Workplace deviance (Berry, Ones, & Sackett, 2007; Bodankin & Tziner, 2009; Cohen-Charash & Mueller, 2007; Dilchert, Ones, Davis, & Rostow, 2007; Levy & Tziner, 2011) is defined as “voluntary behavior that violates significant organizational norms and, in so doing, threatens the well-being of the organization, or its members or both” (Robinson & Bennett, 1995, p. 556). Examples include theft, sabotage, vandalism, embezzlement, withdrawal, harassment, and drug use (Bennett & Robinson, 2000; Gruys & Sackett, 2003; Robinson & Bennett, 1995; Sackett & DeVore, 2001; Spector et al., 2006). These behaviors are defined as dysfunctional because they harm organizations in many respects, including the thwarting of goal achievement, inhibition of fellow employees, and disruption of procedures, productivity, and profitability (Aubé, Rousseau, Mama, & Morin, 2009; Dalal, 2005; Lanyon & Goodstein, 2004; Pearson, Andersson, & Porath, 2005; Robinson, 2008; Spector & Fox, 2005; Spector et al., 2006; Vardi & Weitz, 2004). For instance, in 2010 alone, a loss of 15.9 billion dollars was attributed to employee theft in the U.S.A. (Hollinger & Adams, 2010).

Past research has indicated that individual variables may account for personal differences in work deviance, such as employees’ personal traits and abilities (e.g., Berry et al., 2007; Dalal, 2005; Dilchert et al., 2007; Salgado, 2002; Salgado, Moscoso, & Anderson, 2013), job experiences (e.g., Hollinger & Clark, 1982; Kulas, McInnerney, DeMuth, & Jadwinski, 2007; Zhang, Mayer, & Hwang, 2017), and work stressors, including difficult work conditions and interpersonal conflicts (Bruk-Lee & Spector, 2006; Chen & Spector, 1992; Diefendorff & Mehta, 2007; Mitchell & Ambrose, 2007; Spector & Fox, 2005). Furthermore, one of the prevalent findings is that workplace deviance may be also related to gender. In general, past studies examining the mean differences in aggressiveness have shown that men display and report aggression more frequently than women (e.g., Geen 2001; Griskevicius et al., 2009; Harris, 1996; Hershcovis et al., 2007; Kogut, Langley, & O’Neal, 1992; Martinko, Douglas, & Harvey, 2006; Tavris, 1984). These differences are said to reflect a stable personality disposition, which persists throughout the lifespan and in various life areas (e.g., Walker, Richardson, & Green, 2000). Specifically, men tend more than women to display aggression towards others without provocation and to display their hostility directly. Men are also strongly motivated to retaliate aggressively against self-invalidating events more than women (see Bjorkqvist, Osterman, & Lagerspetz, 1994).

One of the explanations of these findings traces gender-based differences in aggression to physiological dispositions, such as higher levels of testosterone among men (e.g., Archer 2006; Book, Starzyk, & Quinsey, 2001). Another explanation emphasizes internalized gender roles based on culturally prevalent gender stereotypes. While men in most cultures are stereotyped as cold, competitive, self-relying and authoritative, women are traditionally believed to be warm, nurturing, caring, and dependent (Fiske, Cuddy, Glick, & Xu, 2002; Kawakami, White, & Langer, 2000). Accordingly, men are expected to display aggressiveness and anti-social behaviors more than women. Specific to the organizational context, previous research has indicated that these beliefs lead to a double standard that gives men greater freedom than women to express negative feelings such as anger (e.g., Black, 1990). Further, interactions between gender and personality traits were assessed in predicting counterproductive work behaviors directed at individuals. Specifically, agreeableness and pleasantness were found to be negative predictors among men (but not women), whereas emotional stability was a negative predictor among women (but not men) (Gonzalez-Mulé, DeGeest, Kiersch, & Mount, 2013). On the other hand, Hershcovis et al.’s (2007) meta-analysis of workplace aggression indicated that there is little gender difference with respect to indirect forms of aggression. Although this meta-analysis does not address the definitions of “direct” versus “indirect” aggression, we may look at several definitions suggested in the literature. For example, Richardson (2014) defines “direct” aggression as more obvious form of aggression, such as direct physical or verbal attack (e.g., yelling, hitting). In contrast, “indirect” aggression described less obvious acts such as those where a person does not confront the target directly (e.g., spreading rumors, damaging property). Further, according to Warren, Richardson, and McQuillin (2011), direct aggressive behaviors involve confronting another person, whereas indirect aggressive behaviors involve attempting to hurt someone by going through another person or object. Indirect aggression was also conceptualized as behaviors bringing harm by rejection or exclusion, including acts of verbal and physical aggression that are unrelated to relationships (e.g., giving “dirty looks”) (see Marshall, Arnold, Rolon-Arroyo, & Griffith, 2015).

