
in multiple ways the likelihood that unethical behavior
spreads. It reveals furthermore that social relationships may
change in the wake of unethical behavior, such that indirect
negative consequences can arise for organizations. The
proposed framework provides a basis for the development
of a formal stochastic actor-oriented model of network
dynamics which would enable simulations of the spread of
unethical behavior.
Keywords Unethical behavior � Misconduct � Contagion � Spread � Social network analysis
Introduction
The Occupy Wall Street movement has most vividly
expressed a loss of trust in the prevailing (Western) eco-
nomic and political systems in the aftermath of the global
financial crisis. A ‘‘pattern of dishonesty on the part of
financial institutions’’ (Stiglitz 2008, p. 30) that is consid-
ered to have contributed to the global financial crisis has
fueled this loss of trust not only within this movement, but
also with many citizens. This illustrates that the negative
consequences of widespread unethical behavior in organi-
zations can be significant, not only for the involved orga-
nizations, but also for society, because organizations are
the central agents in today’s economic and political sys-
tems. To be able to limit the spread of unethical behavior
and avoid negative consequences, those managing and
regulating organizations need an understanding of the
processes by which unethical behavior spreads in organi-
zations, and of the conditions under which unethical
behavior is particularly likely to spread.
This paper aims at identifying such processes and con-
ditions to further the understanding of the spread of
unethical behavior, which is defined as an increase over
time in the number of acts of unethical behavior, and in the
number of actors involved in these acts (see also Spread, n.
(Def. 4b). March 2013; Spread, v. (Def. 6, 12a). March
2013). In other words, the spread of unethical behavior
occurs when an initial act of unethical behavior is followed
by subsequent acts of unethical behavior (e.g., Ashforth
and Anand 2003; Palmer 2008) by actors actively or pas-
sively involved in the initial act. Unethical behavior is
behavior that is ‘‘either illegal or morally unacceptable to
the larger community’’ (Jones 1991, p. 367).
The spread of unethical behavior in organizations has
mainly been studied in terms of group-level processes
occurring in a general social context (e.g., den Nieu-
wenboer and Kaptein 2008; Pinto et al. 2008), prescinding
from specific relationships between actors involved in an
act, or has focused on collective acts (e.g., Ashforth and
Anand 2003; Brief et al. 2001). The role of social rela-
tionships in understanding the phenomenon of unethical
F. Zuber (&) Department of Business-Society Management, Rotterdam
School of Management, Erasmus University Rotterdam,
P.O. Box 1738, 3000 DR Rotterdam, The Netherlands
e-mail: FZuber@rsm.nl
123
J Bus Ethics (2015) 131:151–172
DOI 10.1007/s10551-014-2270-0
behavior in organizations has been emphasized by Brass
et al. (1998) who have applied a social network perspec-
tive. In their account for the spread of unethical behavior,
they have argued that relationships between perpetrators
and observers lead to similar attitudes toward unethical
behavior, which in turn can cause the spread of unethical
behavior from perpetrators to observers. Building on Brass
et al.’s (1998) work, this paper draws upon recent advances
in modeling the evolution of social networks and findings
in business ethics research to propose a dynamic actor-
oriented social network framework for examining the
spread of unethical behavior.
The dynamic social network perspective proposed here
extends current theoretical approaches to the spread of
unethical behavior in two important respects. First, a three-
fold role of social relationships in the process of spread is
proposed. In addition to considering social relationships as
channels for the transmission of social information about
unethical behavior as in extant research (e.g., ideologies
and practices in Ashforth and Anand 2003; attitudes in
Brass et al. 1998; norms in den Nieuwenboer and Kaptein
2008), the proposed perspective also considers how an
actor’s social relationships influence his cognitive appraisal
of, and ensuing behavioral reaction to an act of unethical
behavior. Furthermore, the proposed perspective examines
how social relationships can change as a result of unethical
behavior, rather than regarding them as antecedent factors
only, and how such changes can facilitate further unethical
behavior in later stages. Second, the role of perpetrators,
victims, and observers in spreading unethical behavior is
examined. While extant research on the spread of unethical
behavior mainly analyzes the role of perpetrators and
observers, considerable work on retaliation and revenge in
the workplace (e.g., Bies and Tripp 2004; Skarlicki and
Folger 2004) has shown how victims’ reactions can also
lead to the spread of unethical behavior.
The mutual dependencies between actors’ interpersonal
relationships and their involvement in acts of unethical
behavior are represented in a dynamic actor-oriented social
network framework that includes actors’ interpersonal
relationships as well as their relationships to acts of
unethical behavior as perpetrators, victims, or observers. In
this theoretical framework, the spread of unethical behavior
is conceptualized as arising from perpetrators’, victims’,
and observers’ reactions to initial unethical behavior in the
context of their specific social relationships. The actors’
reactions are explained by drawing on theories of social
cognition and findings from behavioral business ethics
research, and are represented in the framework as changes
in the actors’ relationships to acts of unethical behavior and
other actors.
This paper’s focus on the spread of unethical behavior
implies that possibilities to confine the spread of unethical
behavior are beyond its scope. Accordingly, I also focus on
subsequent unethical behavior as a reaction to an initial act
of unethical behavior, rather than on other reactions such as
confronting the perpetrators, reporting, whistleblowing, or
reconciliation (e.g., Gundlach et al. 2003; Kaptein 2011;
Palanski 2012). The micro-level perspective on individual
actors’ reactions in the context of their relationships
applied here implies that well-known macro-level charac-
teristics of networks such as structural holes, density, or
cliques are not discussed. Finally, I examine how unethical
behavior spreads once an initial act has been committed,
and do not examine the emergence of initial acts of
unethical behavior. In their pioneering article, Brass et al.
(1998) have studied the ‘‘question of under what social
network conditions are we likely to see unethical behavior’’
(Brass et al. 1998, p. 15).
The remainder of this paper is structured as follows.
First, the dynamic social network perspective on the spread
unethical behavior in organizations is described. Next, I to
propose when and why perpetrators, victims, and observers
are likely to react to an initial act of unethical behavior by
committing subsequent acts, and translate these reaction
tendencies into the social network framework. I conclude
by discussing the proposed framework, its implications and
limitations and provide guidance for future research.
Social Networks and the Spread of Unethical Behavior
The focus on social relationships between actors is at the
core of social network analysis (Brass et al. 1998). Brass
et al. (1998) have pioneered a social network perspective
on ethics and ethical behavior in organizations and have
inspired a variety of research analyzing social networks
and unethical behavior at different levels of analysis (e.g.,
Lyons and Scott 2012; Sullivan et al. 2007). A Special
Issue of the Journal of Business Ethics dedicated to net-
work ethics, which focused in particular on the impact
information and communication technologies (Vaccaro
et al. 2009), illustrates the broad range of possible appli-
cations of a social network perspective. While researchers
use concepts from social network analysis in their analysis
of unethical behavior (e.g., Moore 2009; O’Fallon and
Butterfield 2011; Shadnam and Lawrence 2011), research
using social network models still appears to be rather rare.
In their analysis of the spread of unethical behavior,
Brass et al. (1998) propose two mechanisms to explain why
observers of an initial act of unethical behavior commit
subsequent acts. The cohesion mechanism suggests that
when there is a positive relationship between two actors,
they interact and communicate more frequently, are
therefore likely to develop similar attitudes toward uneth-
ical behavior, and to imitate each other’s unethical
152 F. Zuber
123
behavior (Brass et al. 1998, p. 25). In the equivalence
mechanism, actors who are similarly positioned in the
network compare themselves with each other and are
indirectly aware of the other’s behavior. Therefore, they
tend to adopt the other’s attitudes toward unethical
behavior, and to imitate the other’s behavior (Brass et al.
1998, p. 25). These two mechanisms focus exclusively on
the role of social relationships between perpetrators and
observers as channels for the transmission of attitudes. By
contrast, the possibility that social relationships impact
reactions to unethical behavior, the role of the victim and
his relationships, as well as the impact of unethical
behavior on social relationships are not considered. By
including these elements in a social network framework for
the spread of unethical behavior, a more comprehensive
view on the processes which can cause the spread of
unethical behavior can be achieved.
Relevant Actors and Relationships
Research has investigated how different actors actively or
passively involved in acts of unethical behavior react to
this experience. One line of research has focused on how
perpetrators react to their own acts (e.g., Tenbrunsel and
Messick 2004; Zhong et al. 2009, 2010); a second line of
research has examined victims’ reactions (e.g., Aquino
et al. 2001, 2006; Bies et al. 1997; Kim et al. 2008;
Mitchell and Ambrose 2012; Tripp et al. 2007), and a third
line has studied observers’ reactions (e.g., Gino et al. 2009;
O’Fallon and Butterfield 2011, 2012; O’Reilly and Aquino
2011; Robinson and O’Leary-Kelly 1998; Rupp and Bell
2010; Umphress et al. 2013). This research indicates that
each of these actors can react to an act of unethical
behavior by committing subsequent acts, or, alternatively,
by engaging in other, pro-social behaviors, and underscores
the importance of considering reactions of all three actors
when investigating the spread of unethical behavior. The
reasons which motivate subsequent unethical behavior,
however, differ between perpetrator, victim, and observer,
and will be discussed later.
From a social network analysis perspective, perpetra-
tors, victims, and observers can be seen as having each a
specific type of relationship to an act of unethical behavior.
These specific relationships can be represented in two-
mode networks. Two-mode networks are used in social
network analysis to represent actors’ participation in
activities or membership in groups (Borgatti and Halgin
2011). For example, a perpetrator and an observer of a
given act of unethical behavior can be thought of as being
involved in the same act, where each has a distinct type of
relationship to the act.
With respect to interpersonal relationships, Brass et al.
(1998) have described how positive or neutral relationships
between observers and perpetrators can lead observers to
imitate the perpetrator’s unethical behavior. They have also
noted that negative relationships are expected to be posi-
tively related to unethical behavior due to the lack of
empathy and psychological proximity implied by such
relationships (Brass et al. 1998, p. 18). Negative relation-
ships ‘‘represent an enduring, recurring set of negative
judgments, feelings and behavioral intentions toward
another person’’ (Labianca and Brass 2006, p. 597). Even
though most relationships in organizations are positive or
at least neutral (Labianca and Brass 2006; Robins et al.
2009), negative relationships have a greater impact on task-
related and socioemotional outcomes compared to positive
or neutral relationships due to their higher salience (Labi-
anca and Brass 2006). As a result of this negative asym-
metry, negative relationships can be expected to have an
important impact on the spread of unethical behavior, and
should be considered in the social network perspective
along with positive relationships. The specific role of
negative relationships in the spread of unethical behavior
will be discussed later when describing the reactions of
perpetrators, victims, and observers.
