Developing a Measure of Unethical Behavior
in the Workplace: A Stakeholder Perspective
RSM Erasmus University, P.O. Box 1738, Rotterdam, The Netherlands
To date, only one empirically tested measure of the observed frequency of unethical behavior in
the workplace exists. This widely used measure focuses on intraorganizational cheating and thus
covers only a limited part of the much broader spectrum of unethical behaviors in the work-
place. Given the importance of a valid measure, this article uses stakeholder theory as a con-
ceptual basis to develop a broader and multidimensional measure of unethical behavior in eight
consecutive steps. Exploratory factor analysis generates five subscales comprising 37 items of
unethical behavior primarily related to financiers, customers, employees, suppliers, and society.
Confirmatory factor analysis demonstrates that a five-factor model has a superior fit to a one-
factor model. The subscales display good internal reliability. Preliminary evidence of nomolog-
ical and criterion-related validity is also provided.
Keywords: business ethics; unethical behavior; measure development; stakeholder theory;
Corporate scandals, such as fraudulent bookkeeping, payment of bribes, and the misuse
of confidential information have generated widespread interest in unethical behavior in busi-
ness organizations (Goodpaster, 2007; Paine, 2003). Unethical behavior threatens the repu-
tation (Van Riel & Fombrun, 2007), financial performance (Orlitzky, Schmidt, & Rynes,
2003) and even the continuity (Grant & Visconti, 2006) of business organizations.
Stakeholders, including shareholders, governments, and nongovernmental organizations are
therefore placing increasing pressure on business organizations to better manage unethical
behavior in the workplace (Treviño, Weaver, & Reynolds, 2006).
Author’s Note: Thanks to three anonymous reviewers for their very helpful comments on a previous version of this
article, as well as to Russell Cropanzano for his excellent editorial guidance.
Journal of Management, Vol. XX No. X, Month XXXX xx-xx
© 2008 Southern Management Association. All rights reserved.
Journal of Management OnlineFirst, published on May 20, 2008 as doi:10.1177/0149206308318614
Copyright 2008 by Southern Management Association.
Managing unethical behavior in the workplace raises several pressing questions. What
constitutes unethical behavior? And what types of behaviors can be defined as unethical?
What is the actual and potential frequency of unethical behavior in the workplace? And does
the frequency of unethical behavior vary by organization, industry, job function, and
country? What are the causes and consequences of unethical behavior? And what actions and
interventions are effective in managing unethical behavior? To be able to answer these ques-
tions, sound measures for assessing unethical behavior are required.
Newstrom and Ruch (1975) were the first and, to date, the only ones to develop a measure of
observed unethical behavior in the workplace. Their unidimensional survey measure consists of
17 items, such as taking longer than necessary to do a job,claiming credit for someone else’s
work, and calling in sick to take a day off. Their respondents, 121 managers participating in an
executive development program, were asked how often they observed unethical behavior in their
organization. Despite their great contribution, the measure has at least three limitations. First, it
includes only a part of the spectrum of unethical behaviors. As Newstrom and Ruch themselves
stated, they only focused on “managerial ethics and especially ‘intraorganizational cheating’ . . .
excluding . . . major crimes and other social issues that typically arise at higher organizational lev-
els or between organizations” (1975: 30). Second, the item selection process of the measure—
which is the basis of a good measure (Schriesheim, Powers, Scandura, Gardiner, & Lankau,
1993)—was not very transparent. The only explanation they gave was that previous studies and
reports on managerial ethics were reviewed to develop a master list of possible items, which was
then screened to produce a final list consisting of seventeen items. Third, they did not examine
the internal reliability or the nomological and criterion-related validity of the measure.
Despite these limitations, many scholars have used Newstrom and Ruch’s measure to
assess unethical behavior in the workplace without any further testing (e.g., Akaah, 1992;
Ferrell & Weaver, 1978; Izraeli, 1988; Kantor, 2002). Whereas some added or removed items
without providing conceptual or empirical evidence (e.g., Peterson, 2002; Treviño,
Butterfield, & McCabe, 1998; Treviño & Weaver, 2001; Weaver & Treviño, 1999), others
scaled down the list of items or clustered the items by means of exploratory or confirmatory
factor analyses (e.g., Akaah, 1996; Akaah & Lund, 1994; Akaah & Riordan, 1989; Cardy &
Selvarajan, 2004; Jackson, 2001; Jackson & Artola, 1997; Zey-Ferrell & Ferrell, 1982; Zey-
Ferrell, Weaver, & Ferrell, 1979).
In the absence of a valid list of items that covers the broader spectrum of unethical behav-
ior in the workplace, testing it is useless as adequate content-validity is a necessary precon-
dition for measure validity (Schriesheim et al., 1993). Simply adding or removing items
without conceptual or empirical research is not a sound basis for research either, as scales
have certain psychometric and conceptual properties which require use of the complete
scales as standardized (Fleishman, 1973). Therefore, as will be demonstrated in this article,
we first need to systematically generate items covering the broader spectrum of unethical
behaviors before we can test and apply this new measure.
This article commences with defining unethical behavior. Following this, stakeholder
theory is advanced as conceptual basis for developing a measure and subscales of unethical
behavior. This is followed by a discussion of eight interconnected steps by means of which
the new measure was developed. The article concludes with a discussion of the scientific and
practical implications and limitations of the new measure.
2 Journal of Management / Month XXXX
Understanding Unethical Behavior in the Workplace
The development of a measure requires at least a tentative theoretical model to guide the
process (Hinkin, 1998). In this regard, we face four challenges. The first is to define unethical
behavior in general and to relate it to similar but distinct constructs. The second is to establish
the basis on which behaviors can be considered unethical. The third challenge is to explore what
a measure of unethical behavior in the workplace may look like. The fourth challenge is to iden-
tify a method for generating the items that cover the construct of unethical behavior.
A General Definition of Unethical Behavior
Taylor defines ethics as an “inquiry into the nature and grounds of morality where the
term morality is taken to mean judgments, standards, and rules of conduct” (1975: 1).
According to Beauchamp and Bowie (1983), ethics pertains to good and evil, right and
wrong, and thus what we ought and ought not do. The domain of business ethics concerns
the ethics of business organizations and of individuals and groups in business organizations.
Synthesizing 38 different definitions, Lewis (1985) defines business ethics as comprising the
rules, standards, principles, or codes giving guidelines for morally sound behavior. Ethical
behavior implies adherence to these moral norms whereas unethical behavior implies the
violation of these moral norms. Or, as Jones (1991) puts it, unethical behavior in and of busi-
ness organizations is behavior which is morally unacceptable to the larger community.
The multitude of studies on issues related to unethical behavior in and of business organiza-
tions employ a range of other terms. Vardi and Weitz (2004) focus on misbehavior; Kacmar and
Carlson (1997) on political behavior; Tyler and Blader (2005) on rule breaking; Sutherland
(1940) on criminal behavior; Neill, Stovall, and Jinkerson (2005) on noncompliance; Hollinger
and Clark (1982) on workplace deviance; Analoui (1995) on sabotage; Mangione and Quinn
(1975) on counterproductivity; Ashforth and Anand (2003) on corruption; and Giacalone and
Greenberg (1997) on antisocial behavior. A salient feature of unethical behavior is that it con-
cerns misbehaviors where fundamental interests are at stake. That is, not all kinds of misbehav-
ior or political behavior, for example, are unethical (Velasquez, 2005). In contrast with rule
breaking, criminal behavior and noncompliance, unethical behavior is not limited to violations
of official and explicit standards, rules and laws, but includes violations of informal and implicit
norms. Unethical behavior in the workplace is also not limited to violations of—formal and
informal—organizational norms. Bennett and Robinson (2000) define workplace deviance,
including sabotage, as behavior that violates significant organizational norms. Rather than local
conventions such as organizational norms, unethical behavior primarily concerns moral norms
that are acceptable to the larger community (Vardi & Weitz, 2004). Finally, unethical behavior
does not necessarily bring or intend to bring harm. This is in contrast with, for example, the con-
struct of counterproductivity, corruption, and Giacalone and Greenberg’s (1997) definition of
antisocial behavior as any behavior that brings or intends to bring harm to the organization or its
stakeholders. In addition to the consequentionalist perspective of unethical behavior, the deon-
tological or Kantian view holds that behavior can be wrong in itself, irrespective of the intended
or unintended consequences of that behavior (Velasquez, 2005).
Kaptein / Unethical Behavior in the Workplace 3
The importance of drawing a distinction between unethical behavior and other related
constructs is that for the latter some well-developed measures are available; Bennett and
Robinson (2000) elaborately developed and tested a measure of workplace deviance, as did
Kacmar and Carlson (1997) for political behavior in organizations. Despite the usefulness of
these measures, we cannot simply adopt them to assess unethical behavior in the workplace
given the differences of domain. As noted by Treviño and Weaver (2003), subtle differences
between types of behaviors may have significant consequences for its measurement, under-
standing and management.
