The influence of salesperson depression, low performance, and emotional exhaustion on negative organizational deviance.
This study offers several significant contributions to the workplace deviance literature. First, NOD is particularly relevant to personal selling because salespeople are so autonomous, where they are often in the field and their actions are typically not directly supervised.
Second, NOD is important as it may be influenced by the demanding nature of personal selling. Thus, business-to-business (B2B) salespeople may passively engage in activities that are hurtful to their organization such as not working as hard or not following orders, particularly if the opportunity presents itself.
Third, this study focuses on an area that has received limited attention, individual-level factors that challenge salespeople (e.g., depression, emotional exhaustion, and low sales performance). These factors which tend to make individuals more passive are more logical to connect strongly with NOD, which is also measured with negative, passive behaviors. Prior sales deviance work focused largely on organizational factors but according to a workplace deviance meta-analysis by Berry et al. (2007) these factors were weakly associated with NOD.
Fourth, new explanations are offered in this study with theories not previously used before. Specifically, labeling theory and cognitive consistency theories are offered to the deviance literature for the first time.
A final contribution is that two of the three antecedent factors in this study are new to the workplace deviance literature. The factors depression and low sales performance (LSP) have not been studied with NOD, and emotional exhaustion (EE) has been examined only once.
WORKPLACE DEVIANCE LITERATURE
The workplace deviance literature emerged when Robinson and Bennett (1995) first conceptualized a typology of deviant workplace behaviors with two dimensions: negative organizational deviance (NOD) and negative interpersonal deviance (NID). Later Bennett and Robinson (2000) developed a measure of both NOD and NID. NOD is voluntary behavior that threatens the organization while NID is behavior targeted at individuals within the organization. A workplace deviance meta-analysis by Berry et al. (2007) later affirmed the distinction between NOD and NID. In addition to NOD and NID, a third form of negative customer directed deviance (NCD) was offered by Jelinek and Ahearne (2006a).
While workplace deviance has been studied for some time in the management literature, there are relatively few published sales studies on the topic. The authors identified eight published studies of sales force deviance. Five of these studies are empirical in nature and examine the effect of such factors as: organizational justice and bureaucracy (Jelinek and Ahearne, 2006b), work-family conflict (Swimberghe et al., 2009; Darrat et al., 2010), person-organization fit (Jelinek and Ahearne, 2010), and social undermining and emotional exhaustion (Yoo and Frankwick, 2013). Three studies are conceptual in nature and examined organizational characteristics (Jelinek and Ahearne, 2006a), workplace spirituality (Chawla, 2014) as well as the role of positive deviance behavior in selling (Hochstein, 2014).
As previously noted, three forms of workplace deviance may exist. Yet, NOD differs distinctly from the others where NID and NCD are more aggressive forms of negative deviance compared to NOD (which is more passive). While not including NID and NCD in this study may be viewed as a potential shortcoming, the authors posit that focusing strictly on NOD is more relevant given the passive/withdrawal nature of the study's antecedent variables (e.g., depression, exhaustion, and low performance). Thus, this paper offers a sound contribution by parsimoniously isolating the effects of key "withdrawal" factors solely on NOD.
To better understand NOD, labeling theory suggests what behaviors are socially unacceptable. Labeling theory (Becker, 1963) explains that behaviors are "deviant" only when society labels them as such. So when an individual deviates beyond the norms of society in a negative manner, that person is acting as a "negative deviant" and may be labeled by conforming members as such.
Polls suggest that the general public holds a very low view of the sales profession where salespeople are viewed as dishonest and unethical (Gallup, 2006). Given that salespeople are highly likely to be stigmatized and stereotyped negatively and be viewed as lower in status, how might such "labeling" affect salespeople? Sangtani and Wood (2007) study automobile salespeople and find empirical evidence that not only are salespeople aware of such stigmatization but that their awareness decreases their effort and performance.
In turn, cognitive consistency theory (Rosenberg, 1968) suggests that people seek consistency between beliefs and observable behaviors and desire to resolve any inconsistencies. Therefore, cognitive consistency theory suggests that if one believes him/herself to be a "negative deviant," then it is more likely that s/he will behave in a negatively deviant manner.
