MGMT 314 Rasmussen University Historical Ethical Dilemmas Essay

Description

INCLUDE AN ABSTRACTAnswer the following five questions:1. What are some of the most common forms of unethical behavior in our workforce today? How could leadership in organizations help to minimize this ethical misconduct? Explain and support your positions with relevant course content and outside sources.2. As our businesses have developed over the last 100 plus years, have our modern day businesses evolved to be more ethical today? What are some of the factors that helped you come to your conclusion? Take a position and support your thoughts.3. Would you describe the financial meltdown in our 2007-2008 financial markets as a failure of “people” or of our “capital market processes”? Why? Support your thoughts with ethical theory and examples. Use our library for added research if needed.4. Tell me about why diversity and discrimination are two important ethical factors that leaders should focus on while attempting to manage their workforce? Provide one example of how mismanaging these issues have had an impact on an organization. How would you explain the importance of these to your employees?5. Are corporate outreach and company sponsored volunteer programs a good idea for organizations to implement? Why? From an ethical leadership perspective, why would you choose OR not choose to implement these programs? Use course theory and specific examples to support your conclusionWhat about the workers? The workforce
benefits of corporate volunteer programs
Clinton O. Longenecker, Sam Beard and Joseph A. Scazzero
Clinton O. Longenecker is
based in the Department of
Management, College of
Business Administration,
The University of Toledo,
Toledo, Ohio, USA. Sam
Beard is President and
Co-founder, The Jefferson
Awards. Joseph A.
Scazzero is based in the
Department of Accounting
and Finance, College of
Business Administration,
Eastern Michigan
University, Ypsilanti,
Michigan, USA.
Our organization has a formalized volunteer program for a lot of reasons that include giving back
to our community, supporting causes that are important to our organization, strengthening our
brand in the marketplace […] But when our employees engage in volunteerism, there are wide
ranging personal and professional benefits for all parties concerned (Chief Volunteer Officer,
Fortune 500 organization).
While many organizations around the world demonstrate corporate responsibility by
promoting and engaging in community service and public service events, there is growing
evidence that organizations reap great benefit when they strategically develop and
implement formal employee volunteer programs (Peloza and Hassay, 2006). A formal
employee volunteer program is a strategic and systematic effort on the part of an
organization to create a structured approach to promoting, recruiting, linking and
recognizing employee volunteers serving community needs deemed important by their
employers (Luo and Bhattacharya, 2006). And it is important to note, that while many
organizations are engaged in volunteer initiatives for a wide variety of social and
philanthropic reasons, corporate volunteerism can help an organization’s performance in the
marketplace (Longenecker et al., 2011). Corporate volunteerism has been linked to
improved brand recognition, added media exposure, increase customer loyalty, expanded
community goodwill and creating strategic alliances, among others (Brammer et al., 2007).
Having said this, there is an apparent gap in the research on the actual benefits derived from
these activities from the perspective of the employee volunteer (Davis and MacDonald,
2010). It has been speculated that corporate volunteerism can have a powerful and positive
effect on an organization’s workforce which is not fully understood. The purpose of this article
is to explore the key benefits that employees experience when actively involved in formal
volunteer initiatives.
Our research study
To explore the benefits of formal employee volunteer programs, an electronic survey was
sent to the chief volunteer officer (CVO) of 30 organizations with formal corporate employee
volunteer programs. A total of 26, or 87 percent, of the organizations participated in this
study, representing manufacturing, service, and public sector entities. Surveys were
forwarded to employees with established track records of volunteerism who were then asked
to complete an online survey designed to assess various aspects of their organization’s
volunteer program. A total of 519 employees responded to the survey that included both
structured and open-ended questions. Thus, these respondents represent a convenience
sample from the target population of established volunteers in organizations with structured
volunteer programs.
In this survey, participants were asked to identify the specific reasons that they chose to
engage in these corporate volunteer programs from a list of potential benefits that that had
DOI 10.1108/14777281311291213
VOL. 27 NO. 1 2013, pp. 9-12, Q Emerald Group Publishing Limited, ISSN 1477-7282
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been previously identified in organizational focus groups. Respondents averaged 11.72
hours of volunteer work per month, had an average age of approximately 45 years and had
positions ranging from front-line workers to senior leadership. Frequency counts were
tabulated for each item and a top eight list of the developmental reasons why employees
choose to actively participate as volunteers was identified.
Key research findings
The reasons people volunteer are many but in the end most of our people volunteer to help
people less fortunate than themselves and to make a difference in our communities […] And in
doing so, they experience a wide range of personal and professional benefits (corporate
volunteer coordinator, large financial enterprise).
The participants in our study identify a number of reasons why they participated in their
organizations formal employee volunteer programs. A review of these reasons reveals
specific benefits that employees derive from these experiences.
Reason 1: helps employees develop as people (74 percent)
According to the participants in this study, corporate volunteer initiatives help them develop
as human beings. While this is a very broad statement, a review of their activities shows a
commendable willingness to help other human beings. Corporate volunteers engage in
such endeavors as after school reading programs, working in homeless shelters,
constructing low income housing, cleaning up community parks, and Red Cross blood
drives among others. Employees benefit by having an opportunity to experience such
human feelings as compassion, humility, sympathy, empathy, and joy which are not
necessarily part of or experienced in the modern workplace.
Reason 2: increases employee happiness and satisfaction with life (73 percent)
Volunteering also provides employees an opportunity to experience a higher level of
happiness and satisfaction with life according to the participants in this study. Most
corporate volunteer initiatives focus on serving unmet individual and community needs that
frequently address issues such as hunger, education, disease, community health, children’s
programming, homelessness, youth sports, and combating poverty. When employees help
meet these needs, they are exposed to both individuals and communities that are frequently
less fortunate than themselves. This exposure benefits employees by giving them a sense of
awareness, appreciation and thankfulness for their current circumstances that might not be
so apparent if they were not exposed to these opportunities.
Reason 3: provides an opportunity to meet and work with fellow employees (53 percent)
When organizations formally create volunteer opportunities to support their communities,
employees frequently find themselves working side-by-side with fellow employees outside
their regular work group. Volunteering allows employees the opportunity to interact with
superiors, subordinates, and peers from across the organization while involved in a common
cause. This exposure can benefit employees by helping them build expanded networks and
effective workplace connections that make it easier to get work done in our large, complex,
and dynamic organizations of the twenty-first century.
Reason 4: helps employees maintain work-life balance (42 percent)
While a loss of work-life balance is frequently one of the hallmarks of the modern workplace,
a substantial percentage the participants of this study believe that volunteering helps
maintain this balance. The average participant in this study volunteered over 11 hours each
month, and, in most cases, worked a full-time job. Yet, volunteering, which added more work
to their schedule, actually helped them maintain their work-life balance. This finding may
appear paradoxical until one looks at all of the positive benefits that employees derive from
volunteering, resulting in a more meaningful life.
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PAGE 10 DEVELOPMENT AND LEARNING IN ORGANIZATIONS VOL. 27 NO. 1 2013
Reason 5: improves relationships both inside and outside of work (38 percent)
Volunteering has the potential of not only creating connections and networks, but it also
brings people together to do meaningful work around very important causes. According to
our participants, they benefit from better and more effective relationships at work as well as
relationships and networks outside of the workplace with other members of the community.
Reason 6: provides an opportunity to build workplace camaraderie/teamwork (33 percent)
When employees volunteer around important causes, it provides them an opportunity to
work together and develop an ‘‘espirit de corps.’’ Participants in this study provided
numerous examples of how they work together on a wide variety of ongoing and annual
community service initiatives. When employees are called to rally around volunteer
initiatives, they frequently return to work with the new sense of camaraderie and a willingness
and ability to work to work together more effectively at work.
Reason 7: helps employees develop as professionals (31 percent)
Another important benefit of volunteering is that it provides employees opportunities to
develop skill sets that are directly tied to both current work and future promotions. Many
organizations use their volunteer initiatives as a specific opportunity to help employees
develop ‘‘targeted’’ skills that need development. Strategic skills can be developed sitting
on volunteer boards. Emotional intelligence skills can be developed working in community
outreach. A lack of humility or egocentrism can be addressed by working in a homeless
shelter. Intelligent organizations look for ways to couple development needs to specific
volunteer initiatives which abound in most communities.
Reason 8: provides employees an opportunity to give back to their employer (30 percent)
Our participants made it clear that volunteering gives them an opportunity to give back to the
organizations that they work for. In this sense, volunteering gives employees an opportunity
to make their employers ‘‘look good’’ in their communities by the good deeds that they are
doing both individually and collectively. This ‘‘giving back’’ by employees creates a sense of
appreciation and pride for their employer. This can help the employer with employee
retention, engagement, and commitment.
In closing
I am very thankful that my organization takes employee volunteerism so seriously [. . .] We are a
better organization and I am a better person for it (a corporate volunteer’s observation).
Keywords:
Corporate volunteerism,
Corporate responsibility,
Institutional community
service,
Social responsibility,
Corporate strategy
The purpose of this discussion is to highlight the primary reasons given by surveyed
employees of why they choose to engage in formal corporate volunteer programs. The
strategic benefits of formal corporate volunteerism are well documented, yet the positive
impact that volunteerism can have on an organization’s workforce is not fully understood.
Finally, the findings of this study clearly support the well-established research on the ‘‘power
of the positive psychology’’ which makes a strong case for the multi-faceted benefits derived
when people are actively involved in helping and serving others (Seligman, 2011). It is our
hope that business leaders will consider leveraging the benefits of their corporate
volunteerism efforts by developing more formalized and strategic volunteer initiatives. These
efforts can help your business succeed while at the same time providing your workforce an
