Employee Perception of Leadership Tolerance of Deviance and the Moral Disengagement from Organizational Citizenship Behavior ()
1. Introduction
Organizational leaders set the example for ethics and standards of behavior. Employees view leaders as role models to govern “what is acceptable” ethical behavior (Brown & Trevino, 2006). The social information processing theory is the core theoretical lens for analyzing ethical leadership’s influence on organizational citizenship behavior (Salancik & Pfeffer, 1978; Yang et al., 2019). Organizational citizenship behavior (OCB) is the willingness of employees to go beyond their regular duties and responsibilities (Mo & Shi, 2017). Additionally, employees with OCB strive for organizational success without using formal reward systems (Teng et al., 2020). However, ethical leaders who tolerate deviant workplace behaviors may negatively moderate the relationship with OCB (Weaver et al., 2014; Kong & Yuan, 2018).
The social information processing theory proposes that employees judge leaders to discern what is appropriate or inappropriate workplace behavior. However, the social identity (SI) approach provides two possible enlightenments to understand ethical leadership on OCB better. First, the SI approach reveals that leadership adherence to social norms can camouflage fairness (Gao & He, 2017). Second, social norms create “us” versus “them” power dynamics which adversely modifies ethical behavior (Pryor et al., 2019). Consequently, ethical leaders who repeatedly tolerate deviant behaviors that oppose organizational standards may lead to collective moral disengagement of the standard. Ignoring organizational standards is problematic, and a gap exists in the literature on how moral disengagement is created at the organizational level (Egels-Zandén, 2017; Newman et al., 2020).
Moral disengagement is a person’s process of justifying ignoring standards or laws. For example, people use moral disengagement to justify ignoring a traffic safety law (Holman & Popusoi, 2018). Comparatively, the repeated exposure to a socially deviant behavior that influences decision-making is known as perceived deviance tolerance (Pitesa & Thua, 2013). Perceived deviance tolerance can add to the logic of moral disengagement by suggesting that traffic drivers repeatedly exposed to law enforcement acceptance of that deviant behavior may lead to collective moral disengaging from that law.
Brown and Trevino (2006) propose that employees look to the leader as the role model and standard for ethical behavior. Similarly, employees who repeatedly witness leaders who accept deviant behaviors in the workplace may unknowingly degrade the link between ethical leadership and OCB. For example, people use the moral disengagement process to justify imposing acts of violence on others (Maftei et al., 2021). However, the victims will look to leaders to fairly enforce the law regardless of the offender’s justification. However, members of society who repeatedly witness leadership accept deviant behavior (perceived deviance tolerance) will likely morally disengage by ignoring it.
The examples presented in this introduction are consistent with Kong and Yuan’s (2018) research that perceived deviance tolerance can influence ethical interactions. Moral disengagement is a cognitive process used to rationalize ignoring an ethical standard (Caprara et al., 2014) and perceived deviance tolerance is a better explanation for moral disengagement at the organizational level. However, further investigations are necessary to provide a process to account for employees’ perception of leadership’s tolerance of deviant social behavior in the workplace (Tarrant et al., 2012; Xie et al., 2020).
The foundational leadership theory (FLT) is an ethical leadership perspective that advances the SI approach. Additionally, research on FLT suggests that integrity, assurance, and pragmatism reduce deviant and destructive behaviors associated with the displaced aggression theory (Fuller, 2021a). It is plausible that FLT may have one or more attributes that are resistant to perceived deviance tolerance ability to moderate the relationship between ethical leadership and OCB.
FLT is a relatively new ethical leadership approach that suggests leadership should conduct an inward (self-reflection) and outward examination (employee perception) of behaviors using integrity, assurance, and pragmatism to discern social norm influences on decision-making. FLT integrity, assurance, and pragmatism are known as the Leadership Ethics and Decision-making (LEAD) model, which reduces deviant employee behaviors and diminishes employee perception of distributive injustice in the workplace (Fuller, 2022b). Additionally, FLT-pragmatism is the external examination for leadership decision-making which accounts for employee perception. Therefore, if FLT-integrity, assurance, and pragmatism have a positive relationship with OCB, then perceived deviance tolerance will not moderate the predictive power of LEAD-pragmatism on OCB. The results of this investigation should answer the following research questions.
RQ1: Do employees perceive foundational leadership integrity, assurance, and pragmatism as ethical leadership attributes?
RQ2: Do foundational leadership integrity, assurance, and pragmatism positively predict organizational citizenship behavior?
RQ3: Does perceived deviance tolerance moderate the positive relationship between foundational leadership integrity, assurance, or pragmatism on organizational citizenship behavior?
The remaining sections of this article will provide the literary background on OCB, ethical leadership, and perceived deviance tolerance (PDT). The following section will provide the methodology and data collection to determine the overall reliability of foundational leadership integrity, assurance, pragmatism, PDT, and OCB. Then, a Pearson’s correlation and linear regression will determine if a significant positive relationship exists between FLT integrity, assurance, and pragmatism on OCB. Finally, PDT will be observed to determine if foundational leadership integrity, assurance, or pragmatism is resistant to moderating effect of PDT on OCB. Leaders, managers, and HR departments will benefit by understanding ethical attributes that reduce PDT in the organization.