In sum, labeling theory and cognitive consistency theory work together to explain how salespeople may accept and reinforce being a negative "deviant," particularly if they happen to experience one or more of the factors of depression, LSP, or EE. The development of the study's hypotheses begins with literature related to depression.
Depression has been called the number one public health problem in the world as it can strike any race, sex, age, nationality, or social group at any time in one's life (Bronner, 1999). Depression is described as: "a psychoneurotic or psychotic disorder marked especially by sadness, inactivity, difficulty in thinking and concentration, a significant increase or decrease in appetite and time spent sleeping, feelings of dejection and hopelessness, and sometimes suicidal tendencies" (Merriam-Webster Dictionary, 2013).
While depression is increasingly becoming a problem in U.S. society and in the work place (Ilardi, 2009), the notion of a relationship between sales force depression and NOD has yet to be explored. Depression is on the rise and approximately one in four Americans (over seventy million people) will meet the criteria for major depression at some time in their lives. Depression is also a serious labor concern, costing approximately $44 billion in lost productivity annually according to the Journal of the American Medical Association (Strout, 2004).
Research related to depression and workplace deviance is very limited. However, one study linked depression with NOD. Murphy et al. (2006) found that depression is strongly associated with negative work productivity. Accordingly, HI is offered.
HI: Depression will directly and positively influence salesperson NOD.
Low Sales Performance (LSP)
LSP is forwarded as a possible factor on NOD. The logic here is that if a salesperson is not performing well, s/he may be discouraged and predisposed to start a "negative-spiral" by engaging in negative workplace behavior (such as NOD). Like depression, LSP is a negative state to be in as a salesperson and as labeling and cognitive consistency theories suggest, the salesperson may accept the notion of being a negative deviant if his/her behavior consistently falls below that of peer salespeople.
There is limited support for a positive link between low performance and workplace deviance. In a meta-analysis by Hershcovis et al. (2007), when worker performance diminished due to limited organizational resources, negative emotions emerged among workers which led to negative workplace deviance. Similarly, H2 is forwarded.
H2: LSP will directly and positively influence salesperson NOD.
Further, LSP is conceptualized to indirectly affect NOD as mediated by depression. In prior works, job performance was affected by negative affect (e.g., Adler et al., 2006; Barrick et al., 2003; Berndt et al., 1998; Guy and Patton, 1996). Yet no prior sales research has linked LSP to depression nor linked depression with NOD.
As labeling theory suggests, if a salesperson is not performing well in his/her position, that individual may feel negatively about him/herself and accept a "negative label." In turn, the low sales performance could hurt the salesperson's morale and mental state, thus facilitating the onset of depression, which could reinforce feelings of being a "negative deviant" and further influence the salesperson to behave more similar to his/her beliefs and feelings, as suggested by cognitive consistency theory. Accordingly, H3 is posited.
H3: LSP will indirectly influence NOD as mediated by depression.
Emotional Exhaustion (EE)
EE has reached a dangerous level among today's salespeople (Low et al., 2001) and cost businesses hundreds of billions of dollars annually (Lewin and Sager, 2009). EE frequently occurs in personal selling where physical and emotional depletion occurs along with significant interpersonal contact (Sand and Miyazaki, 2000) and excessive job demands (Zohar, 1997). EE continues to accelerate as sales positions are increasingly subjected to substantial job enlargement with larger territories and additional administrative responsibilities (Boles et al., 1997).
Recently, Yoo and Frankwick (2013) studied EE among salespeople. They found that salespeople who experienced EE tended to engage in negative workplace deviance. Accordingly, H4 is offered.
H4: EE will directly and positively influence salesperson NOD.
The last hypothesis (H5) relates to the relationship of EE and depression. While EE and depression are not identical, they may exhibit similar manifestations (Maslach et al., 2001). Further, when studied together, the directionality of these two factors is unclear (Nyklicek and Pop, 2005). However, Nyklicek and Pop (2005) do offer that EE could conceivably bring about depression. As such, H5 asserts that EE precedes and influences depression.
H5: EE will indirectly influence NOD positively as mediated by depression.
Refer to Figure 1 for the proposed model with hypotheses.