Emergence of Reactions in Social Networks: Social
Cognition
To understand when actors are likely to commit subsequent
unethical behavior after their involvement in an initial act
we need to examine how their reactions emerge. The
reactions of perpetrators, victims, and observers to an act of
unethical behavior are based on their perception and
interpretation of this social event, rather than on its
objective characteristics (if such objective characteristics
exist at all) (Sonenshein 2007). Perpetrator, victim, and
observer each have a different perspective on the act, and
therefore react differently. These different reactions, how-
ever, can all be seen as the outcome of a process of social
cognition (e.g., Aquino et al. 2001; Gundlach et al. 2003;
O’Reilly and Aquino 2011) taking place in the context of
the actors’ social relationships. Affective events theory
(Weiss and Cropanzano 1996) describes this process of
social cognition as a three-stage appraisal process, in which
actors interpret the information conveyed by a social event,
and then react based their appraisal (Weiss and Cropanzano
1996). Each stage of this process is described below, and
will be examined from the specific perspectives of perpe-
trator, victim, and observer later in this paper.
Initial Affective Appraisal
The process ‘‘begins with an event which is initially
evaluated for relevance to well-being in simple positive or
negative terms’’ (Weiss and Cropanzano 1996, p. 31) by
Dynamic Social Network Perspective 153
123
the actor. A negative event is defined as ‘‘one that has the
potential or actual ability to create adverse outcomes for
the individual’’ (Taylor 1991, p. 67). Events which carry an
initial negative affective evaluation elicit higher physio-
logical and psychological arousal compared to positive
events, and lead to increased causal reasoning in the next
stage of the appraisal process (Bohner et al. 1988; Martinko
et al. 2002; Taylor 1991; Weiner 1985a).
From a perpetrator’s perspective, his act of unethical
behavior exposes him to the risk of social and self-sanc-
tions, and can therefore represent a negative event. For a
victim, the adverse outcome of the event is manifest in the
perceived harm caused to him by the act of unethical
behavior. For an observer, an act of unethical behavior can
be a negative event, because it can indicate that he might
become victim of such behavior in the future; because
sanctions directed against the perpetrator could also affect
him to the extent that he is socially related to the perpe-
trator; and/or because the moral norms of the community
are violated, thereby threatening the social order and the
welfare of the community as a whole (Haidt 2003). A
perpetrator’s, victim’s, or observer’s evaluation of an act of
unethical behavior as negative event triggers a process of
intensive causal reasoning and attributions in the secondary
cognitive appraisal stage.
Secondary Cognitive Appraisal
The search for a causal explanation represents a sense-
making process (Martinko et al. 2002, p. 41). Attribution
theory (Kelley 1973) describes how actors generate causal
explanations to make sense of their and other’s behavior.
Based on these causal explanations, actors form judgments
of responsibility for their own or others’ behavior (Weiner
1985b, 1995). Attribution theory has been fruitfully applied
to explain reactions to negative events in research on
counterproductive workplace behavior (Martinko et al.
2002), workplace aggression and revenge (Aquino et al.
2001, 2004; Martinko and Zellars 1998), abusive supervi-
sion (Bowling and Michel 2011; Shoss et al. 2013),
injustice and mistreatment in organizations (Mikula 2003;
O’Reilly and Aquino 2011), and whistle-blowing decisions
(Gundlach et al. 2003).
According to attribution theory, the causal analysis
leading to a judgment of responsibility involves the con-
sideration of three main elements (Weiner 1995): Whether
the actor or the situation is the main cause (personal vs.
situational causality); whether the actor can willfully con-
trol his behavior (controllability); and whether any miti-
gating circumstances are present which could explain the
actor’s behavior. If personal causality, controllability, and
the absence of mitigating circumstances are established, an
actor is assigned responsibility for his act of unethical
behavior. Finally, Weiner (1995) argues that the degree of
responsibility assigned to an actor depends on the assess-
ment of intention as opposed to negligence on the part of
the actor in committing the act. 1
The consideration of personal causality, controllability,
mitigating circumstances, and intention is subject to biases,
both when actors examine their own and when they
examine others’ behavior (Martinko et al. 2006). The bia-
ses depend on the actor’s position in relation to the act
under consideration, and will therefore be different for
perpetrator, victim, and observer of an act of unethical
behavior. I discuss those biases later when addressing the
specific reactions of perpetrator, victim, and observer. With
the assignment (or not) of responsibility for an act of
unethical behavior, the secondary cognitive appraisal of the
act is completed.
Tertiary Emotional Appraisal
The cognitive appraisal then gives rise to ‘‘discrete emo-
tions like anger, sadness and joy’’ (Weiss and Cropanzano
1996, p. 31) in the third stage of the process (Weiner
1985b, 1995). Emotions imply a certain state of action
readiness and create action tendencies to ‘‘establish[ing] or
modify[ing] the relationship between the subject and a
concern-relevant target’’ (Frijda and Parrot 2011, p. 407).
These action tendencies become manifest in the behavioral
reaction to the event (Weiner 1995). While behavioral
reactions to social events can be motivated by different
positive or negative emotions, two negatively valenced
moral emotions (Haidt 2003; Tangney et al. 2007) are
especially relevant for the emergence of reactions to
unethical behavior: Guilt and anger. Positively valenced
moral emotions (elevation, gratitude, and moral pride,
Tangney et al. 2007) are less relevant as I examine reac-
tions to unethical (rather than ethical) behavior. Guilt and
anger motivate reactions to moral transgressions (Haidt
2003; Tangney et al. 2007) and signal the need for cor-
rective reactions (Haidt 2003, p. 862) in the wake of
unethical behavior. In the absence of these emotions, no
motivation for corrective action is triggered, such that
reactions may reinforce rather than counteract the initial
act of unethical behavior.
Guilt arises when an actor judges himself to be
responsible for an act of unethical behavior (Weiner 1985b,
1995). Anger arises when an actor judges another actor to
be responsible for an act of unethical behavior (Gundlach
1 Margolis (2001) provides an insightful discussion on the relation-
ship between causal and moral responsibility involving both norma-
tive arguments on moral agency and descriptive arguments on
psychological and social forces in organizations. I do not repeat this
discussion here due to limitations of space, and instead refer the
reader to Margolis’ article.
154 F. Zuber
123
et al. 2003; Weiner 1995). Both anger and guilt have an
interpersonal dimension, which is particularly important
from a social network perspective: Anger is other-con-
demning (Haidt 2003), in that actors are angry at others
(Gibson and Callister 2010), and evokes behavioral ten-
dencies to attack or get back at the actor held responsible
for the reprehensible behavior (Folger and Skarlicki 2004;
Haidt 2003; Weiner 1995). Guilt in turn arises in particular
when harm is caused to a relationship partner (Baumeister
et al. 1994; Haidt 2003) and involves other-oriented con-
cerns (Tangney et al. 2007). Baumeister et al. (1994,
p. 246) posit that guilt ‘‘combines empathic distress with a
self-attribution of causal responsibility for the other’s suf-
fering’’. Guilt by consequence triggers the motivation to
make up for one’s behavior and the damage caused (Haidt
2003; Tangney et al. 2007), and can motivate compensa-
tory ethical actions as shown for example by Zhong and
Lilijenquist (2006) and Zhong et al. (2009, 2010).
To summarize, perpetrators’, victims’, and observers’
relationships to acts of unethical behavior, their positive
and negative interpersonal relationships, as well as their
reactions to the acts actors are the key elements of a social
network framework for the spread of unethical behavior in
organizations. The basis for such a framework is provided
by a type of dynamic social network models that allows for
these features: actor-oriented models for the evolution of
networks.
Integrating Relationships and Reactions: Actor-
Oriented Models for Network Dynamics
Researchers interested in how social relationships influence
behavior over time, and vice versa, have applied stochastic
actor-oriented models for network dynamics. For example,
they have studied the co-evolution of friendship networks
and delinquent behaviors among adolescents (Burk et al.
2007), or the selection and influence effects of aggression
in adolescent friendship networks (Dijkstra et al. 2011;
Sijtsema et al. 2010). In an organizational context, Schulte
et al. (2012) have studied the co-evolution of interpersonal
relationships and perceptions of team psychological safety
using this type of model.
In stochastic actor-oriented models of network dynam-
ics, a network of directed ties (i.e., a tie from actor i to
actor j is distinct from a tie from actor j to actor i) evolves
over time through the actions or decisions of the actors in
the network. Actors change their relationships such that
they ‘‘attain a rewarding configuration of the network’’
(Huisman and Snijders 2003, p. 257) as formally defined in
their objective function or evaluation function. This func-
tion probabilistically determines what change actors make
in their current outgoing ties when given the opportunity to
do so, and characterizes the ‘‘actor-driven micro-mecha-
nisms’’ of the network (Snijders et al. 2010, pp. 45–46).
Components of this objective function are the so-called
effects, which capture an actor’s tendency to create (or
terminate) relationships in response to specific constella-
tions in his relationships (Snijders et al. 2010). A simple
example for such an effect is the tendency to reciprocate
friendship, i.e., when an actor receives a friendship tie from
another actor he tends to also send a friendship tie to the
other actor. Such models also contain a component which
determines when and which actors have the opportunity to
make a change. These opportunities are assumed to arise
stochastically in continuous time, and are modeled in the
so-called rate function.
The core of actor-oriented models for network dynamics
are actors’ evaluation functions with respect to interper-
sonal relationships and activities. These functions reflect
how actors tend to behave in reaction to the current con-
stellation in their interpersonal relationships and activities,
and thus drive the evolution of the interpersonal relation-
ships and activities. When applying such models to a
particular domain, actors’ behavioral tendencies are iden-
tified on the grounds of relevant theories and previous
empirical findings in this domain, and are then formalized
as effects in the evaluation functions. In the context of the
current paper, effects are derived from the reaction ten-
dencies of perpetrators, victims, and observers following an
act of unethical behavior that emerge from the appraisal
process described in the previous section.
Recently, Snijders et al. (2013) have provided a speci-
fication of stochastic actor-oriented models that includes
both interpersonal and activity networks (one-mode and
two-mode networks), as well as different types of rela-
tionships between actors (multiplexity). The structure of
this model provides the basis for a framework in which the
spread of unethical behavior can be studied as a dynamic
process in social networks driven by individual actors.
A Dynamic Actor-Oriented Framework to Examine
the Spread of Unethical Behavior
Relationships
Positive (or neutral) and negative relationships between
actors are represented in interpersonal (one-mode) net-
works. The actors’ relationships to acts of unethical
behavior can be thought of as ties in two-mode networks
connecting actors to acts (activity networks). Three types
of relationships between actors and acts are distinguished:
perpetrator, victim, and observer relationships, referred to
as P-, V-, and O-relationships respectively for convenience.
