Abstract
Purpose
The purpose of this paper is to examine hostility as a mediator of the relationship between perceptions of organizational politics (POP) and counterproductive work behavior (CWB).
Design/methodology/approach
The authors’ examined the mediation model using a sample of 171 full-time employees studying in an evening MBA program. The authors’ collected the data for this study in three waves.
Findings
The findings supported all of the hypotheses. POP was positively related to both hostility and CWB. Moreover, hostility mediated the relationships between POP and both organizational and interpersonal CWB.
Practical implications
Given that individuals high in emotional intelligence (EI) are better at regulating their negative emotions, EI training may be a powerful tool for reducing the hostility elicited among organizational members in response to POP, and consequently, their engagement in CWB.
Originality/value
The current study uncovered the emotional mechanism that underlies the POP-CWB relationship. The findings have intriguing implications in terms of potential moderators that can be developed through interventions in an attempt to reduce the hostility and CWB that result from POP.
Keywords
Citation
Meisler, G., Drory, A. and Vigoda-Gadot, E. (2020), "Perceived organizational politics and counterproductive work behavior: The mediating role of hostility", Personnel Review, Vol. 49 No. 8, pp. 1505-1517. https://doi.org/10.1108/PR-12-2017-0392
Publisher
:Emerald Publishing Limited
Copyright © 2019, Galit Meisler, Amos Drory and Eran Vigoda-Gadot
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
It is well accepted that perceptions of organizational politics (POP) play a central role in shaping undesirable work outcomes such as job burnout, job dissatisfaction and turnover intentions (Chang et al., 2009; Ferris et al., 1996; Miller et al., 2008). Recently, the notion that POP shapes counterproductive work behavior (CWB), meaning, the destructive attempts of employees to intentionally harm the organization and/or its other members (Bennett and Robinson, 2000; Robinson and Bennett, 1995, 1997; Spector and Fox, 2005; Spector et al., 2006), has also been acknowledged. Specifically, studies have proposed and documented that POP is positively related to CWB. Furthermore, they have established the honesty-humility personality factor (see Ashton and Lee, 2005, 2008) as a moderator of the POP-CWB relationship (Wiltshire et al., 2014; Zettler and Hilbig, 2010). Nevertheless, the mechanism through which POP relates to CWB remains unknown, limiting our understanding about the motives that drive organizational members to engage in CWB in response to POP. Such a lack of knowledge impedes our ability to plan and execute interventions designed to reduce deviant behavior, which is a consequence of POP. Indeed, and as noted above, several studies have determined that honesty-humility moderates the relationship between POP and CWB (Wiltshire et al., 2014; Zettler and Hilbig, 2010). However, the stability of this personality factor challenges the effectiveness of interventions designed to increase it. Therefore, identifying intervening variables that can be developed through training in an attempt to reduce the negative implications of POP on CWB seems extremely necessary. The current research addresses these issues. Relying on Penney and Spector (2008), who argued that perceived organizational stressors elicit negative emotions that result in CWB, we maintain that POP prompts hostility, which then leads organizational members to engage in CWB toward the organization and its other members. We then test these hypotheses empirically.
Theoretical framework
Over the past three decades, most of the research in the field of organizational politics has explored the model of perceptions of organizational politics presented by Ferris et al. (1989). The findings from that research have shown that POP, meaning, the perceptions held by organizational members regarding the level of politics swirling around in their organizations, are positively related to undesirable work outcomes such as stress, job burnout, and turnover intentions, and negatively related to the desirable outcomes of job satisfaction, organizational commitment, task performance, and organizational citizenship behavior (see Chang et al., 2009; Ferris et al., 1996; Miller et al., 2008). As noted earlier, recent studies have also explored the implications of POP for CWB. Specifically, they have investigated the direct association between POP and CWB, and the integrated effect of POP and the honesty-humility personality factor (see Ashton and Lee, 2005, 2008) on CWB. Empirical evidence from these studies has shown that POP and CWB are positively related, and that the POP-CWB relationship is stronger for employees low in honesty-humility than for those with a higher level of this personality factor (Wiltshire et al., 2014; Zettler and Hilbig, 2010). Nevertheless, to date we have no knowledge about the mechanism through which POP relates to CWB. This lack of knowledge limits our general understanding about the motives that drive organizational members to engage in CWB in response to POP. Consequently, our ability to identify potential moderators that can reduce the negative implications of POP for CWB is also limited.