A sample of U.S. B2B salespeople was collected through an online survey. Electronic surveys were gathered by a national online data collection firm. Participants were panelists who received a nominal reward (approximately $6.00 in value) that could be redeemed through the online firm. A total of 4,124 invitations were solicited over a three day period and 329 online surveys were electronically returned, yielding an 8% completion rate. However, there was a screener question at the beginning of the survey indicating that if the respondent was not in B2B sales to not complete the remainder of the survey. Twenty-six respondents who returned their survey did not correctly respond to the
B2B screener question and were eliminated, yielding a total of 303 surveys. After reviewing the respondents' profiles, an additional 71 observations were removed from the data set because they were either determined not to be B2B salespeople or because of excessive missing responses. For example, some profile answers among the 71 omitted respondents indicated such occupations as "clerk," "homemaker," "administrative assistant," or "unemployed." Thus, a total of 232 survey respondents were included in the final analysis of this study.
Respondent anonymity was assured. That is, the online survey company that collected the electronic surveys provided the data set to the researchers on their website without identifying individual participants in any way. Respondents were made aware that their responses were completely anonymous to the researchers.
Survey Respondent Demographics
B2B salespeople respondents were derived from a variety of industries. Overall, the sample was demographically similar to other studies with B2B salespeople. In particular, the majority of the survey respondents were Caucasian (86.6%), consistent with prior B2B sales research (e.g., Marshall et al., 1998). In addition, the division of men and women was relatively equal (51.3% men, 48.3% women, 0.4% no response to gender). The median age of the salesperson sample was 51 years with a range from 24 to 75 years. Also, respondents had been with their firm an average of 10.39 years and had been in sales an average of 19 years.
All variables were measured on a seven-point Likert scale. NOD measured how frequently one engages in "organizational deviance" within the last year where 1 = "Never" and 7 = "Daily." NOD is comprised of seven items from the salesperson organizational deviance scale by Darrat et al. (2010) which were adopted and slightly modified from the Bennett and Robinson (2000) "Organizational Deviance" scale. Depression measured the frequency of experiencing depression symptoms within the past week from 1 = "None of the time" and 7 = "All of the time." Depression was measured by twenty items from the Center for Epidemiologic Studies Depression (CESD) Scale by Radloff (1977). LSP measured how productive the salesperson is relative to accomplishing set sales goals with 1 = "Far Below Average" and 7 = "Far Above Average." (Low) sales performance was measured with five self-reported items developed by Dwyer et al. (2000). EE measured the extent to which an individual is overwhelmed in his/her job. The respondents were asked to rate how they felt about their work on a seven-point Likert scale from 1 = "Strongly Disagree" to 7 = "Strongly Agree." EE was measured by six items from Lewin and Sager (2009) for salespeople.
Analysis and Results
The proposed model was tested using the two-step analytical procedure recommended by Anderson and Gerbing (1988). That is, the utilized constructs were first analyzed with Confirmatory Factor Analysis (CFA) to assure a good fit between the items and the data set. The second step of the process was an evaluation of the proposed model through Structural Equation Modeling (SEM). AMOS 21.0 was utilized to analyze both CFA and SEM.
CFA was used to provide a thorough assessment of the constructs. An initial CFA led to the deletion of seven items based on loading estimates (Anderson and Gerbing, 1988). 7 able 1 illustrates the CFA results using the 38 items constrained congenerically. The model chi-square is 963.9 with 428 degrees of freedom (p<0.001). The Comparative Fit Index (CFI) is 0.904, the root mean squared error of approximation (RMSEA) is 0.074, and the Parsimony Normed Fit Index (PNFI) 0.773. As noted in Table 1, the CFA statistics suggest an acceptable fit of the measurement model.
Construct validity is assessed through convergent validity (i.e., variance-extracted, significance of factor loadings, and construct reliability), discriminant validity, and nomological validity. Each aspect of the analysis of construct validity is described below.
Convergent Validity. First, the average variance-extracted (AVE) estimates range from 56.0% to 73.5% (all above 50% level per Hair et al., 2010). Also, all factor loadings are highly significant (p< 0.001), indicating adequate scale convergence (Anderson and Gerbing, 1988). Construct reliability estimates range from 0.90 (NOD and EE) to 0.95 (depression). Therefore, all scales meet the 0.70 minimum acceptable reliability cut off level (Nunnally, 1978) and suggest appropriate convergent validity.