opportunity for learning and development on both a personal and professional level.
References
Brammer, S., Millington, A. and Rayton, B. (2007), ‘‘The contribution of corporate social responsibility to
organizational commitment’’, International Journal of Human Resource Management, Vol. 18 No. 10,
pp. 1701-19.
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Davis, D. and MacDonald, J. (2010), ‘‘Improving the promotion of CSR initiatives: a framework for
understanding stakeholder communications from a dynamic learning perspective’’, Academy of
Marketing Studies Journal, Vol. 14 No. 2, pp. 77-93.
Longenecker, C.O., Moore, G. and Scazzero, J.A. (2011), ‘‘The benefits of corporate volunteer
programs: an employees’ perspective’’, HR Advisor, September/October, pp. 6-14.
Luo, X. and Bhattacharya, C.B. (2006), ‘‘Corporate social responsibility, customer satisfaction, and
market value’’, Journal of Marketing, Vol. 70 No. 4, pp. 1-18.
Peloza, J. and Hassay, D. (2006), ‘‘Intra-organizational volunteerism: good soldier, good deed, and
good politics’’, Journal of Business Ethics, Vol. 64 No. 4, pp. 357-79.
Seligman, M.E.P. (2011), Flourish: A Visionary New Understanding of Happiness and Well-being, Free
Press, New York, NY.
Corresponding author
Clinton O. Longenecker can be contacted at: Clinton.longenecker@utoledo.edu
To purchase reprints of this article please e-mail: reprints@emeraldinsight.com
Or visit our web site for further details: www.emeraldinsight.com/reprints
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PAGE 12 DEVELOPMENT AND LEARNING IN ORGANIZATIONS VOL. 27 NO. 1 2013
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Social Responsibility Should Be a Participation Essential
Duckworth, Holly A
The Journal for Quality and Participation; Jan 2016; 38, 4; ProQuest Central
pg. 39
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Business Ethics
Copyright © 2014 by Joseph W. Weiss
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Sixth Edition
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2014-1
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Weiss, J. W. (2014). Business ethics : A stakeholder and issues management approach. Berrett-Koehler Publishers, Incorporated.
Created from apus on 2023-04-27 22:16:05.
Brief Contents
Chapter 1
Business Ethics, the Changing Environment, and Stakeholder
Management
Chapter 2
Ethical Principles, Quick Tests, and Decision-Making Guidelines
Chapter 3
Stakeholder and Issues Management Approaches
Chapter 4
The Corporation and External Stakeholders: Corporate Governance:
From the Boardroom to the Marketplace
Chapter 5
Corporate Responsibilities, Consumer Stakeholders, and the Environment
Chapter 6
The Corporation and Internal Stakeholders: Values-Based Moral
Leadership, Culture, Strategy, and Self-Regulation
Copyright © 2014. Berrett-Koehler Publishers, Incorporated. All rights reserved.
Chapter 7
Employee Stakeholders and the Corporation
Chapter 8
Business Ethics and Stakeholder Management in the Global Environment
Weiss, J. W. (2014). Business ethics : A stakeholder and issues management approach. Berrett-Koehler Publishers, Incorporated.
Created from apus on 2023-04-27 22:16:05.
J Bus Ethics (2012) 109:447–461
DOI 10.1007/s10551-011-1139-8
Self-Construal and Unethical Behavior
Irina Cojuharenco • Garriy Shteynberg •
Michele Gelfand • Marshall Schminke
Received: 17 October 2011 / Accepted: 30 November 2011 / Published online: 22 December 2011
Springer Science+Business Media B.V. 2011
Abstract We suggest that understanding unethical behavior in organizations involves understanding how people view
themselves and their relationships with others, a concept
known as self-construal. Across multiple studies, employing
both field and laboratory settings, we examine the impact of
three dimensions of self-construal (independent, relational,
and collective) on unethical behavior. Our results show that
higher levels of relational self-construal relate negatively to
unethical behavior. We also find that differences in levels of
relational self for men and women mediate gender differences in unethical behavior. We discuss both the theoretical
and practical implications of these findings.
Keywords Unethical behavior Self-construal
Relational self
Abbreviations
CFA
Confirmatory factor analysis
SRMR
Standardized root mean square residual
I. Cojuharenco (&)
Católica Lisbon School of Business and Economics,
Universidade Catolica Portuguesa, Palma de Cima,
1649-023 Lisbon, Portugal
e-mail: icojuharenco@clsbe.lisboa.ucp.pt
G. Shteynberg
Kellogg School of Management, Northwestern University,
Evanston, USA
M. Gelfand
Department of Psychology, University of Maryland at College
Park, College Park, USA
M. Schminke
College of Business Administration, University of Central
Florida, Orlando, USA
RMSEA
CFI
PANAS
MEV
Bca CI
Root mean square error of approximation
Comparative fit index
Positive and negative affect schedule
Measure of ethical viewpoints
Bias corrected and accelerated confidence
interval
Unethical behavior is commonly defined as behavior ‘‘that
violates widely accepted (societal) moral norms’’ (KishGephart et al. 2010, p. 2), such as the norms regarding
professional conduct or norms regulating interpersonal
relationships in a variety of social settings. Consequently, it
has received considerable research attention not only from
business scholars, but also from sociologists (Vaughan
1999), psychologists (Moffitt 1993), political scientists
(Pratto et al. 1994), and criminologists (Gottfredson and
Hirschi 1990). Unethical behaviors are studied in various
organizational settings. For example, educational scholars
have examined predictors of academic cheating, rulebreaking, and criminal behaviors in schools, and organizational scholars have looked at theft, neglect for one’s
duties, and disruptive insubordination at work (Robinson
and Bennett 1995). Because unethical behavior violates
social norms and social norms exist for purposes of
aligning the interests of actors in social systems, unethical
acts are often, albeit not always, antisocial in that they
harm the relationship or the social system (Treviño and
Weaver 2001).
In this article, we explore how an actor’s self-construal
(Markus and Kitayama 1991)—the extent to which a person thinks of himself or herself as independent from or
interdependent with social others—influences his or her
propensity to engage in unethical behavior. Our aim is to
show that because self-construal regulates social behavior
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I. Cojuharenco et al.
(Gelfand et al. 2007; Markus and Kitayama 1991), it is an
important predictor of unethical behavior.
which we both manipulate self-construal in the laboratory
and measure it in the field.
Self-Construal
Research Hypotheses
The self-construal literature points to the existence of three
fundamental dimensions of self-definition: the independent
self, the relational self, and the collective self (Kashima
et al. 1995; Sedikides and Brewer 2001). The independent
self reflects self-definition through one’s unique traits and
independence from others. The relational and collective
selves reflect self-definition through a focus on relationships with other individuals and group membership,
respectively (Brewer and Gardner 1996; Turner et al.
1987). In all, the three types of self-construal represent
three distinct ways of defining the self in terms of the
psychological relationship (or lack there of) between the
self and others.
Research reveals stable differences in emphasizing a
specific dimension of self exist across cultures and gender
(Cross and Madson 1997; Kashima et al. 1995; Markus and
Kitayama 1991). When one dimension of self is emphasized over and above the other dimensions, it influences
outcomes by altering basic psychological processes of
person and relationship perception and memory, emotion,
and motivation (Baldwin 1992; Cross et al. 2002; Markus
and Kitayama 1991). Research demonstrates each dimension of self-construal has important effects on a variety of
workplace attitudes and behaviors (e.g., negotiation
behavior (Gelfand et al. 2006), citizenship (Eagley 2009;
Moorman and Blakely 1995), and individual well-being
(Cross and Morris 2003). We suggest that because of the
importance of self-construal to social behavior, an individual’s self-construal is likely to predict his or her propensity to engage in unethical behavior.
In applying a self-construal perspective to the issue of
unethical behavior, we seek to contribute to the literature in
three ways. First, we contribute to the self-construal literature by extending the scope of its predictive powers to
previously unexplored terrain: unethical behavior. Second,
we suggest the addition of self-construal to the conversation on unethical behavior offers the opportunity to shed
light on previous findings in the unethical behavior literature, for example, those concerning gender differences.
Third, it opens novel possibilities for regulating unethical
behavior by means of inducing the salience of specific
dimensions of self-construal.
In what follows we develop research hypotheses that
link the three self-construal dimensions and unethical
behavior, as well as suggest that gender differences in
unethical behavior will be mediated by differences in selfconstrual. We test our hypotheses across multiple studies in
The Independent Self
123
The self-construal literature points to three ways individuals define themselves, in terms of the psychological
relationship (or lack there of) between the self and others.
The first is the independent self.
The representation of one’s self as an entity that is
independent from others is associated with the motive to
protect and enhance the view of one’s self as a unique set
of traits and characteristics (Markus 1977). Ultimately,
individuals who emphasize their independence are less
likely to consider the impact of their decisions on others or,
whether these decisions violate social norms. Thus, we
anticipate independent self-construal will be associated
with lower levels of moral awareness (Rest 1986), an
important cognitive precursor to behaving ethically, and
therefore, higher levels of unethical behavior. Cross and
Madson (1997, p. 7) write: ‘‘For these persons, individual
rights, goals, and wishes are the primary basis for moral
choices. The goals and needs of society, family members,
or others are secondary or subordinate….’’ In part, this is
due to the fact that high levels of independent self are
associated with the belief in autonomy and self-reliance
(Lalwani et al. 2006; Markus and Kitayama 1991). Consequently, little attention is paid to the context of one’s
behavior (Hannover et al. 2006). Thus, little attention is
also paid to the interests of others or norms that exist to
align the interests of various individuals. On the positive
side, individuals that are high on independent self are nonconformist and, therefore, creative (Goncalo and Staw
2006). However, such individuals also find it difficult to
empathize with others (Johnson and Chang 2006), whereas
empathy is an important deterrent of unethical behavior
that harms others (Eisenberg and Miller 1987; Miller and
Eisenberg 1988; Vetlesen 1994). Thus, if some decision
violating a social norm was detrimental to other people
(such as would be involved in committing an unethical
act), individuals with higher levels of independent self
would be less likely to refrain themselves from that
behavior, not only because of the disregard for the norm
but also because they are simply less likely to feel empathetic. The inability to empathize with others is also
reflected in findings from previous research showing that
higher levels of independent self are associated with a
diminished tendency to behave in socially sensitive ways
(Lalwani and Shavitt 2009). Similarly, Johnson and Lord
(2010) provide experimental evidence that the relationship
Self-Construal and Unethical Behavior
between the experience of injustice and theft is mediated
by the greater accessibility of the independent self following the experience of injustice.
To our knowledge, no empirical studies have examined
the relationship between the chronic salience of independent self-construal and unethical behavior. The evidence
we have reviewed suggests that the following positive
relationship holds:
Hypothesis 1 Higher levels of independent self-construal
are associated with greater levels of unethical behavior.
The Relational Self
The second way individuals define themselves, in terms of
the psychological relationship between the self and others,
is the relational self. Relational selves are different from