The current research
Figure 1 presents our research model. According to the model, POP elicits hostility, which in turn affects CWB.
Hostility is a discrete negative emotion classified under the primary category of anger (Shaver et al., 1987). Hostility includes both anger and antagonism toward others (Barefoot, 1992; Bridewell and Chang, 1997; Bushman and Anderson, 2001; Penney and Spector, 2008), and is elicited mainly in response to perceived injustice (Folger, 1987; Folger and Cropanzano, 2001). Given that politically charged organizations are unfair work environments in which employees do not receive appropriate compensation for their efforts (Drory and Vigoda-Gadot, 2010; Ferris et al., 1996; Vigoda, 2002), one may assume that POP elicits hostility among organizational members.
Surely, it is difficult to believe that anger and even hostility do not arise in a politically charged work environment. On the contrary, it is much more reasonable to assume that employees who are personally affected by unfair political events and procedures develop hostility toward their organizations. Moreover, we can also surmise that even employees who only witness unjust political incidents in their work environment might consequently develop hostility toward their organizations. This notion accords with Penney and Spector’s (2008) model, which posits that organizational stressors, such as perceived organizational injustice, elicit negative emotions that result in CWB. Indeed, recent research has acknowledged this notion and suggested that POP evokes hostility among organizational members (Drory and Meisler, 2016). However, this suggestion lacks empirical evidence to support or reject it. Relying on the justifications presented above, we argue that higher levels of POP are associated with greater hostility, and vice versa. In other words, we posit that:
POP will be positively related to hostility.
According to Penney and Spector (2008), negative emotions lead organizational members to engage in CWB. Similarly, our model posits that hostility leads organizational members to engage in CWB toward both the organization and its other members. The former, called organizational CWB (O-CWB), refers to the intentional attempts of employees to harm the organization itself. The latter, called interpersonal CWB (I-CWB), describes the attempts of employees to harm other organizational members (Bennett and Robinson, 2000; Robinson and Bennett, 1995, 1997; Spector and Fox, 2005; Spector et al., 2006). Examples of CWB include sabotaging equipment, theft, abusing others, spreading rumors and unjustified absenteeism (Bennett and Robinson, 2000; Penney and Spector, 2008; Spector and Fox, 2005).
A review of the literature reveals that hostility involves a strong tendency to express external aggression against others, and engage in violent behavior toward them (Bridewell and Chang, 1997; Bushman and Anderson, 2001). As such, experiencing hostility at work can lead organizational members to engage in aggressive and violent behavior, usually as a means of venting their negative emotions (Robinson and Bennett, 1997). Engaging in aggressive and violent behavior in response to hostility can take the form of CWB (Mitchell and Ambrose, 2007; Robinson and Bennett, 1997). Indeed, empirical evidence has shown that hostility predicts CWB over and above the higher-order negative affect construct, and that hostility is as important a predictor of CWB as cognition (Lee and Allen, 2002).
Although these findings advance our general knowledge about the hostility-CWB relationship, additional exploration of the role of hostility in shaping the separate dimensions of CWB, namely, O-CWB and I-CWB (Bennett and Robinson, 2000), is still needed. As noted above, we maintain that experiencing hostility in the workplace leads organizational members to engage in both forms of CWB. Therefore, we argue that:
Hostility will be positively related to O-CWB.
Hostility will be positively related to I-CWB.
As Figure 1 shows, POP leads organizational members to engage in both O-CWB and I-CWB. According to Spector and his colleagues, employees usually engage in CWB in response to organizational stressors such as perceived organizational injustice, psychological contract breaches and organizational constraints that interfere with the achievement or maintenance of personal goals at work (Cohen-Charash and Spector, 2001; Fox et al., 2001; Penney and Spector, 2008; Pindek and Spector, 2016; Spector and Fox, 2002). When faced with such stressors, employees tend to retaliate by engaging in CWB (Mitchell and Ambrose, 2007; Robinson and Bennett, 1997) in order to restore their sense of equity and justice (Fox et al., 2001).
