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Journal of Management

DOI: 10.1177/0149206308318614 2008; 34; 978 originally published online May 20, 2008; Journal of Management

Muel Kaptein Perspective

Developing a Measure of Unethical Behavior in the Workplace: A Stakeholder

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Developing a Measure of Unethical Behaviorin the Workplace: A Stakeholder Perspective

Muel KapteinRSM Erasmus University, P.O. Box 1738, Rotterdam, The Netherlands

To date, only one empirically tested measure of the observed frequency of unethical behavior inthe workplace exists. This widely used measure focuses on intraorganizational cheating and thuscovers 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 eightconsecutive steps. Exploratory factor analysis generates five subscales comprising 37 items ofunethical 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;business codes

Corporate scandals, such as fraudulent bookkeeping, payment of bribes, and the misuseof 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 aretherefore placing increasing pressure on business organizations to better manage unethicalbehavior in the workplace (Treviño, Weaver, & Reynolds, 2006).

978

Author’s Note: Thanks to three anonymous reviewers for their very helpful comments on a previous version of thisarticle, as well as to Russell Cropanzano for his excellent editorial guidance.

Journal of Management, Vol. 34 No. 5, October 2008 978-1008DOI: 10.1177/0149206308318614© 2008 Southern Management Association. All rights reserved.

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Managing unethical behavior in the workplace raises several pressing questions. Whatconstitutes 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 doesthe frequency of unethical behavior vary by organization, industry, job function, andcountry? What are the causes and consequences of unethical behavior? And what actions andinterventions 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 ofobserved unethical behavior in the workplace. Their unidimensional survey measure consists of17 items, such as taking longer than necessary to do a job, claiming credit for someone else’swork, and calling in sick to take a day off. Their respondents, 121 managers participating in anexecutive development program, were asked how often they observed unethical behavior in theirorganization. Despite their great contribution, the measure has at least three limitations. First, itincludes only a part of the spectrum of unethical behaviors. As Newstrom and Ruch themselvesstated, 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 andreports on managerial ethics were reviewed to develop a master list of possible items, which wasthen screened to produce a final list consisting of seventeen items. Third, they did not examinethe internal reliability or the nomological and criterion-related validity of the measure.

Despite these limitations, many scholars have used Newstrom and Ruch’s measure toassess 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 itemswithout providing conceptual or empirical evidence (e.g., Peterson, 2002; Treviño,Butterfield, & McCabe, 1998; Treviño & Weaver, 2001; Weaver & Treviño, 1999), othersscaled down the list of items or clustered the items by means of exploratory or confirmatoryfactor 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 itemswithout conceptual or empirical research is not a sound basis for research either, as scaleshave certain psychometric and conceptual properties which require use of the completescales as standardized (Fleishman, 1973). Therefore, as will be demonstrated in this article,we first need to systematically generate items covering the broader spectrum of unethicalbehaviors before we can test and apply this new measure.

This article commences with defining unethical behavior. Following this, stakeholdertheory is advanced as conceptual basis for developing a measure and subscales of unethicalbehavior. This is followed by a discussion of eight interconnected steps by means of whichthe new measure was developed. The article concludes with a discussion of the scientific andpractical implications and limitations of the new measure.

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Understanding Unethical Behavior in the Workplace

The development of a measure requires at least a tentative theoretical model to guide theprocess (Hinkin, 1998). In this regard, we face four challenges. The first is to define unethicalbehavior in general and to relate it to similar but distinct constructs. The second is to establishthe basis on which behaviors can be considered unethical. The third challenge is to explore whata 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 theterm 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 andwrong, and thus what we ought and ought not do. The domain of business ethics concernsthe ethics of business organizations and of individuals and groups in business organizations.Synthesizing 38 different definitions, Lewis (1985) defines business ethics as comprising therules, standards, principles, or codes giving guidelines for morally sound behavior. Ethicalbehavior implies adherence to these moral norms whereas unethical behavior implies theviolation 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 andCarlson (1997) on political behavior; Tyler and Blader (2005) on rule breaking; Sutherland(1940) on criminal behavior; Neill, Stovall, and Jinkerson (2005) on noncompliance; Hollingerand Clark (1982) on workplace deviance; Analoui (1995) on sabotage; Mangione and Quinn(1975) on counterproductivity; Ashforth and Anand (2003) on corruption; and Giacalone andGreenberg (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 rulebreaking, criminal behavior and noncompliance, unethical behavior is not limited to violationsof official and explicit standards, rules and laws, but includes violations of informal and implicitnorms. Unethical behavior in the workplace is also not limited to violations of—formal andinformal—organizational norms. Bennett and Robinson (2000) define workplace deviance,including sabotage, as behavior that violates significant organizational norms. Rather than localconventions such as organizational norms, unethical behavior primarily concerns moral normsthat are acceptable to the larger community (Vardi & Weitz, 2004). Finally, unethical behaviordoes 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 ofantisocial behavior as any behavior that brings or intends to bring harm to the organization or itsstakeholders. 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 intendedor unintended consequences of that behavior (Velasquez, 2005).