Discriminant Validity. Discriminant validity was assessed using conventional procedures (Gerbing and Anderson, 1988). Results support discriminant validity where all average variance-extracted (AVE) estimates (reported in Table 1) are greater than the squared [PHI] correlation estimates between factors.
Nomological Validity. Nomological validity was examined through inter-construct correlations. Requirements for nomological validity were met as all correlations were appropriately associated according to the underlying theory.
The results generally support the scales' psychometric properties. Therefore, the overall measurement model adequately represents the theorized constructs and is appropriate for use in testing the structural model.
Next, SEM was used to analyze the proposed paths. First, a Full Model containing both direct and mediated (indirect) efFects of the antecedent factors on NOD was tested with SEM. The Full Model chi-square is 963.9 with 428 degrees of freedom (p<0.001). The CFI is 0.904, the PNFI is 0.773, and the RMSEA is 0.074. Results of the SEM with the Full Model are presented in Figure 2.
In the Full Model, depression was positively associated with NOD (t-value=6.074; p<0.001) in support of HI. Second, LSP was positively associated with NOD (t-value= 1.971; p<0.049) in support of H2. Third, LSP was positively mediated with depression (t-value=2.527; p<0.011) in support of H3. Next, EE was not significantly associated with NOD (not supporting H4). Finally, EE was positively mediated with depression (t-value=7.286; p<0.001) offering support of H5.
A follow up step to the Full Model was conducted because EE was not directly, significantly, associated with NOD. Thus, depression was removed and the model was reanalyzed with both LSP and EE directly linked to NOD. Refer to Figure 3 with the Reduced Model # 1.
Results revealed that both LSP (t-value=2.93; estimate=0.15; p<0.003) and EE (t-value=3.94; estimate=0.166; p<0.001) were positively and significantly associated with NOD. However, because the EE-NOD link was not significant when depression was in the Full Model, this finding suggests the presence of a mediating effect of depression between EE and NOD (supporting H5 but not H4).
As a final follow up analysis, a second reduced model (Reduced Model #2) was analyzed with SEM to compare with the Full Model and further test for mediation. In this reduced model, only the direct path linking LSP with NOD was removed. Thus, Reduced Model #2 was tested to determine how taking out the direct path of LSP-NOD would change the model chi-square. Because the direct effect of EE was negligible in the Full Model, that path remained in the reduced model. Refer to Figure 4 with Reduced Model #2.
The chi-square of Reduced Model #2 was 967.9 with 429 degrees of freedom (p<0.001). The CFI was 0.903, the PNFI was 0.775, and the RMSEA was 0.074. In Reduced Model #2, depression was positively associated with NOD (t-value=6.328; estimate=0.42; p<0.001). EE still had a non-significant (t-value=0.124; estimate=0.01; p<0.901) direct path with NOD and was positively mediated with depression (t-value=6.328; estimate=0.15; p<0.001) to NOD. LSP was positively linked and mediated with depression (t-value=7.29; estimate=0.39; p<0.001). In comparing the two models, the reduced model had a larger chi-square value than the Full Model by 4 with 1 df difference, yielding a statistically significant difference between the two models (p<0.045). Therefore, the comparison of Reduced Model #2 with the Full Model suggests that EE is fully mediated with depression while LSP is partially mediated with depression.
In sum, the Full Model (Figure 2) indicates that depression is positively associated with NOD (HI supported), LSP is positively associated with NOD (H2 supported), LSP is positively mediated with depression (H3 supported), EE is not associated with NOD (H4 not supported), and EE is positively mediated with depression (H5 supported).
Within the model, depression explained the most variance of NOD (27%). LSP explained 2% of the variance of NOD and 2% of the variance of depression. EE explained 26% of the variance with depression and 0% of the variance with NOD.
Common method bias was tested using Harmon's one-factor test. All items retained within the CFA in the study were included in an un-rotated, principle components factor analysis. The first factor accounted for 38.37% of the total explained variance. Because the single factor produced from Harmon's one-factor test yielded less than 50% of the total explained variance, common method bias was not considered a problem (Podsakoff et al., 2003).