A politically charged work environment is considered an organizational stressor (see: Chang et al., 2009; Ferris et al., 1989; Harris et al., 2009; Meisler et al., 2017; Miller et al., 2008). In addition, studies have established that organizational politics is positively associated with other organizational stressors, such as organizational injustice, psychological contract breaches and organizational constraints that interfere with the achievement and maintenance of personal work goals (Ferris et al., 1989, 1996; Vigoda, 2002). Hence, we believe that POP can be considered another organizational stressor that leads organizational members to engage in destructive behavior in order to restore their sense of equity and justice (Cohen-Charash and Spector, 2001; Fox et al., 2001; Penney and Spector, 2008; Pindek and Spector, 2016; Spector and Fox, 2002). Indeed, recent studies have found that POP and CWB are positively related (Wiltshire et al., 2014; Zettler and Hilbig, 2010). Nevertheless, to date we have no knowledge about the associations between POP and each of the separate dimensions of CWB (see Bennett and Robinson, 2000). As our model shows, we believe that POP is associated with both forms of CWB. Specifically, we argue that higher levels of POP lead employees to engage in retaliatory behavior against the politically charged organization (O-CWB). Moreover, we maintain that higher levels of POP lead employees to engage in retaliatory behavior against other organizational members (I-CWB) whom they regard as responsible for creating the politically charged work environment. Formally, we suggest that:
POP will be positively related to O-CWB.
POP will be positively related to I-CWB.
According to Figure 1, the relationships between POP and both forms of CWB are mediated by hostility. Following Penney and Spector (2008), who posited that negative emotions mediate the relationship between organizational stressors on the one hand and CWB on the other, we argue that POP elicits hostility (see H1), which in turn leads organizational members to engage in CWB against both the organization and its other members.
A recent study established that hostility mediates the relationship between perceived interpersonal injustice and CWB (Judge et al., 2006). Similarly, we investigated the mediating role of hostility in the relationship between POP and CWB. As noted above, POP is an organizational stressor (Chang et al., 2009; Ferris et al., 1989; Meisler et al., 2017; Miller et al., 2008) associated with unfair political events and procedures that are expected to elicit hostility among organizational members (see H1). Keeping in mind the notion that hostility leads organizational members to engage in both forms of CWB (see H2), it is reasonable to believe that the hostility evoked among organizational members in response to POP will lead them to engage in both O-CWB and I-CWB. In other words, we propose that hostility mediates the relationship between POP and both forms of CWB. Based on these justifications we posit that:
Hostility will mediate the relationship between POP and O-CWB.
Hostility will mediate the relationship between POP and I-CWB.
Method
Sample and procedure
We tested our hypotheses using 171 students in an evening MBA program. All of the participants were full-time employees who had worked in their current jobs for at least six months. The data were collected in three waves with a six-week interval between the first and second waves, as well as between the second and third waves. In wave 1, the participants provided information about POP. In wave 2, they provided information about the hostility they experienced in response to the organizational politics in their organizations and about three control variables (i.e. age, gender and tenure). In wave 3, they provided information about their CWB.
The participants came from a variety of organizations and sectors such as banking, communication, commerce, and insurance, and from different hierarchical levels in the organizations that ranged from employees to low and mid-level managers. A breakdown of the sample revealed that 45 percent of the respondents were males, and their average age was 34.7 (SD=7.9). On average, respondents had 16.2 years of education (SD=1.5), and their average tenure in their organizations was 10.2 years (SD=7.6). Participation in the study was voluntary. Students could choose not to participate in the study and were guaranteed that their interests would not be affected. Participants were assured that the data collected would be used for research purposes only and that the confidentiality of the data would be maintained. Participants were asked to avoid providing any identifying information. The three questionnaires of each participant were matched through a code number. Hence, the anonymity of the participants was assured, reducing the likelihood of social desirability bias.