2. Literature Review
2.1. Organizational Citizenship Behavior and Ethical Leadership
Leadership ethics is essential to the development of employee OCB. OCB is a self-initiated behavior that compels an employee to go beyond their official duties without using formal reward systems (Becton et al., 2008; Newman et al., 2014; Sferrazzo, 2021). For example, employees who measure high in OCB are likely to volunteer for additional tasks, orient new hires, assist coworkers in completing projects, and willingly request additional work responsibilities. OCB principles include self-sacrifice, courtesy, conscientiousness, and sportsmanship. An ethical work climate is salient to promoting OCB (Teng et al., 2020). However, employees may morally disengage from the ethical standards that ethical leaders neglect to enforce.
The social information processing theory (Salancik & Pfeffer, 1978) suggests that employee performance reflects leadership interactions toward organizational practices. The social information processing theory is consistent with PDT and emerges as the psychological influence on ethical decisions, judgments, and behaviors (Desai & Kouchaki, 2017). The literature supports Brown et al. (2005) approach that leadership interactions with employees will influence moral behaviors through inter-communication, reinforcement, and decision-making. Therefore, ethical leaders who allow deviant behaviors to alter decision-making will neglect organizational standards, leading to collective moral disengagement.
Kong and Yuan (2018) add that PDT impacts the leader-employee interaction, affecting OCB. The conclusion suggests that deviant behaviors that ignore organizational standards can quickly degrade OCB. However, Desai and Kouchaki (2017) reveal that standard-bearers who are tolerant of deviant behaviors will alter the ethical judgments of others. These actions are consistent with PDT, and more likely a prerequisite to collective morally disengage.
PDT measures employee perception of their leader’s tolerance of deviance in the workplace. Comparatively, moral disengagement measures the employees’ actions that act in opposition to organizational standards. Numerous research identifies moral disengagement as a standalone theory. However, the social cognitive theory is highly relatable to moral disengagement (Bandura, 1986, 1999; Newman et al., 2014). The social cognitive theory explains that perception is essential for people to navigate their environment and individual behavior. Studying foundational leadership integrity, assurance, and pragmatism will account for employee perception of leadership and the overall influence on employee OCB (Newman et al., 2020).
Bandura (2002) explains that moral disengagement is a linear process that relies on four loci behavior mechanisms. The first locus of moral disengagement addresses employee behavior. Employees in this category rely on social and moral comparisons to discern leadership ethics. Employees may label strong ethical leaders as intolerant for opposing a social or moral purpose. The first loci may explain why leaders may ignore or justify deviant behaviors. However, the inward and outward examination of leadership decisions using foundational leadership integrity, assurance, and pragmatism accounts for social comparisons. As a result, foundational leadership integrity, assurance, and pragmatism have a positive relationship with organizational commitment (Fuller, 2021b), decrease employee deviant behaviors (Fuller, 2021a), and pragmatism should resist PDT moderation on OCB.
The second locus of moral disengagement relates to the agency. Bandura (1999) suggests that individuals use displacement to make sense of their choices and actions at this stage. Employees in the agency category displace responsibility for opposing leaders with opposing solid convictions. Newman et al. (2020) confirmed Bandura’s (1999) statement that displacement of responsibility requires an external force or a decision-maker higher in an organization’s hierarchy. This locus may explain why employees are likelier to label leaders as “intolerant” than their coworkers. However, foundational leadership-integrity and assurance is an inward (self-reflection), and pragmatism is an outward examination (employee perception) that should moderate the employee displacement of responsibility toward organizational leadership hierarchies.
The third locus of moral disengagement accounts for behavioral outcomes on others. These outcomes are the mechanism responsible for disregard or distortion of consequences. For example, a leader may suggest an organizational initiative to volunteer in the local community. However, employees who label leaders as intolerant will minimize their contribution to that community. This locus mechanism is similar to the leader-member exchange (LMX) and uncertainty management theory (UMT). Ethical leadership improves LMX relationships (Gallie et al., 2017), and UMT confirms that opposing beliefs degrade positive behaviors and attitudes (Yang & Wei, 2017). However, foundational leadership integrity, assurance, and pragmatism reduce counterproductive behaviors (Fuller, 2021a) but improve LMX relationships (Fuller, 2021b).
The fourth locus encompasses dehumanization and designation of blame. This final mechanism refers to how a person will seek to blame others, usually the victim, to exonerate themselves from responsibility. The displaced aggression theory (DAT) supports the designation of blame, suggesting that employees use destructive behaviors when they are not treated well by organizational leaders (Ng et al., 2021). An organizational identity (OI) is responsible for the link between the employee and their position in the organization (Ashforth, 2020). However, leaders are organizational representatives who influence OI and are dynamic in resolving opposing tension (Veldsman & Veldsman, 2020). Nonetheless, it is unclear how foundational leadership integrity, assurance, and pragmatism can aid leadership in exonerating themselves from PDT and improving OCB among employees.
