Time Banditry and Impression Management Behavior

Abstract

Time banditry recently has been introduced as a distinct construct in the counterproductive work behavior literature. Employees are engaged in time banditry when they pursue non–task-related activities during work time. We posit that they capitalize on the ambiguity in most work environments to manage impressions that their time banditry behavior really is productive and not counterproductive work behavior. In this investigation, two studies were conducted to explore variables that can be used to classify time bandits into four different categories. Discriminant function analysis was used to determine individual-level and job-level factors that classify time bandits. Results revealed that both situational and dispositional variables can be used to predict time bandit type. Suggestions for future research and implications for managing, reducing, and changing time banditry behaviors are discussed.

Keywords

time theft counterproductive work behavior (CWB)individual differences

The dreamy goal of productivity at work is shared by most employers, because in many cases, employee productivity leads to increased profits and corporate sustainability. As managers, we expect our employees to be productive during the workday, although research has shown that in many cases the amount of time wasted at work can be quite substantial. In 2005, a voluntary online survey through popular websites (AOL and Salary.com) asked 10,044 individuals to estimate the amount of time they wasted in a typical 8-hour workday. Respondents reported wasting just over 2 hours per day, resulting in an estimated loss to American companies of $759 billion annually (Malachowski, 2005). While focused productivity during every moment an employee is at work is an unrealistic expectation, the reduction, but not elimination, of time waste behaviors (henceforth referred to as time banditry) can be accomplished through accurate identification of these employees, which could yield large gains in productivity and have a significant positive financial effect. As companies struggle to find every possible competitive edge, the reduction of time banditry in the workplace would prove to be beneficial and possibly deliver a significant financial return.

Theoretical Foundations, Background Literature, and Hypothesis Development

The concept of time banditry was introduced by Ketchen, Craighead, and Buckley (2008) and was later defined by Martin and colleagues as “the propensity of employees to engage in unsanctioned, non-work related activities during work time” (Martin, Brock, Buckley & Ketchen, 2010, p. 27). As per this definition of time banditry, bandit behaviors can include any behavior that results in decreased effort toward focal job tasks, for instance, using the Internet for personal reasons, taking long lunch breaks, and excessive socializing with coworkers. By definition, time banditry resembles several other constructs such as counterproductive work behavior (CWB) and cyberloafing and encompasses many of the same behaviors. Engagement in time banditry, unlike CWB, is not driven by intent to cause harm to people or the organization (Brock, Martin, & Buckley, 2013; Spector et al., 2006).

CWBs, such as physical theft or sabotage, are driven by aggression and/or hostility (Fox & Spector, 1999) and are often done with intention such as planning revenge for an injustice suffered in the workplace (Jones, 2009). These CWBs are very different from time banditry. Time banditry does not require or imply malice on the employee’s part. Rather, the theft of organizational time could be driven by boredom, laziness, perceptions of injustice, poorly defined tasks, or an inappropriate allocation of personal time during work hours (Ketchen et al., 2008). In addition to the concept of an employee engaging in high or low levels of time banditry, Martin et al. (2010) also suggested that there can be different types of time bandits, who engage in different types of behaviors of different reasons. In addition, these different types of time bandits engage in various forms of impression management to maintain their status as an employee.

Managing the Shared Meaning of Time Banditry Behavior

Certain time banditry behaviors, while harmful to one’s individual productivity, could be rather beneficial to the organization (Brock et al., 2013). Specifically, employees can engage in pro-organizational actions, such as engaging in conversation with coworkers, which helps lead to better team cohesion, or planning a company get together, which helps with overall morale of all employees. In doing so they are taking time away from their assigned duties and their individual productivity can decline. Although CWB, cyberloafing, and withholding effort are forms of time banditry, time banditry can be seen as an umbrella for many behaviors including cyberloafing, shirking, job neglect, social loafing, free riding, socializing, and even occupational helping behaviors as long as they result in the engagement in off-task behavior.

Skilled time bandits present their time banditry behavior in ways that manage shared meaning of positive, beneficial, and effective behavior, which is designed to help others and the organization as a whole. The ambiguity of organizational environments allows such image management behavior to operate successfully (Lerner, 1990). Furthermore, because individuals have a basic concern with how they present themselves to, and are perceived by, others, they carefully craft the particular images they project to others in the workplace and everyday life (e.g., Leary, 1995). Pfeffer (1981, p. 1) suggested that “organizations are viewed as systems of shared meanings and beliefs in which a critical administrative activity involves the construction and maintenance of belief systems.”

Ferris, King, Judge, and Kacmar (1991) stated,

We characterize the management of shared meaning as providing the context or background for organizational politics, and then demonstrate how people in organizations can use the manipulation of shared meaning, in the form of perceived similarity and ‘fit’ to influence important human resources decisions and actions. (p. 41)

Pfeffer (1981) goes on to argue that these shared meanings and belief systems cause actions in organizations to be interpreted in ways compatible with the prevalent values and norms. This context led Jackall (1988) to suggest that

the nonaccountability of the corporation is really a license to exert one’s own will and to improve one’s own fortune by making the system work for oneself as long as one does not overreach one’s power or station, and as long as one maintains crucial alliances and does not get caught. (p. 133)

We argue that time bandits carefully package their time misuse behavior in ways that are intended to be perceived and interpreted by others in organizations as productive actions, designed to assist or support others in effective ways, and as behavior that fits the context and its norms, beliefs, and value system. Certain time banditry behaviors are beneficial to the organization, but can be detrimental to individual productivity (Brock et al., 2013). Some time bandits focus their attention on building social relationship with coworkers, which increases team cohesion, or helping coworkers with extra tasks. For time bandits, they see value in being a “team player” because they are able to manage their outward appearance using impression management techniques. Impression management refers to the process by which individuals attempt to influence the image (Bolino, 1999; Rosenfeld, Giacalone, & Riordan, 1995). Individuals who are conscious of what is deemed socially desirable may try to manipulate others to gain favor by participating in organizational citizenship behaviors (Phipps, Prieto, & Deis, 2015). Although this sounds like a positive, over time, their ability to manage their outward appearance may become a banditry behavior costing the organization.

Two studies were conducted to explore those variables that can be used to target potential and current time bandits and to provide suggestions for managers and Human Resources to reduce the amount of inappropriate time use on the job, thereby reducing the amount of financial waste due to loss of productivity. Study 1 establishes evidence that time banditry can be measured by proxy with personality and organizational measures. This would allow managers to predict an applicant’s propensity to steal time prior to hiring them, saving the company money and improving productivity.