The relationship between actors and acts is considered as
enduring (Snijders et al. 2013): While the actual physical
Dynamic Social Network Perspective 155
123
act of unethical behavior may be completed in a relatively
short time, an actor will remain associated with this act
through his cognitive representation of his relationship to
the act. It is this enduring cognitive representation of the
relationship on which the actor’s reaction depends, and
which therefore is relevant for the spread of unethical
behavior.
The ties to actors and to acts are directed, i.e., there is a
sender and a receiver. In activity networks, only actors can
send relationships to acts; acts of unethical behavior have
no agency (Snijders et al. 2013). For perpetrators, sending a
relationship to an act of unethical behavior represents
committing the act. The commission of an act by a per-
petrator does not imply that there necessarily will be other
actors who perceive themselves as victim or observer of
this act; however, a perpetrator needs to have committed an
act of unethical behavior in order for other actors to be able
to become victims or observers of an act. Other actors first
have to become aware of the perpetrator’s act to become
involved in the act as victim or observer. Whether an
individual actor should be considered as victim of an act of
unethical behavior depends on this individual’s perception
of having been exposed to harmful behavior (Aquino et al.
1999, p. 260). 2
Only actors who perceive themselves as
victims of an act will react to this act based on this per-
ception. Similarly, only actors who directly or indirectly
become aware of an act of unethical behavior will react as
observers. Therefore, victims and observers are considered
to be the originators of their relationships to acts of
unethical behavior in this framework.
Figure 1 illustrates the elements of the framework just
described for a situation where acts of unethical behavior
have been committed by perpetrators, where there are
victims and/or observers of the acts, and where positive and
negative relationships between actors exist.
Reactions
Actors react to the constellation of their current relation-
ships to actors and acts of unethical behavior, such that
relationships evolve through ‘‘processes where one tie is
formed as a reaction to the existence of other ties’’ (Snij-
ders et al. 2010, pp. 45–46). Reactions to acts of unethical
behavior are thus represented by changes actors make in
their relationships to acts or actors given their relationship
to an initial act. For example, when subsequent acts of
unethical behavior are committed in reaction to an initial
act, actors create new P-relationships to acts. Actors can
also change their interpersonal relationships in response to
their involvement in an act. A victim, for instance, can
create a negative relationship to a perpetrator.
Once a change in a relationship has been made by an
actor, the resulting new configuration of the relationships
constitutes the initial state for the next step, in which
changes to the relationships are made in response to that
(new) initial state, and so forth. In other words, an act of
unethical behavior triggers a reaction—represented by a
change of a relationship in this framework—, and this
reaction in turn triggers a next reaction, such that unethical
behavior can spread through a chain of reactions after an
initial act.
The Spread of Unethical Behavior Through
Perpetrators, Victims, and Observers in a Dynamic
Actor-Oriented Framework
Perpetrators, victims, and observers appraise an act of
unethical behavior from their specific perspectives and
react according to their appraisal. In this process, inter-
personal relationships can be conduits for information
about acts, can influence the actors’ reactions through their
impact on the appraisal, and can change as a result of
actors’ cognitive appraisal of an act of unethical behavior.
These three roles of interpersonal relationships are reflec-
ted in different effects in the dynamic actor-oriented
framework described in the following sections. Table 1
provides an overview of these effects, and includes an
illustration along with a formulation of the effects in more
technical terms proper to social network analysis. In what
follows, propositions summarize the circumstances under
which, and the types of reactions through which unethical
behavior is likely to spread.
Perpetrator’s Perspective and Reaction
Biased Attribution
Actors exhibit a self-serving bias in making attributions for
their outcomes and behaviors to maintain a positive self-
concept: negative events tend to be attributed to external,
unstable, and specific causes, while positive events tend to
be attributed to internal, stable, and global causes (Mart-
inko and Gardner 1987; Martinko et al. 2006; Mezulis et al.
2004). Biased causal reasoning also occurs in the domain
of (un)ethical behavior, where individuals are motivated to
avoid the conclusion that they are responsible for their
unethical behavior (Tenbrunsel and Messick 2004).
2 When referring to victims and victimization, it may be useful to
distinguish two dimensions. The first dimension refers to the
(objective) damage caused to a person by another person’s act
(‘‘damage caused’’), and the second dimension refers to the
(subjective) awareness and perception of this damage (‘‘victimization
perceived’’). From the perspective of reactions by victims, and the
potential spread of unethical behavior, the second dimension is most
relevant and therefore referred to in this paper.
156 F. Zuber
123
(a) One-mode network of positive interpersonal relationships
One-mode network of negative interpersonal relationships
Two-mode activity network of relationships from perpetrators to acts of unethical behavior (P-relationships)
Two-mode activity network of relationships from victims to acts of unethical behavior (V-relationships)
Two-mode activity network of relationships from observers to acts of unethical behavior (O-relationships)
Combined view of interpersonal and activity relationships
ji
k
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m
ji
k
l
m
ji
k
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A
B
C m
ji
k
l
A
B
C m
ji
k
l
A
B
C m
k
ji
m
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A
B
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Legend:
Negative relationship
Perpetration
Victimization
Observation
A Act of unethical behavior
Actori
Positive relationship
(b)
(c)
(d)
(e)
(f)
Fig. 1 Illustration of key elements of the dynamic actor-oriented social network framework. a One-mode network of positive interper- sonal relationships. b One-mode network of negative interpersonal relationships. c Two-mode activity network of relationships from perpetrators to acts of unethical behavior (P-relationships). d Two-
mode activity network of relationships from victims to acts of
unethical behavior (V-relationships). e Two-mode activity network of relationships from observers to acts of unethical behavior (O-
relationships). f Combined view of interpersonal and activity relationships
Dynamic Social Network Perspective 157
123
T a b le
1 S
u m
m a ry
o f
p ro
p o
se d
e ff
e c ts
in th
e d
y n
a m
ic a c to
r- o
ri e n
te d
fr a m
e w
o rk
E ff
e c t
n o
.
R e la
te d
a c to
r
D e sc
ri p
ti o
n o
f e ff
e c t
D e sc
ri p
ti o
n o
f e ff
e c t
in so
c ia
l n
e tw
o rk
a n
a ly
si s
te rm
in o
lo g
y G
ra p
h ic
a l
p re
se n
ta ti
o n
1 P
e rp
e tr
a to
r R e p e ti ti o n e ff e c t:
A P
-r e la
ti o
n sh
ip fr
o m
a c to
r i
to a c t A
le a d
s to
th e
c re
a ti
o n
o f
a P
-r e la
ti o
n sh
ip to
a c t B
b y
a c to
r i
A c to r- le v e l d e p e n d e n c y in
tw o
-m o d e n e tw o rk
: T
h e re
is a
p o
si ti
v e
o u
td e g
re e
a c ti
v it
y e ff
e c t
w it
h re
sp e c t
to P
-r e la
ti o
n sh
ip s.
i A B
2 P
e rp
e tr
a to
r R e tr o sp e c ti v e ra ti o n a li za ti o n e ff e c t:
A P
-r e la
ti o
n sh
ip fr
o m
a c to
r i
to a c t
A le
a d
s to
th e
c re
a ti
o n
o f
a n
e g
a ti
v e
re la
ti o
n sh
ip to
a c to
r j
b y
a c to
r i.
A c to r- le v e l d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
A c ti
v it
y
in th
e n
e tw
o rk
o f
P -r
e la
ti o
n sh
ip s
le a d
s to
a c ti
v it
y in
th e
n e tw
o rk
o f
n e g
a ti
v e
re la
ti o
n sh
ip s.