People with repeat exposure to social influence incorporate those behaviors into their ethical decision-making (Pitesa & Thau, 2013). The impact of social influence on ethical decision-making can infiltrate organizational policies. The SI approach reveals that differences between in-group and out-group (us vs. them) can introduce distributive injustices (Fuller, 2022b), which may contribute to moral disengagement. Table 1 provides definitions for the moral disengagement loci and PDT.
2.2. Foundational Leadership-Integrity
The Ethic Position Theory (EPT) suggests that a leader’s moral actions express their ethical position (Forsyth, 1992). The Foundational Leadership Theory (FLT) builds on this premise and concludes that leaders require an inward (self-reflection) and outward examination (employee perception) before expressing their ethical position. Additionally, EPT relies on idealism and relativism to explain the behavior of leaders in ethical scenarios. Leaders who measure high in idealism avoid decisions that may hurt employees. Relativism suggests that leaders evaluate situations by the outcome rather than moral principles. FLT accounts for idealism and relativism by applying an inward and outward examination of decisions using foundational leadership integrity, assurance, and pragmatism. However, there is still much to learn about ethical leadership, collective moral disengagement, and OCB (Desai & Kouchaki, 2017; Kong & Yuan, 2018).
Foundational leadership-integrity (FLI) is the first stage of a cognitive progression technique to improve our understanding of employee perception of ethical leadership. Maslow’s (1954) theory on cognitive progression examines employee perceptions of leadership integrity and identity. Previous research confirms that employees view leadership integrity as fairness, honesty, and trustworthiness (Nangoli et al., 2020). FLI confirms the cognitive progression by the significant positive relationship between employee connection and identity to their organization (Fuller, 2022a).
Integrity is foundational to ethical leadership. The lack of decrement for ethical leadership can result in deviant behaviors that lead to adverse organizational outcomes. As a result, integrity remains the foundation for moral intelligence and shapes employee organizational behaviors and attitudes (Kalshoven et al., 2016). Due to these reasons, integrity is the hallmark of ethical leadership and the first stage of the LEAD model.
Research supports the use of FLI as the first step in ethical leadership. First, integrity is the essence of ethical values (Palanski & Yammarino, 2009) and is vital to leadership-member exchange relationships (LMX; Fuller, 2021b). Additionally, integrity influences employee behaviors and attitudes (Krishnakumar et al., 2015; Tu et al., 2017) and remains significant to procedural aspects of ethics (Brown & Trevino, 2006). Ming et al. (2020) confirm that integrity is a procedural process and links ethical leadership and employee perception.
Integrity is critical to the LEAD model. The inward and outward examination using FLI is a method to discern moral principles. FLI is consistent with Palanski and Yammarino’s (2009) suggestion that ethical leaders must adhere to moral standards. However, there is a lack of research on ethical leadership and collective moral disengagement. The gap in literature may exist due to the underdevelopment and disagreement on the meaning of integrity (Fu et al., 2019). This investigation will help improve the definition of integrity by measuring employee perception of integrity as fair, unbiased, impartial, and not solely for personal gain. FLI will likely not account for perceptions of a leader’s tolerance of deviant behaviors, which is pivotal in resisting collective moral disengagement. Therefore, this research proposes the following hypotheses.
H1a: Foundational leadership-integrity (FLI) will have no relationship with organizational citizenship behavior (OCB).
H1b: Foundational leadership-integrity (FLI) will positively affect organizational citizenship behavior (OCB).
H1c: Perceived deviance tolerance (PDT) will have no moderating effect on the positive relationship between foundational leadership-integrity (FLI) and organizational citizenship behavior (OCB).
H1d: Perceived deviance tolerance (PDT) will moderate the positive relationship between foundational leadership-integrity (FLI) and organizational citizenship behavior (OCB).
2.3. Foundational Leadership-Assurance
Ethical leaders should reassure employees to reduce uncertainty in the workplace. Foundational leadership-assurance (FLA) advances the uncertainty management theory (UTM). UTM analyzes how employees respond to doubts about their leadership in the workplace. However, research confirms that ethical leadership attributes that reassure fairness will more likely reduce uncertainty (Van den Bos & Lind, 2002). Although fairness links to integrity, employees rely on leadership communication to process levels of fairness in the workplace (Yang et al., 2019). FLA focuses on reducing uncertainty in the workplace and contributing to the positive perception of ethical leadership.
Ethical decision-making that reassures employees lead to efficiency and sustainability (Brown et al., 2005). Because employees with OCB attributes go above and beyond their regular duties, foundational leadership assurance is likely to have a positive relationship with OCB. Additionally, FLA reduces stress, anxiety, and uncertainty, influencing organizational commitment (Fuller, 2021a). Ethical leaders can integrate FLA with FLI to reduce workplace uncertainty. However, FLI coupled with FLA may not reduce employee perceptions of leadership’s tolerance of deviance without leadership conducting an outward examination. Therefore, this study proposes the following hypotheses.
H2a: Foundational leadership assurance (FLA) will have no relationship with organizational citizenship behavior (OCB).