Study 2 explores different types of time bandits and whether we can accurately classify those that engage in time banditry into different types. By specifically identifying the type of time bandit, we can better understand how that time bandit “gets away with” waste behaviors via impression management and work to provide organizations with targeted interventions to reduce or change time banditry, thereby increasing productivity and reducing turnover through increased employee engagement.

Predictors of Time Banditry Behavior

Due to the differences in time banditry compared with other deviant constructs, the relationship between time banditry and antecedent variables are currently unknown. There are several factors that are expected to be related to engagement in time banditry—individual-level factors, work/job-level factors, and organization-level factors (Martin et al., 2010). By establishing correlational relationships between time banditry and several constructs, we can then use scores on these constructs to identify whether someone is likely to be high or low on time banditry, as well as attempt to classify them into their time bandit types.

Personality

Personality, specifically conscientiousness, is predicted to have a large impact on one’s propensity to steal time from the organization. Conscientiousness has been shown to be related to increases in productivity (Kamdar & Van Dyne, 2007), job performance (Barrick & Mount, 1991), and engagement (Barrick & Zimmerman, 2009) across different occupations (Salgado, 1997). It is inversely related to CWBs (Salgado, 2002). As time banditry can include behaviors relating to social activities, extraversion is predicted to positively influence the occurrence of time banditry behaviors. Finally, highly neurotic individuals are likely to engage in more time banditry and counterproductive workplace behaviors (Salgado, 2002). These individuals tend to be pessimistic and seek and dwell on the negative aspects of situations. Thus, they are proposed to be more likely to view situations as unfair, and thus have a higher level of perceived injustice. Because of these negative outcomes, the ideal level of neuroticism for employees is low.

Hypothesis 1a: Conscientiousness will be negatively associated with time banditry.

Hypothesis 1b: Extraversion will be positively related to time banditry.

Hypothesis 1c: Neuroticism will be positively related to time banditry.

Affect

Prior research has shown that positive affect is negatively related to CWBs and positively correlated with organizational citizenship behaviors (Avey, Luthans, & Youssef, 2010), which is the same pattern as predicted with time banditry. Based on prior research on CWBs (e.g., Roberts, Harms, Caspi, & Moffitt, 2007), it was hypothesized that positive affect would be negatively related to time banditry but that negative affect would show a positive correlation. This should not be construed as predictions that only negative people engage in time banditry. Rather, the correlations proposed between the positive/negative affect and time banditry are merely predictions of the overall relationship between the constructs.

Hypothesis 2a: Positive affect will be negatively related to time banditry.

Hypothesis 2b: Negative affect will be positively related to time banditry.

Engagement

The extent to which employees are engaged with their job tasks will lead to more time spent on the job and less on non–work-related activities. An unengaged, bored employee is more likely to engage in time banditry (Ketchen et al., 2008). Time banditry is defined as engaging in off-task activities; thus, engagement in work activities will limit the occurrence of time banditry. Whereas time bandits can be engaged, Martin et al. (2010) suggested that individuals who score higher on the Time Banditry Questionnaire will be less engaged, thus providing a negative overall correlation.

Hypothesis 3: Engagement will be negatively related to time banditry.

Organizational Justice

Numerous studies have shown that individual perceptions of justice, or more importantly injustice, can have dramatic effects on the prevalence of CWBs (e.g., Aquino, Lewis, & Bradfield, 1999; Colquitt, Scott, Judge, & Shaw, 2006; Everton, Jolton, & Mastrangelo, 2007; Greenberg, 1990; Skarlicki & Folger, 1997). Although none of these studies use time theft as the sole measure of CWB, it is predicted that time banditry and perceived injustice will mirror the observations in these studies. Thus, feelings of organizational injustice are predicted to be positively correlated with time banditry.

Hypothesis 4: Organizational justice will be negatively related to time banditry.

Organizational Commitment

Organizational commitment is defined as a psychological mind-set, which works to increase the likelihood that an employee will maintain membership in an organization (Allen & Meyer, 1990; Meyer & Allen, 1991). In their three-component model of commitment, they delineate three forms of commitment—affective commitment (desire to remain), continuance commitment (perceived cost of leaving), and normative commitment (perceived obligation to remain). It is assumed that if individuals are committed to their jobs and/or their organizations, they will be less likely to engage in time banditry, and stay with the organization longer (Johnston, Parasuraman, Futrell, & Black, 1990; Spector & Fox, 2002). Specifically, as commitment to the organization begins to decrease, individuals tend to engage in more CWBs. A study by McElroy, Morrow, and Fenton (1995) found that uncommitted workers are more likely to take sick days when they are not sick.

Hypothesis 5: Organizational commitment will be negatively related to time banditry.

Job Complexity

Complex jobs are those that provide job incumbents with independence, opportunity to use a variety of skills, information about their performance, and chance to complete an entire and significant piece of work. Such factors can include autonomy, skill variety, task feedback, task identity, and task significance. Autonomy is the extent of one’s freedom, discretion, and independence in scheduling and in the way in which one performs the job. Autonomy has been shown to correlate with stress-related responses, such as anxiety, intention of quitting the job, job satisfaction, and physical symptoms (e.g., Spector, Dwyer, & Jex, 1988). Skill variety involves the degree to which a job requires a variety of challenging skills and abilities—specifically, doing different things or using different valued skills, abilities, and talents (Hackman & Oldham, 1975). Job feedback is the degree to which the worker gets information about the effectiveness of his or her efforts, either directly from the work itself or from others (Hackman & Oldham, 1975). Task identity is the degree to which a job requires completion of a whole and identifiable piece of work—specifically, doing a complete job from beginning to end. Finally, task significance is defined as the extent to which the job has an impact on the lives of other persons within or outside of the organization (Hackman & Oldham, 1975).

Hypothesis 6: Job complexity will be negatively related to time banditry.

Past research has shown that there are measures that can successfully predict CWBs, such as underperforming and physical theft, though these are specific measures that could be administered in addition to the standard pre-hire battery of tests (Boye & Wasserman, 1996). We hypothesize that a similar process can be used to classify time bandits into high or low engagement categories.

Hypothesis 7: Time bandits can be accurately classified into high and low engagement types.

Profiles of Time Bandit Types

As mentioned previously, Martin et al. (2010) suggested that there is a typology of time bandits, based on an employees’ level of engagement and productivity. The typology of time bandits depicts that an employee that engages in theft can be both productive and engaged in his or her job, which counters most CWB theories. An employee’s level of engagement and productivity yields four different types of time bandits: Weasels, Mercenaries, Sandbaggers, and Parasites.