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The importance of drawing a distinction between unethical behavior and other relatedconstructs is that for the latter some well-developed measures are available; Bennett andRobinson (2000) elaborately developed and tested a measure of workplace deviance, as didKacmar and Carlson (1997) for political behavior in organizations. Despite the usefulness ofthese measures, we cannot simply adopt them to assess unethical behavior in the workplacegiven the differences of domain. As noted by Treviño and Weaver (2003), subtle differencesbetween 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 briefdescription of its distinction from related constructs still leaves the question as to whetherbehavior in organizations can be defined as unethical at all. In order words, do moral normsprevail in the business domain and on what basis can we define behaviors as unethical? Thisquestion should be answered in the affirmative before we can proceed to establish what a listof unethical behaviors may look like.

Many scholars have argued that business organizations and their employees bear ethicalresponsibilities. A much-used theory to ground these ethical responsibilities is stakeholdertheory. 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 withall kinds of individuals, groups and organizations. These so-called stakeholders enter into arelationship with business organizations to protect or promote their interests. Because a busi-ness organization and a stakeholder become interdependent, mutual expectations arisebetween both parties demanding that they engage with each others’ interests in an ethicallyresponsible manner. By viewing these relationships as implicit contracts, contractual busi-ness ethicists, such as Donaldson and Dunfee (1999) and Van Oosterhout, Heugens, andKaptein (2006), demonstrate the moral legitimacy of these expectations. As a result, businessorganizations bear an ethical responsibility to protect and promote the interests of theirstakeholders (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 takeninto account. Such a diverse range of ethical responsibilities would probably lead to morediverse types of unethical behavior than is the case with the very internally focused measureof 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 ofNewstrom and Ruch, most other empirical research into unethical behavior addresses one ortwo 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 ameasure of a behavioral construct, provides, as contended by Fisher and Locke (1992), morevalid and reliable information on the underlying theoretical construct. A broader measurewould also open the door to more comparable and comparative research.

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Dimensions of Unethical Behavior

The question that follows is what a construct of unethical behavior would look like andwhat dimensions or subscales can be expected. Existing measures of unethical behavior orrelated constructs comprise different subscales. For workplace deviance, Bennett andRobinson (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 Newstromand Ruch’s measure of unethical behavior, Akaah and Lund (1994) identify six subscales:personal use, passing blame, bribery, falsification, padding expenses, and deception. In thisarticle, 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 businessorganizations 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 tooffer good working conditions. Toward suppliers, the primary ethical responsibility of theorganization is to seek mutually beneficial relationships. And toward society, including gov-ernments, nongovernmental governments, and media, the primary ethical responsibility ofan organization is to act as a good citizen.

That a stakeholder has a primary interest does not exclude the possibility that it couldhave 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 beenclassified 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, therelationships with stakeholders and the different ethical responsibilities of business organi-zations toward stakeholders is the basis for defining what the applicable norms are and whatcan consequently be regarded as unethical behaviors. Although stakeholders as such are notthe target, in the sense that the aim of unethical behavior is to intentionally harm or damagethe 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 responsibilityof the organization toward financiers as it could undermine the financial performance of theorganization 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 threereasons. First, behaviors within a cluster of unethical behaviors could have similar consequenceswhereas individual clusters could have different consequences. For example, unethical behavior

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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 harassmentor breaching employee privacy, would mostly damage the reputation of the organization asemployer (Van Riel & Fombrun, 2007). Second, behaviors within one cluster of unethicalbehaviors could have similar causes whereas individual clusters could have different causes. Forexample, heightened competition in the labor market may reduce unethical behavior towardemployees as organizations would have to do more to attract and retain employees, whereascompetition in the financial market may increase unethical behavior because of the pressureorganizations 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 culturewithin a business organization, as Jones, Felps, and Bigley (2007) do, it is conceivable that theorganizational culture may differ per stakeholder group leading to different frequencies ofunethical behaviors per stakeholder group. For example, a customer-oriented culture does notimply 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 ofbehaviors 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, jobfunction, and industry (Treviño & Weaver, 2003), we expect to find different frequencies ofeach cluster of unethical behavior in these situations. At the same time, we anticipate that thevariance in the frequency of unethical behavior per similar situation shall be lower thanacross 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 ofbehaviors that can be considered unethical regardless of the situation?