H2b: Foundational leadership assurance (FLA) will positively affect organizational citizenship behavior (OCB).
H2c: Perceived deviance tolerance (PDT) will have no moderating effect on the positive relationship between the foundational leadership assurance (FLA) and organizational citizenship behavior (OCB).
H2d: Perceived deviance tolerance (PDT) will moderate the positive relationship between foundational leadership assurance (FLA) and organizational citizenship behavior (OCB).
2.4. Foundational Leadership-Pragmatism
FLP advances the social exchange theory by Homans (1974) and confirms that pragmatism is an essential ethical leadership attribute (Fuller, 2021b). First, employees who perceive leadership decisions as pragmatic have a stronger desire to contribute to the organization (Anderson & Sun, 2017; Watts et al., 2019). Next, FLP is a suitable approach to managing normative legitimacy (Fuller, 2022a). Normative legitimacy is known as “doing things right” and is deemed more difficult to manage in diverse organizations. Rabl et al. (2020) confirm that normative behavior management is an ethical virtue (Lozano & Escrich, 2017). Therefore, it is likely that pragmatism is resistant to PDT on OCB.
Pragmatism complements discernment for “what is acceptable”. Pragmatic leaders understand there is no one-size-fits-all approach to organizational decision-making. FLP concludes that sensible decisions should align with organizational goals. As a result, employees perceive pragmatic leaders as sense-makers whose decisions help them meet or exceed organizational objectives (Jensen & Sanstrom, 2013). Sense-making is fundamental to ethical leadership (Mumford et al., 2017), improves organizational performance (Marcy & Mumford, 2010), and is vital to leadership ethics (Winter, 2013).
Pragmatism prepares leaders for external factors outside their control (Mumford et al., 2017) and a reflective quality on employees (Jordan et al., 2017). Additionally, pragmatism is the repetitiveness in organizational leadership decision-making (Winter, 2013), seen as reflective on employees (Jordan et al., 2017), and reduces displaced aggression of deviant behaviors due to leadership mistreatment (Fuller, 2022b). FLP account for external factors such as social norms that alter ethical leadership decision-making. Pragmatic leaders are more likely to uphold ethics, enforce standards, and should resist the moderation of PDT on OCB. Therefore, this research proposes the following hypotheses.
H3a: Foundational leadership-pragmatism (FLP) will have no relationship with organizational citizenship behavior (OCB).
H3b: Foundational leadership-pragmatism (FLP) will positively impact organizational citizenship behavior (OCB).
H3c: Perceived deviance tolerance (PDT) will moderate the positive relationship between the Foundational Leadership-Pragmatism (FLP) and organizational citizenship behavior (OCB).
H3d: Perceived deviance tolerance (PDT) will have no moderating effect on the positive relationship between the foundational leadership-pragmatism (FLP) and organizational citizenship behavior (OCB).
Figure 1 is a display of a conceptual model for PDT’s moderation of FLI, FLA, FLP relationship to OCB.
Table 2 below contains the definitions for the LEAD model constructs FLI, FLA, and FLP.
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Figure 1. Perceived Decvaince tolerance, LEAD, and organizational citizenship behavior model.
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Table 2. Leadership ethics and decision-making and organizational citizenship behavior.
Employees reflect their organizational leaders’ ethical behaviors and attitudes (Jordan et al., 2017). However, leaders who ignore deviant actions in the workplace can disrupt ethical behaviors (Kong & Yuan, 2018). Therefore, it is beneficial for leaders, managers, and HR professionals to better understand how FLI, FLA, and FLP ethical attributes may seem resistant to PDT’s negative effect on OCB (Tarrant et al., 2012; Xie et al., 2020). The LEAD model has been shown to measure ethical leadership and positively influence employee commitment and work engagement but reduce deviant behaviors such as knowledge-hiding. Therefore, FLI, FLA, and FLP may provide a reliable and valid ethical leadership approach to reduce deviant behaviors associated with PDT.
3. Methodology
First, the methodology consists of conducting a Cronbach’s alpha coefficient to determine the reliability of the FLI, FLA, FLP, OCB, and PDT measurement scales. Second, a transform variable function computes all measurements into the proper variable. Third, Pearson’s correlation will determine if a significant positive relationship exists between FLI, FLA, FLP, and OCB. Fourth, a simple linear regression will give further insight into the potential predictability of FLI, FLA, and FLP on OCB. Fifth, if a significant regression exists between FLI, FLA, FLP, and OCB, there will be a moderation test using PDT. Sixth, identify LEAD model constructs resistant to PDT to provide leaders with more insight into managing human resources (HR). Last, an ANOVA analysis of gender, age, and income will evaluate participant responses to OCB to determine if any differences exist in OCB perception.
The moderating effect of PDT on FLI, FLA, or FLP on OCB relies on collecting participant responses to a survey. The LEAD models consist of FLI (5 items), FLA (5 items), and FLP (5 items) to measure employee perceptions of ethical leadership behavior. For example, I trust leadership decisions that encourage job security. Each measurement consists of a seven-point Likert-typed scale (1 = strongly disagree, 7 = strongly agree) with a previous Cronbach’s alpha of .95 (Fuller, 2022b). Previous research has shown that LEAD has a significant relationship with organizational commitment (Fuller, 2021c) and reduces knowledge hiding between employees (Fuller, 2021a). Because pragmatism reduces destructive behaviors, PDT should not moderate the FLP relationship with OCB.