A Basis for Considering Behavior as Unethical
Having provided a general definition of unethical behavior in the workplace and a brief
description of its distinction from related constructs still leaves the question as to whether
behavior in organizations can be defined as unethical at all. In order words, do moral norms
prevail in the business domain and on what basis can we define behaviors as unethical? This
question should be answered in the affirmative before we can proceed to establish what a list
of unethical behaviors may look like.
Many scholars have argued that business organizations and their employees bear ethical
responsibilities. A much-used theory to ground these ethical responsibilities is stakeholder
theory. Originally developed by Freeman (1984) and further developed by, for example,
Donaldson and Preston (1995), Jones and Wicks (1999), and Mitchell, Agle, and Wood
(1997), stakeholder theory holds that business organizations have multiple relationships with
all kinds of individuals, groups and organizations. These so-called stakeholders enter into a
relationship with business organizations to protect or promote their interests. Because a busi-
ness organization and a stakeholder become interdependent, mutual expectations arise
between both parties demanding that they engage with each others’ interests in an ethically
responsible manner. By viewing these relationships as implicit contracts, contractual busi-
ness ethicists, such as Donaldson and Dunfee (1999) and Van Oosterhout, Heugens, and
Kaptein (2006), demonstrate the moral legitimacy of these expectations. As a result, business
organizations bear an ethical responsibility to protect and promote the interests of their
stakeholders (and also vice versa).
To develop a valid measure of unethical behavior in the workplace, the broad range of eth-
ical responsibilities business organizations bear toward their stakeholders should be taken
into account. Such a diverse range of ethical responsibilities would probably lead to more
diverse types of unethical behavior than is the case with the very internally focused measure
of Newstrom and Ruch (1975). Such a new measure would be useful for examining unethi-
cal behavior as a more general phenomenon. Besides the use of the 17-item measure of
Newstrom and Ruch, most other empirical research into unethical behavior addresses one or
two unethical behaviors in isolation, such as theft (Hollinger & Clark, 1983), sexual harass-
ment (York, 1989), and accounting fraud (Gerety & Lehn, 1997). Including more items in a
measure of a behavioral construct, provides, as contended by Fisher and Locke (1992), more
valid and reliable information on the underlying theoretical construct. A broader measure
would also open the door to more comparable and comparative research.
4 Journal of Management / Month XXXX
Dimensions of Unethical Behavior
The question that follows is what a construct of unethical behavior would look like and
what dimensions or subscales can be expected. Existing measures of unethical behavior or
related constructs comprise different subscales. For workplace deviance, Bennett and
Robinson (2000) identify a subscale of deviant behaviors directly harmful to the organiza-
tion and a subscale of deviant behaviors directly harmful to other individuals within the orga-
nization. For organizational misbehavior, Vardi and Weitz (2004) identify five subscales:
intrapersonal, interpersonal, production, property, and political misbehavior. For Newstrom
and Ruch’s measure of unethical behavior, Akaah and Lund (1994) identify six subscales:
personal use, passing blame, bribery, falsification, padding expenses, and deception. In this
article, specific unethical behaviors are expected to be clustered around one of the stake-
holders groups whose interest is primarily at stake.
As the primary interest of stakeholder groups differs, the ethical responsibility of business
organizations toward each stakeholder group differs (Donaldson & Dunfee, 1999; Lawrence,
Weber & Post, 2005). An organization’s primary ethical responsibility toward financiers,
such as shareholders and other suppliers of capital, is to achieve a good return on invest-
ments. Toward customers, its primary ethical responsibility is to supply good quality prod-
ucts and services. Toward employees, the organization’s primary ethical responsibility is to
offer good working conditions. Toward suppliers, the primary ethical responsibility of the
organization is to seek mutually beneficial relationships. And toward society, including gov-
ernments, nongovernmental governments, and media, the primary ethical responsibility of
an organization is to act as a good citizen.
That a stakeholder has a primary interest does not exclude the possibility that it could
have interests that overlap with those of other stakeholders. For example, financiers, cus-
tomers, employees, and suppliers are increasingly showing an interest in the ethical respon-
sibilities of business organizations toward society (Van Tulder & Van der Zwart, 2006).
Financiers, for example, may also be interested in the way organizations address their ethi-
cal responsibilities toward other stakeholders because of its potential financial impact.
Numerous behavioral constructs, such as conflict and citizenship behavior, have been
classified in terms of their target (Bennett & Robinson, 2000; Green, 1997; Williams &
Anderson, 1991). Unethical behavior is supposed to be no exception to this. After all, the
relationships with stakeholders and the different ethical responsibilities of business organi-
zations toward stakeholders is the basis for defining what the applicable norms are and what
can consequently be regarded as unethical behaviors. Although stakeholders as such are not
the target, in the sense that the aim of unethical behavior is to intentionally harm or damage
the stakeholder, it is the primary interest of the stakeholder that is at stake. For example,
stealing or misappropriating organizational assets is a violation of the primary responsibility
of the organization toward financiers as it could undermine the financial performance of the
organization and therefore the interests of financiers.
A broad construct of unethical behavior consisting of clusters of specific behaviors per stake-
holder group would help us to better understand and prevent unethical behavior for at least three
reasons. First, behaviors within a cluster of unethical behaviors could have similar consequences
whereas individual clusters could have different consequences. For example, unethical behavior
Kaptein / Unethical Behavior in the Workplace 5
toward financiers, whether bookkeeping fraud or misappropriation of organizational assets,
would mostly damage the financial reputation of the organization (Mazzola, Ravasi, &
Gabbioneta, 2006), whereas unethical behavior toward employees, whether sexual harassment
or breaching employee privacy, would mostly damage the reputation of the organization as
employer (Van Riel & Fombrun, 2007). Second, behaviors within one cluster of unethical
behaviors could have similar causes whereas individual clusters could have different causes. For
example, heightened competition in the labor market may reduce unethical behavior toward
employees as organizations would have to do more to attract and retain employees, whereas
competition in the financial market may increase unethical behavior because of the pressure
organizations feel to fiddle with the books to create a more positive picture of their financial per-
formance (Grant & Visconti, 2006). Also, instead of speaking about one stakeholder culture
within a business organization, as Jones, Felps, and Bigley (2007) do, it is conceivable that the
organizational culture may differ per stakeholder group leading to different frequencies of
unethical behaviors per stakeholder group. For example, a customer-oriented culture does not
imply that the culture is also society or employee oriented (Blodgett, Lu, Rose, & Vitell, 2001).
Similar causes could mean that the frequencies of unethical behaviors within a cluster are inter-
connected and also exchangeable (Bennett & Robinson, 2000). Third, if different clusters of
behaviors exist each with different causes and consequences, it could suggest that similar mea-
sures can be employed to prevent unethical behavior within a certain cluster, whereas for dif-
ferent clusters, different measures could be required.
If not only the circumstances (e.g., causes and preventative measures) of unethical behav-
ior vary per cluster, but the circumstances also vary per situation such as by organization, job
function, and industry (Treviño & Weaver, 2003), we expect to find different frequencies of
each cluster of unethical behavior in these situations. At the same time, we anticipate that the
variance in the frequency of unethical behavior per similar situation shall be lower than
across different situations in this respect.
Business Codes as Source for Generating Items
Another question that arises is whether it is at all possible to develop a generally applic-
able measure of unethical behavior in the workplace. Does what can be considered as uneth-
ical behavior differ per organization or even per person? Or can we find a common set of
behaviors that can be considered unethical regardless of the situation?
On the one hand, as argued by Donaldson and Dunfee (1999), unethical behavior cannot
be reduced to a fixed set of behaviors. On the other hand, as Treviño and Weaver suggest, it
is not impossible to identify a list of unethical behaviors about which there is a significant
degree of social consensus:
Although there may be disagreement at the margins regarding what is and is not ethical business
conduct, most people agree about a wide range of behaviors that can be studied. Most large com-
panies have adopted business codes of ethics in recent years and, despite some company and
industry differences, these codes generally address similar issues with similar standards. As a
result, the business ethics researcher can stay very busy focusing on those ethical and unethical
behaviors about which there is a large degree of social consensus. (2003: 298)
6 Journal of Management / Month XXXX
Following the suggestion of Treviño and Weaver (2003), this article uses business codes
as input to generate a master list of unethical behaviors needed for the development of a mea-
sure of unethical behavior in the workplace.