independent selves because relational selves are driven by
the motive to protect and enhance significant dyadic relationships in which they take part, and a willingness to
initiate new relationships (i.e., parent–child, teacher–student, or supervisor–subordinate) (Brewer and Gardner
1996; Cross et al. 2000, Hazan and Shaver 1994; Reis and
Shaver 1988). Markus and Kitayama (1991, p. 227) note,
‘‘Experiencing interdependence entails seeing oneself as
part of an encompassing social relationship and recognizing that one’s behavior is determined, contingent on, and,
to a large extent organized by what the actor perceives to
be the thoughts, feelings, and actions of others in the
relationship.’’
Relationality is also known to be positively associated
with the ability to empathize with significant others (Cross
and Madson 1997; Gardner et al. 2002). Higher levels of
relational self are associated with a greater preference for
positive interpersonal interactions (Johnson et al. 2006) as
well as relational goals (Gore and Cross 2006) and outcomes (Gelfand et al. 2006). For example, in work settings,
higher levels of relational self predict greater interpersonal
and organizational citizenship (Johnson et al. 2006).
Taken together, this evidence suggests that relational
selves will generally show greater awareness of social
norms, especially when potential violations of such norms
might harm the wellbeing of other individuals. Consequently, we hypothesize that:
Hypothesis 2 Higher levels of relational self-construal
are associated with lower levels of unethical behavior.
The Collective Self
The third way individuals define themselves, in terms of the
psychological relationship between the self and others, is the
collective self. Collective self-construal is driven by the
motive to protect and enhance one’s in-group(s) (Brewer and
449
Gardner 1996). This is another type of self-construal where
emphasis is placed on interdependence. Yet, individuals with
high levels of collective self define themselves in terms of
group membership rather than their relationship with specific
others (e.g., I am a Googler vs. I am Mike’s colleague).
Higher levels of collective self-construal are related to
greater commitment to group goals, and thus, a more likely
honoring of social obligations. Consequently, higher levels
of collective self have been shown to be associated with
greater sensitivity to rules of proper social conduct in groups.
For example, apologies that emphasize the importance of
norms and rules are more effective means of restoring relationships with individuals who have high levels of collective
self (Fehr and Gelfand 2010). Also, higher levels of collective self are associated with greater interpersonal citizenship
at work (Johnson et al. 2006) and relate negatively to the use
of deception in business negotiations with one’s in-group
members (Triandis et al. 2001). Thus,
Hypothesis 3 Higher levels of collective self-construal
are associated with lower levels of unethical behavior.
Gender Differences
Previous research indicates self-construal is an important
dimension of gender differences (Kashima et al. 1995).
From early discussions of agency versus communion orientations of men versus women (Bakan 1966), to gender
socialization theories (Gilligan 1982), to more recent
arguments referring to the tripartite self-construal (Cross
and Madson 1997), a sizable body of research suggests that
women are more likely to emphasize their interdependence
(the relational self, in particular) whereas men are more
likely to emphasize their independence. As discussed previously, greater levels of independent self will relate positively to unethical behavior, whereas greater levels of
either relational or collective self will relate negatively to
unethical behavior. Consistent with the fact that women are
more likely to emphasize interdependence, and our
hypothesized effects of relational and collective selves on
unethical behavior, meta-analytic studies of unethical
behavior and ethical decision-making provide evidence of
mild to moderate gender differences, with women typically
emerging as more ethical than men (Hershcovis et al. 2007;
Kish-Gephart et al. 2010; O’Fallon and Butterfield 2005;
Tenbrunsel and Smith-Crowe 2008; Treviño et al. 2006).
For example, Kish-Gephart et al. (2010) report a significant
meta-analytic correlation of -.09 for gender and unethical
behavior, whereas Hershcovis et al. (2007) report a correlation of -.21 for gender and interpersonally targeted
deviance and -.13 for gender and organizationally targeted
deviance. Similarly, male adolescents score higher than
female adolescents on self-report delinquency variables
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450
I. Cojuharenco et al.
and reputation enhancement variables pertaining to social
deviance (Carroll et al. 2008).
In reviewing the literature on ethical decision-making,
O’Fallon and Butterfield (2005) state ‘‘there are often no
differences found between males and females, but when
differences are found, females are more ethical than
males’’ (p. 379). Notably, Dawson (1997) drew a distinction between gender differences in relational and nonrelational moral dilemmas. In her studies, women were
found to respond more ethically to dilemmas involving
explicit relational concerns, but not otherwise. We suggest
it is the fact that women construe themselves as more
interdependent that helps them avoid certain unethical
actions that men pursue undeterred. Kish-Gephart et al.
(2010) show that gender differences become insignificant
when controlling for individual psychological characteristics, such as machiavellianism, cognitive moral development, idealism, locus of control, and job satisfaction. Yet,
no explicit mediation analyses are conducted to pin down
the exact mediators of the effect of gender. We seek to
bridge this gap in the literature, by examining whether
differences in self-construal mediate the effects of gender
on unethical behavior.
Hypothesis 4 Self-construal will mediate gender differences in unethical behavior.
Figure 1 depicts the relationships we postulate for gender, self-construal, and unethical behavior. Hypotheses 1,
2, and 3 are nested within Hypothesis 4.
Study 1
Study 1 was conducted to test the relationships postulated
in our research hypotheses by examining the differences in
individual tendencies to behave unethically as revealed by
a self-report measure of trait morality (International Personality Item Pool 2001). Undergraduate respondents
indicated to what extent they tended to engage in unethical
behavior of relevance to the student life. In particular, we
were interested in exploring the relationship between selfconstrual and trait morality while controlling for previously
studied predictors of unethical behaviors, namely positive
and negative affectivity (Fredrickson 2001; Gaudine and
Thorne 2001) and ethical orientation (Pearsall and Ellis
2011).
Method
Participants and Procedure
One hundred and fifty-six undergraduates at a business
school participated in an online survey at the beginning of
their organizational behavior course. 51% of the sample
were male. 38% had work experience in part-time jobs.
Average age was 20. The survey included demographic
questions, measures of self-construal, trait morality,
affectivity, and ethical orientation. The final response rate
was 94% (147 participants).
Predictor and Criteria Measures
Self-construal Self-construal was measured using the levels
of self-concept scale (Johnson and Lord 2010; Johnson
et al. 2006). Participants indicated how well 15 statements
(5 items per dimension of self-construal) described them on
a 1–5 scale (1 = strongly disagree; 5 = strongly agree).
Items included ‘‘I thrive on opportunities to demonstrate
that my abilities or talents are better than those of other
people’’ and ‘‘I often compete with my friends’’ (independent), ‘‘I value friends who are caring, empathic individuals’’ and ‘‘Knowing that a close other acknowledges
and values the role that I play in their life makes me feel
like a worthwhile person’’ (relational), and ‘‘When I
become involved in a group project, I do my best to ensure
its success’’ and ‘‘When I’m part of a team, I am concerned
about the group as a whole instead of whether individual
team members like me or whether I like them’’ (collective).
All three dimensions of the scale exhibited acceptable
reliability (independent a = .75, relational a = .79,
Independent self
Hypothesis 1 (path b1)
(path a1)
Gender
Relational self
Hypothesis 2 (path b2)
(path a2)
(path a3)
Collective self
Fig. 1 Self-construal as a mediator of gender differences in unethical behavior
123
Hypothesis 3 (path b3)
Unethical
behavior
Self-Construal and Unethical Behavior
451
collective a = .70). To confirm the three-dimensional
nature of the measure, we conducted a series of confirmatory factor analyses (CFAs). In order to minimize the
occurrence of Type I and Type II errors, Hu and Bentler
(1999) suggest the use of either the standardized root mean
square residual (SRMR) index (good models .08) or the
root mean square error of approximation (RMSEA) index
(good models .06). The three-factor model fit was
acceptable [comparative fit index (CFI) = .91, SRMR =
.078, RMSEA = .06], with all indicator loadings significant and above .40. We also ran a one factor model in
which independent, relational, and collective dimensions
all loaded on a single factor. This model resulted in poor fit
(CFI = .65, SRMR = .12, RMSEA = .12).
Trait morality Trait morality was measured via four
items drawn from the International Personality Item Pool
(2001) that reflect patterns of unethical behavior of relevance to the undergraduate population. Participants
expressed their degree of agreement with each of the items
on a 1–5 scale (1 = strongly disagree; 5 = strongly agree).
Items include ‘‘I scheme against others’’ and ‘‘I act at the
expense of others’’ (a = .67).
Alternative predictor variables We measured several
alternative predictor variables based on extant theory and
empirical research, to rule out the possibility that the
effects of self-construal are confounded with the effects of
already known and qualitatively distinct determinants of
unethical behavior. Trait positive and negative affectivity
was used as an alternative predictor variable because previous research suggested that positive affect may be associated with a smaller and negative affect with a greater
propensity to engage in unethical behavior (Fredrickson
2001; Gaudine and Thorne 2001). Ethical orientation was
another variable that featured in research concerning
unethical behavior (Pearsall and Ellis 2011; Schminke
1997). We used Brady’s (1990) distinction between
formalist and utilitarian ethical orientation. Whereas formalists focus on rules or principles for deciding whether a
certain action is ethical, those who adhere to utilitarian
ethics focus on the outcomes of actions. Demographic
variables were also included as controls.
Positive/negative affect The positive affect negative
affect schedule (PANAS, 20 items) was used to measure
trait positive and negative affect (Watson et al. 1988).
Participants indicated to what extent they generally felt the
emotions and feelings described by the items of the
PANAS on a 1–5 scale (1 = very slightly or not at all;
5 = extremely). Items included ‘‘interested’’ and ‘‘excited’’ (positive affect a = .75), and ‘‘distressed’’ and
‘‘upset’’ (negative affect a = .77).
Ethical orientation The character traits version of the
measure of ethical viewpoints (MEV) was used to assess
ethical orientation (Brady and Wheeler 1996). Participants’
ethical orientation is assessed by the extent to which they
identify a series of adjectives that describe others as being
important to them (1 = not at all; 7 = very important).
When participants rated items ‘‘innovative,’’ ‘‘resourceful,’’ ‘‘effective,’’ ‘‘influential,’’ ‘‘results-oriented,’’ ‘‘productive,’’ ‘‘winner’’ as more important, they indicated
greater utilitarian tendencies (a = .74). When they rated
items ‘‘principled,’’ ‘‘dependable,’’ ‘‘trustworthy,’’ ‘‘honest,’’ ‘‘noted for integrity,’’ ‘‘law abiding,’’ and ‘‘dutiful’’ as
more important, they indicated greater formalist tendencies
(a = .63).
Results
Descriptive statistics, scale alphas, as well as inter-correlations between study variables are presented in Table 1.
We analyzed the relationship between self-construal and
trait morality using hierarchical regression. In the first step,
we entered the demographic variables of gender and age. In
Table 1 Descriptive statistics for Study 1 variables with internal reliabilities on the diagonal
Variables
1. Gender (0 = F; 1 = M)
M
SD
1
2
3
4
5
6
7
8
9
.49
.50