Measures
Perceptions of organizational politics
We measured POP using the six-item scale of Hochwarter et al. (2003). Sample items include: “There is a lot of self-serving behavior going on;” “People do what’s best for them, not what’s best for the organization” and “Many employees are trying to maneuver their way into the in group.” Responses ranged from 1 (never true) to 5 (always true), and the reliability was 0.92.
Hostility
We assessed hostility using the six-item hostility scale of the positive and negative affect schedule – expanded form (PANAS-X) (Watson and Clark, 1994). Unlike the PANAS (Watson et al., 1988), which contains two general scales – one for positive affect and the other for negative affect – the PANAS-X includes four different scales for the following four discrete negative emotions: hostility, fear, guilt and sadness. Moreover, it contains scales for three discrete positive emotions, as well as for four other affective states. Participants were instructed to indicate the extent to which they experienced each of the feelings included on the hostility scale in the last six months due to the organizational politics in their organizations. Sample items for the hostility scale include: “angry,” “irritable” and “disgusted.” The scale ranged from 1 (not at all) to 5 (very much), and the reliability was 0.91.
Counterproductive work behavior
This variable was assessed using Bennett and Robinson’s (2000) interpersonal and organizational deviance scale. The scale consists of 19 items divided into two dimensions: 12 items for the organizational deviance dimension and seven items for the interpersonal deviance dimension. Participants were asked to indicate how often they engaged in various behaviors in the workplace during the last six months. Sample items for the organizational CWB dimension include: “Taken property from work without permission” and “Intentionally worked slower than you could have worked.” Sample items for the interpersonal CWB dimension include: “Played a mean prank on someone at work” and “Said something hurtful to someone at work.” Responses ranged from 1 (never) to 7 (daily). The reliabilities for the O-CWB and the I-CWB measures were 0.85 and 0.88, respectively.
Control variables
We collected data about age and gender because previous research found them to be significantly related to CWB (Berry et al., 2007). Age was measured as continuous variable, while gender was measured as a categorical one.
Data analysis
The mediation models were analyzed using the PROCESS procedure for SPSS Version 3.00 (Hayes, 2013). The zero-order associations between the variables were examined using Pearson’s correlation coefficient. Prior to testing the hypotheses, we conducted several confirmatory factor analyses using Mplus Version 8.0 (Muthén and Muthén, 2017) to validate the theoretical constructs.
Results
As noted above, we used Mplus Version 8.0 to confirm the dimensionality of CWB. We compared three options: a two-factor model (O-CWB and I-CWB as two different constructs), a one-factor model (O-CWB and I-CWB as one construct), and a second-order construct. The two-factor model resulted in a better model fit (CFI=0.936, TLI=0.917, RMSEA=0.071, SRMR=0.054) than the one-factor option (CFI=0.869, TLI=0.832, RMSEA=0.101, SRMR=0.068). The second-order factor option yielded a negative residual variance, so we rejected it as an alternative factor structure. We also excluded item 12 from the O-CWB scale given its low loading (λ<0.30) on this factor. In line with the suggested original dimensionality of the scale (see: Bennett and Robinson, 2000; Robinson and Bennett, 1995), the two-factor model, meaning, O-CWB and I-CWB as separate constructs, was the superior option. Thus, we tested the research model separately for each dependent indicator. In addition, we also tested the four research factors altogether (two factors for CWB, one factor for POP, and one factor for hostility) within a measurement model. The model resulted in a reasonable fit: CFI=0.937, TLI=0.928, RMSEA=0.056, χ2=583.43, df=381, p<0.001, SRMR=0.057 (Wang and Wang, 2012). An exploratory test showed that the one-factor model explained 39.1 percent of the variance in the two CWB constructs, and 28.3 percent for all four theoretical constructs in the model, below the suggested minimum of 50 percent (Harman’s one-factor exploratory test; Harman, 1976).