i j
A
3 P
e rp
e tr
a to
r P ro sp e c ti v e ra ti o n a li za ti o n e ff e c t:
A P
-r e la
ti o
n sh
ip fr
o m
a c to
r i
to a c t
A ,
a n
d a
n e g
a ti
v e
re la
ti o
n sh
ip fr
o m
a c to
r i
to a c to
r j
le a d
to th
e
c re
a ti
o n
o f
a P
-r e la
ti o
n sh
ip to
a c t B
b y
a c to
r i
A c to r- le v e l d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
A c ti
v it
y
in th
e n
e tw
o rk
o f
P -r
e la
ti o
n sh
ip s
a n
d in
th e
n e tw
o rk
o f
n e g
a ti
v e
re la
ti o
n sh
ip s
le a d
to fu
rt h
e r
a c ti
v it
y in
th e
n e tw
o rk
o f
P -r
e la
ti o
n sh
ip s
ji A B
4 V
ic ti
m S p e c ifi c re ta li a ti o n e ff e c t v ic ti m
: A
P -r
e la
ti o
n sh
ip fr
o m
a c to
r j
to a c t A
,
a V
-r e la
ti o
n sh
ip fr
o m
a c to
r i
to th
is a c t A
, a n
d a
P -r
e la
ti o
n sh
ip fr
o m
a c to
r i
to a c t B
le a d
s to
th e
c re
a ti
o n
o f
a V
-r e la
ti o
n sh
ip b
y a c to
r j
to
a c t B
D e p e n d e n c y b e tw e e n tw o -m
o d e n e tw o rk s:
T h
e re
is a
te n
d e n
c y
fo r
m u
lt ip
le x
fo u
r- c y
c le
s fo
rm e d
a c ro
ss V
- a n
d P
-r e la
ti o
n sh
ip s,
w h
e re
tw o
P -r
e la
ti o
n sh
ip s
a n
d o
n e
V -r
e la
ti o
n sh
ip le
a d
to a n
o th
e r
V -r
e la
ti o
n sh
ip (t
e n
d e n
c y
fo r
c lo
su re
)
i A B
j
5 V
ic ti
m G e n e ra l re ta li a ti o n e ff e c t v ic ti m
: A
V -r
e la
ti o
n sh
ip fr
o m
a c to
r i
to a c t
A le
a d
s to
th e
c re
a ti
o n
o f
a P
-r e la
ti o
n sh
ip b
y a c to
r i
to a c t B
A c to r- le v e l d e p e n d e n c y b e tw e e n tw o
-m o d e n e tw o rk s:
A c ti
v it
y in
th e
n e tw
o rk
o f
V -r
e la
ti o
n sh
ip s
le a d
s to
a c ti
v it
y in
th e
n e tw
o rk
o f
P -r
e la
ti o
n sh
ip s
i A B
6 V
ic ti
m G e n e ra l a tt ri b u ti o n e ff e c t v ic ti m
: A
V -r
e la
ti o
n sh
ip fr
o m
a n
a c to
r i
to a c t
A le
a d
s to
th e
c re
a ti
o n
o f
a n
e g
a ti
v e
re la
ti o
n sh
ip to
a c to
r j
b y
a c to
r i
A c to r- le v e l d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
A c ti
v it
y
in th
e n
e tw
o rk
o f
V -r
e la
ti o
n sh
ip s
le a d
s to
a c ti
v it
y in
th e
n e tw
o rk
o f
n e g
a ti
v e
re la
ti o
n sh
ip s
i j
A
7 V
ic ti
m S p e c ifi c a tt ri b u ti o n e ff e c t v ic ti m
: A
V -r
e la
ti o
n sh
ip fr
o m
a c to
r i
to a c t
A a n
d a
P -r
e la
ti o
n sh
ip fr
o m
a c to
r j
to th
e sa
m e
a c t A
le a d
to th
e
c re
a ti
o n
o f
a n
e g
a ti
v e
re la
ti o
n sh
ip to
a c to
r j
b y
a c to
r i
T ri a d ic
d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
T h
e re
is a
te n
d e n
c y
fo r
m ix
e d
tr ip
le ts
fo rm
e d
a c ro
ss V
-, P
-, a n
d n
e g
a ti
v e
re la
ti o
n sh
ip s,
w h
e re
a P
-r e la
ti o
n sh
ip a n
d a
V -r
e la
ti o
n sh
ip le
a d
to a
n e g
a ti
v e
re la
ti o
n sh
ip
i j
A
8 O
b se
rv e r
O b se rv a ti o n
-v ia
-p e rp e tr a to r e ff e c t:
A P
-r e la
ti o
n sh
ip fr
o m
a c to
r j
to a c t
A ,
a n
d a
p o
si ti
v e
re la
ti o
n sh
ip fr
o m
a c to
r i
to a c to
r j
le a d
to th
e
c re
a ti
o n
o f
a n
O -r
e la
ti o
n sh
ip b
y a c to
r i
to a c t A
T ri a d ic
d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
T h
e re
is a
te n
d e n
c y
fo r
m ix
e d
tr ip
le ts
fo rm
e d
a c ro
ss p
o si
ti v
e ,
P -
a n
d
O -r
e la
ti o
n sh
ip s,
w h
e re
a p
o si
ti v
e re
la ti
o n
sh ip
a n
d a
P -r
e la
ti o
n sh
ip
le a d
to a n
O -r
e la
ti o
n sh
ip
i j
A
9 O
b se
rv e r
O b se rv a ti o n
-v ia
-v ic ti m
e ff e c t:
A V
-r e la
ti o
n sh
ip fr
o m
a c to
r j
to a c t A
,
a n
d a
p o
si ti
v e
re la
ti o
n sh
ip fr
o m
a c to
r i
to a c to
r j
le a d
s to
th e
c re
a ti
o n
o f
a n
O -r
e la
ti o
n sh
ip b
y a c to
r i
to a c t A
T ri a d ic
d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
T h
e re
is a
te n
d e n
c y
fo r
m ix
e d
tr ip
le ts
fo rm
e d
a c ro
ss p
o si
ti v
e ,
V -
a n
d
O -r
e la
ti o
n sh
ip s,
w h
e re
a p
o si
ti v
e re
la ti
o n
sh ip
a n
d a
V -r
e la
ti o
n sh
ip
le a d
to a n
O -r
e la
ti o
n sh
ip
i j
A
158 F. Zuber
123
Research on rationalization (e.g., Ashforth and Anand
2003; Bandura et al. 1996; Bandura 1999; Sykes and Matza
1957) has identified various techniques that are used by
perpetrators to retrospectively defend, or prospectively
enable unethical behavior. Techniques such as denial of
injury and denial of victims, social weighting, appeal to
higher loyalties, and obedience to authorities (Ashforth and
Anand 2003; Moore 2008; Sykes and Matza 1957) allow
perpetrators to negate the harm caused by their behavior, to
deny personal causality and controllability, and to construct
mitigating circumstances such that judgments of responsi-
bility can be avoided (Weiner 1995).
Baumeister et al. (1994) view these strategies as means for
perpetrators to avoid feelings of guilt. Without perceived
personal responsibility for an act of unethical behavior, per-
petrators can ‘‘disengage from moral self-sanctions’’ (Pillutla
2011, p. 356) in the form of guilt, and can view themselves as
moral persons. Guilt serves an inhibitory function (Tangney
et al. 2007, p. 354) and motivates corrective or reparative
reactions (Haidt 2003; Tangney et al. 2007). Conversely, its
absence enables further unethical behavior by the perpetrator.
Further unethical behavior is also facilitated as retrospective
rationalizations of initial acts can serve as blueprint for pro-
spective rationalizations of subsequent acts of unethical
behavior. Perpetrators’ tendency to engage in subsequent
unethical behavior corresponds to the following effect in the
social network framework:
Effect 1 Repetition effect: A P-relationship from actor i
to act A leads to the creation of a P-relationship to act B
by actor i.
Impact of Perpetrator’s Social Relationships on His
Reactions
The perpetrator’s appraisal of his initial act of unethical
behavior and the ensuing reaction also depends on his direct
and indirect social relationships to the victim. Feelings of
guilt are particularly likely to arise as a result of behavior
which causes harm to others (Baumeister et al. 1994;
Tangney 1992), and when there is a communal (positive)
relationship between the perpetrator and the affected others
(Baumeister et al. 1994; Haidt 2003). A positive relationship
to the victim implies that the perpetrator is likely to have an
empathic concern for the victim’s suffering (Baumeister
et al. 1994), which fosters feelings of guilt. Therefore, a pre-
existing positive relationship from the perpetrator to the
victim increases the likelihood that the perpetrator’s
appraisal process results in feelings of guilt, which inhibit
subsequent acts of unethical behavior. Beyond a direct
relationship, indirect positive relationships between perpe-
trator and victim, where they are connected through their
relationships to an intermediary actor, also impact theT a b le
1 c o
n ti
n u
e d
E ff
e c t
n o
.
R e la
te d
a c to
r
D e sc
ri p
ti o
n o
f e ff
e c t
D e sc
ri p
ti o
n o
f e ff
e c t
in so
c ia
l n
e tw
o rk
a n
a ly
si s
te rm
in o
lo g
y G
ra p
h ic
a l
p re
se n
ta ti
o n
1 0
O b
se rv
e r
Im it a ti o n /r e ta li a ti o n e ff e c t o b se rv e r:
A n
O -r
e la
ti o
n sh
ip fr
o m
a c to
r i
to
a c t A
le a d
s to
th e
c re
a ti
o n
o f
a P
-r e la
ti o
n sh
ip to
a c t B
b y
a c to
r i
A c to r- le v e l d e p e n d e n c y b e tw e e n tw o
-m o d e n e tw o rk s:
A c ti
v it
y in
th e
n e tw
o rk
o f
O -r
e la
ti o
n sh
ip s
le a d
s to
a c ti
v it
y in
th e
n e tw
o rk
o f
P -r
e la
ti o
n sh
ip s
i A B
1 1
O b
se rv
e r
S p e c ifi c a tt ri b u ti o n e ff e c t o b se rv e r:
A n
O -r
e la
ti o
n sh
ip fr
o m
a c to
r i
to
a c t A
, a n
d a
P -r
e la
ti o
n sh
ip fr
o m
a c to
r j
to th
e sa
m e
a c t A
le a d
to th
e
c re
a ti
o n
o f
a n
e g
a ti
v e
re la
ti o
n sh
ip to
a c to
r j
b y
a c to
r i
T ri a d ic
d e p e n d e n c y b e tw e e n o n e - a n d tw o -m
o d e n e tw o rk s:
T h
e re
is a
te n
d e n
c y
fo r
m ix
e d
tr ip
le ts
fo rm
e d
a c ro
ss O
-, P
-, a n
d n
e g
a ti
v e
re la
ti o
n sh
ip s,
w h
e re
a P
-r e la
ti o
n sh
ip a n
d a n
O -r
e la
ti o
n sh
ip le
a d
to a
n e g
a ti
v e
re la
ti o
n sh
ip
i j
A
S q u a re s
re p
re se
n t
a c ts
, c ir c le s
re p
re se
n t
a c to
rs . S o li d li n e s
re p
re se
n t
p o
si ti
v e
re la
ti o
n sh
ip s,
so li d li n e s w it h a m in u s si g n
n e x
t to
th e m
n e g
a ti
v e
re la
ti o
n sh
ip s,
d a sh e d li n e s
re p
re se
n t
P -r
e la
ti o
n sh
ip s
(p e rp
e tr
a to
rs to
a c ts
), d a sh e d -d o tt e d li n e s
V -r
e la
ti o
n sh
ip s
(v ic
ti m
s to
a c ts
), a n
d d o tt e d li n e s
O -r
e la
ti o
n sh
ip s
(o b
se rv
e rs
to a c ts
). B la c k
b o
ld ti
e s
a re
th o
se w
h ic
h a re
a ss
u m
e d
to
e x
is t
fi rs
t in
a g
iv e n
e ff
e c t,
su c h
th a t
th in
g re y
ti e s
a re
fo rm
e d
in re
a c ti
o n
to th
e e x
is te
n c e
o f b la c k
b o
ld ti
e s
Dynamic Social Network Perspective 159
123
perpetrator’s reaction. They can create feelings of related-
ness and empathy, but to a lesser extent than direct rela-
tionships, and accordingly have a weaker impact on the
likelihood that feelings of guilt arise (Baumeister et al.
1994).
Conversely, the existence of a negative relationship or,
to a lesser degree, the absence of a positive relationship,
between the victim and the perpetrator reduces empathic
concern, facilitates rationalization by the perpetrator, and
lowers the likelihood that feelings of guilt arise. When the
perpetrator perceives the victim to have ‘‘little in common’’
with him, and not to be related to him (Baumeister et al.
1994, p. 259), it is easier for him to believe that the victim
deserved the harm (denial of victims, Ashforth and Anand
2003; Sykes and Matza 1957). The following proposition
summarizes under which circumstances unethical behavior
is likely to spread through the perpetrator of the initial act:
Proposition 1 Unethical behavior is more likely to spread
through the perpetrator’s reaction when the perpetrator has
no direct and indirect positive pre-existing relationships, or
has a pre-existing negative relationship, to the victim,
compared to when the perpetrator has pre-existing direct or
indirect positive relationships to the victim.
This proposition can be linked to arguments of cohesion
in relation to actors’ direct relationships (Bond and Harri-
gan 2011, p. 203; Brass et al. 1998, p. 25). It suggests that
unethical behavior toward actors outside the organization,
such as suppliers or competitors, is more likely to lead to
subsequent unethical behavior by the perpetrator, com-
pared to unethical behavior toward actors inside the orga-
nization, because the perpetrator is more likely to have
positive direct relationships to other actors inside the
organization (higher cohesion) than to actors outside the
organization (lower cohesion).