In addition to Harmon's one-factor test, an even more rigorous test of common method bias (CMB) was used following the recommendation of Podsakoff et al. (2003) with a single-method-factor approach. The factor of procedural justice by Parker et al. (1997) was measured with a four-item scale in the study. This measure was selected as it may have minimal theoretical relevance to the four factors analyzed in this study (see Berry et al., 2007). Thus, procedural justice was used as a SEM marker variable which is considered by Podsakoff et al. (2003) and other researchers as a more conservative test for CMB because it has the advantages of estimating method biases at the measurement level and controlling for measurement error. In the single-method-factor approach prescribed by Podsakoff et al. (2003), the marker variable procedural justice was placed within the proposed SEM model where procedural justice was connected to each of the 31 items measured by the four model factors. The new SEM model was analyzed and the path relationships were compared with the prior SEM model to determine if the nature of those hypothesized relationships changed as a result of introducing another factor (the marker variable procedural justice) that had been measured but had not been theorized. If the model's path relationships change noticeably as a result of introducing the SEM marker variable, then common method bias may be prevalent. In the CMB analysis with the marker variable, the path relationships remained stable, suggesting no concerns with CMB.
As further support that CMB may not be a concern, Sientensen et al. (2010) assert that the length of a survey as well as the number and spacing of items within the survey may diminish possible effects of common method bias. Accordingly, the study's survey contained over 100 items and there were a number of other measures interspersed with the studied constructs in the survey instrument. In sum, CMB does not appear to be present.
The most striking finding in this study is that depression is strongly positively associated with NOD. Thus if one is depressed and has feelings of hopelessness and lack of energy, s/he is more likely to exhibit NOD withdrawal behaviors such as not working as hard or purposefully not following the directions of superiors. While such behaviors may be passive, they are hurtful to the organization and are consistent with the withdrawal behavior one may have who is depressed. This finding also seems to be supported by labeling theory and cognitive consistency theory where if one feels worse or different from peers, that individual could not only accept such a "label" but move into a downward spiral if negative consequences are further reinforced with cognitive consistency (i.e., if I am behaving badly, then maybe I am bad).
While depression may be the result of a mental illness or prolonged negative thoughts and feelings based either on work or non-work factors, EE relates to negative feelings and thoughts about being overwhelmed in one's career as a salesperson. Surprisingly, EE does not appear to have a direct association with NOD. This result here is inconsistent with Yoo and Frankwick (2013) who find EE is positively associated with negative salesforce deviance behaviors. It remains unclear why EE is not linked to NOD in the current study. While EE and depression bear many similarities to one another, their impact on B2B salespeople is indeed different.
Interestingly, EE is mediated with depression in an indirect, positive relationship with NOD. This result emulates the effects of Mulki et al. (2006) who find that among health care service providers, EE negatively mediates job satisfaction and organizational commitment, which in turn negatively affects workplace deviance.
As hypothesized, LSP had a direct and positive association with NOD. Labeling theory and cognitive consistency theory help explain the positive association of LSP with NOD. That is, where LSP occurs, the salesperson may be viewed by others as a "negative deviant" and consequently identify with and fulfill that role.
Finally, LSP also has a positive indirect link with NOD. That is, depression mediates LSP positively with NOD. Thus, LSP is positively associated with depression, and depression is positively linked with NOD. So LSP, like EE, may affect how one views him/herself relative to others within the organization and if negative outcomes occur, the salesperson may accept the label of being a "negative deviant," and in turn experience strong negative emotions (e.g., depression) which could affect one's propensity to behave negatively toward his/her organization in a way that is harmful and violates accepted norms.
Because this study finds a strong positive association between depression and NOD, recognizing depression is important. Yet, depression is called an "invisible illness" because it often remains hidden from view and one cannot always tell from appearances if someone is depressed or not (Bronner, 1999). Thus, depression often remains untreated.
The responsibility for handling depression starts with the individual who suffers with the affliction. A salesperson has an obligation to be a productive person within the organization. At work, the sales manager also has an obligation to make sure that his/her salespeople are not succumbing to the weight of depression. However, salespeople may not want to discuss depression or personal issues with their manager. Thus, an employee assistance program (EAP) may be one solution. EAPs are designed to aid employees in dealing with personal problems that may affect their job and well-being. EAPs normally include short-term counseling and referral services for employees. EAPs are typically free to employees and are prepaid by employers (U.S. Office of Personnel Management, 2016).