2. Age
20.20
1.87
.02

3. Independent self
3.13
.73
.19*
-.23**
.75
4. Relational self
4.15
.62
-.29**
-.33**
.16
.79
5. Collective self
4.09
.59
-.29**
-.17*
.08
.55**
6. Positive affect
3.64
.48
-.17*
-.14
.17*
.33**
7. Negative affect
2.52
.59
.08
-.05
.17*
8. Utilitarian
5.40
.71
-.09
-.02
.10
.31**
.32**
.47**
-.15
.74
9. Formalist
5.31
.68
-.22*
-.03
-.06
.29**
.23**
.20*
-.04
.50**
.63
10. Trait Morality
4.03
.67
-.21*
-.06
-.18*
.42**
.41**
.23**
-.30**
.31**
.34**
-.16
10
.70
.42**
.75
-.18*
-.14
.77
.67
N = 147
* p .05, ** p .01
123
452
I. Cojuharenco et al.
the second step, we entered trait positive and negative
affect. In the third step, we entered measures of utilitarian
and formalist ethical orientations. Finally, in the fourth
step, we entered the three dimensions of self-construal:
independent, relational, and collective. Self-report trait
morality was the dependent variable.
Table 2 reports the results for the hierarchical regression. Consistent with hypotheses 1, 2, and 3, the independent self-construal was related negatively to trait morality
(b = -.19 (.07), p .01); whereas, the relational selfconstrual was related positively to trait morality (b = .26
(.10), p .01), as was the collective self-construal
(b = .21 (.10), p .05). The three self-construal dimensions explained additional variance in trait morality
(DR2 = .11, p .01) after we controlled for the effects of
gender, positive affect, negative affect, and formalist and
utilitarian ethical orientation.
Next, we used the multiple mediators bootstrapping
method described by Preacher and Hayes (2008) to
examine whether self-construal mediated gender differences in trait morality. There are several advantages to
using this statistical method. First, it allows for the examination of multiple mediators in the same model. The use of
a multiple mediator model avoids biased parameter estimates that result from testing each indirect effect separately
through a series of simple mediator models (Judd and
Kenny 1981; Preacher and Hayes 2008). Unlike simple
mediator models, multiple mediator models test each
indirect effect while controlling for other hypothesized
indirect effects, insuring that the findings are specific to
each mediator. Second, the multiple mediator bootstrapping method allows for the examination of all of our
hypotheses in one statistical model, minimizing the number
Table 2 Study 1 results of
hierarchical regression analyses
predicting trait morality
Independent variables
of inferential tests and hence the possibility of Type I error.
Finally, for mediation analysis, the bootstrapping method
does not rely on the often-problematic assumption of a
normal sampling distribution (MacKinnon et al. 2004;
Preacher and Hayes 2004; Shrout and Bolger 2002).
Instead, using 5,000 bootstrap samples with replacement
from the data, we construct 95% confidence intervals,
adjusting for median bias and skew (Bca CI in the presentation of results below will refer to such bias corrected
and accelerated confidence intervals (Efron and Tibshirani
1993).
To conduct the analysis, we used the SPSS macro for
multiple mediator models created by Preacher and Hayes
(2008). Trait morality was entered as the dependent variable, gender was entered as the predictor variable, and all
three self-construal dimensions were entered as mediators.
Age, affect, and ethical orientations were entered as control
variables in both the mediator and dependent variable paths.
As depicted in Fig. 1, the a path is defined as the relationship between gender and self-construal dimensions, the
b path is defined as the relationship between self-construal
dimensions and trait morality, controlling for gender.
Hence, the ab path is defined as the indirect effect of
gender on trait morality. Finally, the c path is defined as the
total effect of gender on trait morality, and the c0 path,
which is not depicted in the figure, is the direct effect
which is the difference between the total and the indirect
effect of gender on trait morality.
In Table 3, each b path coefficient indicates the relationship between a particular self-construal dimension and
trait morality when controlling for gender, age, affect,
and ethical orientation and the other two self-construal
dimensions.
Step 1
Step 2
Step 3
Step 4
Gender (1 = Male, 0 = Female)
-.28 (.11)*
-.28 (.10)**
-.22 (.10)*
-.02 (.10)
Age
-.02 (.03)
-.02 (.03)
-.02 (.03)
.00 (.03)
Positive affect

.20 (.11)*
.08 (.12)
.01 (12)
Negative affect

-.34 (.09)**
-.32 (.09)**
-.20 (.08)*
Demographics
Positive/negative affect
Ethical orientation
Utilitarian


.10 (.09)
.08 (.08)
Formalist


.22 (.09)**
.16 (08)
Self-construal
N = 147. Parameter estimates
are unstandardized. Standard
errors are shown in parentheses
* p .05, ** p .01
123
Independent