The first type of time bandit is the weasel. Weasels are time bandits that are both productive and engaged, but still steal time. They have learned how to manipulate their environment to be able to “weasel” out of work and are fully capable of performing more and/or better work. For example, this type of time bandit may give the impression that their tasks will take longer to complete than they actually do, and in doing so they appear very hard working, but in reality they get more time for themselves on the job to engage in off-task behaviors. To be successful as a “weasel” this type of employee is constantly managing the time expectations of work to peers and supervisors. Although weasels steal organizational time, this is the most positive type of time bandit because they are still reasonably engaged, committed, and productive, but the additive effect of their behavior remains a problem. The second type of time bandit is productive but not engaged. These workers are termed mercenaries. These are workers who “go through the motions” but would much rather be somewhere else and would arguably perform another job better if more engaged. This type of bandit only does what they have to in order to keep their job, and are hypothesized to be more common in jobs where there are specific and concrete job performance standards, such as piece rate work. This time banditry profile might also be appropriate for individuals who do not seek to remain with the company or advance their position, thus giving them little motivation to commit to the organization.

The next type of bandit is the sandbagger, who is engaged but unproductive. They are very excited about what they are doing, but they do not really do a lot of work that is job related. This type of time bandit might exhibit a pattern of occupational helping behaviors. Specifically, you will likely find this individual helping others with their problems rather than accomplishing their own tasks. A sandbagger is someone that appears to be involved but their involvement is largely for the sake of managing impressions. Because the sandbagger is already engaged in their work, they are likely going to be the easiest type of bandit to manage or fix. Managers should focus their efforts and enthusiasm toward positive organizational goals, using performance goals and incentives to reduce time banditry behaviors.

The final and most harmful type of bandit is the parasite. They are neither productive nor engaged but draw the same organizational resources as a worker who produces much more. The behaviors that are categorized under the parasite type are those which are typically identified as time misuse in previous research and include such behaviors as social loafing (Latane, Williams, & Harkins, 1979), free riding (Albanese & Van Fleet, 1985), shirking (Judge & Chandler, 1996), and job neglect (Albanese & Van Fleet, 1985). The Parasite likely engages in little impression management. They are employed by the organization due to a lack of oversight from management or because of a poor ethical culture or work climate, which has created a shared understanding that the waste or misuse of time is not something that is policed.

It is expected that each type of bandit will engage in the act of time theft but the individual and organizational antecedents will vary by type. As mentioned previously, research has shown that there are proxy measures that can successfully predict those that are likely to engage in CWB (Boye & Wasserman, 1996), thus we hypothesize that we can use measured constructs to predict time bandit types.

Hypothesis 8: Time bandits can be accurately classified into types utilizing proxy measures.

Study 1: Method

Participants

Four hundred and forty-six students who were currently employed at least part-time (20 hours per week) were solicited from undergraduate and graduate business courses to participate in the survey for course credit. Participants ranged in age from 18 to 51 years, with a mean of 20.54 years. The sample contained slightly more females (51.4%) than males (48.6%). The majority of the participants identified their primary ethnicity as Caucasian (79%). Fifteen participants identified their primary ethnicity as Hispanic, and 21 participants identified themselves as Asian, while 21 classified themselves as primarily African American. One participant classified himself or herself as a Pacific Islander, and 11 participants identified themselves as “Other.” Forty-eight participants identified with more than one race, with the most frequent classification being “Other.” The sample was mainly composed of native English speakers (91.5%), and 90% of nonnative English speakers classified themselves as fully proficient to bilingual.

Measures

Recent research has shown that changing employee attitudes can reduce time banditry and the organization’s culture, with both changes focused on identifying and discouraging time banditry behavior (Henle, Reeve, & Pitts, 2010). Thus, there are two major sources of change identified: individual level and organization level. To assess each of these factor levels, different measures were included in the battery of surveys administered. To measure individual characteristics, the Big Five and the Positive and Negative Affect Schedule (PANAS) were included. Individuals’ personalities have been shown to be relatively stable across time and across jobs, and personality measures are commonly administered in pre-hire screening procedures to help the organization decide which employees will perform well and stay with the organization (Barrick & Zimmerman, 2009).

To assess the organization-level factors, measures of engagement and productivity, perceptions of organizational justice, and deception were administered. These factors are predicted to be influenced more by the employee’s current working situation and less on factors that are constant when an employee changes jobs or when the organization’s situation changes.

Time Banditry Questionnaire

The measure of time theft used in this study was the Time Banditry Questionnaire (TBQ). This 31-item measure that has shown high internal consistency (α = .90) and can be applied to a wide variety of employment situations (Brock et al., 2013).

Big Five Mini-Markers

The Big Five personality factors questionnaire (Saucier, 1994) was used in this study to measure participant’s conscientiousness (α = .81), agreeableness (α = .76), openness (α = .77), emotional stability (α = .73), and extraversion (α = .85). Full scale reliability was α = .82.

Positive and Negative Affect Schedule

The PANAS (Watson, Clark, & Tellegen, 1988) was used in this study to measure participant’s levels of affect both positive (α = .86) and negative affect (α = .84). This scale is easy to use and has been shown to be both reliable and valid (Crawford & Henry, 2004).

Productivity and Engagement Measure

This 60-item scale included several subscales and was fairly specific in its orientation to employees in the service field (Singh, 2000). These items were modified for a more diverse sample and recoded to create productivity (α = .76) and engagement (α = .86) subscales.

Utrecht Work Engagement Scale

This 17-item scale measures the work engagement for individuals (Schaufeli, Bakker, & Salanova, 2006; α = .78). This scale was included in the present effort because the measure of time banditry developed should correlate negatively overall with this scale of work engagement. Whereas time bandits can be engaged, it is predicted that individuals who score higher on the time banditry measure will be less engaged, thus providing a negative overall correlation. Including this measure, along with the previously described measure, allows for a comparison between the two measures of engagement.

Organizational Justice

This 17-item organizational justice measure, validated by Lim (2002), was used to assess feelings of justice within the workplace. This measure taps three subcomponents of organizational justice: distributive (α = .91), procedural (α = .94), and interactional (α = .94).

Paulhus Deception Scale

The Paulhus Deception Scale (PDS) is a measure that assesses the tendency to provide socially desirable responses (Paulhus, 1991). It was included because of the self-report nature of the study, given that the focal behaviors may be construed as negative in the workplace, particularly if the answers were given to a member of management. The measure contains two subscales self-deceptive enhancement (α = .75) and impression management (α = .73).