PDT consists of a 3-item measurement scale by Kong and Yuan (2018) with a Cronbach’s alpha score of .80. Although this scale is acceptable, the term “tolerate” is consistent throughout the measurement scales. This research included two additional measurement scales to better account for employee perceptions of tolerance. For example, my leader accepts employee behaviors that may damage company morale, and my leaders allow employees to conduct behaviors that lower job performance. Participants will answer each PDT question using a 7-point Likert scale (1 = strongly disagree to 7 = strongly agree). The 3-item scale by Kong and Yang (2018) will be compared to the 5-item scale to determine the most reliable measurement of PDT. The scale was sent to a sample group of 42 full-time employees to test the validity of the 5-item scale. The Cronbach’s alpha test was acceptable at .83 and this 5-item scale will be added to the overall survey.
OCB relies on a 3-item scale by Linden et al. (2005). The most recent Cronbach’s alpha score was .80 suggesting a good measurement (Babalola et al., 2019). However, this research introduces two additional questions to measure assisting coworkers and taking responsibility for tasks outside their regular duties. For example, I help coworkers with tasks even though my leadership may not recognize me; even though I was not asked to do so, I accept mutual responsibility for the tasks I helped other coworkers complete. These questions should strengthen the previous reliability of .80 and improve our investigation of LEAD on OCB. Participants will answer each OCB question using a 7-point Likert scale (1 = strongly disagree to 7 = strongly agree). This research will compare Linden et al.’s. (2005) 3-item scale with this 5-item to determine the most reliable measurement for OCB. The scale was sent to a sample group of 42 full-time employees to test the validity of the 5-item scale. The Cronbach’s alpha test was acceptable at .84 and this 5-item scale will be added to the overall survey.
The research will use age, income, and gender to determine the differences in responses to OCB questions. Chizema and Pogrebna (2019) suggest that an employee’s age has no significant effect on organizational relationships. Comparatively, Peng and Wei’s (2018) study confirm that gender may influence perceptions of ethical leadership. Therefore, employee age, gender, and income will determine if there are statistically significant differences in their view on OCB to confirm positive relationships between LEAD and the potential moderating effect of PDT.
The sample population will consist of full-time employees from across the United States of America (USA). However, part-time and seasonal employees may produce inconsistencies within responses to the variables. Therefore, only full-time employees will contribute to this study. As of July 2022, the US Bureau of Labor and Statistics calculates 158.43 million full-time employees. Cochran (1977) used a sample size formula, using a 95% confidence interval (CI) and a 4% - 6% margin of error. The acceptable sample population size was >300 participants. The aim was to collect data from a minimum of 350 participants to validate the LEAD, PDT, and OCB measurement scales, observe potential correlations, conduct a regression analysis, and determine any moderating or mediating effects between the IV and DV.
The US Department of Labor Footnote 2 suggests that their data does not fully represent all ethnicities. This information said “race” was a biased control variable. The ANOVA results represent differences in responses on OCB using age, gender, and income. Participants will answer survey questions via SurveyMonkey™. Personally identifiable information (PII) is not a requirement for this study. Each respondent must be >18 years of age to participate. Microsoft Excel and IBM Statistical Program for Social Sciences (SPSS) are the analytic software technologies for this study. A total of 402 employees accepted and agreed to participate in the study.
4. Results
The researcher contracted 430 full-time employees for this survey, and 402 were selected to participate in this study. First, the data was analyzed to locate missing. As a result, 378 of 402 responses were used in this analysis, exceeding the minimum of 350 participants per Cochran’s (1977) sample size formula. The summary statistics calculated for the LEAD model, OCB, and PDT is in Table 3.
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Table 3. Summary statistics table for interval and ratio variables.
Second, the frequencies and percentages for gender, income, and age were completed and presented in Table 4.
Third, outliers were examined for each variable’s measurement scale. The standard for outliers is values that fall outside the range of +/− 3.29 standard deviations from the mean (Tabachnick & Fidell, 2019). Based on this standard, FLI, FLA, FLP, OCB, and PDT did not contain outliers. Fourth, a Cronbach’s alpha coefficient was calculated for the FLI, FLA, FLP, OCB, and PDT scales. The Cronbach’s alpha coefficient was evaluated using the guidelines suggested by George and Mallery (2018) where >.9 excellent, >.8 good, >.7 acceptable, >.6 questionable, >.5 poor, and ≤.5 unacceptable. Items that have >.7 are considered a reliable measurement scale for that particular variable. This analysis aims to determine if FLI, FLA, FLP, OCB, and PDT are still reliable scales. Scale reliability is essential in ensuring the validity of the regression and moderation analysis.
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Table 4. Frequency table for nominal variables.
*Note. Due to rounding, percentages may not equal 100%.