A business code of ethics can be defined as “a written, distinct, formal document which
consists of moral standards which help guide employees or corporate behavior” (Schwartz,
2002: 28). Business codes of ethics, also called codes of conduct, are a self-regulatory instru-
ment for organizations. Although the implementation, and by implication, the effectiveness
of business codes has been the subject of much criticism (Cowton & Thompson, 2000; Sims
& Brinkmann, 2003; Somers, 2001), there is much agreement that business codes generally
cover the most important and relevant ethical norms that are applicable to business organi-
zations (Carasco & Singh, 2003; Donaldson & Dunfee, 1999; Kolk, Van Tulder, & Welters,
1999). Organizations install various checks and balances to ensure that their business code
of ethics includes the applicable ethical norms, or at least does not include norms that con-
flict with the interests and views of stakeholders and the community at large. Business codes
of ethics are often developed on the basis of an intensive consultation process with internal
and external stakeholders and with the help of academic experts and consultants (KPMG,
2008; Singh, 2006). As business codes of ethics are also often public documents, business
organizations will try to avoid introducing codes stakeholders disapprove of (Van Tulder &
Van der Zwart, 2006).
By analyzing the content of business codes, specific behaviors can be distilled that com-
panies and stakeholders view as unethical. As the number of business organizations with a
code increased rapidly in recent years (Bondy, Matten, & Moon, 2004; Waddock, Bodwell,
& Graves, 2002), an extensive list can be compiled. In view of the fact that a business code
usually applies to the behavior of all employees, the items generated are likely to be recog-
nizable and relevant to employees. An additional advantage of using business codes as a
source for identifying specific unethical behaviors is that developing a measure of unethical
behavior that corresponds with that which business organizations regard as unethical behav-
ior will promote its use by those organizations. Although using business codes may implic-
itly commit a researcher and research subjects to a particular normative stance, such a
commitment is not problematic if it is recognized as a description of what is typically viewed
as unethical in a particular social context (Treviño & Weaver, 2003).
In short, the development of a broad construct of unethical behavior in the workplace is
necessary and possible. This construct is expected to capture clusters of specific unethical
behaviors along the different stakeholder groups. Examining the content of business codes
can generate specific unethical behaviors which can form the foundation for developing and
testing a measure for unethical behavior.
Methods and Results
Developing a measure is a difficult and time-consuming process (Schmitt & Klimoski,
1991), which should be carried out by using multiple methods and samples (Hinkin, 1995,
1998; Schwab, 1980). As discussed below, a new measure of observed unethical behavior
was developed and tested in eight interconnected steps.
Kaptein / Unethical Behavior in the Workplace 7
Step 1: Item Generation
To generate an initial set of items, the behaviors that companies address in their business code
of ethics were used as input. Much research has been conducted into the content of business
codes of ethics (Cressey & Moore, 1983; Schlegelmilch & Langlois, 1990; White &
Montgomery, 1980). As the measure was to cover a broad spectrum of norms companies around
the world include in their codes, the research of Kaptein (2004), who was first in collecting and
analyzing the business codes of multinational companies, was used. Of the 200 largest compa-
nies in the world, 105 companies had a business code of ethics. These companies were head-
quartered in 11 different countries and in most cases had subsidiaries throughout the world. The
number of codes analyzed per country where company headquarters were based was United
States (40), France (10), Germany (10), Japan (23), Switzerland (5), England (4), Italy (3),
Netherlands (3), England/Netherlands (2), South Korea (2), England/United States (1), Canada
(1), and Sweden (1). Whereas some codes were developed recently, others had been developed
some decades ago and remained unchanged. The business codes of ethics collected were all ana-
lyzed independently by two researchers, resulting in 86 different behavioral items. Some fre-
quently included items were supplying high-quality goods (67%), observing relevant laws and
regulations (57%), and treating the natural environment with due care (56%). To avoid method
artifact, it is worth noting that although many of the companies use their responsibilities toward
stakeholders to structure their business code, many more structure their business codes differ-
ently, such as by business principle, core value, corporate asset, issue, or a combination of these
elements (Kaptein, 2004).
Although Treviño and Weaver (2003) note that business codes generally address similar
issues with similar norms, there are also some issues that are addressed by only a few com-
panies. To compile a general list of unethical behaviors, items that are addressed in 10% or
less of the business codes of ethics were eliminated. This rule of 10% is arbitrary, but the
main reason for introducing the threshold was to exclude items that are hardly included in
business codes of ethics. At the same time, an effort was made to avoid making the thresh-
old too high. In total, 35 items were dropped, such as no arms and weapons in the workplace
(1%), preventing harm to animals (2%), and timely payment of taxes (1%).
Although the study of Kaptein formulated all items in positive terms, for the present study
the remaining 51 items were reformulated by the author in negative terms as unethical. However,
not every positive responsibility has a clear opposite. For example, whereas companies see it as
their ethical responsibility to generate a profit, it is not unethical not to generate a profit
(Primeaux & Stieber, 1994). In reformulating the items into one or sometimes two negative
items, the challenge was to keep the descriptions relatively generic and applicable across orga-
nizations, occupations, sectors, and nations. Defining behaviors too narrowly can easily result in
a too extensive list of unethical behaviors, thus increasing the respondent burden and creating
problems of low base-rate. For example, discrimination against employees could be subdivided
into discrimination based on gender, age, nationality, race, ethnic background, creed, religion,
disabilities, and marital or parental status. The more specific the item, the lower its frequency,
and the greater the psychometric challenges in studying them. To prevent item wording effects
(Schriesheim & Eisenbach, 1995), I refrained from mentioning specific stakeholders in as many
items as possible. The result was 53 items of unethical behavior.
8 Journal of Management / Month XXXX
Step 2: Item Review
The remaining list of items was presented to 6 other business ethics scholars, 8 ethics offi-
cers, 11 business ethics consultants, and 20 business students to review it for redundancies
and unclear formulations. All items were rated for clarity using a 6-point scale ranging from
1 =Very Unclear to 6 =Very Clear. Participants also had to provide their interpretation of
every question, along with suggestions for improvement. All items that received an average
score of 4.0 or lower were reworded. The review led to 41, some slightly rephrased, items.
For example, the items intimidation, harassment, and threatening behavior; sexual harass-
ment; racism and racist insinuation; verbal abuse; and physical violence were consolidated
into the item engaging in (sexual) harassment and creating a hostile work environment (e.g.,
intimidation, racism, pestering, verbal abuse, and physical violence) as the separate items
lacked conceptual clarity. Four other business ethics scholars, 4 ethics officers, and 4 ethics
consultants were then asked to check whether the revised list of 41 items lacked significant
examples of unethical behavior and whether there were still unclear formulations. No ques-
tion had again a clarity score of 4.0 or less. However, four items were combined to create 2
new items, as some participants responded that it was difficult for them to distinguish
between them. For example, the items making improper political contributions to domestic
officials and making improper payments or bribes to foreign officials were combined into
making improper political or financial contributions to domestic or foreign officials. This
resulted in a list of 39 items of unethical behavior.
Other decisions that had to be taken concerned the object, the method, and the frequency
scale of measurement to be used. Although self-reported behavior may be more precise, it
was decided to focus on observed behaviors of others because of the significantly lower like-
lihood of social desirability response bias coming into play (Treviño & Weaver, 2003). Even
more so than measures of related constructs, the list of unethical behaviors includes severe
violations, the disclosure of which could have far-reaching repercussions for the responding
perpetrator. Furthermore, other reports corresponds with our level of analysis and definitions
of business ethics and business codes as unethical behavior that takes place within the orga-
nization, whether it is at individual, group, or organizational level (Vardi & Weitz, 2004).
Also, as shown by Newstrom and Ruch (1975) and Tyson (1990), other reports create higher
frequencies and more variance of unethical behaviors, thereby making the psychometric
challenges in studying them less complicated. Following Newstrom and Ruch (1975) and
several other scholars in this field (e.g., Treviño & Weaver, 2003), a questionnaire was
selected as the method of enquiry. Following Treviño and Weaver (2003), a timeframe of 12
months was chosen, reading “In the past 12 months, I have personally seen or have first-hand
knowledge of employees or managers . . . ” A 5-point frequency scale was chosen, with 1 =
Never,2 =Rarely,3 =Sometimes,4 =Often, and 5 =(Almost) always.
Step 3: Exploratory Factor Analysis
To conduct a factor analysis, data were collected on a diverse sample of the Dutch working
population. Treviño and Weaver (2003) suggested a panel survey to circumvent the problem
Kaptein / Unethical Behavior in the Workplace 9
of companies’ reluctance to participate in research where unethical behavior is the object of
research. Anonymity of the respondents is also better guaranteed which has been found to
reduce the level of social desirability bias in business ethics research (Fernandes & Randall,
1992). The selection of the sample was based on the recommendation of Hinkin (1995) that
the sample should be representative of the population that the researcher will be studying in
the future and with reference to which the results will be generalized.