Impact on Perpetrator’s Social Relationships
Negative relationships cannot only facilitate rationaliza-
tions, but can instead be created as a result of rationaliza-
tions. Rationalizations which denigrate the victim imply a
negative attitude toward the victim. Negative attitudes in
turn characterize negative relationships (Labianca and Brass
2006). Hence, the perpetrator is likely to create a negative
relationship to the victim of the initial act of unethical
behavior because of the use of such rationalizations. This
argument is reflected in the following social network effect:
Effect 2 Retrospective rationalization effect: A P-rela-
tionship from actor i to act A leads to the creation of a
negative relationship to actor j by actor i.
When the rationalization employed involves the per-
ception that ‘‘the victim is an interchangeable member of a
social category’’ (Ashforth et al. 2008, p. 20) whose
members deserve the harm, negative relationships can also
be created from the perpetrator to actors perceived as
similar to the victim. Brass et al. (1998) have argued that
negative relationships are positively related to unethical
behavior, because negative relationships ‘‘do not include
the constraining effect of empathy’’ (p. 18). Accordingly, a
negative relationship created in the aftermath of an act of
unethical behavior can enable the prospective rationaliza-
tion and commission of a subsequent act. This results in an
indirect pathway for the spread of unethical behavior
through the perpetrator, in which an initial act of unethical
behavior leads to the creation of negative relationships
which in turn lead to subsequent unethical behavior. In the
social network framework, this pathway is captured by the
following effect:
Effect 3 Prospective rationalization effect: A P-rela-
tionship from actor i to act A, and a negative relationship
from actor i to actor j lead to the creation of a P-rela-
tionship to act B by actor i.
To sum up, unethical behavior can spread through per-
petrators because they use rationalizations to avoid feelings
of guilt, which enables further unethical behavior and may
lead to negative relationships.
Victim’s Perspective and Reactions
Perception of Being a Victim
Unethical behavior can only spread through the reaction of
victims if there are actors who perceive themselves to be
victims. Some forms of unethical behavior cause obvious
harm to an actor, such as verbal or physical mistreatment of
others. The literature on workplace aggression, workplace
revenge, and retaliatory behavior (e.g., Aquino et al. 2001,
2006; Bies and Tripp 2004; Skarlicki and Folger 1997,
2004; Tripp et al. 2007) extensively investigates victims’
reactions to interpersonal forms of unethical behavior.
With this type of behavior, the targeted actor is most likely
to be aware of the unethical behavior and to perceive
himself as victim. With other forms of unethical behavior,
by contrast, it is less clear whether harm is caused to an
individual actor who could perceive himself as victim. For
example, an employee who submits claims for his private
expenses or misreports the hours worked causes damage to
the organization. It is difficult, however, to ascertain,
which, if any, representative of the organization might
perceive himself as victim of this behavior. Acts which do
not cause detectable and direct harm to specific individual
actors have thus a lower potential for spread t
hrough reactions of victims as set out in the following
proposition:
160 F. Zuber
123
Proposition 2 Unethical behavior is more likely to
spread through reactions of a victim when there is direct
and detectable damage caused to a specific individual
victim, compared to situations where the negative conse-
quences of the act are less visible and/or do not affect a
specific individual.
Individual actors can also perceive themselves as vic-
tims when no harm has directly been inflicted upon them.
For example, consider customers who fraudulently return
purchased products. The employee handling the product
return may feel personally affected by such unethical
behavior, even though the damage is the organization’s
rather than his. Social identity theory (Tajfel and Turner
1979) holds that an individual personally experiences
successes and failures of the social aggregate with which
he identifies (Ashforth and Mael 1989). By this argument,
individuals are likely to perceive harm caused to their
organization as if they were personally affected and see
themselves as victims if they identify with the organiza-
tion. To the extent that organization members perceive
themselves as victims, they will react accordingly, and
unethical behavior can spread through their reactions, as
summarized in the following proposition:
Proposition 3 Social identification with a group can lead
individual actors to perceive themselves as victims of an
act of unethical behavior even when this act does not
directly harm them, and this perception in turn can lead to
the spread of unethical behavior through reactions of the
victims.
Attributions and Retaliation
While actors tend to bias their causal attributions for their
own actions toward situational and non-controllable factors
to avoid responsibility (Martinko et al. 2006, p. 138), they
tend to ‘‘minimize the causal effect of the situation and
overestimate the causal contribution of the individual’’
(Weiner 1995, p. 253) when assessing others’ behavior,
and are therefore more likely to hold another actor per-
sonally responsible. This fundamental attribution error or
actor-observer bias has been confirmed in numerous
empirical studies (Martinko et al. 2006; Weiner 1995). Due
to this bias, victims are likely to attribute personal
responsibility to the perpetrator of unethical behavior.
Attribution of responsibility in turn results in anger toward
the perpetrator (Weiner 1995), and motivates retaliatory
actions against the perpetrator (Haidt 2003; Weiner 1995).
Research on workplace revenge (e.g., Aquino et al.
2001, 2006; Bies and Tripp 2004; Kim et al. 2008; Tripp
et al. 2007) and retaliatory behavior (e.g., Skarlicki and
Folger 1997; Skarlicki et al. 1999, 2004) has demonstrated
how victims react ‘‘to some perceived harm or wrongdoing
by another party’’ by actions ‘‘which [are] intended to
inflict damage, injury, discomfort, or punishment on the
party judged responsible’’ (Aquino et al. 2001, p. 53).
According to this perspective, victims may retaliate for an
act unethical behavior by a subsequent act of unethical
behavior against the (original) perpetrator, as indicted by
the following effect:
Effect 4 Specific retaliation effect victim: A P-relation-
ship from actor j to act A, a V-relationship from actor i to
this act A, and a P-relationship from actor i to act B leads
to the creation of a V-relationship by actor j to act B.
Whether direct retaliation by the victim against the
perpetrator is possible depends on the relative social
position of these two actors. If the victim is less powerful
than the perpetrator, the victim may direct his retaliatory
action against another target with the intention to harm the
perpetrator (Skarlicki and Folger 2004). For example, if an
employee sees himself as the victim of sexual harassment
by his manager, he may react instead by stealing supplies,
knowing that his manager will be held responsible for any
missing supplies. When the victim cannot even indirectly
harm the perpetrator, the retaliatory act may also be carried
out against any other innocent, but accessible actor,
including actors outside the organization (see Hoobler and
Brass 2006). In the workplace aggression literature, this
phenomenon is described as displaced aggression. In the
social network framework, this translates into the following
effect:
Effect 5 General retaliation effect victim: A V-relation-
ship from actor i to act A leads to the creation of a
P-relationship by actor i to act B.
This effect can be considered a generalization of the
specific retaliation effect described above, because it does
not specify which actor is likely to be the victim of the
subsequent act in contrast to the specific effect.
It is also possible that the victim holds an actor other
than the perpetrator (co-)responsible for the unethical
behavior, and retaliates against this other actor. Research
on abusive supervision suggests that victims at least partly
hold the organization responsible for the perpetrator’s
behavior and retaliate by engaging in unethical behavior
which causes harm to the organization (Bowling and
Michel 2011; Shoss et al. 2013; Tepper et al. 2008). Sup-
porting this argument, meta-analytic research has identified
positive correlations between workplace harassment expe-
rienced by victims and their counterproductive workplace
behavior (Bowling and Beehr 2006), and between aggres-
sion by outsiders and employees’ organizational deviance
(Hershcovis and Barling 2010).
Dynamic Social Network Perspective 161
123
Impact on Victim’s Social Relationships
The involvement in unethical behavior as a victim can also
affect the victim’s interpersonal relationships. The attribution of
responsibility for an act of unethical behavior to another actor
leads to the emotion of anger. ‘‘Negative emotions such as
anger are likely to manifest in negative attitudes’’ (Douglas
et al. 2008, p. 430), and negative attitudes in turn characterize
negative relationships (Labianca and Brass 2006). Therefore,
the victim’s attribution of responsibility for an act of unethical
behavior to the perpetrator (or to another actor) can lead to a
negative relationship from the victim to the perpetrator (or other
actor held responsible for the act). The creation of a negative
relationship due to attributions of responsibility is reflected in
the following effect in the social network framework:
Effect 6 General attribution effect victim: A V-relation-
ship from an actor i to act A leads to the creation of a
negative relationship to actor j by actor i.
While the victim can attribute the act of unethical
behavior to any other actor, it is most likely that it is
attributed to the perpetrator, and therefore, that a negative
relationship to the perpetrator arises, as represented in the
following effect:
Effect 7 Specific attribution effect victim: A V-relation-
ship from actor i to act A and a P-relationship from actor j
to the same act A lead to the creation of a negative rela-
tionship to actor j by actor i.
In sum, unethical behavior can spread through victims’
reactions to unethical behavior because of direct, indirect,
or displaced retaliatory acts. Actors not only may perceive
themselves as victims when harm is caused directly to
them, but also when they identify with the collective to
which the harm is caused.
Observer’s Perspective and Reactions
Observers’ Social Relationships as Conduits
In order for actors to become observers of, and react to an
act of unethical behavior, their ‘‘awareness must be high
enough to instigate a cognitive appraisal’’, even though
they may not ‘‘necessarily directly observe the […] behavior’’ (Treviño 1992, p. 650). Some forms of unethical
behavior in organizations are rather covert and difficult to
observe for others, such as abusing confidential informa-
tion or insider trading, and therefore are less likely to be
noticed by actors other than the perpetrator himself. The
possibility to observe another actor’s behavior depends not
only on the characteristics of the act itself, but also on the
interaction between the perpetrator and other actors.
Interactions provide the opportunity to observe or learn
about others’ behavior, and are likely to take place when
there is a positive interpersonal relationship. The more
positive relationships a perpetrator has to other actors, the
higher therefore the likelihood that other actors observe the
perpetrator’s behavior (Venkataramani and Dalal 2007)
and may subsequently also commit acts of unethical
behavior. This leads to the following proposition:
Proposition 4 The higher the number of positive rela-
tionships of the perpetrator, expressed as degree centrality,
the higher the likelihood that his act of unethical behavior
is observed, and that, by consequence, unethical behavior
spreads through observers’ reactions.
If the perpetrator is located in a cohesive part of the
network of positive relationships, characterized by high
density of (direct) relationships between actors inside and
typically fewer ties with actors outside this part of the
network (Borgatti and Halgin 2011, p. 427), his unethical
behavior is thus more likely to be observed. In the social
network framework, actors’ tendency to observe the
unethical behavior of other actors to whom they have a
positive relationship translates into the following effect:
Effect 8 Observation-via-perpetrator effect: A P-rela-
tionship from actor j to act A, and a positive relationship
from actor i to actor j lead to the creation of an O-rela-
tionship by actor i to act A.