-.19 (.07)*
Relational



.26 (.10)**
Collective
Model fit



.21 (.10)*
R2
.05*
.17**
.25**
.35**
DR2
.05*
.12**
.08**
.11**
Self-Construal and Unethical Behavior
453
Table 3 Study 1 self-construal mediation of the effects of gender on trait morality
a path coef.
b path coef.
ab path coef.
95% Bca CI
Lower
Upper
Independent self
.3285**
-.1859**
-.0611
-.0090*
-.1469
Relational self
-.2900**
.2624**
-.0761
-.0146*
-.2080
Collective self
-.2681**
.2140*
-.0574
-.0076*
-.1439
N = 147; 5,000 bootstrap samples. All analyses control for age, affect and ethical frameworks. BCa CI = bias corrected and accelerated
bootstrapping confidence intervals. Confidence intervals not containing zero are interpreted to be significant
* p .05, ** p .01
Results indicate that the relationship between gender
and trait morality was significantly mediated by the independent self (ab path = -.06, 95% Bca CI = -.01, -.15),
the relational self (ab path = -.08, 95% Bca CI = -.02,
-.21) and the collective self (ab path = -.06, 95% Bca
CI = -.01, -.14). Self-construal dimensions fully mediated gender differences in trait morality (c0 path = -.02,
t = .19, p = .85).
Discussion
Our findings demonstrate that self-construal is an important
predictor of trait morality or, the tendency of individuals to
engage in unethical behaviors. Higher levels of independent self are associated with more unethical behavior,
whereas higher levels of relational and collective self are
associated with less. These effects were robust to controlling for positive/negative affect and ethical orientation,
which have been associated with unethical behavior in
previous research. We have also shown that gender differences in trait morality are explained through differences
in self-construal.
Although these findings are encouraging, they may
suffer from a common source bias as both independent and
dependent variables were self-report. Also, we used no
control for respondent susceptibility to a social desirability
bias (Strahan and Gerbasi 1972). Finally, our findings are
not sufficient to demonstrate that the relationship between
self-construal and trait morality is causal. In Study 2, we
conduct an experimental test of the relationship between
self-construal and unethical behavior, employing a behavioral (rather than self-report) measure of unethical
behavior.
Study 2
Study 2 was designed to test whether the lessons learned
from Study 1 may be applied to influence levels of
unethical behavior in a laboratory setting. In this study,
we chose to focus on survey cheating. Researchers and
analysts have to rely on survey data, and conclusions
drawn from such data depend on how much consideration
respondents give to the questions they answer. Concerns
about potential cheating by survey respondents manifest
themselves in significant efforts invested in survey design.
Among other things, good survey design is meant to
prevent respondents from skipping questions, ‘‘straightlining,’’ or answering general knowledge questions with
information aids that respondents are not supposed to use.
The fact that respondents cheat on the assumed obligation
to provide truthful and well-considered answers (in
exchange for pay) is detrimental for the credibility of
entire panels, and harms the ability of analysts to learn
from surveys.
In Study 1, we offered to the undergraduate students the
choice of participating in an online survey in exchange for
participation in a lottery for a cash prize of 100 euros. Most
importantly, if respondents chose to participate, they were
asked to explicitly promise to provide ‘‘truthful and wellconsidered answers to all survey questions.’’
Our dependent variable was operationalized as failing
to answer four trap questions which could be missed
only if the respondents did not read survey questions.
Survey cheating in this setting is unethical not only
because of the explicit violation of a previously assumed
obligation and the harm to the analyst collecting the
data, but also because such cheating lowers the chances
of honest survey respondents to earn the deserved cash
prize.
Building on our hypotheses, we predicted that focusing
respondent attention on their independent self will lead to
more survey cheating than if respondent attention is
focused on their relational self. For purposes of testing this
prediction, we set up an experiment in which survey
respondents were primed to focus on either their independent or relational self, and then observed to assess whether
they conformed to their explicit commitment to provide
truthful and well-considered answers to all survey questions in exchange for a promised cash prize.
123
454
I. Cojuharenco et al.
Method
Dependent Measure
Participants and Design
Survey cheating was operationalized in two ways. First, we
summed up all instances of failure to respond correctly to
the trap questions. However, because respondents who
encountered one trap question might have been more likely
to be careful in responding to the following questions, their
performance on different trap questions might have been
non-independent. Thus, we also used the failure to respond
correctly to at least one trap question as our alternative
measure of survey cheating.
One hundred and thirty-six undergraduates at a business
school were invited to participate in an online survey after they
completed a mid-term course evaluation survey for their class
of organizational behavior. These students were not the same
students as in Study 1, representing a different cohort, but a
similar population, in terms of academic background and
demographics. Students were free to volunteer for survey
participation. It was advertised that the survey was administered by a US-based researcher, that participation would allow
students to qualify for a lottery prize of 100 euros, and that by
clicking on the survey link students assume the obligation to
provide truthful and well-considered answers to all survey
questions. If students were willing to participate, they were
directed to click on the top link in a randomized list of survey
links assigning participants to three experimental conditions:
independent prime, relational prime, and neutral.
One hundred and seventeen participants chose to participate. Forty-seven percent of the sample were male.
Average age was 19. Forty-one participants were assigned
to the independent prime, 39 to the relational prime, and 37
to the neutral condition.
Procedure
In the first page of the survey, participants worked through
the priming manipulation. We used an online adaptation of
the pronoun circling task (Gardner et al. 1999) for priming
independent and relational self-construal. This priming task
is the most widely used task in the literature (Oyserman
and Lee 2008). In the neutral condition, participants read a
text which contained variations of the pronoun ‘‘it’’ instead
of the pronouns ‘‘I’’ for the independent prime or ‘‘we’’ for
the relational prime.
Following the priming manipulation, participants were
invited to complete a series of multi-item scales, totaling
106 items. We used the PANAS (20 items), the trendsetting tendency scale (9 items), a specially designed
intention to modify consumer products scale (4 items), the
attitude toward consumer innovation scale (9 items),
importance of specific motivational factors for innovation
scale (20 items), a multiple choice question asking about
the intention to share with others the result of one’s innovation, a justice sensitivity scale (10 items), and personality
measures (44 items). Inserted amidst these items were trap
questions. There was a total of four trap questions inserted
after item 30 (Please, check button ‘‘2’’ on the scale here),
item 42 (Please, check button ‘‘7’’ on the scale here), item
53 (Please, check button ‘‘6’’ on the scale here), and item
94 (Please, check button ‘‘1’’ on the scale here).
123
Results
Manipulation Check
We checked whether respondents in different experimental
conditions correctly identified pronouns corresponding to
their experimental condition, and answered all manipulation questions correctly (manipulation questions asked
participants to state the total number of pronouns they
encountered and to write down the very last pronoun
given). Twenty-nine of 117 respondents failed to identify
the required pronouns and were excluded from further
analysis. As a result, we analyzed the data of 33 participants in the independent prime condition, 31 participants in
the relational prime condition, and 24 participants in the
neutral condition.
Survey Cheating
Figure 2 plots the results regarding observed survey
cheating by experimental condition. As predicted, participants cheated more in the independent prime condition
than in the relational prime condition. For example, 27% of
participants failed at least one trap question in the independent prime condition. These respondents participated in
a lottery for a prize of 100 euros without having given, as
promised at the beginning of the survey, careful consideration to all survey questions. In contrast, only 6% failed
at least one trap question in the relational prime condition.
The difference in survey cheating in the independent and
the relational prime conditions was statistically significant
for both measures of cheating, the overall failure to answer
trap questions: t(62) = 2.37, p .05, and the failure to
answer at least one trap question: z = 2.21, p .05. Participants in the neutral condition showed intermediate
levels of cheating, which were not significantly different
from the other experimental conditions.
Post-hoc analyses showed additionally that women and
men were similarly affected by the manipulation of selfconstrual (when primed with independent self, both women
and men cheated more than when primed with relational
Self-Construal and Unethical Behavior
30%
455
27%
25%
20%
17%
15%
10%
6%
5%
0%
Independent prime
Neutral
Relational prime
Fig. 2 Survey cheating rates across experimental conditions in Study
2 (percentage of respondents who cheated at least once)
self). Also, for women, there was a statistically significant
difference in rates of survey cheating between the relational prime and the neutral condition (0 vs. 19%, respectively, cheated at least once), z = 1.65, p .05, but not
between the independent prime and the neutral condition
(29 vs. 19% cheated at least once), z = .69, ns., suggesting
that the overall effect of priming was due to relational
prime acting as a deterrent of unethical behavior.
Discussion
The results of our experiment in Study 2 demonstrate a causal
relationship between the salience of a specific dimension of
self-construal and the propensity to engage in unethical
behavior. Primed with independent self, over a quarter of
participants cheated at least once. By doing so and participating in the lottery, they effectively lowered the chances of
participants who provided well-considered answers to all
survey questions in order to win the 100 euros prize. Primed
with relational self, participants were four times less likely to
cheat. Thus, settings that focus the attention of individuals on
their relational rather than their independent self may act as
effective deterrents of unethical behavior.
Both Studies 1 and 2 were conducted using convenience
samples of undergraduate students. Consequently, it
remains to be tested whether our findings would generalize
to samples of employed adults and behaviors of relevance
to business organizations. In Study 3, we test our hypotheses using a sample of employed adults. Moreover, we
examine both survey cheating and self-report unethical
behaviors in the workplace.
cheating. This was done by placing a ‘‘trap’’ question in the
survey so as to detect those who do not fully follow the
survey’s instructions, thus violating the contractual obligation of a survey respondent toward the market research
company and its clients. Prior to joining a market research
panel, respondents agree to provide truthful and wellconsidered answers to all survey questions. In return, they
receive study-specific and membership incentives (PayPal,
cash, gift certificates, and products).
Given our interest in workplace unethical behavior, we
expanded the set of control variables to include perceptions
of organizational justice which, in addition to self-construal, may influence levels of workplace unethical
behavior (Johnson and Lord 2010). Also, we included a
measure of the individual’s susceptibility to the social
desirability bias.
Method
Participants and Procedure
Six hundred and seven US-based full-time employees with
at least 2 years of work experience were recruited online
through CT Marketing Group, a marketing research company. The sample was 45% male, average age was 43.
Eight percent had a junior college degree at a minimum,
including 19% who have completed graduate studies. The
majority of participants were Caucasian (80%). Asian
Americans, African-Americans, and Hispanics constituted
6.6, 5.6, and 5.1% of the sample, respectively. Average
work experience amounted to 19 years. A variety of
occupations was represented, the most frequent being
management (11%); education, training and library (11%);
computer and mathematical (10%); office and administrative support (10%); healthcare (7%); and business and
financial operations (7%).
Respondents completed an online survey. They
answered demographic and self-construal questions first.
We then collected measures of positive and negative affect,
ethical orientation, workplace unethical behavior, perceived organizational justice and finally, social desirability
measures. A trap question was placed half-way through the
survey. Respondents were asked to choose ‘‘2’’ on the
7-point agreement–disagreement scale they used to
respond to previous questions. Eighty-six participants
(14%) failed to make the right choice.
Study 3
Predictor and Criteria Measures
We conducted Study 3 to test our hypotheses about the
effects of self-construal on unethical behavior among
adults. Moreover, as participants completed a survey about
their behaviors at work, we monitored for potential survey
Self-construal Self-construal was measured using the levels
of self-concept scale (Johnson and Lord 2010; Johnson
et al. 2006). Participants indicated how well 15 statements
(5 items per dimension of self-construal) described them on
123
456
a 1–7 scale (1 = strongly disagree; 7 = strongly agree).
All three dimensions of the self-construal scale exhibited
good reliability (independent a = .86, relational a = .90,
collective a = .89). Again, to confirm the three-dimensional nature of the self-construal measure, we conducted a
series of CFAs. The three-factor model fit was acceptable
(CFI = .94, SRMR = .08, RMSEA = .07), with all indicator loadings significant and above .40. Notably, the
above analysis included individuals who deviated from the
survey’s instructions. Model fit was nearly identical when
those who deviated were excluded from the above analysis.
Thus, survey unethical behavior did not affect the validity
of the three-factor model. Finally, as in the previous study,
the fit of the one factor model in which independent,
relational, and collective dimensions all loaded on a single
factor had a very poor fit (CFI = .67, SRMR = .16,
RMSEA = .19).
Unethical behavior Unethical behavior was measured
using Treviño and Weaver (2001) scale. Participants
reported how often over the past year they engaged in
specific behaviors on a 1–7 scale (1 = never; 7 = daily).
Items included: ‘‘Unauthorized personal use of company
materials or services’’ and ‘‘Falsifying time/quality/quantity reports’’ (a = .95).
Survey cheating A dummy variable was used to document instances of respondents answering the trap question
correctly (no cheating) or incorrectly (cheating).
I. Cojuharenco et al.
Schminke (2009). Participants expressed their degree of
agreement with each of the items on a 1–7 scale
(1 = strongly disagree; 7 = strongly agree). Items included ‘‘Overall, I am treated fairly by my organization’’ and
‘‘In general, I am able to count on my organization to be
fair’’ (a = .97).
Demographic variables We used gender, age, work
experience and racial background (1 for Caucasian, and 0
otherwise) as control variables.
Results
Descriptive statistics, scale alphas, as well as inter-correlations between study variables are presented in Table 4.
We analyzed the relationship between self-construal and
the dependent variables of unethical behavior and survey
cheating using two hierarchical regressions. In the first
step, we entered the demographic variables of gender, age,
work experience, and racial background. In the second
step, we entered social desirability and organizational
justice. In the third step, we entered trait positive and
negative affectivity. In the fourth step, we entered measures of utilitarian and formalist ethical orientation.
Finally, in the fifth step we entered the three dimensions of
self-construal: independent, relational, and collective.
Unethical behavior and survey cheating were the dependent variables, respectively. Table 5 reports the results for
both hierarchical regressions.
Alternative Predictor Variables
Workplace Unethical Behavior
Positive/negative affect The PANAS (20 items) was used
to measure trait positive and negative affect (Watson et al.
1988). Participants indicated to what extent they generally
felt the emotions and feelings described by the items of the
PANAS on a 1–7 scale (1 = very slightly or not at all;
7 = extremely). (PA a = .93; NA a = .93).
Ethical orientation The 20-item character traits version
of the MEV was used to assess ethical predispositions
(utilitarian and formalist) (Brady and Wheeler 1996).
Participants indicated the extent to which they identify a
series of adjectives that describe others as being important
to them (1 = not at all; 7 = very important) (Utilitarian
a = .87; Formalist a = .87).
Social desirability Susceptibility to the social desirability bias was measured using Strahan and Gerbasi’s
(1972) version of Marlow-Crowne social desirability scale
(11 items). Respondents indicated whether the items of the
scale were true or false. Items included ‘‘No matter who
I’m talking to, I’m always a good listener’’ and ‘‘I’m
always willing to admit it when I make a mistake’’
(a = .68).
Organizational justice Perceptions of organizational
justice were measured using three items from Ambrose and
123
Consistent with Hypothesis 2, relational self-construal was
related negatively to unethical behavior (b = -.27 (.06),
p .01); whereas, Hypotheses 1 and 3 (independent and
collective self-construal) were not supported. The effect of
relational self was robust to controlling for the effects of
gender, years of work experience, social desirability bias,
perceptions of organizational justice, negative affect, positive affect, and formalist and utilitarian ethical orientation.
Survey Cheating
Consistent with Hypothesis 2, relational self-construal
explained additional variance in the proclivity to engage in
survey cheating (b = -.10 (.02), p .01).
Gender Differences
To mirror the analyses we conducted in Study 1, we used
the SPSS macro for multiple mediator models created by
Preacher and Hayes (2008) to examine whether self-construal mediated the effect of gender on workplace unethical
behavior and survey cheating (Table 6).
5.83
5.59
4.82
2.71
5.37
5.47
1.76
1.14
8. Relational self
9. Collective self
10. Positive affect
11. Negative affect
12. Utilitarian
13. Formalist
14. Workplace unethical
behavior
15. Survey cheating
* p .05, ** p .01
N = 607
5.33
4.35
.62
5. Social des.
6. Org. fairness
7. Independent self
.20
4. Race (0 = W; 1 = Oth)
19.2
3. Work experience
.45
43.1
M
2. Age
1. Gender (0 = F; 1 = M)
Variables
.35
1.20
.90
.92
1.21
1.09
1.05
1.0
1.47
1.34
.22
.40
11.4
10.8
.50
SD
.00
.06
.07
.02
.07
.14**
-.06
.03
-.01
.08
-.04
-.11**
-.01
.10*