A panel of 750 members of the Dutch working population was invited to complete a Web-
based questionnaire.1The sample was compiled on the basis of its representativity by the
private panel database firm MWM where these individuals are listed. Respondents were
instructed to complete the survey as it applies to their current working situation. Individual
respondents to the survey received two euros cash as bonus for their participation. Four hun-
dred usable questionnaires were returned, achieving a response rate of 53.3 percent and an
item-to-response ratio that is above the required 1:10 (Schwab, 1980). Of the respondents,
52% were male and 13.3% held the position of manager. Their average age was 41 years.
An exploratory factor analysis (principal axis factoring) with an oblique rotation (direct)
oblimin was conducted allowing for correlations among factors (Fabrigar, Wegener,
MacCallum, & Strahan, 1999). Evaluation of the eigenvalues greater than 1.0 suggested six fac-
tors. Based on parallel analysis relative to random eigenvalues (Montanelli & Humphreys,
1976), a steep break in the eigenvalues plot between the fifth factor (1.89) and sixth factor (1.01),
however, indicated a five-factor solution. Within these factors, individual items were retained if
their loading was greater than .40. Items were eliminated if an item’s loading was .30 or greater
for more than one factor. The six factor was dropped because no item scored even .25 or greater
on this factor. In total, 37 items were extracted. Two items were dropped: violating my organi-
zational values and principles and abusing substances (drugs, alcohol) at work. As shown in
Table 1, all remaining items load strongly on their factor. The initial eigenvalues of these factors
were 13.70, 3.44, 3.24, 1.98, and 1.89. The variance accounted for by these factors was respec-
tively 37.01, 9.30, 8.76, 5.34, and 5.11 for a proportion of 65.52 of the total variance.
As expected, each of the five factors centered on a single stakeholder group. Factor 1
included items that were primarily related to the ethical responsibilities of the company toward
financiers, Factor 2 toward customers, Factor 3 toward employees, Factor 4 toward suppliers,
and Factor 5 toward society. A possible reason why the first item—which loaded on all factors—
was dropped is that it is very general, potentially covering responsibilities toward all five stake-
holders. A reason why the second dropped item loaded on two factors (i.e., financiers and
employees) is that abusing substances can have an impact on the financial performance as well
as the performance and satisfaction of employees (e.g., Hawks, 1991).
As shown in Table 2, the correlations between the five factors were moderate (rranged
between .20 and .50, p < .01). This indicates that the types of unethical behavior are distinct
Step 4: Confirmatory Factor Analysis
To conduct confirmatory factor analysis, another sample was used. As this sample also
had to be used to assess differences between industries and job functions (Step 5), a large
10 Journal of Management / Month XXXX
Kaptein / Unethical Behavior in the Workplace 11
Step 3.1: Pattern Matrix of Rotated Factor Loadings From the
Exploratory Factor Analysis of Unethical Behavior Items (N ==400)a
Unethical Behavior Toward
Item (Exact Formulation) Financiers Customers Employees Suppliers Society
1.1 Falsifying or manipulating financial 0.77 0.07 −0.12 −0.03 0.09
1.2 Falsifying time and expense reports 0.67 -0.01 0.06 −0.09 0.03
1.3 Stealing or misappropriating assets 0.49 0.02 0.21 −0.04 0.02
(e.g., money, equipment, materials)
1.4 Breaching computer, network, or 0.70 0.01 0.03 0.03 0.04
1.5 Abusing or misusing confidential 0.61 0.00 0.21 0.01 0.02
or proprietary information
of the organization
1.6 Violating document retention rules 0.70 0.04 0.11 −0.03 −0.10
1.7 Providing inappropriate information 0.70 0.08 −0.07 −0.06 0.14
to analysts and investors
1.8 Trading securities based on inside 0.86 0.01 −0.25 −0.03 0.04
1.9 Engaging in activities that pose a 0.73 0.03 0.01 0.03 0.01
conflict of interest (e.g., conflicting
sideline activities, favoritism of family
and friends, use of working hours for
private purposes, executing
1.10Wasting, mismanaging, or abusing 0.58 -0.04 0.24 0.00 0.00
2.1 Engaging in false or deceptive sales 0.01 0.72 0.16 −0.01 −0.04
and marketing practices (e.g., creating
2.2 Submitting false or misleading −0.04 0.79 0.01 −0.13 −0.08
invoices to customers
2.3 Engaging in anticompetitive practices 0.16 0.81 −0.06 −0.05 −0.11
(e.g., market rigging, quid pro quo deals,
offering bribes or other improper gifts,
favors, and entertainment to
2.4 Improperly gathering competitors’ 0.12 0.80 0.00 −0.01 −0.06
2.5 Fabricating or manipulating product −0.03 0.88 −0.09 −0.03 0.09
quality or safety test results
2.6 Breaching customer or 0.04 0.66 0.14 0.09 0.06
2.7 Entering into customer contracts −0.05 0.85 −0.13 −0.01 0.12
relationships without the proper terms,
conditions, or approvals
2.8 Violating contract terms with customers −0.03 0.77 0.06 0.01 0.10
12 Journal of Management / Month XXXX
Table 1 (continued)
Unethical Behavior Toward
Item (Exact Formulation) Financiers Customers Employees Suppliers Society
3.1 Discriminating against employees 0.09 0.00 0.62 −0.08 0.02
(on the basis of age, race, gender, religious
belief, sexual orientation, etc.)
3.2 Engaging in (sexual) harassment or 0.05 0.05 0.59 −0.08 0.10
creating a hostile work environment
(e.g., intimidation, racism, pestering,
verbal abuse, and physical violence)
3.3 Violating workplace health and 0.00 0.09 0.65 0.02 0.12
safety rules or principles
3.4 Violating employee wage, overtime, 0.06 0.05 0.61 −0.03 0.04
or benefits rules
3.5 Breaching employee privacy 0.11 0.00 0.63 −0.14 0.05
4.1 Violating or circumventing supplier 0.04 0.19 0.05 −0.55 0.02
4.2 Accepting inappropriate gifts, favors, 0.09 0.03 0.18 −0.63 0.02
entertainment, or kickbacks
4.3 Paying suppliers without accurate −0.01 −0.01 −0.04 −0.88 −0.01
invoices or records
4.4 Entering into supplier contracts that −0.06 −0.01 0.01 −0.85 0.11
lack proper terms, conditions,
4.5 Violating the intellectual property rights 0.05 −0.02 −0.01 −0.91 −0.02
or confidential information of suppliers
4.6 Violating contract or payment terms −0.03 −0.01 0.04 −0.94 0.00
4.7 Doing business with disreputable 0.03 0.04 0.00 −0.85 0.02
5.1 Violating environmental standards 0.00 −0.04 0.20 −0.04 0.65
5.2 Exposing the public to safety risk 0.05 0.00 0.15 −0.08 0.58
5.3 Making false or misleading claims 0.07 0.07 0.17 0.12 0.62
to the public or media
5.4 Providing regulators with false or 0.08 0.02 0.03 −0.07 0.71
5.5 Making improper political or financial 0.05 0.20 −0.14 −0.02 0.63
contributions to domestic or foreign officials
5.6 Doing business with third parties that 0.03 −0.07 −0.22 −0.22 0.64
may be involved in money laundering
or are prohibited under international
trade restrictions and embargos
5.7 Violating international labor or 0.04 0.01 0.05 −0.01 0.60
Initial eigenvalues 13.70 3.44 3.24 1.98 1.89
Explained variance 37.01 9.30 8.76 5.34 5.11
Cumulative explained variance 37.01 46.31 55.07 60.41 65.52
Rotated extraction sums of squared loadings 9.68 8.23 8.28 5.03 7.71
a. Statistics that load ≥.40 are in bold.
sample was collected. A digital survey was sent to 6,797 adults working for U.S. organiza-
tions with at least 200 employees. The sample was compiled on the basis of its representa-
tivity by the private panel database firm National Family Opinion in which these individuals
are registered. Respondents were instructed to complete the survey as it applies to their cur-
rent working situation. Individual respondents to the survey received $1 cash as bonus for
their participation. With a return of 4,056 completed questionnaires, a response rate of 59.7
percent was achieved.
Of the respondents, 53% were female. As for job tenure, 8% had been working for less
than a year, 31% between 1 and 5 years, 17% between 6 and 10 years, and 44% for more
than 10 years. Thirty-six percent of the respondents worked for an organization with 200 to
1,000 employees, 24% with 1,000 to 5,000 employees, 11% with 5,000 to 10,000 employ-
ees, and 28% with more than 10,000 employees. Regarding the geography, 28% of the
respondents were living in the Midwest, 22% in the Northeast, 19% in the Southeast, 14%
in the West, 10% in the Southwest, and 7% in the Mid-Atlantic. Thirty-two percent of the
respondents held a managerial position, 13% as supervisor, 12% as mid-level manager, 4%
as senior manager or junior executive, and 3% as senior executive or director.