Actors can also become aware of the act of unethical
behavior by observing the harm caused to the victim when
they have a (positive) relationship to the victim, and
interact with the victim. Furthermore, victims may also
engage in explicit social rumination where they ‘‘and
observers try to make sense of an event by discussing it’’
(Pinto et al. 2008, p. 693). The more positive relationships
a victim has, the higher the likelihood that he engages in
social rumination with other actors, who thus become
observers of the act of unethical behavior. Proposition 5
follows from these arguments:
Proposition 5 The higher the number of positive rela-
tionships of the victim, expressed as degree centrality, the
higher the likelihood that the act of unethical behavior is
observed directly or indirectly, through social rumination,
by additional actors, and that, by consequence, unethical
behavior spreads through observers’ reactions.
Similar to proposition 4 above, if the victim is located in
a cohesive subgroup in the network of positive relation-
ships, the likelihood that other actors become aware of the
unethical behavior due to their relationship with the victim
is higher. The tendency for actors to become observers of
an act of unethical behavior when they have a positive
relationship to the victim is reflected by the following
effect:
162 F. Zuber
123
Effect 9 Observation-via-victim effect: A V-relationship
from actor j to act A, and a positive relationship from actor
i to actor j leads to the creation of an O-relationship by
actor i to act A.
Impact of Observer’s Social Relationships on His
Reactions
While the perpetrator’s and the victim’s perspectives are
defined by their commission of, and suffering from the act
respectively, observers are less immediately affected by the
act, such that their perspective can either be more alike to
the victim’s, or to the perpetrator’s. Both possibilities have
been explored in the literature. On the one hand, work on
deonance theory (e.g., Folger 2012; O’Reilly and Aquino
2011; Skarlicki and Folger 2004; Skarlicki and Kulik 2004;
Umphress et al. 2013) has shown that third parties react
with outrage or moral anger to unjust treatment suffered by
others. Empathy enables the observer to take the victim’s
perspective and share the victim’s emotions (Tangney et al.
2007, p. 362), such that his reaction is likely to be similar
to the victim’s and can include retaliatory actions against
the perpetrator. Empathy in turn is fostered by a positive
relationship between the observer and the victim (Brass
et al. 1998).
On the other hand, research has revealed that observers
of an act of unethical behavior can experience guilt for a
perpetrator’s act (Fortune and Newby-Clark 2008; Gino
et al. 2009; Tangney et al. 2007). In particular, observers
can experience vicarious guilt when they have a personal
relationship to the perpetrator (Lickel et al. 2005; Tangney
et al. 2007). This finding suggests that an observer’s
appraisal of the act is similar to the perpetrator’s when
there is a (positive) relationship between the observer and
the perpetrator.
Indirect relationships between the observer and the
perpetrator or the victim may also have an impact on the
observer’s reaction, albeit less so than direct relationships.
Indirect relationships between two actors can indicate that
they belong to the same social group, since groups are
characterized by mutual connectedness and high density
(Scott 2000). A shared social identity with the perpetrator
based on group membership has been shown to elicit
feelings of guilt in the observer (Tangney et al. 2007).
Similarly, indirect relationships to the victim can lead to
increased empathy of the observer, and reactions alike to
the victim’s. These arguments lead to the following
proposition:
Proposition 6 The higher (lower) the number of direct
and indirect positive relationships between the observer of
an act of unethical behavior and the perpetrator relative to
the number of direct and indirect positive relationships
between the observer and the victim, the higher (lower) the
likelihood that the observer’s reactions are similar to the
perpetrator’s reactions, and the lower (higher) the likeli-
hood they are similar to the victim’s.
Reactions Similar to the Perpetrator’s
When the observer’s perspective is similar to the perpe-
trator’s, there are also similar biases and underlying
motivations involved in the appraisal of the act of unethical
behavior. First, the observer is motivated to avoid feelings
of guilt over the act. Just as a perpetrator’s feelings of guilt
arise once he has assigned responsibility for the act to
himself, Lickel et al. (2005, p. 153) argue that vicarious
guilt is experienced by the observer if he has previously
assigned responsibility for the act to the perpetrator. To
avoid feelings of guilt, the observer will employ the same
rationalization techniques as the perpetrator to avoid the
conclusion that the perpetrator is responsible for the act of
unethical behavior. Consistent with this idea, Gino and
Galinsky (2012) have found that observers who felt con-
nected to a perpetrator engaged in ‘‘vicarious justification’’
of the perpetrator’s act, which in turn led them to engage in
subsequent unethical behavior themselves.
In the absence of vicarious guilt, processes of social
learning (Bandura 1973) can instead shape the observer’s
subsequent behavior (e.g., O’Leary-Kelly et al. 1996; Rob-
inson and O’Leary-Kelly 1998). Social learning theory
emphasizes the importance of models from which certain
behaviors can be learnt. While leaders are particularly
attractive as ethical role models due to their social status and
power (Brown and Treviño 2006, p. 597), employees over-
whelmingly identified colleagues with whom they interacted
personally and frequently as ethical role models in an inter-
view study by Weaver et al. (2005). This finding underscores
the importance of the personal relationship and interaction
between a perpetrator and an observer in influencing the
observer’s behavior. The following effect reflects observers’
tendency to engage in unethical behavior:
Effect 10 Imitation effect: An O-relationship from actor i
to act A leads to the creation of a P-relationship to act B
by actor i.
This effect, together with the observation-via-perpe-
trator effect reflects that an actor who has a positive rela-
tionship to the perpetrator is likely to observe the unethical
behavior, and to emulate it. Investigations of observers’
behavior in relation to their peers’ behavior often focus on
the same or very similar kinds of unethical behavior (e.g.,
academic dishonesty in McCabe et al. 2006; O’Fallon and
Butterfield 2012; or antisocial behavior in Robinson and
O’Leary-Kelly 1998). However, Keizer et al. (2008) have
demonstrated in their field experiments on cross-norm
Dynamic Social Network Perspective 163
123
inhibition that observing the violation of one norm (e.g.,
anti-graffiti norm; prohibition of locking bicycles to a
fence) can lead to violation of another norm (e.g., anti-
littering norm; prohibition to use an entrance). This sug-
gests that one type of unethical behavior can also encroach
to other types of unethical behavior.
To the extent that an observer shares the same role as the
perpetrator and faces similar situations, he is more likely to
have the opportunity to engage in the same kind of
unethical behavior as the perpetrator. From a social net-
work perspective, an actor’s role, or position in a social
system, is characterized by the pattern of his social rela-
tionships (Scott 2000). When two actors share the same
role in the social system, they are considered regularly
equivalent (Scott 2000). Regular equivalence refers to the
idea that ‘‘units are equivalent if they link in equivalent
ways to other units that are also equivalent’’ (Doreian et al.
2005, p. 80). This argument leads to the following
proposition:
Proposition 7 When an observer is regularly equivalent
to the perpetrator in the network of positive relationships,
the observer is more likely to subsequently engage in the
same type of unethical behavior as the perpetrator, com-
pared to an observer who is not regularly equivalent to the
perpetrator.
Reactions Similar to the Victim’s
The literature on third party’s reactions to injustice and
mistreatment (e.g., Folger and Skarlicki 2004; O’Reilly and
Aquino 2011; Skarlicki and Folger 2004; Umphress et al.
2013) shows that actors can be motivated to react with
retaliatory behavior against the perpetrator, or compensa-
tory behavior toward the victim upon witnessing unethical
behavior. While other reactions such as whistle-blowing
(Gundlach et al. 2003) or helping the victim (O’Reilly and
Aquino 2011) are possible, some research indicates that
observers are more likely to punish the perpetrator than to
help the victim (Skarlicki and Kulik 2004, p. 206). Reac-
tions against the perpetrator can be motivated by ‘‘deontic
anger’’ (Folger and Skarlicki 2004) which is triggered
when the observer attributes responsibility for violating
moral norms to the perpetrator. Following the arguments
presented in relation to the victim’s reaction, the attribution
of responsibility can lead to a negative relationship
between the observer and the perpetrator, as reflected in the
following effect:
Effect 11 Specific attribution effect observer: An
O-relationship from actor i to act A, and a P-relationship
from actor j to the same act A lead to the creation of a
negative relationship to actor j by actor i.
Deontic retaliatory reactions of the observer can also be
represented by effect 10 described earlier, which holds that
an O-relationship from an actor to an initial act leads to the
creation of a P-relationship by this actor to a subsequent
act. Thus, effect 10 can be re-labeled as imitation/retalia-
tion effect observer. Cases where the observer engages in
retaliatory unethical behavior because of his positive
relationship with the victim are reflected in the social
network framework by a combination of the observation-
via-victim effect and this imitation/retaliation effect.
To recapitulate, unethical behavior can spread through
observers when they react by retaliating like victims, or
when they imitate the perpetrator’s behavior in function of
their relationships to victim and perpetrator. The observer’s
perspective completes the discussion of reaction tendencies
after an initial act of unethical behavior which can lead to
subsequent acts of unethical behavior. I have shown how
reaction tendencies of perpetrators, victims, and observers
can be translated into effects in the dynamic actor-oriented
framework. These effects define which changes actors are
likely to make in their relationships to acts and actors in
reaction to their existing relationships to acts of unethical
behavior and to actors. The spread of unethical behavior,
then, corresponds to an increase in the number of rela-
tionships between acts and actors: More actors commit acts
of unethical behavior (P-relationships), which in turn can
lead to ties from victims and observers to committed acts
(V- and O-relationships), such that the number of actors
having relationships to acts of unethical behavior increases
over time. Each actor who has at least one relationship to
an act of unethical behavior is a potential propagator of
unethical behavior through his reaction to this experience.
Discussion
This paper has argued that unethical behavior spreads when
the perpetrator, victim, and/or observer commit subsequent
acts of unethical behavior in reaction to their involvement
in an initial act. Focusing on individual, but socially con-
nected actors, processes of social cognition, affective
reactions, and ensuing behavioral reactions, a dynamic
actor-oriented social network framework has been devel-
oped to examine the spread of unethical behavior. In this
theoretical framework, the social relationships of actors
influence their awareness of acts of unethical behavior,
impact their appraisal of and behavioral reaction to acts,
and can be affected by unethical behavior. While this
framework’s focus on the spread of unethical behavior may
appear to suggest that initial acts of unethical behavior
almost inevitably lead to subsequent acts, the framework
‘‘is meant to be probabilistic, suggesting [reaction]
164 F. Zuber
123
tendencies, not deterministic’’ (Ashforth and Anand 2003,
p. 41). This point is also reflected in the stochastic nature of
the dynamic social network models which serve as basis
for the proposed framework.