1
.75**
-.17**
-.24**
.25**
.18**
-.24**
.13**
.15**
.15**
.10*
-.16**
.23**
-.24**

2
-.21**
-.24**
.25**
.17**
-.26**
.07
.15**
.14**
.13*
-.17**
.14**
-.23**

3
.02
.13**
.02
.06
.07
-.05
.01
.04
.09*
.02
-.04

4
.65
-.09*
.29**
.25**
.21**
-.29**
.24**
.17**
.17**
.23**
-.23**
5
Table 4 Descriptive statistics for Study 3 variables with internal reliabilities on the diagonal
.29**
.40**
.32**
.97
.03
-.21**
-.25**
.35**
.38**
-.33**
6
.09*
.13**
.08*
.22**
.24**
.23**
.22**
.14**
.86
7
.37**
.75**
.90
-.41**
-.39**
.65**
.54**
-.26**
8
.89
.50**
-.32**
-.33**
.65**
.63**
-.29**
9
-.04
-.07*
.53**
.64**
-.12**
.93
10
.42**
.57**
-.28**
-.29**
.93
11
-.25**
-.27**
.82**
.88
12
-.33*
-.30**
.87
13
.61**
.95
14

15
Self-Construal and Unethical Behavior
457
123
458
I. Cojuharenco et al.
Table 5 Study 3 results of hierarchical regression analyses on dependent variables
Independent variables
Step 1
Step 2
Step 3
Step 4
Step 5
Unethical behavior as a dependent variable
Gender (1 = M, 0 = F)
Age
.36(.09)**
.33(.08)**
.29(.08)**
-.01(.01)
.37(.10)**
-.01(.01)
.36(.09)**
.00(.01)
.00(.01)
.00(.01)
-.01(01)
Work experience
-.02(.01)**
-.02(.01)**
-.01(.01)
-.01(.01)
Race (0 = W; 1 = Oth)
-.01(.12)
.07(.12)
.06(.10)
.04(.10)
.04(.10)
Social desirability