The discriminant and convergent validity of the five unethical behavior subscales was
analyzed by a second-order confirmatory factor analysis in which each of the subscales was
assumed to originate from an encompassing construct of unethical behavior in the workplace
(Jarvis, MacKenzie, & Podsakoff, 2003; Spreitzer, 1995). The objective of this analysis was
to establish whether the five subscales can indeed be interpreted as distinct subscales of
unethical behavior (discriminant validity) and whether the relation between the overall
unethical behavior construct and each of the separate subscales is positive as it should be
according to the model assumptions (convergent validity). Four commonly used fit indices
(i.e., NFI, NNFI, CFI, and RMSR) were used (Hu & Bentler, 1999; Jöreskog & Sörbom,
1993; Medsker, Williams, & Holohan, 1994).
The results of the second-order confirmatory factor analysis with maximum likelihood
estimation are summarized in the structural equation model in Figure 1. The overall fit of the
five-factor model was fair (NFI =.897, NNFI =.913, CFI =.898, RMSR =.041) and supe-
rior to a one-factor model (NFI =.771, NNFI =.786, CFI =.784, RMSR =.064). An X2dif-
ference test between these two models was significant (∆X2 =10,542, ∆df =4, p < .01). The
convergent validity was supported in each of the subscales, with the lowest parameter esti-
mate being λ=.797 for item 1.10. All of the Lambda parameter estimates were statistically
significant. The t-values were all above 2.0 and significant at the p < .01 level (Jöreskog &
Sörbom, 1993). Composite reliability (γ) for each of the subscales was higher than the rec-
ommended .6 (Bagozzi & Yi, 1988), with the lowest being .81 for unethical behavior toward
employees. The average variances extracted, which should be at least .5 (Bogozzi & Yi,
1988) were .88, .90, .65, .87, and .80 for respectively the subscales of unethical behavior
toward financiers, customers, employees, suppliers, and society.
Discriminant validity was assessed by comparing the variance-extracted estimate to the
square of the phi matrix. For all items, the estimate was greater than the recommended .5
(Fornell & Larcker, 1981), with the smallest being .62 for item 1.10 and exceeded the square
of the phi matrix. The factor correlations (phi coefficients) ranged from .55 to .77. The results
demonstrated excellent internal consistency (α)—much higher than the recommended
Kaptein / Unethical Behavior in the Workplace 13
minimum of .7 (Nunnally, 1978): .93, .93, .90, .95, and .93 for respectively the subscales of
unethical behavior toward financiers, customers, employees, suppliers, and society.
Step 5: Mean-Difference Test for Industry and Job Functions
A measure of unethical behavior should—as indicated in the introduction of this article—
help us to establish whether the observed frequencies in unethical behavior across, for
example, organizations, industries, and job functions differ. Should they exist, we can start
to seek an explanation for such differences so as to determine which management actions
need to be taken to prevent unethical behavior in different contexts. In Step 6, the differences
between three business organizations were analyzed; here differences between industries and
job functions were examined. Multivariate analyses of variance were conducted on the same
sample of the U.S. working population as used in Step 4. As shown in Tables 3 and 4, there
were significant differences on the five subscales of unethical behavior, although the differ-
ences are in most cases not that large. For job functions, the MANOVA F-value was statis-
tically significant (F =4.98, p <.01), suggesting an overall difference across job functions.
For the sectors, the test of difference between means also yielded a significant MANOVA F-
value (F =6.56, p <.01).
Respondents working in public relations and public management observed about twice as
much unethical behavior toward society than respondents in other job functions, which can
14 Journal of Management / Month XXXX
Step 4.3: Results of Second-Order Confirmatory Factor Analysis of
Unethical Behavior Subscales (N ==4,046)
be explained by the fact that they largely maintain relationships with societal stakeholders,
such as governments, politicians, nongovernmental organizations, citizens, and the media.
Buyers also witnessed much more unethical behavior toward suppliers than respondents in
other job functions. Less expected is that buyers were also the most frequent observers of
Kaptein / Unethical Behavior in the Workplace 15
Step 3.2: Correlations Between Factors of Unethical Behavior (N ==400)
Unethical Behavior Toward
Financiers Customers Employees Suppliers
Employees .41** .35**
Suppliers .43** .23** .20**
Society .50** .35** .49** .29**
Step 5.1: Results of MANOVA for Unethical Behavior
Subscales by Job Function (N ==3,345)a, b
Unethical Behavior Toward (In Percentages)
Job Function Financiers Customers Employees Suppliers Society
Sales/marketing (N =479) 41 (24) 41 (21) 47 (29) 17 (8) 22 (8)
Operations/service (N =542) 49 (31) 42 (19) 58 (37) 23 (10) 33 (13)
Manufacturing/production (N =314) 50 (32) 41 (19) 69 (48) 26 (12) 38 (17)
Research/development/engineering (N =262) 54 (32) 35 (10) 53 (30) 23 (9) 27 (6)
Purchasing/procurement (N =50) 50 (44) 62 (34) 60 (38) 42 (28) 32 (16)
Technology (N =295) 55 (35) 40 (18) 53 (30) 23 (9) 25 (11)
Training/education (N =167) 48 (33) 35 (14) 60 (40) 15 (8) 35 (13)
Quality/safety/environmental (N =94) 48 (28) 39 (20) 61 (37) 31 (15) 35 (17)
Clerical/support (N =389) 39 (25) 32 (13) 48 (34) 16 (8) 20 (8)
General management/administration (N =311) 55 (33) 36 (14) 45 (26) 22 (9) 22 (6)
Finance/accounting (N =203) 48 (37) 38 (17) 53 (35) 19 (10) 24 (7)
Legal/compliance (N =43) 55 (31) 28 (9) 45 (31) 19 (10) 28 (9)
Internal audit/risk management (N =31) 58 (42) 39 (26) 58 (39) 26 (16) 26 (10)
Public/media relations (N =23) 57 (39) 43 (26) 70 (52) 35 (17) 55 (23)
Government/regulatory affairs (N =142) 56 (42) 42 (20) 67 (50) 28 (17) 48 (25)
F-value 6.09** 4.39** 5.09** 7.38** 3.57**
Job effect Wilks’ Lambda =.91 F=4.98
a. Of the 4,046 respondents, 701 indicated to have another function.
b. Percentages without brackets indicate the relative number of respondents who have observed unethical behavior
at least once in their direct working environment in the past 12 months (mean <5.0), whereas the percentages
within brackets indicate the relative number of respondents who have observed unethical behavior at least three
times in their direct working environment in the past 12 months (mean ≤4.5).
unethical behavior toward customers, whereas salespersons and marketers observed one third
less unethical behavior toward customers than did buyers. Of the five subscales, unethical
behavior toward employees was observed most frequently in most job functions. The highest
frequency of unethical behavior toward employees was reported by respondents working in
manufacturing, public relations, and public management. Respondents working in internal
16 Journal of Management / Month XXXX
Step 6: Results of MANOVA for Unethical Behavior
Subscales by Organization (N ==3)
Unethical Behavior Toward (in Percentages)
Financiers Customers Employees Suppliers Society
Organization A 37 24 36 13 15
Organization B 6 24 53 11 8
Organization C 50 45 61 21 48
F-value 42.17** 5.78** 8.38** 2.02 27.01**
Company effect Wilks’ Lambda =.78, F=15.93**
Step 5.2: Results of MANOVA for Unethical
Behavior Subscales by Industry (N ==3,825)a
Unethical Behavior Toward (in Percentages)
Financiers Customers Employees Suppliers Society
Banking and finance (N =390) 47 (29) 35 (13) 45 (24) 14 (6) 16 (6)
Communications and media (N =318) 47 (31) 43 (22) 54 (36) 20 (11) 30 (10)
Electronics, software and services (N =202) 49 (33) 43 (18) 46 (24) 23 (6) 22 (4)
Energy and chemicals (N =203) 51 (33) 36 (14) 55 (35) 30 (11) 40 (11)
Food, retail, and distribution (N =417) 41 (25) 36 (19) 53 (35) 18 (8) 31 (10)
Manufacturing (N =471)b50 (31) 44 (21) 63 (44) 29 (16) 33 (11)
Pharmaceutical (N =309) 44 (28) 34 (14) 54 (35) 22 (10) 23 (10)
Healthcare (N =545) 47 (29) 41 (14) 57 (38) 18 (8) 28 (9)
Insurance (N =361) 43 (23) 33 (14) 44 (27) 15 (6) 14 (3)
Public sector (N =532) 53 (40) 37 (17) 63 (43) 24 (12) 41 (14)
Real estate (N =77) 32 (16) 38 (16) 34 (18) 18 (8) 19 (5)
F-value 3.57** 2.63** 9.10** 5.72** 12.17**
Sector effect Wilks’ Lambda =.91 F=6.56
a. Percentages without brackets indicate the relative number of respondents who have observed unethical behavior
at least once in their direct working environment in the past 12 months (mean <5.0), whereas the percentages
within brackets indicate the relative number of respondents who have observed unethical behavior at least three
times in their direct working environment in the past 12 months (mean ≤4.5).
b. For example, consumer products, packaged goods, automotive, aerospace, and defense.
auditing most frequently observed unethical behavior toward financiers, whereas respondents
working in sales and support observed unethical behavior toward financiers least frequently.