This paper contributes to the literature by offering a
theoretical framework in which insights from recent
behavioral business ethics research and the social network
perspective introduced by Brass et al. (1998) can be
combined to identify mechanisms of the spread of unethi-
cal behavior. By applying the social network perspective,
individual reactions studied in behavioral business ethics
research can be examined in the context of social rela-
tionships; using insights from behavioral business ethics
research, a detailed account of the ‘‘generative principles’’
(Snijders et al. 2013, p. 266) in social networks can be
provided. This approach follows the idea of Brass et al.
(1998, p. 27) who saw the social network perspective on
unethical behavior ‘‘as a perspective to be combined with
previous research.’’
The social network perspective proposed in this paper
differs from prominent accounts for the spread or contagion
of unethical behavior (e.g., Ashforth and Anand 2003; Brief
et al. 2001; Palmer 2008) because the focus is not on col-
lective acts and processes at the group level, but rather on
individual acts, and processes at the individual level in the
context of individuals’ social relationships. As a result, this
perspective uncovers some previously underexplored
aspects of the spread of unethical behavior. For example, it
highlights how unethical behavior can engender indirect
negative consequences for the organization due to the neg-
ative relationships arising as a result of perpetrators’, vic-
tims’ or observers’ appraisals of unethical behavior. The
quality of the interpersonal relationships within the organi-
zation impacts the degree to which members are affectively
committed to their organization, such that negative rela-
tionships decrease the organizational commitment (Labianca
and Brass 2006). When the number of negative relationships
increases subsequent to acts of unethical behavior, actors’
affective commitment is therefore likely to decrease.
Affective commitment—‘‘the emotional attachment to,
identification with the organization, and involvement in the
organization’’ (Meyer et al. 2002, p. 21)—has been found to
positively correlate with attendance, performance, and
organizational citizenship behavior (Meyer et al. 2002), and
negatively with organizational deviance (Liao et al. 2004;
Tepper et al. 2008). Negative relationships arising in the
wake of unethical behavior can thus lead to various negative
outcomes, including increased deviance and further unethi-
cal behavior.
The emergence of negative relationships in the wake of
unethical behavior also connects research on the spread of
unethical behavior to literature which examines how rela-
tionships and trust damaged by negative events such as
unethical behavior can be repaired (e.g., Dirks et al. 2009;
Ferrin et al. 2007; Gillespie and Dietz 2009; Ren and Gray
2009; Tomlinson and Mayer 2009). This research provides
a host of insights into how the indirect negative impact of
unethical behavior due to negative relationships may be
reduced through the use of social accounts and rituals, or
substantive actions such as restitution to the victim (Dirks
et al. 2009).
The perspective proposed here also calls attention to
how unethical behavior can spread inside an organization
when members react as victims or observers of unethical
behavior committed by external actors. As as members
have relationships both inside and outside the organization,
‘‘the consideration of relationships [is] not limited to the
boundaries of an organization’’ (Brass et al. 1998, p. 28). In
particular, boundary-spanning members have relationships
to representatives of different stakeholders of the organi-
zation, such as clients, suppliers, or regulatory authorities.
Barling et al. (2009, p. 684) for example report that a
substantial share of the aggression suffered by employees
in the workplace is committed by outsiders of the organi-
zation such as customers.
Stopping the Spread of Unethical Behavior
The analysis of the spread of unethical behavior—almost
necessarily—entails the important question of how the
spread of unethical behavior in organizations may be hal-
ted. Along the lines of Palmer’s (2012) distinction between
measures for curbing wrongdoing by others, and curbing
one’s own wrongdoing, the framework proposed here
points to two possible areas for intervention. First, those
responsible for leading and managing organizations can
create an environment in which, for the members of the
organization, engaging in further unethical behavior
becomes a less likely reaction to an initial act of unethical
behavior compared to other reactions. Second, the role of
social cognitive processes in determining an individual’s
reaction to unethical behavior suggests that each individ-
ual’s awareness of these processes and inherent biases—
including those arising from their relationships to others
involved in an act of unethical behavior—could enable
them to more consciously control their reactions, and steer
away from further unethical behavior.
Regarding the first area, certain (perceived) character-
istics of organizational environments that are intimately
linked to justice concepts have been highlighted in prior
research as important factors in shaping reactions to
unethical behavior. On the one hand, the role of procedural
justice climate (Aquino et al. 2006), of beliefs in the
organizational justice system (O’Reilly and Aquino 2011),
and of retributive justice and punishments (Treviño 1992)
has been examined. This research suggests that credible
Dynamic Social Network Perspective 165
123
formal mechanisms for enforcing justice and punishing the
perpetrator can serve as an outlet for victim’s and obser-
ver’s anger against a perpetrator, and prevent unethical
behavior arising from retaliatory motivations (Tripp et al.
2007). Thus, a credible disciplinary system in organiza-
tions may counteract retaliatory effects identified in this
paper (see effects 4, 5, and 10). Furthermore, deterrence
theory posits that sanctioning a perpetrator for unethical
behavior deters the punished behavior both in the perpe-
trator as well as in observers, especially if the punished
perpetrator is perceived to be similar by the observer
(Treviño 1992). Therefore, formal punishment could pre-
vent the repetition effect for perpetrators (effect 1) and the
imitation effect for observers (effect 10).
Victims and observers, however, can only be expected
to rely on the organizational justice system to take care of
the act of unethical behavior if the act of unethical behavior
is known to a representative of the organization who has
the authority to start disciplinary proceedings. Therefore, it
is also important for halting the spread of unethical
behavior that organizations establish channels through
which unethical behavior can be reported to competent
persons within the organization who can take the necessary
actions as suggested by literature on whistle-blowing (e.g.,
Mesmer-Magnus and Viswesvaran 2005; Miceli et al.
2009).
On the other hand, the restorative justice perspective
highlights another set of organizational characteristics than
can help to prevent the spread of unethical behavior.
Recognizing ‘‘how unethical behavior can undermine
important moral dimensions of relationships in organiza-
tions’’ (Goodstein and Butterfield 2010, p. 453), this per-
spective suggests creating ‘‘a workplace context supporting
the restoration of relationships for the offender, the victim,
and others in the organization’’ (Goodstein and Butterfield
2010, p. 462). Similar to research forgiveness in organi-
zations (e.g., Fehr and Gelfand 2012; Palanski 2012), the
importance of ‘‘values such as compassion, collective
mercy, and hope’’ (Goodstein and Butterfield 2010, p. 462)
is emphasized.
The restorative perspective proposes that perpetrators,
motivated by feelings of guilt, can acknowledge their
wrongdoing, accept responsibility, and make amends. Such
a reaction by the perpetrator can be expected to preempt
retaliatory reactions by the victim and/or observers (see
effects 4, 5, and 10). Making amends also is likely to
prevent the perpetrator from engaging in further unethical
behavior, because it represents at the same time ‘‘a process
of self-forgiveness and reconciliation that can help
offenders rebuild their personal integrity’’ (Goodstein and
Butterfield 2010, p. 465). The notion of self-forgiveness
and reconciliation with others has also been linked to
spiritual rituals of confession (Murray-Swank et al. 2007),
and experimental evidence shows that confession after
committing unethical behavior reduced subsequent uneth-
ical behavior (Ayal and Gino 2012). 3
Self-forgiveness and
reconciliation by the perpetrator could therefore prevent
repetition and rationalization effects (see effects 1–3).
The victim, in turn, can extend forgiveness to, and/or
reconcile with the perpetrator, instead of retaliating against
the perpetrator. Forgiveness and reconciliation can ‘‘free
the future from the impact of past wrongs’’ (Goodstein and
Butterfield 2010, p. 460) and may prevent the creation of
negative relationships due to attributions of responsibility
by victims (see effects 6 and 7). Observers of unethical
behavior can provide the perpetrator the opportunity to be
re-integrated into the community (Goodstein and Butter-
field 2010). Reintegration may be an alternative reaction to
creating negative relationships, such that attribution effect
for observers (see effect 11) can be avoided
In the proposed social network framework, forgiveness
can not only be interpreted with respect to interpersonal
relationships, but could also be conceptualized as the
deletion of the relationship from the victim, observer, or
perpetrator (self-forgiveness) to the act of unethical
behavior. Forgiveness would then amount to relinquishing
the cognitive connection to the act of unethical behavior,
such that this act no longer impacts the actor’s behavior in
the future. Reconciliation and re-integration into the com-
munity in turn can be represented in this framework as
either deleting negative interpersonal relationships created
in the aftermath of unethical behavior, or as preventing the
their creation in the first place.
Regarding the second area of intervention related to pro-
cesses of social cognition, behavioral business ethics
researchers have made a range of recommendations for
improving individuals’ ethical behavior. These recommenda-
tions generally aim at making individuals aware of the psy-
chological and cognitive processes, their undesired side-
effects, and (unconscious) biases affecting (un)ethical behav-
ior, and at devising strategies to limit the impact of such side-
effects and biases (e.g., Banaji et al. 2003; Bazerman and
Tenbrunsel 2011; Tenbrunsel et al. 2010). Such recommen-
dations, however, may be limited in their practicability: Being
aware of the psychological and cognitive processes that are
ongoing in one’s mind and the application of bias-limiting
strategies appears to require individuals to be in a ‘‘hyper-
rational state’’ (Palmer 2012, p. 278), in which they are con-
tinually and consciously monitoring their thoughts and emo-
tions. In addition, Palmer (2012, p. 278) argues that strategies
proposed to address cognitive limitations and biases
3 They also note, however, that confession can increase rather than
reduce unethical behavior in the longer run because perpetrators know
that they will be able to restore their moral self-concept after
unethical behavior (Ayal and Gino 2012, pp. 156–157).
166 F. Zuber
123
essentially ask individuals to overcome tendencies that are
deeply engrained into the functioning of the human mind.
Thus, stopping the spread of unethical behavior by intervening
at the level of actors’ social cognitive processes may still be a
rather challenging endeavor in the current state of knowledge.
Limitations and Future Research
I have proposed a theoretical framework for examining the
spread of unethical behavior using a dynamic actor-oriented
social network perspective, rather than a fully specified formal
social network model. A major area for future research is thus
the development of a fully specified formal model. Several
requirements implied by the framework proposed here need
careful consideration in the formal specification of a sto-
chastic actor-oriented model for the multiplex dynamics two-
mode and one-mode networks. 4
Most importantly, an obser-
ver’s and a victim’s relationship to an act of unethical
behavior can only be created once the perpetrator has created a
relationship to this act, i.e., has committed it. This logical
sequence implies that a formal model has to incorporate
restrictions on the possible sequence of the creation of certain
relationships. This feature cannot yet be represented in the
specification of stochastic actor-oriented models for the
multiplex dynamics two-mode and one-mode networks cur-
rently proposed by Snijders et al. (2013).