-1.20(.21)**
-.69(.19)**
-.67(.19)**
-.74(.19)**
Organizational justice

-.14(.03)**
-.03(.03)
-.01(.03)
.01(.03)
Positive affect


.02(.04)
.12(.05)*
.15(.05)**
Negative affect


.49(.04)**
.47(.04)**
.45(.04)**
Utilitarian



-.09(.08)
-.07(.08)
Formalist
Independent






-.15(.08)

.05(.08)
-.02(.03)
Relational




-.27(.06)**
Collective




-.05(.06)
2
2
R /DR
.09/.09**
.18/.09**
.37/.20**
.39/.02**
.43/.04**
Survey cheating as a dependent variable
Gender (1 = M, 0 = F)
.06(.03)*
.06(.03)*
.06(.03)*
.03(.03)
.02(.03)
Age
.00(.00)
.00(.00)
.00(.00)
.00(.00)
.00(.00)
-.01(.00)**
-.01(.002)*
.004(.002)*
.00(.00)
.00(.00)
Work experience
Race (0 = W; 1 = Oth)
Social desirability
.02(.04)
.02(.03)
.00(.03)
.00(.03)

.01(.04)
-.04(.07)
.07(.06)
.10(.06)
.09(.06)
-.02(.01)*
-.01(.01)
Organizational justice

-.04(.01)**
Positive affect


Negative affect


.10(.01)**
.09(.01)**
Utilitarian



.01(.03)
.01(.03)
Formalist



-.12(.03)**
-.05(.03)
Independent
Relational








.01(.01)
-.10(.02)**
Collective



R2/DR2
.05/.05**
.09/.04**
The relationship between gender and workplace unethical behavior was significantly mediated by the relational
self (ab path = .04, 95% Bca CI = .01, .10). The relational
self also mediated the relationship between gender and
survey cheating (ab path = .13, 95% Bca CI = .01, .31).
For survey cheating, the mediation was full (c0 path =
-.04, z = -.12, p = .91).
Discussion
Study 3 results are consistent with our findings in previous
studies albeit we considered more varied forms of unethical
behavior by working adults. For example, participants
reported how often over the past year they engaged in
unethical behavior at work. We included a measure of
social desirability bias and perceptions of organizational
justice as additional control variables in all analyses of
123
.01(.01)
.05(.02)**
.11(.01)**