Yet, in relation to both types of aggressive and anti-social behavior, including in the organizational context, findings of studies that examined gender differences in terms of mean scores of behaviors are still in question. These scores are mainly obtained from self-report measures or descriptions of external observers, such as colleagues or supervisors. However, while these comparisons provide information on the magnitude of a general tendency of each gender to behave in certain way (and indicate whether any differences in these tendencies are statistically significant), they led only to rough distinctions but did not provide data regarding the prevalence of more specific behavioral manifestations (see Bjorkqvist et al., 1994; Kogut et al., 1992; Meyers-Levy & Loken, 2015). Since the previous gender differences studies were based on overall or average measure of verbal and physical aggression (e.g., Marshall, et al., 2015) or of direct and indirect aggressive behaviors (e.g., Warren et al., 2011), not a specific measure of them, it would not be possible to identify which subscales or items (included in the mean score) are responsible for gender differences.

With respect to workplace deviance, in particular, Bennett and Robinson (2000) asserted that two conceptual dimensions comprise interpersonal deviance and organizational deviance. Interpersonal deviance is targeted at its members (e.g., managers, supervisors, colleagues), while organizational deviance is targeted at the organization, per se. Although both types of behavior vary along the dimension of severity, this distinction is important since, following Bennett and Robinson (2000), there is a qualitative difference between them and each category of deviant behavior is indicated to be motivated by different factors. Accordingly, past research suggested separate targets of workplace deviance in order to demonstrate different patterns of such behavior (e.g., Hershcovis et al., 2007).

A review of empirical ethical decision making literature, in the scope of eight years, conducted by O’Fallon and Butterfield (2005) showed that relatively small amount of studies has examined moderators to the ethical decision-making process. Yet, they argue that examining interaction effects has a potential to broaden the understanding of the decision making addressing ethical issues. Exploring individual factors relevant to ethical decisions as well as using various statistical methods are said to be the strengths of organizational behavior research (O’Fallon & Butterfield, 2005). Accordingly, in the present study we aimed to explore the moderating effect of employee’s gender, implementing a profile analysis paradigm. Further, although there is an empirical support for high correlation between interpersonal and organizational deviance, the two types were found to have different relationships with personal characteristics such as Big Five variables, lending support for assessing these types of deviance separately (see Berry et al., 2007; Robinson & Bennett, 1995). Therefore, Berry et al. (2007) propose that organizations concerned with instances of employees’ deviance should examine individual traits correlated with such behavior.

We focused on examining the role of gender in the two categories of workplace deviance recorded above (i.e., interpersonal and organizational) through the employment of a statistical method, namely, Profile Analysis via Multidimensional Scaling (PAMS; Kim, Annunziato, & Olatunji, 2017; Kim, Frisby, & Davison, 2004). Unlike the previous studies that examined mainly mean differences in gender, we sought to examine which counterproductive work behaviors measuring variables (relevant to interpersonal and organizational deviance) made gender differences. This novel profile approach augments the mean difference analyses, making it possible to compare specific deviance behavior indicators between males and females included in the profiles. Therefore, the current profile analysis (PAMS) includes much richer information to assess deviance behaviors displayed by men and women more specifically.

Although the statistical method of multidimensional scaling has been used to study organizational deviance in the past (indicating different dimensions of workplace deviant behavior; see Robinson & Bennett, 1995), the PAMS technique utilizes nonmetric multidimensional scaling (MDS) estimating scale values for input variables (in the present project, workplace deviant behaviors) and “interprets” an array of scale values in a given dimension as their profile pattern, which is considered to represent a core profile for individual person response profiles. Interpreting dimensions as core profiles has been supported and validated by numerous studies (e.g., Frisby & Kim, 2008; Kim, 2013; Kim et al., 2017; Kim, Davison, & Frisby, 2007; McKay et al., 2014; Olatunji, Kim, & Wall, 2015; Sosinsky & Kim, 2013). Specifically, person p’s response profile can be replicated with PAMS parameter estimates, indicating a level index for person p (mean of input variable scores) + person p’s weights on core profiles + a residual.

The benefits of the PAMS method can be summarized as follows: (1) PAMS summarizes numerous person profiles with a few core profiles, to make it easier to understand the individual response profiles; (2) accordingly, PAMS allows us to explain participants’ response profiles in terms of both observed mean scores and latent dimension scores; (3) further, PAMS interprets dimensions not as single construct factors but as core profiles that include all input variables as a constellation of individual persons’ profiles.

In sum, our research sought to contribute to the literature addressing individual differences in workplace deviant behavior through the discovering of interpersonal and organizational behavior patterns. Specifically, given the inconsistent evidence on gender differences in workplace deviance, in the present exploratory research we aimed to investigate further manifestations of two particular types of workplace deviance implementing an analysis technique which is capable to unveil profiles of the deviant behavior rather than comparing between mean scores of the behaviors in question.

In the present report, we label interpersonal deviance as ID and organizational deviance as OD. We start with presenting PAMS’ results on: 1) relations between gender and inter-personal deviance versus organizational deviance and 2) profiles of OD & ID separately for men and women.