Demographics

Basic demographic information such as participants’ age, gender, ethnicity, primary language, major, year in school, past work history, level of employment experience, and numbers of hours worked per week were collected.

Procedure

Participants completed an online survey in a single session through SurveyMonkey. On completion of all study materials, participants were given a code to e-mail to the principal investigator for purposes of assigning course credit. Using this method allowed participants to remain anonymous, which would lessen the chance of social desirability. Most participants completed the measures in less than 2 hours. Two participants finished less than 25% of the measures, and their responses were not included in any analyses.

Study 1: Data Analyses and Results

Correlational Analysis Results

A correlational analysis was conducted to establish the relationship between time banditry and the factors expected to classify time bandits as either high or low on time banditry. Correlations of all variables are presented in Table 1. The personality measures of the PANAS and Big Five Mini Markers revealed interesting results. As expected, correlations between the time banditry measure and the PANAS were significant. Time banditry was significantly related to negative affect (r = .31, p < .01) and negatively related to positive affect (r = −.16, p < .01). Thus, individuals who display more negative affect are more likely to steal time from their organizations.

Table 1.

Correlation Matrix Study 1.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)	(17)	(18)
Demographics
(1) Age	1
(2) Gender	−.19**	1
PANAS
(3) Positive Affect	−.01	.06	1
(4) Negative Affect	−.11*	.11	.04	1
Big 5 Mini-Markers
(5) Openness	.02	.04	.47**	.12*	1
(6) Conscientiousness	.12*	.13*	.50**	−.12*	.38**	1
(7) Extraversion	.02	.02	.48**	−.09	.30**	.29**	1
(8) Agreeableness	−.02	.23**	.46**	−.15**	.44**	.48**	.24**	1
(9) Neuroticism	−.08	.10*	−.08	.66**	.09	−.14**	−.03	−.16**	1
Paulhus Deception Scale
(10) Impression Management	−.03	−.03	.06	.13**	.07	.06	.07	.03	.17**	1
(11) Self Deceptive Enhancement	.01	.04	.20**	.06	.10*	.13**	.10*	−.01	−.02	.37**	1
(12) Deviant Behavior	.01	−.17**	−.14**	.25**	−.17**	−.33**	−.06	−.36**	.30**	.21**	.12**	1
(13) Workplace Engagement	−.13**	−.15**	−.32**	.27	−.22	−.40**	−.17**	−.36**	.27**	.09	−.09	.54**	1
(14) Organizational Justice	.00	.04	.21**	−.16**	.04	.18**	.07	.17**	−.18**	−.04	.03	−.15**	−.27**	1
(15) Utrecht	.09*	.03	.34**	−.10*	.07	.28**	.17**	.15**	−.17**	.03	.18**	−.09	−.44**	.52**	1
(16) Engagement	−.01	.04	.09	.12*	.11*	.05	.12*	.05	.12*	.07	.15**	.08	.06	.17**	.08	1
(17) Productivity	.10*	.06	.31**	−.16**	.29**	.34**	.21**	.32**	−.13**	−.06	.13**	−.27**	−.38**	.39**	.33**	.54**	1
(18) Time Banditry	.10*	−.17**	−.16**	.31**	−.14**	−.24**	.01	−.24**	.25**	.06	−.02	.43**	.60**	−.13**	−.24**	.15**	−.27**	1

Denotes significance at the .05 level. **Denotes significance at the .01 level.

The Big 5 Mini Marker correlation results presented some unexpected findings. First, conscientiousness was significantly related to time banditry (r = −.24, p < .01). Employees with higher levels of conscientiousness demonstrated fewer behaviors of time banditry. This was expected based on prior literature. No relationship between extraversion and time banditry was observed (r = .01, p > .05). From prior research, we expected that the two factors would be positively correlated. Openness to new experiences had negative correlation with time banditry (r = −.14, p < .01), when no significant correlation was expected. Agreeableness was not predicted to be significantly related to time banditry, but a significant and negative relationship was observed (r = −.24, p < .01), meaning that less agreeable individuals were more likely to steal organizational time. Finally, neuroticism shared a positive relationship with time banditry (r = .25, p < .01), such that more neurotic individuals were more likely to display time banditry behaviors.

The PDS was administered because of the nature of the constructs being measured, and thus, no correlations between either scale and time banditry was predicted. Time banditry was not related to the impression management subscale (r = .06, p > .05) of the PDS, nor was the self-deceptive enhancement scale related to time banditry (r = −.02, p > .01).

Situation-level variables provided further evidence of the importance of time banditry. The results for the relationship about time banditry and engagement were mixed. Surprisingly, time banditry was found to be positively related to employee levels of engagement, yielding a positive correlation (r = .15, p < .01) in one measure, but negatively related to time banditry in another measure (r = −.24, p < .01). The two measures of engagement were negatively related to each other (r = −.44, p < .01), suggesting that the two measures are assessing different facets of engagement. Finally, justice and time banditry were found to be negatively related (r = −.13, p < .01), such that more time banditry is reported when there are lower levels of organizational justice.

Discriminant Analysis Results

For the initial discriminant analysis, only the PANAS and the Big 5 Mini Markers, in addition to the demographic factors of age and gender, were used. These two chosen measures assess personality and are more independent of the workplace situation than the other administered measures. These two measures were examined for their predictive value of classifying employees who are more or less likely to steal time from an organization.

The results of this discriminant analysis were significant (p = .00). Time banditry can be predicted using measures of the organizational situations. Using just the personality measures of the Big Five and the PANAS, the discriminant analysis results were significant (p = .00), meaning that the time banditry behaviors could be predicted based on personality characteristics (see Table 2). The variables used correctly classified 71.8% of study participants as exhibiting either high or low amounts of time banditry behavior.

Table 2.

Discriminant Analysis: Personality Variables.