.20/.12**
.00(.01)
.05(.02)**
-.01(.02)
.26/.06**
.30/.05**
workplace unethical behavior. Levels of relational self
related negatively to unethical behavior. Similarly, levels
of relational self related negatively to survey cheating
observed unobtrusively through the use of a trap question.
Moreover, men reported higher levels of unethical behavior
and were more likely to cheat than women, and levels of
relational self mediated this gender difference either partially (in the case of workplace unethical behavior) or fully
(in the case of survey cheating).
It was important to test our research hypotheses in a
sample of employed adults. For example, we did not find
support for Hypotheses 1 and 3 although coefficient estimates for the effects of levels of independent and collective
self had the sign (positive and negative, respectively)
predicted by our research hypotheses. The lack of statistical
significance for these coefficient estimates (compared to
Study 1 findings) may be due to the higher situational
Self-Construal and Unethical Behavior
459
Table 6 Self-construal mediation of the effects of gender on dependent variables
a path coef.
b path coef.
ab path coef.
95% Bca CI
Lower
Upper
Unethical behavior
Independent self
.2183*
-.0212
-.0046
-.0243
.0046
Relational self
-.1526*
-.2670**
.0407
.0085*
.0952
Collective self
-.0846
-.0544*
.0046
-.0028
.0304
Survey cheating
Independent self
.2183*
.4428*
.0967
.0002
.2794
Relational self
Collective self
-.1526*
-.0846
-.8441**
-.2902
.1288
.0271
.0122*
-.0190
.3113
.1552
N = 607; 5,000 bootstrap samples. All analyses control for age, years of work experience, race, social desirability, perceptions of organizational
fairness, affect, and ethical frameworks. BCa CI bias corrected and accelerated bootstrapping confidence intervals. Confidence intervals not
containing zero are interpreted to be significant
* p .05, ** p .01
strength (Weiss and Adler 1984) of the work setting,
diminishing the ability of individual difference variables to
predict behavior. Importantly, the effect of levels of relational self predicted behavior even in this ‘‘stronger’’ setting and provided an explanation for the observed gender
differences.
General Discussion
We showed that self-construal is not only an important
predictor of unethical behavior but also a mediator of the
relationship between gender and unethical behavior. We
tested our research hypotheses in three studies, focusing on
unethical behavior by undergraduate students (Studies 1
and 2) and working adults (Study 3). The measures of
unethical behavior we employed were both self-report
(Studies 1 and 3) and directly observable (Studies 2 and 3).
Across a variety of settings, from student life to the
workplace, one dimension of self-construal—the relational
self—was consistently associated with a lower likelihood
of engaging in unethical behavior.
Overall, our findings contribute to the growing literature
on the effects of relationality (Gelfand et al. 2006), but also
offer a novel variable to consider in research on unethical
behavior. These findings suggest that, for example, gender
differences in unethical behavior may be manageable. For
example, men and women may be more or less unethical
depending on the salience of their relational self. Previous
research on self-construal shows that although the self is
three-dimensional, some facets of it may be dormant,
whereas others are salient and affect individual judgment
and behavior (Hannover et al. 2006). Chronic differences in
self-construal are frequently altered in laboratory settings
using a variety of priming manipulations (e.g., Brewer and
Gardner 1996; Hogg and Turner 1985; Oyserman and Lee
2008). Similarly, self-construal can be altered by features
of situations that men and women face. For example,
interdependent job tasks may bolster the salience of one’s
role in dyadic relationships. Our work indicates doing so
might be an effective way of curbing unethical behavior.
Because self-construal reflects a subjective self-definition, it is important to note that our findings compliment
in important ways previous theorizing in the literature
that explores unethical behavior as a function of the
individual’s objective position in a social network (Brass
et al. 1998), or similarity with others (Jones 1991). Like
self-construal, these objective factors contribute to perceptions of independence versus interdependence. Not
surprisingly then, the effects of greater levels of relational
self associated with perceived interdependence are similar
to the effects postulated for objective interdependence
and psychological closeness due to high similarity with
others.
As is often the case, however, ‘‘our strength grows out of
our weaknesses,’’ and research shows that individuals with
higher levels of relational self are also more likely to be
prone to the influence of close others who might be
unethical (Gino et al. 2009). They might more likely engage
in unethical behaviors when the well-being of a close other
is at stake (Wiltermuth 2010). Because organizational settings are replete with occasions for individuals to consider
unethical acts in the absence of influence attempts by the
unethical and/or the need to ‘‘rescue’’ someone, we focused
on the relationship between self-construal and unethical
behavior, ceteris paribus. Overall, our findings contribute to
a more balanced view of the effects of self-construal,
shedding light on positive consequences of being relational,
in terms of avoiding unethical behaviors that are harmful to
the ongoing social relationships.
123
460
Acknowledgment This research was funded by Grant PTDC/EGEGES/098856/2008 of the Portuguese Foundation for Science and
Technology (FCT) with funds co-financed by the state budget through
the program PIDDAC.
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
International Journal of Management & Information Systems – Third Quarter 2015
Volume 19, Number 3
Current Trends Of Unethical
Behavior Within Organizations
Octavia A. Askew, University of Phoenix, USA
Jeffrey M. Beisler, University of Phoenix, USA
Jetonga Keel, University of Phoenix, USA
ABSTRACT
A substantial body of research reveals that unethical behavior continues to be a concern in the
workplace. This article presents information on the prevalence of unethical behavior, antecedents
of unethical behavior, the organizational environment, cognitive moral development, and trends of
unethical behavior over a 3 year span. Findings of earlier studies generally agree that unethical
behavior has a negative effect in the workplace. The greatest research effort on this issue has
been to continue to conduct studies within organizations, identifying if the issue of unethical
behavior is improving or stagnant.
Keywords: Ethics; Unethical Behaviors; Antecedents of Unethical Behavior; Behavioral Ethics
E
thical and unethical behaviors are behaviors that occur within organizations by employees on a daily
basis (Jex & Britt, 2008). Ethical behavior is the behavior companies seek to drive performance and
success. Companies are highly concerned about unethical behavior for a number of reasons. Decreases
in organizational performance, financial losses, reputational damage, safety concerns, and a loss of customers are all
concerns that are connected with unethical behavior. Understanding the why behind these types of behaviors could
possibly dictate the success of a given organization.
Therefore, within this paper, the areas of focus include understanding categories of antecedents and the
most important category of antecedents with regard to unethical behavior in organizations. Abiding by standards
and guidelines are imperative components to ensure that unethical behaviors do not occur within the workplace.
Ethical actions within organizations is employee behavior that is just and above constitutional laws (Reiss & Mitra,
1998). Companies want employees to exhibit ethical behavior in order to produce outcomes that are beneficial. In
contrast, unethical behavior is an area of great concern. Unethical behavior violates generally accepted moral
norms, is widespread, and the costs involved are high (Kaptein, 2011).
According to Gomez-Mejia and Balkin (2002), various countries follow different norms and internationally
an important concern is defining ethical behavior. Business ethics serve as guidelines or standards for an
organization when making decisions. When guidelines or standards are not present within the workplace, the
organization is not on one accord in terms of the principles that are important and the criteria that determines
unethical behavior (Gomez-Mejia & Balkin, 2002). The purpose of this review is to explore current trends within
organizations concerning unethical behavior. A discussion of ethical and unethical behavior within organizations is
presented followed by an analysis of several studies relating to current trends within organizations.
THE “WHY” BEHIND UNDERSTANDING ETHICAL BEHAVIOR
According to McIntire and Miller (2007), ethics focuses on processes and topics that guide the decision
making process in terms of what is right. Ethical standards are a group of professional process guidelines or codes
for doing what is considered the right practice (McIntire & Miller, 2007). Thus, ethics are important in order to
ensure that processes and practices are doing what is considered to be morally right. Ethics differ from organization
to organization based on the organization’s specific ethical values and issues. According to Cascio and Aguinis
(2011), employers have ethical responsibilities, which are often demonstrated through the execution of company
Copyright by author(s); CC-BY
107
The Clute Institute
International Journal of Management & Information Systems – Third Quarter 2015
Volume 19, Number 3
ethics programs. Ethical actions are not dictated by specific and strict guidelines; it changes and evolves in response
to social standards and the wishes and interests of those aided by the profession (Cascio & Aguinis, 2011).
Business ethics are different from laws because in some circumstances it may not be illegal to engage in
unethical behavior (Gomez-Mejia & Balkin, 2002). According to Hoyk and Hersey (2009), an organization in
which coworkers ignore, justify, or accept unethical behavior, is supporting the viewpoint of the transgressor. When
moral standards are accepted by the majority of the group and a behavior or action by an employee exhibits
behaviors or actions that do not reflect what is considered to be the norm, then the group would deem the behavior
or action unethical (Kish-Gephart, Harrison, & Trevino, 2010). Unethical behaviors that occur most frequently
within the workplace setting are covering up problems, short-cutting quality of work, abusing sick days, and lying to
customers (Gomez-Mejia & Balkin, 2002).
Bowditch, Buono, and Stewart (2007) posit there are growing numbers of occurrences when employees
experience situations where peers and supervisors encourage unethical behavior. For instance, unethical behavior
may be an employee looking in the opposite direction of a wrongdoing, failure to report wrongdoings, or directly
engaging in unethical activity (Bowditch et al., 2007). Cheney (2008) stated it is essential to understand how
organizational cultures suppress or promote certain ethical practices (Bisel, Kelley, Ploeger, & Messersmith, 2011).
It is imperative to condemn unethical behavior and discourage the imitative practices, reducing the risk of an
organizational culture that promotes political backstabbing that drives away talent and takes away the energy of the
remaining employees (Gomez-Mejia & Balkin, 2002).
When employees do not follow the written standards of the organization, the behavior impedes the
organization’s ability to meet corporate goals making understanding ethical behavior in organizations essential.
Unethical behavior can impact the organization financially. For example, counterproductive behavior is a type of
unethical behavior where actions go against the organization’s goals (Jex & Britt, 2008). Forms of counterproductive
behavior include turnover, ineffective job performance, absenteeism, and unsafe behavior and additionally less
common forms such as violence, theft, substance abuse, and sexual harassment (Jex & Britt, 2008). These actions
impact the organizations financial bottom-line and can cost the organization thousands of dollars each year (Jex &
Britt, 2008). Thus, it is critical to understand unethical behavior in organizations.
Unethical behaviors lead to detrimental consequences for others through ignoring rules, standards,
regulations, and company guidelines (Tonus & Oruç, 2012). The damaging consequences slow performance and
growth. Unethical actions foster an environment of conflict, disrupt the company culture, and minimalize employee
commitment, performance, and inspiration (Tonus & Oruç, 2012). When employee commitment, performance, and
motivation decrease the organization suffers significantly. As a result, companies want to prevent unethical
behaviors and to promote ethical behaviors. The best option is through understanding the driving forces behind
unethical decision-making in order to predict behavior.
PREDICTING UNETHICAL BEHAVIOR: THE ANTECEDENTS
According to Kish-Gephart, Harrison, and Trevino (2010), the three most important precursors of unethical
behavior are the individuals, the ethical issue itself, and the organizational environment. The individual can be an
antecedent to unethical behavior when considering the individual differences or characteristics of that person and
how these differences influence unethical choices at work. Results presented from research conducted by KishGephart, Harrison, and Trevino (2010) state that individuals who make poor desions because of negative influences,
think more for themselves than the group, exhibit counterproductive actions, avoid consequences for their actions,
and fail to make the connection that their actions cause chain reactions will more than likely act in a manner that is
unethical. Therefore, individuals who demonstrate behavior or actions that reflect negative characteristics are
considered to be more prone to behavior that is unethical.
Additional antecedents of unethical behavior include moral identity, cognitive moral development, moral
philosophies, and empathy (Moore, Detert, Trevino, Baker, & Mayer, 2012). Moral identity refers to the indivdiuals
reasonings skill, intuition, and perception, which represents their cognitive ability (Woo Jin & Winterich, 2013).
Virtuosity refers to moral traits, honesty, compassion, and fairness (Woo Jin & Winterich, 2013). Cognitive moral
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The Clute Institute
International Journal of Management & Information Systems – Third Quarter 2015
Volume 19, Number 3
development is the process of developing integrity, virtue, or character intentions (Andreoli & Lefkowitz, 2009).
Moral philosophies are basic beliefs about how to deal with ethical decision-making. Empathy is the ability to
understand how others feel. Each antecedent offers insight into why people make unethical decisions.
Individual qualities, organizational characteristics, and cultural affects are categories of antecedents for
predicting unethical behavior (Rusaw, 2001). Prominent qualities of an individual can be understood by the theories
of moral development. Personal attributes to moral development occur as individuals mature in terms of education
and experience, which provides the development for greater morality (Rusaw, 2001). Self-mastery is another
component of moral development and as individuals mature they will develop self-control enabling the individual to
self-reflect on actions and be able to adapt the actions to particular situations (Rusaw, 2001).
Rusaw (2001) posit organizational characteristics that hinder ethical development are organizational
structure, organizational climate, job characteristics, and supervisory style. When the organization has a clear
mission, ethical behavior within the organization may increase (Rusaw, 2001). According to Rusaw (2001), jobs that
promote risk-taking to attain goals will foster behavior that is ethical if the risk taking is legitimate. Rusaw (2001)
assert the cultural norms of an organization can inhibit consequently a member’s ethical development.
Organizations must realize the factors that influence ethical growth including the level of responsibility, potential to
take risks, decision making authority, and the amount of accountability (Rusaw, 2001). Cultural affects consist of
belief systems, which develop from family, religion, values, and school socialization (Rusaw, 2001). Rusaw (2001)
stated, when the atmosphere consists of trust, fairness, and personal security, individuals will learn how to
appropriately make and enforce rules.
ORGANIZATIONAL ENVIRONMENT NAMED MOST IMPORTANT ANTECEDENT
Of the three categories of antecedents to unethical behavior, it is argued the most important category in
understanding unethical behavior is the organizational environment. The individual and the ethical issue itself are
antecedents of unethical behavior, but can be considered factors that cannot be changed. However, the organization
environment can be changed in order to influence the behavior of employees. The organizational environment
includes the ethical climate, culture, and codes of conduct established within the organization. Ethical climate is
based on what the majority group considers to be ethically sound and what the group has collectively identified to be
issues that are deemed unethical in which the group is to resolve. The shared viewpoints of ethical appropriateness
and the approach to addressing ethical issues in the company is the ethical climate (Peterson, 2002).
According to Bowditch, Buono, and Stewart (2007), organizational climate is about measuring the extent to
which individual’s expectations of working within an organization are met. Organizational climate is a perception of
measurement and includes job performance, satisfaction of the job, interaction within groups, and withdrawal
behaviors (Bowditch, Buono, & Stewart, 2007). The commonality of beliefs which are shared and actions which
reflect the common beliefs demonstrates an ethically sound culture (Key, 1999). Corporate codes of conduct use
instruments to re-direct an employee’s action and set in place characteristics that exhibit responsibility within the
organization (Erwin, 2011).
According to Winthanage (2010), a code of ethics or conduct is a statement of central company values
supporting best practices, behaviors, and standards and although each code of ethics may vary from company to
company, there are several ethics that are held in common. Trust, honesty, fairness, respect, and equality are
common ethics and adhering to these qualities is considered to be ethical behavior while straying from these
qualities would be considered unethical behavior (Winthanage, 2010). It is not enough to have a code of ethics, but
rather enforce the policies established. According to Winthanage (2010), standards and guidelines are to be
established to prevent an environment that promotes a workplace that is unethical. Establishing and enforcing the
code of conduct or ethics will help in creating an organizational environment that encourages ethical behavior
amongst employees.
Research from Key (1999) suggests that the individual employee may be influenced by certain behaviors in
the workplace changing their perception of ethical behavior. Additionally, the way in which an employee is treated
will dictate their actions and behaviors (Key, 1999). Thus, how an employee views the culture of an orga…
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