The highest frequency of observed unethical behavior toward financiers was reported by
respondents from the public sector. The frequency of observed unethical behavior toward
customers had the least variance across sectors. Unethical behavior toward employees was
most frequently observed within the public and manufacturing sector. Unethical behavior
toward suppliers was most frequently observed in the energy and manufacturing sector.
Unethical behavior toward society was most frequently observed by respondents from the
energy and chemicals sector and the public sector. Unethical behavior was least frequently
observed in real estate, banking and finance, and insurance.
Step 6: Mean-Difference Test for Business Organizations
To examine the question of whether organizations have identifiable scores for the mea-
sure of unethical behavior, multivariate analyses of variance were conducted on respondents
from three financial institutions in the Netherlands. Treviño and Weaver warn that
the current legal environment discourages companies from self-assessment in the area of ethics and
legal compliance, making it difficult for business ethics researchers to gain access to organizations,
particularly if unethical or illegal conduct is the dependent variable of interest. (2003: 303)
Although this may hold true for the U.S., it was less problematic to gain access to orga-
nizations in the Netherlands. Of the five medium-sized business organizations in the bank-
ing sector that were approached, three organizations responded positively, whereas the other
two organizations preferred to postpone the study by a year. The first organization had
recently conducted an employee satisfaction survey and the second was in the middle of an
employee compliance and integrity awareness program. In all three participating organiza-
tions, the compliance officer approved the list of items without suggesting new items or
rephrasing any questions, thus providing some additional support for the content validity of
the measure. All employees of the three participating organizations received the survey with
a letter of endorsement from the board. Completion of the survey was completely voluntary
and anonymous. The response rates of usable questionnaires were 38% (N =375), 72% (N =
180), and 48% (N =57), of a total of 612 questionnaires.
To determine whether it was appropriate to aggregate individual responses to the organi-
zational level, the James, Demaree, and Wolf (1993) within-group agreement index (Rwg)
was calculated. For all five subscales, the mean Rwg was above the minimum of .70: .84 for
financiers, .87 for customers, .82 for employees, .92 for suppliers, and .92 for society.
The results of the multivariate analysis of variance by organization are depicted in Table
5. The results indicate a significant overall difference between the three organizations (F =
15.93, p <.01). Univariate analyses of variance revealed differences on all the subscales
except suppliers. The greatest contrast was found in unethical behavior toward society (6%
of the respondents of Organization B had witnessed unethical behavior toward society com-
pared to 50% of the respondents of Organization C). The data shows that the unethical
behavior subscales were sufficiently strong and identifiably different to produce significant
discrimination among the participating organizations.
Kaptein / Unethical Behavior in the Workplace 17
Step 7: Discriminant and Nomological Validity
To further assess the discriminant and nomological validity of the construct, a study was
set up in which the new measure was compared to other theoretically relevant constructs. A
sample of 100 MBA students from a large public university in the Netherlands with at least
five years’ work experience was invited to participate. Initially, 54 students responded posi-
tively, but eventually 41 questionnaires were received.
The scores obtained by means of the new measure of unethical behavior were compared
with scores obtained by means of the scale of unethical behavior as developed by Newstrom
and Ruch (1975) as well as with two well-developed scales of related constructs for unde-
sirable behavior in the workplace—the Bennett and Robinson (2000) scale of deviance and
the Kacmar and Carlson (1997) scale of political behavior—and one scale for desirable
behavior—the Farh, Podsakoff, and Organ (1990) scale of altruistic behavior. It had been
expected that the new measure would have a moderately positive relationship with scores on
other undesirable behavior scales, and a moderately negative relationship with the constructs
of desirable behavior. Two measures of an unrelated construct were also added, the Song,
Montoya-Weiss and Schmidt (1994) scale of cooperative behavior and the Scott and Bruce
(1994) scale of innovative behavior, of which no significant relationship was expected at all.
Social desirability was assessed with the impression management scale of Paulus’ Balanced
Inventory of Desirable Responding (1991). Following Brown, Treviño, and Harrison (2005),
one item was dropped (I never read sexy books or magazines) because it is too offending.
After reformulating some items, a social desirability score was calculated by counting all
extreme scores (6, 7) on a 7-point response format as 1 and all other responses as 0. The
response of 10 participants was dropped because their score was higher than 0.75. Table 6
depicts the means, standard deviations, and correlations for the measures.
As expected, the measure correlated most positively with Newstrom and Ruch’s scale of
unethical behavior—intraorganizational cheating (r =.81, p <.01), somewhat less positively
with deviant behavior (r =.64, p <.01), and moderately with political behavior (r =.51, p <
.01). Unexpectedly, the measure did not correlate negatively with altruism (r =.05, ns) sug-
gesting that, at least in this study, unethical behavior and altruism, which was mainly oper-
ationalized here as internal supportive behavior, are not two sides of the same coin. In terms
of discriminant validity, the measure of unethical behavior did not show any correlation with
cooperative behavior (r =.04, ns) or innovative behavior (r =.05, ns). These findings sug-
gest that the new measure of unethical behavior is robust and specific enough to focus
respondents’ attention on patterns of unethical behavior in the workplace.
Step 8: Criterion-Related Validity
The results so far are necessary but not sufficient to demonstrate the utility of the new
measure of unethical behavior. Criterion-related or predictive validity also has to be estab-
lished in the construct validation process (Nunnally, 1978). A final study was conducted to
start to address this issue. In this step, a study was conducted to determine the capacity
of the new measure to incrementally predict relevant outcomes. A critical choice in any
18 Journal of Management / Month XXXX
Step 7: Correlations for Discriminant and Nomological Validity (N ==31)
Variable Mean SD 11a1b1c1d1e2 345 6
1. Unethical behavior toward 1.35 .28
1a. Financiers 1.42 .36 .74**
1b. Customers 1.36 .36 .63** .24
1c. Employees 1.42 .42 .74** .44* .34
1d. Suppliers 1.48 .56 .82** .45* .43* .48**
1e. Society 1.15 .23 .85** .57** .48* .54** .74**
2. Intraorganizational cheating 2.06 .46 .81** .64** .39* .73** .64** .67**
3. Deviant behavior 1.97 .53 .64** .42* .21 .72** .56** .51** .81**
4. Political behavior 2.85 .50 .51** .54** .17 .38* .42* .35 .62** .56**
5. Altruistic behavior 3.40 .65 −.05 −.12 .28 −.21 −.09 .01 −.12 −.27 −.17
6. Cooperative behavior 3.32 .64 .04 .02 .14 −.02 −.01 .03 .02 −.03 −.10 .66**
7. Innovative behavior 3.40 .65 −.05 −.13 .21 −.08 −.11 −.02 −.02 −.18 −.19 .77** .74**
construct validation effort is the choice of outcome variables. The reputation of the organi-
zation was selected as an important outcome as this indicates how stakeholders experience
and evaluate unethical behavior of the organization which subsequently influence their atti-
tudes and behavior toward the organization (Van Riel & Fombrun, 2007).
Three hundred sixty students of a business school in the Netherlands who were enrolled
in a bachelor course were asked whether they were acquainted with someone in a manager-
ial function and if so, whether they would like to ask that person to participate in this study.
The managers were requested to complete a brief questionnaire about the implemented
ethics instruments in their organization and to give two different questionnaires to two
employees under their supervision. As reward for their participation, the managers would
receive a brief report about the general findings. Each potential respondent promptly
returned their survey to the student. The use of separate samples allowed us to assess the
incremental predictive power of the new measure without associated problems of common
source variance (Podsakoff, MacKenzie, & Lee, 2003).
Eight ethics measures, such as an ethics code, ethics training, and ethics officer, were
selected on the basis of the study of Treviño and Weaver (2003). An explorative factor analy-
sis showed one factor with a Cronbach’s alpha of .84. One employee had to complete a ques-
tionnaire focusing on observed unethical behavior in the work environment. The other had
to complete a questionnaire focusing on the reputation of the organization per stakeholder
group. A 5-point response format ranging from 1 =Strongly Disagree to 5 =Strongly Agree
was used. One hundred fourteen completed sets of three questionnaires were obtained. Table
7 depicts the means, standard deviations, and correlations.