FLI Cronbach’s alpha coefficient is .90 indicating excellent reliability. FLA Cronbach’s alpha coefficient is .86, indicating good reliability. FLP Cronbach’s alpha coefficient is .84, indicating good reliability. The results validate the measurement scale by Fuller (2022a). Additionally, OCB Cronbach’s alpha coefficient is .85, indicating good reliability, which is more reliable than the previously validated 3-item by Babalola et al. (2019). Finally, PDT Cronbach’s alpha coefficient is .88, indicating good reliability, which is higher than the 3-item scale by Kong and Yuan (2018). Table 5 presents the results of the reliability analysis for each variable.
The fifth step was to conduct a Pearson correlation analysis. The Pearson correlation analysis will determine if a relationship exists between FLI and OCB, FLA and OCB, and FLP and OCB. A relationship between each IV on the DV is necessary to determine if the LEAD model influences OCB. However, if the LEAD model does not relate to OCB, the research must accept the null hypothesis. Cohen’s standard was used to evaluate the strength of the relationship, where coefficients between .10 and .29 represent a small effect size, coefficients between .30 and .49 represent a moderate effect size, and coefficients above .50 indicate a large effect size (Cohen, 1988). The correlation result was examined based on an alpha value of .05. A significant positive correlation was observed between FLI and OCB with a correlation of .46, indicating a moderate effect size (p < .001, 95.00% CI = [.37, .53]). This suggests that as FLI increases, OCB tends to increase. There is a significant positive correlation between FLA and OCB, with a correlation of .53, indicating a large effect size (p < .001, 95.00% CI = [.45, .60]). This suggests that as FLA increases, OCB tends to increase. Finally, A significant positive correlation was observed between FLP and OCB, with a correlation of .62, indicating a large effect size (p < .001, 95.00% CI = [.56, .68]). This suggests that as FLP increases, OCB tends to increase. Therefore, the LEAD model attributes of FLI, FLA, and FLP have a significant positive relationship with OCB. This suggests that a linear regression model can be implemented to observe LEAD model attributes that may resist the negative moderation of PDT on OCB. Table 6 contains the Pearson correlation output.
The fifth step consists of three phrases to assess moderation on OCB. The first phase required a simple effects model using linear regression of each LEAD
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Table 5. Reliability table for independent, depending, and moderator variables.
Note. The lower and upper bounds of Cronbach’s α were calculated using a 95.00% confidence interval.
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Table 6. Pearson correlation results between FLI, FLA-, FLP, and OCB.
construct as the predictor variable of OCB. The second phase created a non-interaction model by adding PDT to each linear model and an interaction model between PDT in each linear model. The third phase followed the assumptions for linear regression analysis. Mean centering was used for PDT. The moderation analysis aimed to assess if PDT moderates the relationship between FLI, FLA, and FLP on OCB.
The assumption of normality was assessed by plotting the quantiles of the model residuals against the quantiles of a Chi-square distribution, also called a Q-Q scatterplot (DeCarlo, 1997). The normality assumption was met because the quantiles of the residuals did not strongly deviate from the theoretical quantiles. Homoscedasticity was evaluated by plotting the residuals against the predicted values (Bates et al., 2014; Field, 2017). The points appear randomly distributed with zero mean and no apparent curvature.
Variance Inflation Factors (VIFs) were calculated to detect the presence of multicollinearity between predictors. High VIFs indicate increased effects of multicollinearity in the model. VIFs greater than 5 are cause for concern, whereas VIFs of 10 should be considered the maximum upper limit (Menard, 2010). All predictors in the regression model have VIFs less than 10. Therefore, it is appropriate to assess the conditions for moderation.
For moderation to be supported, two conditions must be met (Netemeyer et al., 2001). First, FLI, FLA, and FLP must significantly predict OCB in the simple effects model (step 1). FLI, FLA, and FLP have a significant positive relationship with OCB. However, FLI, FLA, and FLP must predict OCB to proceed to moderation and discover attributes of the LEAD model that are likely to resist PDT on OCB.
The regression model on FLI and OCB was conducted to test H1c and h1d. FLI significantly predicts OCB, B = .47, t(374) = 9.97, p < .001 which meets the first condition. The partial F-test, F(1,372) = 11.12, p < .001, on FLI, PDT, and OCB indicated that the interaction model explained significantly more variance than the non-interaction model based on an alpha of .05. Therefore, the second condition was met. FLI significantly predicts OCB, but the interaction model explains significantly more variance of OCB than the non-interaction model (condition 2). However, PDT significantly moderated the effect FLI had on OCB with an alpha of .05, B = −.02, t(372) = −3.33, p < .001 and on average, a one-unit increase of PDT causes a .02 decrease in the slope of FLI on OCB. FLI is not resistant to PDT negative moderation on PCB. Ethical leaders with integrity are less likely to reduce the deviant behaviors associated with PDT.