In order to rule out the effect of common method variance, in addition to both our surveys taken at three points in time and the practice of ensuring the complete anonymity of the participants, we performed several statistical tests that Podsakoff et al. (2003) suggested. First, we followed the guidance of Bagozzi et al. (1991) and examined the correlation matrix. As the results that appear in Table I show, the correlations among the research variables were low-to-moderate, except for a high correlation between the two dimensions of CWB. The Cronbach’s α of the research variables were well above the suggested value of 0.70 (Nunnally, 1978). Second, we compared the fit results of the four factors to a single-method factor approach, as in Podsakoff et al. (2003, 3A), and found a small difference between the two approaches (with CMV: χ2/df=1.536, CFI=0.937, RMSEA=0.056 vs original model: χ2/df=1.531, CFI=0.942, RMSEA=0.056). Finally, we constructed a series of two-factor models to assess the discriminant validity between each pair of constructs (Bagozzi et al., 1991). The findings exhibited a significant reduction in the model fit when the correlation between each pair of factors was constrained to 1, as opposed to an unconstrained estimation. Such findings suggest that the factors indicate discriminant validity. Based on these results we constructed four indicators for each of the latent factors that were tested.
Next, we examined the mediation models using the PROCESS procedure for SPSS Version 3.00 (Hayes, 2013). Note that age and gender were included in the analyses as control variables, and that all of the variables were z-transformed prior to the analyses such that the estimates proxied the effect size, as in the direct standardized regression estimates. Tables II and III present the standardized regression coefficients.
To test the mediating effect of hostility on the association between POP and both O-CWB and I-CWB, we employed a bias-corrected bootstrapping method (Model 4: Hayes, 2013). The results of the mediation analyses indicated that POP was indirectly related to both O-CWB and I-CWB through its relationship with hostility. Specifically, POP and hostility were positively associated (Model 2: β=0.24, p=0.01). Moreover, hostility was positively associated with both O-CWB (Table II, Model 3: β = 0.26, p=0.001) and I-CWB (Table III, Model 3: β=0.19, p=0.01). The positive direct effects of POP on O-CWB and I-CWB, without taking into account the indirect effect of POP on these outcomes through hostility, were significant for both O-CWB (Table II, Model 1: β=0.17, p=0.03) and I-CWB (Table III, Model 1: β=0.15, p=0.05). However, after taking into account the indirect effect of POP on O-CWB and I-CWB through hostility, the direct effects of POP on O-CWB (Table II, Model 3: β = 0.11, p=0.17) and I-CWB (Table III, Model 3: β=0.11, p=0.17) became insignificant. A 95% bias-corrected confidence interval based on 10,000 bootstrap resamples indicated that the indirect effects of POP on both O-CWB (β=0.063, 95% Boot CI: Lower=0.013,Upper=0.128) and I-CWB (β=0.045, 95% Boot CI: Lower=0.005, Upper=0.095) were significantly different from zero. Hence, the indirect effects of POP on these two outcomes were significant. In other words, our analyses suggest that hostility completely mediated the relationships between POP and both forms of CWB.
Discussion
The current research explored the mediating mechanism through which POP and CWB relate to each other. The research presented and empirically investigated a model in which hostility mediates the relationship between POP and both forms of CWB. The findings provide support for all of the hypotheses. Specifically, POP was positively associated with hostility, as well with both forms of CWB, supporting H1, H3a and H3b. Additionally, hostility was positively associated with O-CWB and I-CWB, and played a mediating role in the relationships between POP and these two outcomes, confirming H2a, H2b, H4a and H4b.
By shedding light on the emotional motives that lie underneath the organizational surface and shape the destructive implications of POP, our findings demonstrate the central role of emotion in organizational politics. We believe that our findings are very encouraging given that they have potential practical implications that will be discussed in the following section.
Contributions and implications
This study makes several contributions to the literature. First, it provides empirical evidence for the proposition that hostility mediates the relationship between POP and both forms of CWB. Such evidence advances our knowledge about the mechanism through which POP relates to CWB, accentuating the contribution of negative emotions to explaining the destructive implications of POP. Second, unlike previous research that explored the association between POP and the overall construct of CWB (Wiltshire et al., 2014; Zettler and Hilbig, 2010), we investigated the relationships between POP and the separate dimensions of CWB.