Measure	Subscale	Standardized canonical coefficients	Structure coefficients	Wilks’ lambda	F	Sig.
Demographics	Gender	.50	.33	.97	12.66	.00
Demographics	Age	.23	.16	.99	2.86	.09
PANAS	Positive Affect	.26	.40	.95	18.58	.00
PANAS	Negative Affect	−.65	−.58	.90	40.08	.00
Big Five	Openness	.38	.43	.94	21.63	.00
Big Five	Conscientiousness	.21	.54	.91	34.79	.00
Big Five	Extraversion	−.35	.04	1.00	.16	.69
Big Five	Agreeableness	.06	.55	.91	36.33	.00
Big Five	Neuroticism	−.05	−.45	.94	24.34	.00

For the next analysis, only the situational measures were used to predict time banditry. This analysis was conducted to determine if the organizational situations can be used to predict the level of time banditry of current employees. When using only the organizational situational variables, correct classification was improved over the personality measures alone, with a total correct classification of 80.7%. Results from this analysis are shown in Table 2. Table 3 provides the discriminant analysis results that include both personality and situational measures. This results in a correct classification percentage of 82.4%, which is not a statistically significant gain in predictive power over situational measures alone. For overall discriminant analysis results, see Table 4.

Table 3.

Discriminant Analysis: Previously Validated Measures.

Measure	Subscale	Standardized canonical coefficients	Structure coefficients	Wilks’ lambda	F	Sig.
Workplace Engagement	Work Engagement	.67	.90	.65	198.84	.00
Utrecht Work Engagement Scale	Work Engagement	−.04	−.30	.94	22.61	.00
Organizational Justice Scale	Organizational Justice	.11	−.17	.98	7.31	.01
Paulhus Deception Scale	Impression Management	−.01	.10	.99	2.37	.12
Paulhus Deception Scale	Self-Deception	−.02	−.03	1.00	.28	.60
Productivity Engagement Measure	Engagement	.34	.14	1.00	5.05	.03
Productivity Engagement Measure	Productivity	−.42	−.40	.91	38.45	.00

Table 4.

Discriminant Analysis: Overall.

Measure	Subscale	Standardized canonical coefficients	Structure coefficients	Wilks’ lambda	F	Sig.
Productivity Engagement Measure	Engagement	−.00	.05	1.00	4.28	.04
Productivity Engagement Measure	Productivity	−.08	−.16	.91	37.63	.00
Demographics	Gender	−.07	−.09	.97	13.09	.00
Demographics	Age	.09	−.04	.99	3.04	.08
PANAS	Positive Affect	−.03	−.11	.95	18.28	.00
PANAS	Negative Affect	.03	.16	.90	39.51	.00
Big Five	Openness	−.18	−.12	.94	21.82	.00
Big Five	Conscientiousness	.09	−.15	.91	34.69	.00
Big Five	Extraversion	.03	−.01	1.00	.13	.72
Big Five	Agreeableness	.01	−.15	.91	36.74	.00
Big Five	Neuroticism	−.02	.12	.94	23.56	.00
Workplace Engagement	Work engagement	.00	.36	.65	195.52	.00
Utrecht Work Engagement Scale	Work Engagement	−.05	−.12	.94	22.46	.00
Organizational Justice Scale	Organizational Justice	.03	−.07	.98	7.33	.01
Paulhus Deception Scale	Impression Management	.05	.03	1.00	1.53	.22
Paulhus Deception Scale	Self-Deception	−.03	.02	1.00	.40	.53

Study 1: Discussion

This study sought to investigate the relationships between and the predictive power of proxy measures for the level of time banditry behaviors an employee displays. From the results of this study, several interesting conclusions can be made.

First, it appears that certain personality characteristics are related to time banditry. Conscientiousness was negatively related to time theft, which is in agreement with existing literature on CWBs. Extraversion was not found to be significantly correlated with time banditry. This was a surprising finding, given that engaging in social exchanges during work hours is a time banditry activity; thus, a positive correlation was expected. It may be that while there is a social aspect to time banditry (e.g., talking to others at work), there is also a social aspect to task-oriented behaviors (e.g., work groups), and this could be diluting the results. Neuroticism was significantly positively related to time banditry while openness and agreeableness were significantly negatively related to the construct. For the purposes of this study, prior research had shown that extraversion and conscientiousness were both reliably related to CWBs, so they were the focal personality measures investigated in this study.

The observed correlations between time banditry and the PANAS were as expected, and were in agreement with existing literature on positive and negative affect and CWBs. This means that, in general, happy people are less likely to engage in time banditry, though these same workers are also more likely to be committed and satisfied with their organizations, which could also minimize their time banditry activities. However, controlling for positive affect did not alter the analyses.

The organizational situational variables also largely were in line with previous research on CWBs. Perceptions of organizational justice were negatively related to time banditry behaviors. This finding presents interesting implications for practitioners and researchers alike, because interventions have been developed to improve organizational justice, which may lead to lower levels of time banditry behaviors.

Engagement is a factor that is traditionally thought to be negatively related to CWBs. However, it was suggested that individuals who are engaged in their jobs can also steal a significant amount of organizational time (Martin et al., 2010). From the results of this study in which two separate measures of engagement were administered, both a significant positive and negative correlation is observed. It is clear from the correlation between the two measures of engagement that they are not measuring the same construct; the two measures are significantly negatively correlated. However, further research should break down the engagement construct to fully determine the relationship between it and time banditry.

The PDS was included to determine if participants were trying to provide socially desirable responses on the TBQ. No significant correlation with time banditry was observed on either of the two deception scales.

The discriminant analysis using personality factors showed that there is significant predictive power using both measures focused on personality characteristics and measures focused on organizational aspects of one’s current working situation. Simply by understanding these factors, we can predict with relatively accuracy whether an employee can be classified as either very likely to waste time or not very likely to waste time in the workplace. These results could assist in hiring, placement, and promotion decisions, ultimately saving the company’s valuable resources.

Study 1 provides evidence that certain variables are useful in establishing proxy measures between time banditry and both personality and situational factors. Furthermore, these variables can be used to inform managers in hiring situations about the propensity of an applicant to engage in time banditry behaviors while at work. The current variables combined can correctly classify 82.4% of participants as either very likely or not very likely to engage in time banditry behaviors.

Study 2: Overview

Study 1 established a precedent for classifying employees as either more or less likely to engage in time banditry using proxy measures. This information is helpful in screening and hiring potential employees but cannot provide much benefit to the company when identifying existing employees in the organization who are currently engaging in time banditry. For example, knowing that someone is likely to commit a high level of time banditry behaviors is helpful information before, not after, they are hired. By classifying what type of time bandit an individual is likely to be, we can gain a better understanding of how said employee manages their time and expectations of managers. Further we can use this information to provide targeted interventions to reduce time banditry in a workplace. Study 2 will use similar proxy measures, focusing of productivity and engagement to classify individuals into the four different types of time bandits using proxy measures.