Next, regression and moderation on FLA and OCB were observed to test H2C and H2d. FLA significantly predicts OCB, B = .49, t(374) = 12.07, p < .001 and meets the first condition for moderation as well. The partial F-test, F(1,372) = 9.18, p = .003, indicated that the interaction model explains significantly more variance than the non-interaction model using the alpha of .05. The second condition was met and supports that PDT significantly moderates the effect FLA has on OCB based on an alpha of .05, B = −.02, t(372) = −3.03, p = .003. On average, a one-unit increase of PDT will cause a .02 decrease in the slope of OCB on FLA. FLA alone is not resistant to the deviant behaviors associated with PDT.
The final attribute of the LEAD model is FLP. FLP is the outward examination of ethical behavior that help employees excel in job tasks. The regression model indicates that FLI significantly predicted OCB, B = .70, t(374) = 15.37, p < .001. Therefore, the first condition was met, and the partial F-test, F(1,372) = 3.86, p = .050, indicates that the interaction model did not explain significantly more variance than the non-interaction model based on an alpha of .05. Therefore, the second condition was not met, and PDT did not moderate the predictability of FLP on OCB. Therefore, ethical leaders who exhibit the attributes associated with FLP will make decisions more likely resistant to the deviant behaviors associated with PDT. Figure 2 represents the results of the hypotheses for this study.
Finally, an analysis of variance (ANOVA) was conducted to determine whether there were significant differences in OCB based on age, gender, and income. The results of the ANOVA on Age were not significant, F(3, 371) = 1.55, p = .202; Gender was not significant, F(1, 373) = 1.09, p = .297; income was not significant, F(10, 364) = 1.52, p = .131, indicating there were no significant differences between Age, Gender, and Income levels on OCB. There were no significant effects in these models. As a result, posthoc comparisons were not conducted.
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Figure 2. Perceived decvaince tolerance, LEAD, and organizational citizenship behavior model.
The regression analysis results revealed that FLI, FLA, and FLP predict OCB. However, only FLP is resistant to the moderating effect of PDT on OCB. Because FLP FLP is an outward examination of ethical decisions that help employees meet or exceed job tasks, it was hypothesized that FLP would resist the negative moderation of PDT on OCB. Therefore, ethical leaders who apply the LEAD model will include an inward and outward examination based on integrity, assurance, and pragmatism, reducing employee perception of leadership’s tolerance to deviance and improving OCB in the workplace.
5. Implications
This research aims to determine ethical leadership attributes that account for the exposure of employees to deviant behaviors and the negative impact on OCB (Kong & Yuan, 2018). Previous research suggests that employees may perceive leadership with solid ethical convictions as threatening (Stouten et al., 2013) and intolerant (Weaver et al., 2014). Therefore, it was beneficial to conduct this investigation and fill the gap in the literature on types of ethical leadership practices that can reduce moral disengagement at the organizational level (Egels-Zandén, 2017; Newman et al., 2020).
5.1. Theoretical Implications
The first theoretical implication builds on the social exchange theory (SET). SET links leadership with employee behaviors and attitudes (Breevaart & Bakker, 2017; Breevaart & Zacher, 2019). FLI, FLA, and FLP apply the SI approach and advance our understanding of SET with OCB. The positive correlation between each LEAD construct on OCB confirms that employees reflect the behaviors and attitudes of leadership. Additionally, FLI, FLA, and FLP’s significant positive relationship with OCB support Newman et al. (2020) findings that moral disengagement does not stand alone but relates to social cognitive theory, which contributes to the employee’s ability to accept or reject organizational standards.
The second theoretical implication contributes to the social information processing theory. Although social information processing theory has been the primary lens to analyze ethics on OCB (Teng et al., 2020), this research adds that employees rely on social comparisons, which contributes to destructive workplace behaviors (Dempsey et al., 2018). Because PDT is responsible for moral disengagement, which is a cognitive process to justify deviant behaviors and moderate the positive relationship on OCB, ethical leaders must display more than integrity and assurance to account for employee perception of leadership’s tolerance of dishonesty or immoral behavior (Tarrant et al., 2012; Xie et al., 2020). However, FLP accounts for “doing things right”. Therefore, PDT did not moderate the relationship between OCB. Therefore, employees who perceive leadership as having integrity, assurance, and pragmatism are less likely to exhibit the four loci of moral disengagement in the workplace (Newman et al., 2020).
The third theoretical implication advances FLT. The findings conclude that integrity, assurance, and pragmatism are ethical leadership attributes. Additionally, ethical leaders should conduct an inward and outward examination of decision-making using the process of FLI, FLA, and FLP. Previous research confirms that PDT alters leadership ethics and employee judgment (Desai & Kouchaki, 2017). However, FLP is resistant to PDT and thus reduces employee exposure to leadership acceptance of deviant behavior in the workplace.
5.2. Practical Implications
Employees perceive leaders who examine decisions using integrity, assurance, and pragmatism as ethical. Leaders who rely on integrity are more likely to adhere to moral standards (Palanksi & Yammarino, 2009). FLI Cronbach’s alpha coefficient of >.90 fills gaps in the literature on the underdevelopment of integrity measurements (Fu et al., 2019) and provides a reliable measurement for ethical leadership. Additionally, integrity is responsible for building OCB. Therefore, leaders with integrity are ethical, which contributes to employees going above and beyond their regular duties and responsibilities. However, integrity alone does not reduce deviant behaviors associated with PDT, and FLA was observed better to determine the proper management of OCB in the workplace.