On the one hand, as argued by Donaldson and Dunfee (1999), unethical behavior cannotbe reduced to a fixed set of behaviors. On the other hand, as Treviño and Weaver suggest, itis not impossible to identify a list of unethical behaviors about which there is a significantdegree of social consensus:

Although there may be disagreement at the margins regarding what is and is not ethical businessconduct, 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 andindustry differences, these codes generally address similar issues with similar standards. As aresult, the business ethics researcher can stay very busy focusing on those ethical and unethicalbehaviors about which there is a large degree of social consensus. (2003: 298)

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Following the suggestion of Treviño and Weaver (2003), this article uses business codesas 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 whichconsists 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 effectivenessof business codes has been the subject of much criticism (Cowton & Thompson, 2000; Sims& Brinkmann, 2003; Somers, 2001), there is much agreement that business codes generallycover 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 codeof 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 codesof ethics are often developed on the basis of an intensive consultation process with internaland 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, businessorganizations 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 acode 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 codeusually 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 asource for identifying specific unethical behaviors is that developing a measure of unethicalbehavior 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 acommitment is not problematic if it is recognized as a description of what is typically viewedas unethical in a particular social context (Treviño & Weaver, 2003).

In short, the development of a broad construct of unethical behavior in the workplace isnecessary and possible. This construct is expected to capture clusters of specific unethicalbehaviors along the different stakeholder groups. Examining the content of business codescan generate specific unethical behaviors which can form the foundation for developing andtesting 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 behaviorwas developed and tested in eight interconnected steps.

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Step 1: Item Generation

To generate an initial set of items, the behaviors that companies address in their business codeof ethics were used as input. Much research has been conducted into the content of businesscodes of ethics (Cressey & Moore, 1983; Schlegelmilch & Langlois, 1990; White &Montgomery, 1980). As the measure was to cover a broad spectrum of norms companies aroundthe world include in their codes, the research of Kaptein (2004), who was first in collecting andanalyzing 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. Thenumber of codes analyzed per country where company headquarters were based was UnitedStates (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 developedsome 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 andregulations (57%), and treating the natural environment with due care (56%). To avoid methodartifact, it is worth noting that although many of the companies use their responsibilities towardstakeholders 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 theseelements (Kaptein, 2004).

Although Treviño and Weaver (2003) note that business codes generally address similarissues 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% orless of the business codes of ethics were eliminated. This rule of 10% is arbitrary, but themain reason for introducing the threshold was to exclude items that are hardly included inbusiness 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 studythe 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 astheir 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 negativeitems, 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 ina too extensive list of unethical behaviors, thus increasing the respondent burden and creatingproblems of low base-rate. For example, discrimination against employees could be subdividedinto 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 manyitems as possible. The result was 53 items of unethical behavior.

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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 redundanciesand unclear formulations. All items were rated for clarity using a 6-point scale ranging from1 = Very Unclear to 6 = Very Clear. Participants also had to provide their interpretation ofevery question, along with suggestions for improvement. All items that received an averagescore 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 consolidatedinto 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 itemslacked conceptual clarity. Four other business ethics scholars, 4 ethics officers, and 4 ethicsconsultants were then asked to check whether the revised list of 41 items lacked significantexamples 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 2new items, as some participants responded that it was difficult for them to distinguishbetween them. For example, the items making improper political contributions to domesticofficials and making improper payments or bribes to foreign officials were combined intomaking improper political or financial contributions to domestic or foreign officials. Thisresulted in a list of 39 items of unethical behavior.

Other decisions that had to be taken concerned the object, the method, and the frequencyscale of measurement to be used. Although self-reported behavior may be more precise, itwas 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). Evenmore so than measures of related constructs, the list of unethical behaviors includes severeviolations, the disclosure of which could have far-reaching repercussions for the respondingperpetrator. Furthermore, other reports corresponds with our level of analysis and definitionsof 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 higherfrequencies and more variance of unethical behaviors, thereby making the psychometricchallenges in studying them less complicated. Following Newstrom and Ruch (1975) andseveral other scholars in this field (e.g., Treviño & Weaver, 2003), a questionnaire wasselected as the method of enquiry. Following Treviño and Weaver (2003), a timeframe of 12months was chosen, reading “In the past 12 months, I have personally seen or have first-handknowledge 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 workingpopulation. Treviño and Weaver (2003) suggested a panel survey to circumvent the problem

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of companies’ reluctance to participate in research where unethical behavior is the object ofresearch. Anonymity of the respondents is also better guaranteed which has been found toreduce 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) thatthe sample should be representative of the population that the researcher will be studying inthe 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.1 The sample was compiled on the basis of its representativity by theprivate panel database firm MWM where these individuals are listed. Respondents wereinstructed to complete the survey as it applies to their current working situation. Individualrespondents 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 anitem-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 iftheir loading was greater than .40. Items were eliminated if an item’s loading was .30 or greaterfor more than one factor. The six factor was dropped because no item scored even .25 or greateron 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 inTable 1, all remaining items load strongly on their factor. The initial eigenvalues of these factorswere 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 1included items that were primarily related to the ethical responsibilities of the company towardfinanciers, 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 andemployees) is that abusing substances can have an impact on the financial performance as wellas the performance and satisfaction of employees (e.g., Hawks, 1991).