As expected, ethics instruments have a negative relationship with the observed frequency
of unethical behavior. The relationships differed for each subscale. Only the relationship
between ethics measures and society was insignificant, although it was almost significant
with p =.06. As anticipated, the new measure of observed unethical behavior in the work-
place showed a negative relationship with the reputation of the business organization to each
stakeholder group. As expected, there were different correlations for each subscale. Only the
reputation to employees and society were related to all five subscales. Four of the five cate-
gories of organizational reputation had the highest correlation with its related primary stake-
holder (i.e., the highest r in each row). Only the reputation to society had a higher correlation
coefficient with another stakeholder (i.e., customers). Unethical behavior toward customers
seemed to have a higher impact on the reputation of the organization to society than unethical
behavior had toward society. The reputation of the organization to employees had the highest
correlation coefficient for all five types of unethical behavior (the highest rin each column).
Even though business ethics is topical both in research and practice, Newstrom and
Ruch’s (1975) measure of observed unethical behavior in the workplace continues to be used
by scholars despite its limitations. Not only does it cover a limited part of the full scope of
20 Journal of Management / Month XXXX
this construct, the process of item generation was not very transparent and only superficially
tested by them and others. As a result, most studies of the frequency, antecedents, and con-
sequences of observed unethical behavior in the workplace do not focus on unethical behav-
ior but largely on intraorganizational cheating which Newstrom and Ruch themselves cite
as the object of their research. The purpose of this study was to systematically develop an
instrument to measure a wider range of unethical behaviors in the workplace and to take the
first steps in demonstrating its convergent, discriminant, and criterion-related validity.
For the first time, items have systematically been generated to create a more accurate and
comprehensive list of unethical behaviors in the workplace. Business codes of ethics of the
largest companies in the world were drawn on to produce these items. The generated items
have been refined and validated by exploratory and confirmatory factor analyses. Large,
diverse, and unique samples were collected and used. According to Bollen (1989), empirical
support for multidimensionality is not essential for a multidimensional scale to be theoreti-
cally superior to a unidimensional scale. Nevertheless, the results resonate well with other
conceptual approaches that endorse a stakeholder model of business organizations’ respon-
sibilities. Because they have different ethical responsibilities to each stakeholder group, dif-
ferent types of unethical behavior exist toward each stakeholder group. The results display
five behavioral subscales, clustered around the most important stakeholder groups: unethical
behavior toward financiers, customers, employees, suppliers, and society. The goodness-of-
fit of the model is fair, whereas the internal reliability of the subscales is good. Industries,
job functions, and business organizations score demonstrably differently on the five sub-
scales. The new measure correlates with related constructs and does not correlate with unre-
lated constructs. The results also indicate that there is a negative correlation between
unethical behavior and the reputation of the organization to each stakeholder group and to
existing management instruments to prevent unethical behavior.
Kaptein / Unethical Behavior in the Workplace 21
Step 8: Correlations of Unethical Behavior Subscales with Ethics
Measures and Reputation to Stakeholders (N ==114)
Unethical Behavior Toward
Financiers Customers Employees Suppliers Society
Mean 1.33 1.30 1.58 1.24 1.23
SD .66 .64 .77 .65 .58
Antecedent Ethics 3.82 .81 −.19* −.23* −.19* −.24* −.17
Reputation toward Financiers 3.78 .77 −.23* −.21* −.20* −.19* −.16
Customers 3.90 .70 −.23** −.28** −.16 −.21* −.23*
Employees 3.61 1.02 −.34** −.41** −.54** −.31** −.32**
Suppliers 3.63 .76 −.20* −.19* −.16 −.24* −.21*
Society 3.64 .76 −.26** −.34** −.21* −.24* −.29**
In contrast with Newstrom and Ruch’s (1975) measure of unethical behavior and the
slightly adapted versions used by others, the new measure incorporates a variety of different
items. It includes not only intraorganizational unethical behaviors, but also the as yet
neglected extraorganizational unethical behaviors. Drawing on business codes to generate
items offers a better and more transparent coverage of the content validity of the construct
compared to that of the measure developed by Newstrom and Ruch. Whereas Newstrom and
Ruch’s measure has a unidimensional structure, the new measure structures unethical behav-
iors according to five different stakeholder groups thereby creating meaningful patterns out
of the wide range of unethical behaviors. Moreover, each subscale includes five to ten items,
which is at or above the recommended minimum of 3 (Harris & Schaubroeck, 1990) or 5
items (Hinkin, 1995). Such an aggregated measure is usually more reliable and valid than
specific measures (Rushton, Brainerd, & Pressley, 1983) and thus overcomes the low base
rate problems commonly associated with measuring these types of behaviors. The 37-item
measure is relatively concise and can easily be incorporated into other survey research.
The high observed frequency of unethical behaviors in this research among, for instance,
the U.S. working population demonstrates the importance of management taking measures
to prevent unethical behavior in the workplace in view of the associated costs and conse-
quences (Gagne, Gavin, & Tully, 2005). Even if respondents’ perceptions are wrong and
unethical behavior is not as prevalent as they believe it to be, the mere fact that they have
these perceptions has great implications for their attitudes and behavior (Robinson &
O’Leary-Kelly, 1998; Treviño & Weaver, 2003; Tyson, 1990). Empirical research by Izraeli
(1988) shows that employees who observe unethical behavior in others are more likely to
engage in unethical behavior themselves.
This article presents empirical support for understanding the ethics of business in terms
of unethical behaviors toward various stakeholders. In this research no evidence was found
to suggest the need to incorporate other dimensions such as those found in related constructs.
Robinson and Bennett (1995) draw a distinction between minor versus serious deviant
behaviors. That this dimension did not crop up in the current research is understandable as
we defined unethical behavior as deviant behavior where fundamental interests are at stake.
The items were also not grouped along interpersonal and organizational behaviors, which is
the second dimension Robinson and Bennett (1995) identified. A possible explanation for
this is that interpersonal behaviors, which usually only focus on relationships within the
organization and not with external stakeholders, are included in the subscale of unethical
behavior toward employees, where the offender could be the organization (e.g., in the case
of breaching employee privacy) or colleagues (e.g., in the case of creating a hostile work
environment). The items that would mostly coincide with the organizational dimension, such
as stealing or misappropriating assets, are included in the measure as developed in this arti-
cle within the subscale of unethical behavior toward financiers.
The identified factors also did not correspond with the type of motives usually advanced
to categorize different types of unethical behavior—unethical behavior for personal gain and
22 Journal of Management / Month XXXX
for organizational gain (Ashforth & Anand, 2003; Coleman, 1987). A conceivable reason for
this is that motives are difficult, if not impossible, to uncover when measuring the observed
frequency of unethical behavior. Motives are not always visible to bystanders or even known
to offenders themselves (Cressey, 1953). Furthermore, unethical behavior can be driven by
a variety of motives (Di Norcia & Larkins, 2000). And the same types of unethical behavior
can be fuelled by different motives (Giacalone & Greenberg, 1997).
The same line of reasoning applies to the dimension of overt versus covert behaviors, a
distinction drawn by Analoui and Kakabadse (1992) and Analoui (1995) in a study of uncon-
ventional behaviors in the workplace. In the present study the items were not clustered along
this dimension. This can be explained by the response scale used, which focused on observed
behavior of others—which, to the respondent at least, is overt.
A further distinction frequently made is between illegal, immoral, and antisocial behav-
ior, based on the three-stage model of corporate social responsibility by Carroll (1979). The
results of the present study show no correspondence with his model. This can be attributed
to the fact that respondents could not have known what the normative source of many of the
items of unethical behavior was (i.e., laws, moral principles, or societal expectations). For
most items, all three sources are present—at least in the setting of our samples in the U.S.
and The Netherlands—given that unethical behavior, which in this article is defined as
behavior that is morally unacceptable, is usually also strongly prohibited by laws and soci-
etal expectations (Donaldson & Dunfee, 1999; Stone, 1975).
That our items coincide with different stakeholder groups does not imply that other
dimensions are not relevant. Further research using other methods, such as self-reported
behavior could lead to a refined model in which, for example, unethical behavior toward
each stakeholder is subdivided into covert and noncovert behavior or into behavior that cor-
responds or conflicts with the interests of the organization. So far, a measure structured in
terms of stakeholder groups will—as argued in the second section of this article—help us to
better understand and prevent unethical behavior for at least three reasons. First, behaviors
within a cluster of unethical behaviors could have similar consequences whereas different
clusters may have different consequences. Second, the behaviors within a cluster of unethi-
cal behavior could have similar causes whereas different clusters could have different causes.