Study 2: Method

Participants

One hundred and thirty-four students employed at least part-time (20 hours per week) were recruited from undergraduate and graduate business courses to participate in a series of surveys for course credit, of which 125 completed all study materials. The employees were 57% female, came from both public (57%) and private sectors (43%), and held various positions within their respective organizations, both supervisory (18%) and nonsupervisory (82%).

Measures

Job Complexity

This was measured with items from the Job Diagnostic Survey (Hackman & Oldham, 1980). Three items were used to assess each of the five job dimensions: autonomy, skill variety, task feedback, task identity, and task significance. Respondents indicated on a scale ranging from “very inaccurate” (1) to “very accurate” (7) the extent to which the statements accurately described their jobs. To form an overall complexity index, scores for all 15 items were averaged (α = .82).

Time Banditry Questionnaire

This 31-item questionnaire measures the extent to which an employee purloins time from the workplace (α = .90). The measure contains three subscales measuring classical time banditry (α = .88), technology-related time banditry (α = .92), and socially oriented time banditry (α = .71; Brock et al., 2013).

Productivity and Engagement Measure

This 60-item scale included several subscales and was somewhat specific in its orientation to employees in the service field (Singh, 2000). These items were modified for a more diverse sample and recoded to create productivity (α = .76) and engagement (α = .86) subscales.

Organizational Commitment

Organizational commitment was measured using Allen and Meyer’s (1990) three-component measure of commitment. Seven items assessed affective commitment (e.g., “I believe in the value of this change”; α = .82), seven items assessed continuance commitment (e.g., “I have no choice but to go along with this change”; α = .86), and eight items assessed normative commitment (e.g., “I would feel guilty about opposing this change”; α = .77). Responses were made using a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Paulhus Deception Scale

The PDS is a measure that assesses the tendency to provide socially desirable responses (Paulhus, 1991). It was included because of the self-report nature of the study, given that the focal behaviors may be construed as negative in the workplace, particularly if the answers were given to a member of management. There should be no meaningful correlation between this measure and time banditry. The measure contains two subscales self-deceptive enhancement (α = .72) and impression management (α = .70).

Demographic Factors

Certain demographic factors including age, gender, ethnicity, college major, year in school, and number of hours worked per week were collected.

Procedure

As with Study 1, participants completed all study materials online via a dedicated SurveyMonkey website. Anonymity was guaranteed, such that participants received a code to e-mail to the principal investigator on completion of study materials for purposes of assigning course credit.

Study 2: Results

By examining constructs that previously have been linked to CWB and using them as predictors of time banditry types, we can begin to make new associations between personality characteristics and time theft, which will establish time banditry as a subdimension of CWB. Discriminant function analysis was used to classify the four different types of time bandits using proxy measures. Prior to conducting any analysis, individuals were sorted into their time bandit type. Median splits were used to sort participants as high and low on productivity and engagement, and next they were sorted into types as identified in the Martin et al.’s (2010) typology—Weasels (high engagement–high productivity), Mercenaries (low engagement–high productivity), Sandbaggers (high engagement–low productivity), and Parasites (low engagement–low productivity). Means, standard deviations, and correlations of study variables can be seen in Table 5.

Table 5.

Study 2 Means, Standard Deviations, and Correlations.

	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13
1. TBQ	69.04	15.18	1.00
2. Extraversion	26.27	6.51	−.05	1.00
3. Emotional Stability	27.46	5.14	−.23^*	−.11	1.00
4. Conscientiousness	31.64	5.19	−.33^**	.19	.11	1.00
5. Affective Comm	31.75	11.09	−.06	.14	.11	.15	1.00
6. Continuance Comm	33.65	10.92	.08	.01	−.03	.02	.25^*	1.00
7. Normative Comm	32.89	8.04	−.16	.13	−.25^*	.24^*	.45^**	.17	1.00
8. Positive Emotions	48.75	13.88	−.02	.19	.18	.09	.69^**	.08	.27^*	1.00
9. Negative Emotions	42.42	14.87	.18	−.06	−.26^*	−.06	−.21	.24^*	−.01	−.37^**	1.00
10. Skill Variety	12.75	4.72	−.09	.08	.17	.14	.59^**	.19	.28^**	.52^**	−.09	1.00
11. Task Identity	15.42	3.62	−.17	.14	.15	.24^*	.43^**	.18	.27^*	.38^**	−.17	.53^**	1.00
13. Engagement	114.81	12.51	−.01	.26^*	.11	.12	.65^**	.13	.27^*	.57^**	−.50^**	.57^**	.44^**	1.00
14. Productivity	152.18	14.98	−.22^*	.28^**	.10	.29^**	.19	.11	.14	.19	−.07	.22^*	.56^**	.33^**	1.00

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

A one-way ANOVA was conducted to determine whether the types of time bandits differed on the TBQ. The results of the ANOVA demonstrate that there is a significant difference between groups, F(3, 121) = 2.64, p < .05, on the TBQ (see Table 6). This table also provides evidence that all of those that participated engage in time banditry, despite their level of productivity and engagement, with weasels engaging in the least (M = 63.38) and Parasites engaging in the most (M = 72.20).

Table 6.

Means and Standard Deviations on Time Banditry Questionnaire by Type.

Types	Mean	N	SD
1. Weasel	63.38	37	11.79
2. Sandbagger	70.25	20	13.95
3. Mercenary	66.71	24	13.79
4. Parasite	72.2	44	17.36
Total	68.22	125	14.95

Discriminant analysis depends on clear classification of group membership and relies on the presence of categorical variables. Performance and engagement were measured on a continuous scale and were transformed into interval data using the distribution quartiles. To determine how the types of time bandits differed with respect to their responses to several job-level and individual-level factors, a discriminant function analysis was conducted. A series of ANOVAs were conducted to identify the variables in which there were significant group differences. The results of these analyses showed that groups differed on the following individual-level factors: extraversion, F(3,121) = 4.26, p < .01; conscientiousness, F(3, 121) = 5.74, p < .00; openness, F(3, 121) = 3.62, p < .02; continuance commitment, F(3, 121) = 2.95, p < .03; affective commitment, F(3, 121) = 12.02, p < .00; positive affect, F(3, 121) = 15.60, p < .00; and negative affect, F(3, 121) = 3.52, p < .02.