As shown in Table 2, the correlations between the five factors were moderate (r rangedbetween .20 and .50, p < .01). This indicates that the types of unethical behavior are distinctbut related.

Step 4: Confirmatory Factor Analysis

To conduct confirmatory factor analysis, another sample was used. As this sample alsohad to be used to assess differences between industries and job functions (Step 5), a large

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988 Journal of Management / October 2008

Table 1Step 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 0.09reporting information

1.2 Falsifying time and expense reports 0.67 -0.01 0.06 −0.09 0.031.3 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

database controls1.5 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 −0.101.7 Providing inappropriate information 0.70 0.08 −0.07 −0.06 0.14

to analysts and investors1.8 Trading securities based on inside 0.86 0.01 −0.25 −0.03 0.04

information1.9 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 conflicting tasks)

1.10 Wasting, mismanaging, or abusing 0.58 -0.04 0.24 0.00 0.00organizational resources

2.1 Engaging in false or deceptive sales 0.01 0.72 0.16 −0.01 −0.04and marketing practices (e.g., creating unrealistic expectations)

2.2 Submitting false or misleading −0.04 0.79 0.01 −0.13 −0.08invoices 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 influence customers)

2.4 Improperly gathering competitors’ 0.12 0.80 0.00 −0.01 −0.06confidential information

2.5 Fabricating or manipulating product −0.03 0.88 −0.09 −0.03 0.09quality or safety test results

2.6 Breaching customer or 0.04 0.66 0.14 0.09 0.06consumer privacy

2.7 Entering into customer contracts −0.05 0.85 −0.13 −0.01 0.12relationships without the proper terms, conditions, or approvals

2.8 Violating contract terms with customers −0.03 0.77 0.06 0.01 0.10

(continued)

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Kaptein / Unethical Behavior in the Workplace 989

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 0.10creating 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 0.12safety rules or principles

3.4 Violating employee wage, overtime, 0.06 0.05 0.61 −0.03 0.04or benefits rules

3.5 Breaching employee privacy 0.11 0.00 0.63 −0.14 0.054.1 Violating or circumventing supplier 0.04 0.19 0.05 −0.55 0.02

selection rules4.2 Accepting inappropriate gifts, favors, 0.09 0.03 0.18 −0.63 0.02

entertainment, or kickbacks from suppliers

4.3 Paying suppliers without accurate −0.01 −0.01 −0.04 −0.88 −0.01invoices or records

4.4 Entering into supplier contracts that −0.06 −0.01 0.01 −0.85 0.11lack proper terms, conditions, or approvals

4.5 Violating the intellectual property rights 0.05 −0.02 −0.01 −0.91 −0.02or confidential information of suppliers

4.6 Violating contract or payment terms −0.03 −0.01 0.04 −0.94 0.00with suppliers

4.7 Doing business with disreputable 0.03 0.04 0.00 −0.85 0.02suppliers

5.1 Violating environmental standards 0.00 −0.04 0.20 −0.04 0.65or regulations

5.2 Exposing the public to safety risk 0.05 0.00 0.15 −0.08 0.585.3 Making false or misleading claims 0.07 0.07 0.17 0.12 0.62

to the public or media5.4 Providing regulators with false or 0.08 0.02 0.03 −0.07 0.71

misleading information5.5 Making improper political or financial 0.05 0.20 −0.14 −0.02 0.63

contributions to domestic or foreign officials5.6 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 0.60human rights

Initial eigenvalues 13.70 3.44 3.24 1.98 1.89Explained 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.

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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 individualsare 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 fortheir participation. With a return of 4,056 completed questionnaires, a response rate of 59.7percent was achieved.

Of the respondents, 53% were female. As for job tenure, 8% had been working for lessthan a year, 31% between 1 and 5 years, 17% between 6 and 10 years, and 44% for morethan 10 years. Thirty-six percent of the respondents worked for an organization with 200 to1,000 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 therespondents 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 therespondents 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 wasanalyzed by a second-order confirmatory factor analysis in which each of the subscales wasassumed to originate from an encompassing construct of unethical behavior in the workplace(Jarvis, MacKenzie, & Podsakoff, 2003; Spreitzer, 1995). The objective of this analysis wasto establish whether the five subscales can indeed be interpreted as distinct subscales ofunethical behavior (discriminant validity) and whether the relation between the overallunethical behavior construct and each of the separate subscales is positive as it should beaccording 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 likelihoodestimation are summarized in the structural equation model in Figure 1. The overall fit of thefive-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 X2 dif-ference test between these two models was significant (ΔX2 = 10,542, Δdf = 4, p < .01). Theconvergent 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 statisticallysignificant. 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 towardemployees. 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 behaviortoward financiers, customers, employees, suppliers, and society.