The present investigation sought to examine gender differences in two types of workplace deviance - interpersonal and organizational - by adopting a profile analysis approach that allows us to discover specific behavioral profiles and, accordingly, to compare gender differences in their behavioral patterns. Unlike comparing mean differences between genders, we compared the effect sizes for all interpersonal deviance (ID) and organizational deviance (OD) measuring variables included in male and female profiles. Since all measuring variables were included in a single profile, we could easily inspect gender differences appearing in specific variables simultaneously across latent dimensions. Hence, the profile analysis adopted here carries gender difference information not only in observed mean scores of individual input variables (represented in the first dimension or core profile) but also in latent scores of them (represented in the subsequent dimension or core profile coordinates). The unique aspect of the present study consists in casting a further “luminous” light on gender differences in organizational and interpersonal deviance behaviors relative to the conventional mean score-comparison approach. As shown in Tables 5 and 7, there was no virtual mean difference of ID or OD items between males and females but substantial gender differences were found in profile coordinates.

Table 7

Note. The values are observed means that are used as core profile coordinates and the values in parentheses are coordinate standard errors estimated by bootstrapping. Except the male org5 and the female org15 z-ratios, all other z-ratios between coordinates and standard errors are equal to or larger than |2.00|, which indicates statistical significance for the coordinates. Since the male org5 and the female org15 z-ratios are less than |2.00|, we may consider their coordinates statistically to be insignificant (considered to be 0), and those effect sizes are recalculated.

The gender differences found in the core profiles are consistent with the past research findings pointing to lesser direct aggression among women compared to men (e.g., Arnocky, Sunderani, Miller, & Vaillancourt, 2012; Bjorkqvist et al., 1994; Card, Stucky, Sawalani, & Little, 2008; Cross, Copping, & Campbell, 2011). However, none of the previous studies has reported all these gender differences appearing in ID and OD measurement altogether as shown in the current study. Accordingly, of interest are present findings indicating that the gender differences were apparent on both inter-personal and organizational levels. Specifically, direct aggression was found in males on inter-personal level items, such as “Ethnic/religious/racial remarks” and “Cursing” and on organizational level items, such as “Leaving work for someone else”, “Taking property”, “Littering work environment”, and “Losing temper”.

In contrast, women reported more indirect aggression on inter-personal level item, “Publicly embarrassing someone”, and on organizational level items, “Falsifying receipts”, “Dragging out work”, “Working slower”, and “Discussing confidential organizational information” (as shown in Tables 3 and 5). Therefore, the current study reveals that gender differences in aggressive workplace behavior are not only those apparent in inter-personal relations, as studied by the previous research, but also when directed towards the organization, its goals, or values.

Interestingly, no gender difference was found in mean score profiles which were in fact the first core profiles and this finding complements the conventional mean difference methods (e.g., t-test or ANOVA). Hence, if we relied on the conventional mean difference approach, we would not find any gender differences with our current data.

Based on gender differences appearing in core profile patterns, the present findings may imply further that the organizational context, particularly, brings diverse suggestions for interpersonal deviance for males and females, beyond the differentiation of directness of aggressive behavior. This notion, which could be the subject of further research, is consistent with the findings of Santos and Eger (2014) indicating that organizational context has specific implications for aggressive behavior, as males exhibiting higher organizational workplace deviance, in contrast to interpersonal workplace deviance, were those with over five years working experience in the company.

There may be psychological factors, such as stress related problems (e.g., O’Leary-Kelly, Griffin, & Glew, 1996), experiencing low self-esteem, increased lack of confidence at work, and physical and psychological pains (e.g., Griffin, O’Leary, & Collins, 1998), that account for these gender differences. One plausible explanation is that mirroring the picture of aggressive behavior in broader social contexts, direct deviant behaviors in the workplace characterize men more than women. Another possibility is that, given gender differences in the content of deviant behaviors shown in the present work, men and women interpret differently the plausibility of certain behavior in organizational context. For example, status differences of men and women in the workplace may be a possible reason. Past research has shown the relevance of gender to different aspects of career and employment. Although much has changed through the years, women still enjoy lesser career advancement and employment prestige compared to men (Timberlake, 2005) and perceived as more “applicable” for support roles than for leadership roles (Eagly & Karau, 2002; Eagly & Sczesny, 2009). Accordingly, women’s reports of indirect aggression on interpersonal deviance (e.g., publicly embarrassing someone) and organizational deviance items (e.g., falsifying receipts, dragging out work, working slower, and discussing confidential organizational information) may be attributed to perceived threat on employment status. Women, being aware of their initially lower status compared to men as well as of social stereotypes allowing men to exhibit aggression more than to women (e.g. Heliman & Chen, 2005; Kark, Waismel-Manor, & Shamir, 2012), may forecast high costs in manifesting direct aggression and choose indirect acts instead.