With respect to job-related factors, groups differed on feedback, F(3, 121) = 17.61, p < .00; autonomy, F(3, 121) = 15.25, p < .00; skill variety, F(3, 121) = 12.73, p < .00; task identity, F(3, 121) = 17.57, p < .00; and task significance, F(3, 121) = 6.43, p < .00. These variables were used to predict the four different time banditry groups (1 = Weasel: high engagement–high productivity; 2 = Sandbagger: high engagement–low productivity; 3 = Mercenary: low engagement–high productivity; 4 = Parasite: low engagement–low productivity).

The data were subjected to a discriminant function analysis in a stepwise fashion using the Wilks method of selecting variables to be entered or deleted, and using the default p criterion for entering and removing variables. Because of the exploratory nature of this study, there were no a priori predictions regarding the order of entry of the variables into the discriminant analysis. A stepwise discriminant analysis was conducted. Before proceeding to the results of the classification, the hypothesis that the variance/covariance matrices of the four groups are in the same population was tested using Box’s M statistic (Box’s M = 63.359, F = 1.29, p > .05). Thus, the null hypothesis with respect to the homogeneity of variance/covariance matrices in the population is accepted.

Only two of the discriminant functions were statistically significant, DF1, Λ = .375, χ²(15) = 117.27, p < .000, DF2 Λ = .727, χ²(8) = 38.12, p = .000, and DF3 Λ = .950, χ²(3) = 6.15, p = .104 (see Table 7). Using the two significant discriminant functions, 67.2% of participants were correctly classified. Group classification results can be seen in Table 8.

Table 7.

Functions at Group Centroids.

Types	Function
Types	1	2.00	3.00
1. Weasel	1.258	0.26	−0.15
2. Sandbagger	.540	−0.87	0.35
3. Mercenary	−.692	0.83	0.27
4. Parasite	−.926	−0.27	−0.18

Note. Unstandardized canonical discriminant functions evaluated at group means.

Table 8.

Classification Results.

		Types	Predicted group membership				Total
		Types	1	2	3	4	Total
Original	Count	1. Weasel	31.00	1	2	3	37
		2. Sandbagger	7.00	8	0	5	20
		3. Mercenary	4.00	1	11	8	24
		4. Parasite	2.00	3	5	34	44
	%	1. Weasel	83.78	2.7	5.4	8.1	100
		2. Sandbagger	35.00	40.0	.0	25.0	100
		3. Mercenary	16.67	4.2	45.8	33.3	100
		4. Parasite	4.55	6.8	11.4	77.3	100

Note. 67.2% of original grouped cases correctly classified.

Results of the predictor variable analysis revealed that 5 of the 12 independent predictor variables included in the analysis are useful in distinguishing between the different types of time bandits: autonomy, task identity, skill variety, conscientiousness, and extraversion. Three variables (autonomy, skill variety, and extraversion) distinguish highly engaged groups (Weasels and Sandbaggers) from the other two groups (Mercenaries and Parasites). Only task identity significantly predicted group differentiation on productivity (Weasels and Mercenaries; see Table 9). Table 10 shows a consistent pattern of results for skill variety and extraversion.

Table 9.

Correlations Between IVS and DF Scores.

	Function
	1	2	3
Autonomy	.618^a	−.246	−.154
Skill Variety	.550^a	−.246	−.488
Extraversion	.334^a	.017	−.107
Task Identity	.574	.626^a	−.343
Conscientiousness	.328	.207	.726^a

Largest absolute correlation between each variable and any discriminant function.

Table 10.

Predictor Means and Standard Deviations by Type.

		M	SD
1. Weasels	Autonomy	17.03	2.76
	Task Identity	17.86	2.55
	Skill Variety	15.30	3.79
	Conscientiousness	33.14	4.75
	Extraversion	29.16	4.95
2. Sandbaggers	Autonomy	16.25	3.26
	Task Identity	13.85	3.01
	Skill Variety	13.85	3.56
	Conscientiousness	32.60	4.65
	Extraversion	27.25	8.05
3. Mercenaries	Autonomy	12.54	2.86
	Task Identity	15.04	2.49
	Skill Variety	9.63	4.41
	Conscientiousness	32.04	3.57
	Extraversion	24.96	6.96
4. Parasites	Autonomy	13.16	3.62
	Task Identity	12.95	3.83
	Skill Variety	11.07	4.15
	Conscientiousness	28.95	5.68
	Extraversion	24.66	5.53

Study 2: Discussion

Study 2 provided suggestions for managing time banditry by exploring the typology of time bandits and the factors that predict bandit type. The results of this study indicate that levels of job autonomy, skill variety, extraversion, task identity, and conscientiousness can be used to predict time bandit type. As was discussed in the typology of time banditry, time bandits are broken down by levels of engagement and productivity. Autonomy, skill variety, and extraversion combine to distinguish those individuals that are high on productivity: those classified into Weasels (high engagement–high productivity) and Sandbaggers (high engagement–low productivity). High productivity is a common factor for Weasels (high engagement–high productivity) and Mercenaries (low engagement–high productivity), and it appears that task identity is the significant discriminating factor.

Discriminant analyses provided between a 60% and 70% accuracy of categorization, and thus offers some preliminary evidence for dispositional traits that have been suggested to be related to time banditry. The five largest structure coefficients were autonomy, skill variety, extraversion, task identity, and conscientiousness. Autonomy, skill variety, and extraversion were found to be important variables in the first discriminant function, which distinguishes Groups 1 and 2 from Groups 3 and 4. For the second discriminant function, task identity was the only significant predictor, which distinguishes highly productive groups (Groups 1 and 3) from the other two groups.

Understanding what factors predict time bandit type provides managers information for variables that can be altered to reduce time theft. Although there are many ways we could summarize our interpretation, one way is to explore each individual type of time bandit. It is suggested that a manager focus time banditry reduction effort on Mercenaries and Sandbaggers, as they would theoretically require fewer interventions than a Parasite.

Weasels were predicted to demonstrate the lowest levels of time banditry and were expected to be highly engaged and productive on their jobs, and results were consistent with this. Managers might be hesitant to correct behaviors of the Weasel, as they tend to be highly engaged and highly productive employees. These employees could potentially have higher levels of productivity and engagement if small changes are made in every day work. For instance, all the significant predictors have an impact on the Weasel. Thus, providing these employees with more autonomy and variety in their task might reduce their time banditry behaviors. For workers with the Weasel profile, managers should attempt to simply decrease the amount of time banditry behaviors that are acceptable, possibly through a culture change or by implementing performance standards with reinforcements for achieving production goals and consequences for falling short of such goals.