Finally, this study has intriguing practical implications. Specifically, our findings establish that hostility is a consequence of POP that leads organizational members to engage in destructive behavior toward the organization and its other members. Keeping in mind that: a) individuals high in emotional intelligence (EI) are better at regulating their negative emotions (Mayer and Salovey, 1997; Salovey and Mayer, 1990), and dwell less on the circumstances in their workplace that evoke these emotions (Meisler, 2013, 2014; Meisler and Vigoda-Gadot, 2014; Meisler et al., 2013, 2017), and b) EI training improves one’s EI level (Edelman and van Knippenberg, 2017; Hodzic et al., 2017; Mattingly and Kraiger, 2019; Nelis et al., 2009), interventions aimed at enhancing employees’ EI have the potential to reduce the hostility elicited among organizational members in response to POP, and consequently, the engagement of organizational members in CWB.
Strengths and limitations
This study has several strengths worthy of elaboration. First, it integrates knowledge from the literature of organizational politics with the literature of workplace deviance. Such integration provides new insights and advances our understanding about organizational politics and its consequences. Second, the data collection used a three-wave study design, which increased the reliability of the collected data. Third, the research model was tested on a large number of participants who comprised a very heterogeneous group. Finally, the participants came from a variety of organizations, sectors and hierarchical levels in the organizations, enhancing our ability to generalize our findings.
Despite its strengths, this research has a major limitation in that the data in the current study were collected from a single source (i.e. self-report questionnaires). Self-report data raise concerns about common method variance and social desirability bias. Although several scholars have argued that common method variance does not invalidate most research findings (see Crampton and Wagner, 1994; Doty and Glick, 1998; Spector, 2006), relying solely on self-report data may raise concerns about this issue. In order to reduce the likelihood of common method variance and social desirability bias we utilized six procedures and statistical remedies suggested by Podsakoff et al. (2003). First, we created a 12-week interval between the data collection of the independent and the dependent variables in an attempt to reduce the perceptions of the participants about any potential connection between them. Second, we assured the complete anonymity of the participants by instructing them to avoid providing any identification information, and by using code numbers to match the collected questionnaires of the participants. Third, we tested an exploratory one-factor model in which all of the four research variables were loaded onto a single factor. This model explained 28.3 percent of the variance, which is below the cut-off suggested in the literature. Fourth, we conducted partial correlation analyses and found that the correlations between the research variables were low-to-moderate, except for the two CWB dimensions. Fifth, we created a series of two-factor models to assess the discriminant validity between each pair of constructs (Bagozzi et al., 1991) and determined that the constructs indicated discriminant validity. Sixth, we tested the model with and without a CMV factor and discovered little difference. Although all of the statistical tests showed that the possibility of CMV did not impede the research measurements, we suggest that future studies try to replicate our model using multiple methods of data collection.
Directions for future research
The current study empirically explored a research model in which hostility mediated the POP-CWB relationship. We believe that the organizational politics literature would benefit from expanding our model to include additional discrete emotions and additional work outcomes. More specifically, given that different discrete emotions have different behavioral implications (Frijda, 1986; Roseman, 1984; Roseman et al., 1994), exploring additional discrete emotions such as frustration, resentment, and sadness as mediators of the POP-CWB relationship can advance our knowledge about the contribution of emotion to explaining the engagement of organizational members in deviant behavior in response to POP. Additionally, exploring various discrete emotions as mediators in the associations between POP and other work outcomes such as job satisfaction, turnover intentions, task performance, and organizational citizenship behavior can also enrich our cumulative knowledge about this issue. We believe that the literature on organizational politics would also benefit from an empirical exploration of the interplay between political behavior, discrete emotions, and employees’ work attitudes and behaviors. Finally, previous research has acknowledged the contribution of EI to explaining the negative implications of POP (Meisler and Vigoda-Gadot, 2014; Poon, 2003; Vigoda-Gadot and Meisler, 2010). Similarly, we have acknowledged the potential contribution of EI and suggested that EI training would be effective in reducing the hostility evoked in response to POP, and subsequently, the engagement of organizational members in CWB. Testing this suggestion empirically would be an important avenue for future research.
Summary
The current study incorporates knowledge from the literatures of organizational politics and workplace deviance to determine the role played by hostility in the POP-CWB relationship. Our findings raise some intriguing ideas for future research and have practical implications as well. Hence, we encourage other researchers to explore the role of emotion in organizational politics further, in an attempt to expand our knowledge about this fascinating topic.