Third, if different clusters of behaviors exist each with different causes and consequences, it
could mean that similar management interventions are required to prevent unethical behav-
ior within a cluster whereas different interventions are required for different clusters.
Implications for Future Research
The newly developed measure of unethical behavior in business organizations generates
much opportunity for future research. To date, empirical research on unethical behavior in
the workplace has not been abundant. A possible explanation of this lack of research might
be the difficulty inherent in measuring sensitive behavior. The results of this study demon-
strate that people are willing to participate provided a carefully devised procedure is fol-
lowed whereby they are not required to give self-reports but to report on unethical behavior
of others in the work environment.
Kaptein / Unethical Behavior in the Workplace 23
Most of the empirical studies that are based on the measure of Newstrom and Ruch (1975)
could be enhanced by using this new and broader measure. This applies, for example, to
studies that aim to explain the difference in impact of ethical climate and ethical culture on
unethical behavior (Treviño, Butterfield, & McCabe, 1998), the best typology of ethical cli-
mate that explains unethical behavior (Peterson, 2002), and the differences in unethical
behavior at different hierarchical levels (Akaah, 1996) and between business organizations
(Treviño & Weaver, 2001), countries (Jackson, 2001) and sexes (Kidwell, Stevens, &
Bethke, 1987). In this article, results of the new measure have been presented for differences
per job function and industry in the U.S. and for three organizations in the Netherlands.
However, much more comparative research should be conducted using the new standardized
measure to identify similarities and differences for these variables and to further develop
theory on the basis of these findings.
With a much broader, inductively derived and empirically tested measure of unethical
behavior in the workplace, more sophisticated studies of the antecedents and consequences
of unethical behavior can be conducted, yielding more reliable results. Different types of
unethical behavior may have different causes and different effects (Robinson & Greenberg,
1998; Treviño & Weaver, 2003; Vardi, 2001) which, when proven, would further strengthen
the criterion-validity of the measure. By drawing a distinction between five types of unethi-
cal behavior, the relationship between these types of behavior can be further examined which
could lay the foundation for developing a comprehensive theory or a set of theories to under-
stand the relation between different types of unethical behavior. This study has already indi-
cated that different unethical behaviors may have different consequences for the reputation
of the organization to each stakeholder group.
Although this study makes several contributions, it also has several limitations. Three lim-
itations will be discussed here.
First, the measure is unable to account for unethical behaviors that are specific to partic-
ular organizational contexts and periods in time. As the aim of this study was to develop a
general measure that can be applied to a range of organizational contexts, it includes only
those behaviors that are addressed in more than 10% of the business codes of the largest 200
companies in the world. No other empirical sources of moral norms for business organiza-
tions have been used, such as external codes, stakeholder expectations, more specific and
detailed internal standards of organizations, the codes of smaller organizations, or the codes
of organizations whose headquarters are based in countries other than the 11 countries in
which the largest 200 companies in the world are headquartered. Nor were items generated
on the basis of an analysis of business ethics literature. Although the article presented argu-
ments for using business codes as a useful source for generating items on the individual,
group and organizational level, the question remains whether other legitimate sources for
ethical norms would not have led to other items. Thus far, however, the participating experts
and business organizations in this research have not come up with any other relevant items
of unethical behavior. The question is also whether new ethical issues would lead to changes
24 Journal of Management / Month XXXX
in business codes of ethics and consequently to new items and to other subscales. So far, the
chosen level of abstraction of the items in the measure allows for a certain degree of flexi-
bility to accommodate different situations and new issues. Furthermore, as the sample of 105
business codes of ethics covers the last few decades because of the fact that some codes have
not or hardly changed in this period, the generated items cover quite a long period of time.
Finally, if new issues were to lead to new items, the robustness of the existing five subscales
renders it unlikely that the structuring of items along the five stakeholder groups would
The second limitation concerns the risks associated with approaching managers and
employees to give their opinion. A first risk in this regard concerns the subjectivity of
respondents’ interpretation of items. If definitions of unethical behavior vary across organi-
zational levels, companies, industries, countries, and even individuals (Greenberg, 1996), the
question arises as to what is measured: the frequency of the type of unethical behavior that
is examined or what respondents regard as unethical? The answer is probably both. However,
to avoid contamination of the results with the normative beliefs of respondents, the items
were formulated as clearly as possible and extensively tested for clarity. In future research
this issue could be dealt with by asking respondents to indicate to what extent they perceive
the behavior described as unethical, something which was done by Newstrom and Ruch
Another risk related to approaching managers and employees to give their opinion is the
risk of social desirability response bias. Unethical behaviors could indeed be prone to this
bias (Fernandes & Randall, 1992; Randall & Fernandes, 1991). Assuring respondents’
anonymity aimed to reduce the social desirability response bias in the current research pro-
ject. The high frequency of observed unethical behaviors for the various samples suggests
that a large group refrained from giving a socially desirable response. For future research,
the social desirability scale of Paulus (1991) as used in Step 7 in this research could be added
to the new measure to test its impact.
A third limitation concerns the interpretation of information provided by respondents.
When the measure is used to measure the perception of employees within one organization,
special care should be taken in interpreting the results. If, for example, breaching customer
or consumer privacy scores 50% it does not mean that the privacy of 50% of the customers
are breached, or that 50% of the employees breach the privacy of customers. It only means
that 50% of the respondents have directly observed or have first-hand knowledge of cus-
tomer privacy being breached at least once in the past 12 months. In the survey among the
U.S. working population, it is unlikely that two or more respondents worked for the same
organization. Therefore when they indicated that they had observed a violation, it is safe to
assume that different practices were referred to. However, when a survey is conducted
among employees in the same organization, observations of unethical behavior can refer to
the same practice. The risk of duplication therefore increases. This issue was partly
addressed by asking the respondents in Step 6 to limit the behaviors they observed to their
own team or department. The objective of a survey using the new measure cannot be to
establish the exact number of times unethical behavior occurs. However, future surveys
could for each unethical behavior also include questions regarding the number and type of
people involved. This would help us to get a better understanding of whether unethical
Kaptein / Unethical Behavior in the Workplace 25
behavior occurs at the individual, group, or organizational level (Vardi & Weitz, 2004) and
whether or not it occurs in collaboration with external stakeholders. Future research could
compare the frequency of reported unethical behavior examined by means of a questionnaire
with other sources available in an organization, such as a misconduct reporting system, the
use of the whistle-blowing procedure, and records of unethical behavior compiled by depart-
ments such as Human Resources, Security and Finance (internal audits).
Validating a construct is almost never final (Robinson & Bennett, 1995). Only by con-
ducting multiple studies can evidence be provided to support or weaken the validity of a par-
ticular measure. More research is therefore required to confirm the validity of the new
measure of unethical behavior in the workplace and its five subscales.
Measuring unethical behavior in the workplace is essential for business organizations to
decide whether and which measures need to be taken to enhance the ethics of the organiza-
tion. In this article a measure was developed that covers a wide range of unethical behaviors.
The outcome of the current research project is a 37-item questionnaire, clustered around five
stakeholder groups. Aware of the limitations of the measure, organizations, like those in Step
6 of this study, could use this questionnaire by distributing it among employees. An analysis
of the response could provide an overview ranking the unethical behaviors based on their
observed frequency, and if necessary, also a break-down structured around background vari-
ables such as job function and department. Following this, the organization can determine
which unethical behaviors require attention and in what sequence. The frequency of unethi-
cal behaviors can be evaluated in terms of seriousness, for example, the impact it may have
on each stakeholder group as well as on the performance of the organization, and/or how it
compares to the observed frequencies within other organizations or other departments within
the organization. Another option is to include a measure of the ethical climate (Victor &
Cullen, 1988) and ethical culture (Treviño & Weaver, 2003) in the questionnaire and to carry
out regression analyses to determine to what extent the organizational climate and culture
stimulate each type of unethical behavior and which aspects of the climate and culture need
to be improved to reduce the occurrence of unethical behavior in the workplace. By con-
ducting the survey again after management actions have been taken, developments—and
hopefully improvements—will become visible. If this is achieved, this research project has
1. Following the suggestions of Harkness and Schoua-Glusberg (1998), the questionnaire was translated into
Dutch by the author who grew up in the Netherlands. Two bilingual colleagues also independently translated the
questionnaire into Dutch after which the three versions were discussed to produce a consensual version. Blind to
the original questionnaire, a professional translator translated the Dutch questionnaire back into English. The author
and the translator compared the back-translated text for inconsistencies with the original version to finalize the
Dutch version. A version of the Dutch survey is available on request from the author.
26 Journal of Management / Month XXXX
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Muel Kaptein is professor of Business Ethics and Integrity Management at RSM Erasmus University. His research
interests include the management of ethics, the ethics of management, and the measurement of ethics.
Kaptein / Unethical Behavior in the Workplace 31