Further, a formal specification has to include a basic
tendency to create relationships to initial acts of unethical
behavior, i.e., relationships in the two-mode network that
are the starting point for the creation subsequent relation-
ships to further acts of unethical behavior and are not
themselves based on previous relationships to acts. For-
mally, this can be achieved by including an outdegree
effect that ‘‘represents the basic tendency to have ties at
all’’ (Snijders et al. 2010, p. 47). In addition to the ten-
dencies to create relationships, the formal specification also
has to account for tendencies to delete ties in order not to
represent ever-growing networks. In stochastic actor-ori-
ented models for dynamics of one-mode and two-mode
both creation and termination of relationships is possible
(Snijders et al. 2013, p. 266), and can be formally repre-
sented by effects with a negative sign where a relationship
is terminated (or not formed) in response to a specific
constellation in the network. 5
In the context of this paper,
for example, termination of relationships to acts of uneth-
ical behavior could represent forgiveness as outlined in the
discussion of stopping the spread of unethical behavior. As
further examples, the termination of positive interpersonal
relationships could be introduced as a consequence to
involvement in acts of unethical behavior, and the termi-
nation of negative interpersonal relationships as a result of
reconciliation.
The theoretical framework proposed in this paper can
serve as a stepping stone toward simulation approaches for
modeling the dynamics of unethical behavior, as proposed
by Moore (2009, p. 61). Once the model is formally
specified as outlined above, computer simulations of the
spread of unethical behavior in social networks could be
carried out using the RSiena package (Ripley et al. 2013) in
the statistical system R (R Development Core Team 2012).
Simulation appears particularly appealing option for future
research as the challenges in collecting empirical data that
would allow to empirically test a fully specified model
based on the framework proposed in this paper appear quite
demanding: Testing would require longitudinal data about
experiences as perpetrators, victims, and observers of
unethical behavior for a group of individuals, as well as
data about their interpersonal relationships. The well-
known difficulties of collecting data about unethical
behavior (see e.g., Treviño and Weaver 2003, Chap. 11) are
compounded by the requirement to collect such data in
non-anonymous form for a group of persons and for mul-
tiple points in time (e.g., Moore 2009). In addition, the
collection of longitudinal data about interpersonal rela-
tionships in itself can already be challenging (Ahuja et al.
2012; Marsden 2011).
The framework proposed in this paper has several lim-
itations, which imply, at the same time, opportunities for
future research. I have focused on acts of unethical
behavior committed by individual actors. Future research
may extend the proposed framework by considering how
several perpetrators jointly engage in an act of unethical
behavior, and the conditions under which they are likely to
do so (e.g., positive mutual relationships and individual
involvement previous acts of unethical behavior). In formal
stochastic actor-oriented models, simultaneous coordinated
actions by individual actors can currently not be repre-
sented (Snijders et al. 2010). Also, the proposed actor-
oriented perspective views individuals as actors, and does
not consider organizations themselves as actors. This view
is based on the idea that ‘‘firm behavior is necessarily
underpinned by the actions of individuals’’ (Moore 2009,
p. 37), as ‘‘individuals [are] acting as agents on behalf of
their organization’’ (Ashforth et al. 2008, p. 673).
The analysis proposed in this paper further focuses on
the individuals, their relationships, and their reactions, but
does not address dynamics at the group or organizational
4 I thank an anonymous reviewer for highlighting these requirements
for the specification of a formal model. 5
For example, Snijders et al. (2013, p. 272) report a negative
outdegree popularity effect in friendship and advice networks,
meaning that an actor’s current number of outgoing relationships in
these networks negatively impacts the probability that this actor
retains existing or receives new incoming relationships, and thus
conversely increases the probability that existing incoming relation-
ships are terminated (see also Snijders et al. 2013, p. 271).
Dynamic Social Network Perspective 167
123
level. At the organizational or macro-level, future research
could also examine network characteristics, such as net-
work density, centralization, structural holes, and clusters,
and cliques of the interpersonal networks and their impact
on the spread of unethical behavior. As such macro-level
network characteristics emerge as a result of the process
taking place at the micro level in the actor-oriented per-
spective on network dynamics applied in this paper, the
impact of unethical behavior on the macro-level charac-
teristics could also be explored (see Snijders and Steglich
2013, for a detailed discussion).
While I have examined how social relationships of the
actors involved in the initial act impact the likelihood that
subsequent unethical behavior is committed, individual-
level factors have been shown to influence actors’ reactions
to unethical behavior as well. O’Reilly and Aquino (2011)
suggest that moral identity and beliefs in the organizational
justice system impact observers’ reactions to unethical
behavior, and Aquino et al. (2006) found that victims’
perceptions of the procedural justice climate in an orga-
nization moderate the impact of other variables on the
likelihood of revenge, retaliation, and reconciliation in
reaction to workplace offenses. These findings suggest that
it may be worthwhile to investigate how individual-level
characteristics impact, on the one hand, the reaction pro-
pensities of an actor when being perpetrator, observer, and
victim, and, on the other hand, the likelihood to become
perpetrator, victim or observer, of an act of unethical
behavior in the first place. 6
In stochastic actor-oriented
models, the impact of such individual-level factors, or actor
attributes, can be modeled by including them as covariates
and allowing for interaction effects in the model, such that
the strength of an effect depends on an actor attribute
(Snijders et al. 2010). For example, an actor’s hostile
attribution style (Aquino et al. 2004) could increase the
probability that an actor perceives himself as victim, and
could also interact positively with the retaliation effect
proposed in the current framework.
Practical Implications
The analysis in this paper implies that organizations should
consider the likelihood that particular types of unethical
behavior spread once an initial act has occurred when
assessing the risks related to unethical behavior. Such risk
assessments are recommended in the United States Sen-
tencing Commission’s Guidelines Manual for Sentencing
Organizations as part of an effective compliance and ethics
program. However, the criteria usually recommended for,
and used in such risk assessments include only impact or
severity, and the likelihood of occurrence of an initial act
(e.g., The Institute of Internal Auditors et al. 2008; United
States Sentencing Commission 2012). These risk assess-
ments serve organizations as basis for prioritizing and
developing measures to prevent and detect unethical
behavior. Disregarding the potential for spread in this
assessment may, for example, lead to insufficient attention
to types of unethical behavior which are assessed as having
a low impact, but which may easily spread and have a
detrimental impact when occurring repeatedly.
This paper reveals some criteria for identifying types of
unethical behavior that have a high potential for spread.
For example, acts which can easily be observed by actors
socially close to the perpetrator, and which cause rather
diffuse harm to socially distant, not personally identifiable
actors are particularly likely to spread: First, there is likely
to be a high number of observers who could imitate this
behavior. Second, the social relationship between the per-
petrator and the observer increases the likelihood for a
biased cognitive appraisal by observers. And third, social
distance to non-identified victims and diffuse harm facili-
tate the rationalization of the unethical behavior, enabling
subsequent unethical behavior by the perpetrator and
observers. Some forms of unethical behavior against
external stakeholders may typically fit such a description,
and—in the short run—may even benefit the organization,
which provides a further rationalization (see also Umphress
et al. 2010; Umphress and Bingham 2011). Such behaviors
may thus have a high potential for spreading within the
organization.
Managers have to carefully consider whether they are not
tacitly condoning unethical behavior to the benefit of the
organization against external stakeholders, while expecting
the organization members to adhere to rules for their behavior
toward the organization. Cialdini et al. (2004) cite the
example of a consultant who was incited by her manager to
withhold information from a client, and later ‘‘found herself
regularly cheating on her travel expenses’’ (p. 70). The ana-
lysis provided here suggests that one form of unethical
behavior may lead to subsequent unethical behavior of a
different form for several reasons. First, cross-norm inhibition
effects can lead observers and perpetrators to subsequently
engage in different forms of unethical behavior. Second, as set
out in proposition 7, observers may also engage in different
forms of unethical behavior if their role in the organization
differs from the perpetrator’s, and offers different opportu-
nities for unethical behavior. Third, direct retaliation and
especially indirect or displaced retaliation by victims can take
a different form than the initial act. Therefore, leaders of
organizations should not assume that they can successfully
curtail one form of unethical behavior while conniving in
other forms. A consistent and well-coordinated approach
targeting all types of unethical behavior relevant for the
6 I thank an anonymous reviewer for highlighting the possibility of
such role-dependencies based on actors’ individual attributes.
168 F. Zuber
123
organization is likely to lead to better results than a com-
partmentalized, eclectic approach targeting single types of
unethical behavior. It also seems advisable to foster coordi-
nation among the different functional areas that traditionally
look after specific types of unethical behavior (e.g., Human
Resources, Compliance, Legal, Security, Internal Audit, and
Risk Management) to develop a joint and consistent approach
addressing all relevant types of unethical behavior.
Finally, earlier in the discussion, I have highlighted
some areas where those responsible for managing organi-
zations could take action to reduce the likelihood that
unethical behavior spreads. I hope that the dynamic social
network perspective proposed in this paper not only con-
tributes to a better understanding of how unethical behavior
can spread, but also provides some new ideas to those who
are trying to reduce unethical behavior in organizations.
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Franziska Zuber is a PhD student at the Department of Business- Society Management at Rotterdam School of Management, Erasmus
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international assurance and advisory firm KPMG. Her current
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172 F. Zuber
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- c.10551_2014_Article_2270.pdf
- Spread of Unethical Behavior in Organizations: A Dynamic Social Network Perspective
- Abstract
- Introduction
- Social Networks and the Spread of Unethical Behavior
- Relevant Actors and Relationships
- Emergence of Reactions in Social Networks: Social Cognition
- Initial Affective Appraisal
- Secondary Cognitive Appraisal
- Tertiary Emotional Appraisal
- Integrating Relationships and Reactions: Actor-Oriented Models for Network Dynamics
- A Dynamic Actor-Oriented Framework to Examine the Spread of Unethical Behavior
- Relationships
- Reactions
- The Spread of Unethical Behavior Through Perpetrators, Victims, and Observers in a Dynamic Actor-Oriented Framework
- Perpetrator’s Perspective and Reaction
- Biased Attribution
- Impact of Perpetrator’s Social Relationships on His Reactions
- Impact on Perpetrator’s Social Relationships
- Victim’s Perspective and Reactions
- Perception of Being a Victim
- Attributions and Retaliation
- Impact on Victim’s Social Relationships
- Observer’s Perspective and Reactions
- Observers’ Social Relationships as Conduits
- Impact of Observer’s Social Relationships on His Reactions
- Reactions Similar to the Perpetrator’s
- Reactions Similar to the Victim’s
- Discussion
- Stopping the Spread of Unethical Behavior
- Limitations and Future Research
- Practical Implications
- References