Leaders who reassure employees are more likely to improve commitment to the organization. Employees who perceive leadership as having FLA have less stress and anxiety, which reduces doubt in the workplace. Comparatively, FLA’s significant positive relationship with OCB confirms that decision-making that reassures employees reduces uncertainty (Van den Bos & Lind, 2002) by promoting fairness in the workplace (Yang et al., 2019). The findings of this research support Brown et al. (2005) study that ethical leaders who reassure employees create organizational sustainability. Therefore, leaders can examine decision-making using FLI and FLA to reduce workplace uncertainty and increase OCB, which is essential to organizational sustainability. Nonetheless, PDT can still impact employee social information processing through social comparison, leading to negative perceptions of ethical leadership positioning on deviant behaviors. The last step in the LEAD model is FLP which is an outward examination of ethical decision-making based on helping employees meet or exceed organizational tasks and goals.
FLP is a LEAD model construct that justifies an outward examination of decision-making based on the ability to help employees perform above and beyond on the job. Previous literature suggests that employees with pragmatic leaders commit to the organization (Anderson & Sun, 2017). It was hypothesized that FLP would predict OCB and be resistant to the negative moderation of OCB. The research confirmed that FLP not only creates OCB but is resistant to PDT.
FLP confirms that pragmatic leaders are better prepared for external factors which may adversely impact employee commitment (Mumford et al., 2017). Additionally, the findings suggest that FLP directly reflects an employee’s level of productivity (Jordan et al., 2017). The overall impact of FLP predicts positive employee commitment, productivity, and resistance to the moderating effect of PDT on OCB. Because PDT is a prerequisite to destructive behaviors that justify violating laws (Holman & Popusoi, 2018; Maftei et al., 2021), leaders who apply FLP along with FLI and FLA are more likely to have employees who go “above and beyond” their regular duties and less likely to disengage from OCB morally. More importantly, leaders who apply the LEAD model will increase OCB without using a formal reward system. As a result, leaders, managers, and HR professionals can better account for social influence on decision-making by applying the LEAD model and focusing on pragmatism as an ethical attribute to reduce deviant behaviors in the workplace.
Ethical leaders who ignore or accept deviant behaviors in the workplace may experience collective moral disengagement. However, this study reveals that the more ethical leadership uses the LEAD model, employees are more likely to exhibit OCB attributes. However, employees are less likely to demonstrate deviant behaviors or morally disengage from leadership decisions that help them meet or exceed organizational goals. As a result, employees who perceive ethical leaders as making pragmatic decisions are less affected by PDT, which reduces the positive outcomes associated with OCB.
Organizations consist of diverse employees from various backgrounds. Unfortunately, diversity can lead to employees relying on social comparisons, which can alter the perception of ethical leadership. Therefore, this study on OCB considered potential differences based on employee demographics of age, gender, and income levels. However, participant age, gender, and income did not have significant differences, which indicate that the LEAD model is consistent across diverse categories in predicting OCB and the resistance to PDT.
The findings support Chizema and Pogrebna’s (2019) conclusion that age does not affect leader-to-employee relationship building. However, it contradicts Peng (2013) that gender may influence employees’ perception of their leader. Similarly, income level was not significant on OCB and suggests the LEAD model is a reliable, ethical leadership construct to promote OCB and reduce the likelihood of workplace deviance. Therefore, employee ages (18 - 65+), gender (Female = 50.8%; Male = 48.94%), and income level (US $10K → $200) agree on OCB and FLP can aid in helping ethical leadership decision-making become more resistant to the negative moderation of PDT.
The research has some limitations. First, the entire US workforce was not used to conduct this study. Second, this is a cross-sectional, correlational, moderation study. Appropriate sample size was established to collect responses on LEAD, PDT, and OCB studies to mitigate the errors associated with this study. Employee perception can change over time and slightly vary on LEAD and OCB. Therefore, future research should focus on alternative ethical leadership styles and the resistance to PDT.
6. Conclusion
Ethical leadership styles are essential in the development of organizational citizenship behavior. Previously, studies revealed that leaders with strong ethical convictions were viewed as threatening (Stouten et al., 2013) or intolerant (Weaver et al., 2014), which can alter their decision-making. Additionally, employees who repeatedly witness leaders tolerate deviant behavior in the workplace may disengage morally. The purpose of this research was to determine ethical attributes that are resistant to PDT negative impact on OCB. Pearson’s correlation, regression analysis, and moderation tests were conducted in this examination. FLI, FLA, and FLP significantly predicted OCB. Consequently, PDT decreased the overall effectiveness of FLI and FLA on OCB. However, FLP is an outward examination of ethical decision-making that employees perceive helps them meet or exceed organizational goals and is found to be resistant to the negative effects of PDT on OCB. Therefore, leaders who rely on FLI, FLA, and FLP, will inspire employees who go above and beyond regular job duties without using a formal reward system and reduce deviant behaviors associated with the four loci of moral disengagement.