Discriminant validity was assessed by comparing the variance-extracted estimate to thesquare 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 squareof the phi matrix. The factor correlations (phi coefficients) ranged from .55 to .77. The resultsdemonstrated excellent internal consistency (α)—much higher than the recommended

990 Journal of Management / October 2008

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Kaptein / Unethical Behavior in the Workplace 991

minimum of .7 (Nunnally, 1978): .93, .93, .90, .95, and .93 for respectively the subscales ofunethical 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, forexample, organizations, industries, and job functions differ. Should they exist, we can startto seek an explanation for such differences so as to determine which management actionsneed to be taken to prevent unethical behavior in different contexts. In Step 6, the differencesbetween three business organizations were analyzed; here differences between industries andjob functions were examined. Multivariate analyses of variance were conducted on the samesample of the U.S. working population as used in Step 4. As shown in Tables 3 and 4, therewere 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 asmuch unethical behavior toward society than respondents in other job functions, which can

Figure 1Step 4.3: Results of Second-Order Confirmatory Factor Analysis of

Unethical Behavior Subscales (N == 4,046)

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992 Journal of Management / October 2008

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 inother job functions. Less expected is that buyers were also the most frequent observers of

Table 2Step 3.2: Correlations Between Factors of Unethical Behavior (N == 400)

Unethical Behavior Toward

Financiers Customers Employees Suppliers

Customers .42**Employees .41** .35**Suppliers .43** .23** .20**Society .50** .35** .49** .29**

**p < .01

Table 3Step 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 behaviorat least once in their direct working environment in the past 12 months (mean < 5.0), whereas the percentageswithin brackets indicate the relative number of respondents who have observed unethical behavior at least threetimes in their direct working environment in the past 12 months (mean ≤ 4.5).**p < .01.

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Kaptein / Unethical Behavior in the Workplace 993

unethical behavior toward customers, whereas salespersons and marketers observed one thirdless unethical behavior toward customers than did buyers. Of the five subscales, unethicalbehavior toward employees was observed most frequently in most job functions. The highestfrequency of unethical behavior toward employees was reported by respondents working inmanufacturing, public relations, and public management. Respondents working in internal

Table 5Step 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 15Organization B 6 24 53 11 8Organization C 50 45 61 21 48F-value 42.17** 5.78** 8.38** 2.02 27.01**Company effect Wilks’ Lambda = .78, F = 15.93**

**p < .01.

Table 4Step 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)b 50 (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 behaviorat least once in their direct working environment in the past 12 months (mean < 5.0), whereas the percentageswithin brackets indicate the relative number of respondents who have observed unethical behavior at least threetimes in their direct working environment in the past 12 months (mean ≤ 4.5).b. For example, consumer products, packaged goods, automotive, aerospace, and defense.**p < .01.

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994 Journal of Management / October 2008

auditing most frequently observed unethical behavior toward financiers, whereas respondentsworking in sales and support observed unethical behavior toward financiers least frequently.

The highest frequency of observed unethical behavior toward financiers was reported byrespondents from the public sector. The frequency of observed unethical behavior towardcustomers had the least variance across sectors. Unethical behavior toward employees wasmost frequently observed within the public and manufacturing sector. Unethical behaviortoward suppliers was most frequently observed in the energy and manufacturing sector.Unethical behavior toward society was most frequently observed by respondents from theenergy and chemicals sector and the public sector. Unethical behavior was least frequentlyobserved 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 respondentsfrom 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 andlegal 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 othertwo organizations preferred to postpone the study by a year. The first organization hadrecently conducted an employee satisfaction survey and the second was in the middle of anemployee compliance and integrity awareness program. In all three participating organiza-tions, the compliance officer approved the list of items without suggesting new items orrephrasing any questions, thus providing some additional support for the content validity ofthe measure. All employees of the three participating organizations received the survey witha letter of endorsement from the board. Completion of the survey was completely voluntaryand 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 forfinanciers, .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 Table5. 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 subscalesexcept 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 unethicalbehavior subscales were sufficiently strong and identifiably different to produce significantdiscrimination among the participating organizations.