Figures
Descriptive statistics, intercorrelations and reliabilities (in parentheses)
| Variable | Mean | SD | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|---|---|
| 1. Age | 34.7 | 7.87 | (−) | |||||
| 2. Tenure | 10.2 | 7.62 | 0.73*** | (−) | ||||
| 3. POP | 2.69 | 1.02 | −0.26** | −0.16* | (0.92) | |||
| 4. Hostility | 1.84 | 0.87 | −0.13 | −0.07 | 0.27*** | (0.91) | ||
| 5. O-CWB | 1.76 | 0.73 | −0.13 | −0.15* | 0.21** | 0.31*** | (0.85) | |
| 6. I-CWB | 1.69 | 0.84 | −0.21** | −0.13 | 0.22** | 0.26*** | 0.64*** | (0.88) |
Notes: n = 171. POP, Perceptions of organizational politics; O-CWB, organizational counterproductive work behavior; I-CWB, interpersonal counterproductive work behavior. *p ⩽ 0.05; **p ⩽ 0.01; ***p ⩽ 0.001
Hostility as a mediator in the relationship between POP and O-CWB
| Model | Models summary | Path | β | LLCI | ULCI |
|---|---|---|---|---|---|
| 1 | R2 = 0.07, F (3,167) = 4.14, p ⩽ 0.01 | POP → O-CWB | 0.17* | 0.02 | 0.32 |
| Age | −0.12 | −0.27 | 0.04 | ||
| Gender | −0.15 | −0.30 | 0.01 | ||
| 2 | R2 = 0.08, F (3,167) = 4.99, P ⩽ 0.01 | POP → Hostility | 0.24** | 0.09 | 0.39 |
| Age | −0.09 | −0.25 | 0.06 | ||
| Gender | −0.07 | −0.22 | 0.08 | ||
| 3 | R2 = 0.13, F (4,166) = 6.26, p ⩽ 0.001 | POP → O-CWB | 0.11 | −0.05 | 0.26 |
| Hostility | 0.26*** | 0.11 | 0.41 | ||
| Age | −0.09 | −0.24 | 0.06 | ||
| Gender | −0.13 | −0.27 | 0.02 |
Notes: POP, Perceptions of organizational politics; O-CWB, organizational counterproductive work behavior. *p ⩽ 0.05; **p ⩽ 0.01; ***p ⩽ 0.001
Hostility as a mediator in the Relationship between POP and I-CWB
| Model | Models summary | Path | β | LLCI | ULCI |
|---|---|---|---|---|---|
| 1 | R2 = 0.14, F (3,167) = 9.24, p ⩽ 0.001 | POP → I-CWB | 0.15* | 0.01 | 0.30 |
| Age | −0.23** | −0.38 | −0.08 | ||
| Gender | −0.26*** | −0.41 | −0.12 | ||
| 2 | R2 = 0.08, F (3,167) = 4.99, p ⩽ 0.01 | POP → Hostility | 0.24** | 0.09 | 0.39 |
| Age | −0.09 | −0.25 | 0.06 | ||
| Gender | −0.07 | −0.22 | 0.08 | ||
| 3 | R2 = 0.17, F (4,166) = 8.71, p ⩽ 0.001 | POP → I-CWB | 0.11 | −0.04 | 0.25 |
| Hostility | 0.19** | 0.04 | 0.33 | ||
| Age | −0.22** | −0.36 | −0.07 | ||
| Gender | −0.25*** | −0.39 | −0.11 |
Notes: POP, Perceptions of organizational politics; I-CWB, interpersonal counterproductive work behavior. *p ⩽ 0.05; **p ⩽ 0.01; ***p ⩽ 0.001
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Further reading
Hodzic, S., Scharfen, J., Ripoll, P., Holling, H. and Zenasni, F. (2017), “How efficient are emotional intelligence trainings: a meta-analysis”, Emotion Review, doi: 10.1177/1754073917708613.
Ortony, A. and Turner, T.J. (1990), “What’s basic about basic emotions?”, Psychological Review, Vol. 97 No. 3, pp. 315-331.