Sandbaggers could be more productive in their work by defining their task identity and being able to take ownership on some of what they produce. If these individuals cannot identify with their own tasks, they may actively recruit other employees to help; they are more likely to shirk their responsibilities for a task/activity that allows them to gain more personal reward. Thus, the individual is involved and engaged but completes relatively little of their own work.

Mercenaries need improved engagement for better organizational outcomes. This type of bandit does only the bare minimum. It is hypothesized to be more common in jobs where there are specific and concrete job performance standards, such as piece rate work. Furthermore, these types of time bandits show lower levels of organizational commitment and higher organizational turnover. If employees are already certain that they will turnover relatively soon, there is little that the manager can do to curb time banditry short of creating a new shared meaning of appropriate time use by using and enforcing policies against stealing organizational time. Another way to reduce time banditry with Mercenaries would be to enlist these employees as trainers or leaders of divisions. Empowerment can increase the employees’ level of importance to the organization, which in turn can work to provide them the motivation to commit to the organization.

Finally, for the Parasite, or the unengaged and unproductive worker, the manager can choose to either terminate the employment relationship or “rehabilitate” the employee. For the Parasite, all factors predicting group member ship should be explored. Perhaps this person is simply in the wrong position, but they are clearly not contributing to organizational success. Managers could use a variety of tactics to improve performance, such as training, and different ways to increase engagement, such as empowerment and job enrichment and rotation.

On a broader scale, the results of this study provide further insight into CWB by specifically exploring the unique subdimension of time banditry. It was found that time banditry can be split into four types of time bandits. In addition, this research suggests that those individuals that engage in CWB are not necessarily unengaged and unproductive, which is in contrast to past research (e.g., Fox & Spector, 1999). The notion that employees can be both productive and engaged in their job while still engaging in time banditry is novel.

General Discussion

Limitations and Future Research Directions

A potential limitation in these studies is the use of self-report measures, as they might have inflated the relationships among the study variables because of common method bias. There is also a potential of range restriction. Specifically, it may be the case that participants underestimated their time banditry behaviors, a limitation that was hopefully reduced by collecting data anonymously. Although it has been advised that counterproductive behaviors be collected from multiple sources (Sackett, Burris, & Callahan, 1989), these sources are subject to their own set of biases. Furthermore, time banditry and other counterproductive behaviors assessed by other means may not be more accurate than self-ratings (Berry, Ones, & Sackett, 2007; Ones, Viswesvaran, & Schmidt, 1993). Regardless, a fecund path for future research would be the utilization of outcome measures of productivity and engagement from both objective and subjective sources.

As skilled time bandits are likely to hide their off task behaviors via impression management from their managers and coworkers, there is a lack of opportunity to observe time banditry, creating another potential limitation to this study (Martin et al., 2010). Furthermore, Mercenaries and Sandbaggers fall in the middle of the continuum of productivity and engagement and are thus less understood and harder to classify. To increase accuracy of time bandit measurement and classification, future research should include additional predictor variables. In addition, the measurement of time banditry needs to be refined to better represent the different behaviors the types of time bandit’s engagement. Specifically, Martin et al. (2010) note that time banditry can take the form of an OCB and can be positive in nature. The current version of the TBQ only captures the more negative connotation of time banditry; thus, it is not surprising that a similar pattern of result as compared to previous CWB literature. Finally, because of the variety of different ways in which one can engage in time banditry and the rational for engaging in the different behaviors vary and it would be fruitful to explore time banditry at the daily level within individual as well as to explore the cognitive justifications worker make before and after engaging in time banditry behavior.

The concept and research on time banditry is in its infancy leaving much unknown. To date research on time banditry has focused on only job- and individual-level factors. According to the time banditry model (Martin et al. 2010), individual, job, and organizational factors lead to the engagement of time banditry. The presented studies primarily focused on both individual- and job-level antecedents. It is imperative that future research explores organizational-level factors such as climate, as the perceptions of organizations members have a large influence on employee’s behaviors, both productive and counterproductive (e.g., Dieterly & Schneider, 1974; Fleishman, 1953; Griffin, 2001). Furthermore, exploring the impact of organization climate on time banditry can shed light on why parasites persist in organizations.

Conclusion

The phenomenon of time banditry is not a new epidemic. However, organizations have seen and will continue to see massive changes in their organizational structure and in the way work is performed, thus creating new opportunities for time bandits to exist. Moreover, we see that at times it is difficult to delineate time banditry behaviors from individuals who are truly engaged and productive. Time banditry research provides a new awareness to the way individual’s work and helps shed light on impression management and organizational citizenship behaviors. Some individuals, such as sandbaggers, are quick to use impression management and give back to the organization as a whole, but in the meantime are low on individual productivity. By introducing the four types of time bandits, we are better able to help managers be aware of these behaviors. Such changes include the introduction of new technology, some of which might change the nature of one’s job, making it less time consuming and possibly creating new opportunities for time banditry. With such changes comes an adjustment in how employee’s complete tasks, and organizations need information to respond to this dynamic situation in the most efficient manner possible. Taken together, these two studies have shown that individuals can be identified as more or less likely to engage in time banditry behaviors and can further be delineated into one of four groups, making targeted interventions much more likely to succeed.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Meagan E. Brock Baskin is an assistant professor of management in the College of Business at University of Central Oklahoma. She earned her PhD in industrial/organizational psychology from the University of Oklahoma. Her research interests include unethical climate, time waste, counterproductive behaviors, and pro-social rule-breaking. Her research has been presented and published in the proceedings of regional, national, and international conferences and in peer-reviewed journals including Human Resource Management Review, Journal of Occupational and Organizational Psychology, International Journal of Selection and Assessment, and Journal of Behavioral and Applied Management.

Victoria McKee is an assistant professor of management in the College of Business at University of Central Oklahoma. She earned her PhD in management from the University of North Texas. She has focused her research interests in the areas of leadership, different types of leadership, dark leadership, and issues regarding negative work behavior. Her work has been published in Team Performance Management and a book chapter on Applying Fuzzy Set Methodology to Evaluate Substitutes for Leadership.

M. Ronald Buckley holds the JC Penney Company Chair of Business Leadership and is a professor of management and a professor of psychology in the Michael F. Price College of Business at the University of Oklahoma. He earned his PhD in industrial/organizational psychology from Auburn University. His research interests include, among others, work motivation, racial and gender issues in performance evaluation, business ethics, interview issues, and organizational socialization. His work has been published in journals such as the Academy of Management Review, Personnel Psychology, Journal of Applied Psychology, Organizational Behavior and Human Decision Processes, and the Journal of Management.

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