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Kaptein / Unethical Behavior in the Workplace 995

Step 7: Discriminant and Nomological Validity

To further assess the discriminant and nomological validity of the construct, a study wasset up in which the new measure was compared to other theoretically relevant constructs. Asample of 100 MBA students from a large public university in the Netherlands with at leastfive 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 comparedwith scores obtained by means of the scale of unethical behavior as developed by Newstromand 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 andthe Kacmar and Carlson (1997) scale of political behavior—and one scale for desirablebehavior—the Farh, Podsakoff, and Organ (1990) scale of altruistic behavior. It had beenexpected that the new measure would have a moderately positive relationship with scores onother undesirable behavior scales, and a moderately negative relationship with the constructsof 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’ BalancedInventory 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 allextreme scores (6, 7) on a 7-point response format as 1 and all other responses as 0. Theresponse of 10 participants was dropped because their score was higher than 0.75. Table 6depicts the means, standard deviations, and correlations for the measures.

As expected, the measure correlated most positively with Newstrom and Ruch’s scale ofunethical behavior—intraorganizational cheating (r = .81, p < .01), somewhat less positivelywith 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 termsof discriminant validity, the measure of unethical behavior did not show any correlation withcooperative 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 focusrespondents’ 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 newmeasure 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 tostart to address this issue. In this step, a study was conducted to determine the capacityof the new measure to incrementally predict relevant outcomes. A critical choice in any

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Tabl

e 6

Step

7:

Cor

rela

tion

s fo

r D

iscr

imin

ant

and

Nom

olog

ical

Val

idit

y (N

==31

)

Var

iabl

eM

ean

SD1

1a1b

1c1d

1e2

34

56

1. U

neth

ical

beh

avio

r to

war

d1.

35.2

81a

. Fin

anci

ers

1.42

.36

.74*

*1b

. Cus

tom

ers

1.36

.36

.63*

*.2

41c

. Em

ploy

ees

1.42

.42

.74*

*.4

4*.3

41d

. Sup

plie

rs1.

48.5

6.8

2**

.45*

.43*

.48*

*1e

. Soc

iety

1.15

.23

.85*

*.5

7**

.48*

.54*

*.7

4**

2. I

ntra

orga

niza

tiona

l che

atin

g2.

06.4

6.8

1**

.64*

*.3

9*.7

3**

.64*

*.6

7**

3. D

evia

nt b

ehav

ior

1.97

.53

.64*

*.4

2*.2

1.7

2**

.56*

*.5

1**

.81*

*4.

Pol

itica

l beh

avio

r2.

85.5

0.5

1**

.54*

*.1

7.3

8*.4

2*.3

5.6

2**

.56*

*5.

Altr

uist

ic b

ehav

ior

3.40

.65

−.05

−.12

.28

−.21

−.09

.01

−.12

−.27

−.17

6. C

oope

rativ

e be

havi

or3.

32.6

4.0

4.0

2.1

4−.

02−.

01.0

3.0

2−.

03−.

10.6

6**

7. I

nnov

ativ

e be

havi

or3.

40.6

5−.

05−.

13.2

1−.

08−.

11−.

02−.

02−.

18−.

19.7

7**

.74*

*

*p <

.05.

**

p <

.01.

996

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Kaptein / Unethical Behavior in the Workplace 997

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 experienceand 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 enrolledin 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 implementedethics instruments in their organization and to give two different questionnaires to twoemployees under their supervision. As reward for their participation, the managers wouldreceive a brief report about the general findings. Each potential respondent promptlyreturned their survey to the student. The use of separate samples allowed us to assess theincremental predictive power of the new measure without associated problems of commonsource variance (Podsakoff, MacKenzie, & Lee, 2003).

Eight ethics measures, such as an ethics code, ethics training, and ethics officer, wereselected 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 hadto complete a questionnaire focusing on the reputation of the organization per stakeholdergroup. A 5-point response format ranging from 1 = Strongly Disagree to 5 = Strongly Agreewas used. One hundred fourteen completed sets of three questionnaires were obtained. Table7 depicts the means, standard deviations, and correlations.

As expected, ethics instruments have a negative relationship with the observed frequencyof unethical behavior. The relationships differed for each subscale. Only the relationshipbetween ethics measures and society was insignificant, although it was almost significantwith 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 eachstakeholder group. As expected, there were different correlations for each subscale. Only thereputation 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 correlationcoefficient with another stakeholder (i.e., customers). Unethical behavior toward customersseemed to have a higher impact on the reputation of the organization to society than unethicalbehavior had toward society. The reputation of the organization to employees had the highestcorrelation coefficient for all five types of unethical behavior (the highest r in each column).

Discussion

Summary

Even though business ethics is topical both in research and practice, Newstrom andRuch’s (1975) measure of observed unethical behavior in the workplace continues to be usedby scholars despite its limitations. Not only does it cover a limited part of the full scope of

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998 Journal of Management / October 2008

this construct, the process of item generation was not very transparent and only superficiallytested 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 citeas the object of their research. The purpose of this study was to systematically develop aninstrument to measure a wider range of unethical behaviors in the workplace and to take thefirst steps in demonstrating its convergent, discriminant, and criterion-related validity.

For the first time, items have systematically been generated to create a more accurate andcomprehensive list of unethical behaviors in the workplace. Business codes of ethics of thelargest companies in the world were drawn on to produce these items. The generated itemshave been refined and validated by exploratory and confirmatory factor analyses. Large,diverse, and unique samples were collected and used. According to Bollen (1989), empiricalsupport for multidimensionality is not essential for a multidimensional scale to be theoreti-cally superior to a unidimensional scale. Nevertheless, the results resonate well with otherconceptual 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 displayfive behavioral subscales, clustered around the most important stakeholder groups: unethicalbehavior 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 betweenunethical behavior and the reputation of the organization to each stakeholder group and toexisting management instruments to prevent unethical behavior.

Table 7Step 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 1.23SD .66 .64 .77 .65 .58

Antecedent Ethics 3.82 .81 −.19* −.23* −.19* −.24* −.17measures

Reputation toward Financiers 3.78 .77 −.23* −.21* −.20* −.19* −.16Customers 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**

*p < .05. **p < .01.

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In contrast with Newstrom and Ruch’s (1975) measure of unethical behavior and theslightly adapted versions used by others, the new measure incorporates a variety of differentitems. It includes not only intraorganizational unethical behaviors, but also the as yetneglected extraorganizational unethical behaviors. Drawing on business codes to generateitems offers a better and more transparent coverage of the content validity of the constructcompared to that of the measure developed by Newstrom and Ruch. Whereas Newstrom andRuch’s measure has a unidimensional structure, the new measure structures unethical behav-iors according to five different stakeholder groups thereby creating meaningful patterns outof 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 5items (Hinkin, 1995). Such an aggregated measure is usually more reliable and valid thanspecific measures (Rushton, Brainerd, & Pressley, 1983) and thus overcomes the low baserate problems commonly associated with measuring these types of behaviors. The 37-itemmeasure 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 measuresto 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 andunethical behavior is not as prevalent as they believe it to be, the mere fact that they havethese 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 toengage in unethical behavior themselves.

Other Dimensions

This article presents empirical support for understanding the ethics of business in termsof unethical behaviors toward various stakeholders. In this research no evidence was foundto 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 deviantbehaviors. That this dimension did not crop up in the current research is understandable aswe defined unethical behavior as deviant behavior where fundamental interests are at stake.The items were also not grouped along interpersonal and organizational behaviors, which isthe second dimension Robinson and Bennett (1995) identified. A possible explanation forthis is that interpersonal behaviors, which usually only focus on relationships within theorganization and not with external stakeholders, are included in the subscale of unethicalbehavior toward employees, where the offender could be the organization (e.g., in the caseof breaching employee privacy) or colleagues (e.g., in the case of creating a hostile workenvironment). The items that would mostly coincide with the organizational dimension, suchas 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 advancedto categorize different types of unethical behavior—unethical behavior for personal gain and

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for organizational gain (Ashforth & Anand, 2003; Coleman, 1987). A conceivable reason forthis is that motives are difficult, if not impossible, to uncover when measuring the observedfrequency of unethical behavior. Motives are not always visible to bystanders or even knownto offenders themselves (Cressey, 1953). Furthermore, unethical behavior can be driven bya variety of motives (Di Norcia & Larkins, 2000). And the same types of unethical behaviorcan be fuelled by different motives (Giacalone & Greenberg, 1997).

The same line of reasoning applies to the dimension of overt versus covert behaviors, adistinction 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 alongthis dimension. This can be explained by the response scale used, which focused on observedbehavior 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). Theresults of the present study show no correspondence with his model. This can be attributedto the fact that respondents could not have known what the normative source of many of theitems of unethical behavior was (i.e., laws, moral principles, or societal expectations). Formost 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 asbehavior 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 otherdimensions are not relevant. Further research using other methods, such as self-reportedbehavior could lead to a refined model in which, for example, unethical behavior towardeach 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 interms of stakeholder groups will—as argued in the second section of this article—help us tobetter understand and prevent unethical behavior for at least three reasons. First, behaviorswithin a cluster of unethical behaviors could have similar consequences whereas differentclusters 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, itcould 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 generatesmuch opportunity for future research. To date, empirical research on unethical behavior inthe workplace has not been abundant. A possible explanation of this lack of research mightbe 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 behaviorof others in the work environment.

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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, tostudies that aim to explain the difference in impact of ethical climate and ethical culture onunethical behavior (Treviño, Butterfield, & McCabe, 1998), the best typology of ethical cli-mate that explains unethical behavior (Peterson, 2002), and the differences in unethicalbehavior 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 differencesper 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 standardizedmeasure to identify similarities and differences for these variables and to further developtheory on the basis of these findings.

With a much broader, inductively derived and empirically tested measure of unethicalbehavior in the workplace, more sophisticated studies of the antecedents and consequencesof unethical behavior can be conducted, yielding more reliable results. Different types ofunethical behavior may have different causes and different effects (Robinson & Greenberg,1998; Treviño & Weaver, 2003; Vardi, 2001) which, when proven, would further strengthenthe 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 whichcould 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 reputationof the organization to each stakeholder group.

Limitations

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 ageneral measure that can be applied to a range of organizational contexts, it includes onlythose behaviors that are addressed in more than 10% of the business codes of the largest 200companies 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 anddetailed internal standards of organizations, the codes of smaller organizations, or the codesof organizations whose headquarters are based in countries other than the 11 countries inwhich the largest 200 companies in the world are headquartered. Nor were items generatedon 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 forethical norms would not have led to other items. Thus far, however, the participating expertsand business organizations in this research have not come up with any other relevant itemsof unethical behavior. The question is also whether new ethical issues would lead to changes

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in business codes of ethics and consequently to new items and to other subscales. So far, thechosen 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 105business codes of ethics covers the last few decades because of the fact that some codes havenot 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 subscalesrenders it unlikely that the structuring of items along the five stakeholder groups wouldchange quickly.

The second limitation concerns the risks associated with approaching managers andemployees to give their opinion. A first risk in this regard concerns the subjectivity ofrespondents’ interpretation of items. If definitions of unethical behavior vary across organi-zational levels, companies, industries, countries, and even individuals (Greenberg, 1996), thequestion arises as to what is measured: the frequency of the type of unethical behavior thatis 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 itemswere formulated as clearly as possible and extensively tested for clarity. In future researchthis issue could be dealt with by asking respondents to indicate to what extent they perceivethe behavior described as unethical, something which was done by Newstrom and Ruch(1975).

Another risk related to approaching managers and employees to give their opinion is therisk of social desirability response bias. Unethical behaviors could indeed be prone to thisbias (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 suggeststhat 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 addedto 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 customeror consumer privacy scores 50% it does not mean that the privacy of 50% of the customersare breached, or that 50% of the employees breach the privacy of customers. It only meansthat 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 theU.S. working population, it is unlikely that two or more respondents worked for the sameorganization. Therefore when they indicated that they had observed a violation, it is safe toassume that different practices were referred to. However, when a survey is conductedamong employees in the same organization, observations of unethical behavior can refer tothe same practice. The risk of duplication therefore increases. This issue was partlyaddressed by asking the respondents in Step 6 to limit the behaviors they observed to theirown team or department. The objective of a survey using the new measure cannot be toestablish the exact number of times unethical behavior occurs. However, future surveyscould for each unethical behavior also include questions regarding the number and type ofpeople involved. This would help us to get a better understanding of whether unethical

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behavior occurs at the individual, group, or organizational level (Vardi & Weitz, 2004) andwhether or not it occurs in collaboration with external stakeholders. Future research couldcompare the frequency of reported unethical behavior examined by means of a questionnairewith other sources available in an organization, such as a misconduct reporting system, theuse 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 newmeasure of unethical behavior in the workplace and its five subscales.

Practical Implications

Measuring unethical behavior in the workplace is essential for business organizations todecide 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 fivestakeholder groups. Aware of the limitations of the measure, organizations, like those in Step6 of this study, could use this questionnaire by distributing it among employees. An analysisof the response could provide an overview ranking the unethical behaviors based on theirobserved frequency, and if necessary, also a break-down structured around background vari-ables such as job function and department. Following this, the organization can determinewhich 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 haveon each stakeholder group as well as on the performance of the organization, and/or how itcompares to the observed frequencies within other organizations or other departments withinthe 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 carryout regression analyses to determine to what extent the organizational climate and culturestimulate each type of unethical behavior and which aspects of the climate and culture needto 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—andhopefully improvements—will become visible. If this is achieved, this research project hasbeen valorized.

Note

1. Following the suggestions of Harkness and Schoua-Glusberg (1998), the questionnaire was translated intoDutch by the author who grew up in the Netherlands. Two bilingual colleagues also independently translated thequestionnaire into Dutch after which the three versions were discussed to produce a consensual version. Blind tothe original questionnaire, a professional translator translated the Dutch questionnaire back into English. The authorand the translator compared the back-translated text for inconsistencies with the original version to finalize theDutch version. A version of the Dutch survey is available on request from the author.

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Biographical Note

Muel Kaptein is professor of Business Ethics and Integrity Management at RSM Erasmus University. His researchinterests include the management of ethics, the ethics of management, and the measurement of ethics.

1008 Journal of Management / October 2008

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