Organizations may also consider administering periodic confidential mental health surveys (similar to the CES-D Scale). Perhaps an even more comprehensive plan to combat the deleterious effects of depression is for an organization to enroll in the "Depression: Awareness, Recognition, and Treatment (D/ART) Program." D/ART was created by the National Institute of Mental Health (NIHM) and seeks to create awareness and sensitivity for businesses regarding the widespread impact of depression to better facilitate effective organizational policy changes. Organizations that participate in D/ART receive information for employees along with management training.
A word of caution is warranted regarding the implementation of any sort of systemic measure to identify and treat depression. Requiring employees to take a mental health survey may infringe on employee's personal freedoms/rights or sense of privacy. Thus, health screeners or surveys should probably be used on a voluntary basis and done so judiciously. Ultimately, there certainly must be a balance between the organization's desire to help its employees and the employee's right to privacy and not feeling threatened or intimidated.
While EE is not directly linked with NOD, EE is positively mediated with depression to NOD. So if one is overwhelmed at work, EE may affect one's depression, which in turn adversely affects NOD. Just as the organization, sales managers, and salespeople should all seek to manage depression, EE must be managed too since it can lead to numerous ill effects including absenteeism and burnout. Similar precautions for managing depression also would apply to managing EE and ethical treatment of employees is always paramount. As mentioned earlier, an EAP is one possible solution for helping employees with emotional exhaustion.
Because there is support that LSP has both a direct and indirect effect on NOD as mediated through depression, LSP is a major concern for the organization, sales managers, and salespeople. Like EE, LSP may also adversely affect depression. So LSP is potentially a "triple threat," where: (1) poor sales performance first hurts the organization's bottom line in financial terms, (2) LSP appears to be directly linked with salesperson NOD, and finally (3) LSP appears to be positively associated with depression, which is also detrimental to both the individual salesperson and his/her organization.
Areas to help improve LSP may include: (1) improved sales manager-salesperson communication, (2) increase supervision and/or observation, (3) training, or (4) visit with clients. The first suggestion is possibly the easiest but most important to pursue. Having managers just talking informally with salespeople may reveal issues that can be treated directly rather than making incorrect assumptions. Just as marketers must understand their customers, so must organizations and managers understand their employees.
Increasing supervision and/or keeping a closer eye through observation are more formal steps a manager may consider to improve LSP. Here, the manager could either "ride-along" and work with the salesperson or simply observe (either directly or indirectly) what the salesperson is doing to see if any changes are needed (e.g., time management, focus on new or current clients).
Training may be used but only if necessary. Training is likely a later option once it has been determined that a salesperson has a deficiency that needs to be overcome via training. Such a need can only be determined by discussions with or from observations of the salesperson.
A fourth likely option to improve LSP is visiting or talking with the salesperson's clients. The salesperson may not be aware of problems that are upsetting customers. If the clients are willing to talk frankly with the sales manager, issues can be uncovered and resolved that otherwise may have gone unnoticed. Like training, this option is probably not the first choice to consider but may prove fruitful if other actions do not seem to work.
LIMITATIONS AND FUTURE RESEARCH DIRECTIONS
One limitation is the use of self-reported performance measures. Self-report performance measures are subject to bias by the rater as it is difficult to be completely objective in assessing one's own performance. However, using the self-rating approach for measuring sales performance is common in sales survey research (e.g., Behrman and Perreault, 1982).
A second limitation is the response rate. Eight percent is below the desirable response level for a survey. However, there is evidence to suggest that response rates are significantly lower for online surveys than traditional mail-in surveys (Scherbaum, 2009).
A third possible limitation is the use of online panel data. Panel members were compensated with $6 for completing the survey. However, it remains unclear if the compensation may have affected results. Some general disadvantages of using online panel data include a higher dropout rate than with traditional methods (Birnbaum, 2004) and a restriction to users who have access to the internet. However, using online panel data offers some advantages including access to large and specialized national samples with cleaner data (Birnbaum, 2004). Empirical research of online versus paper and pencil data collection methods indicates that both techniques provide similar covariance structures (Stanton, 1998).
Future researchers in the area of workplace deviance behavior may want to continue to tap into additional factors similar to those identified in the current study. For example, job autonomy, job satisfaction, emotional labor, organizational commitment, and organizational citizenship may be rich areas to study.
Yet another promising area for future research could be to examine how negative workplace deviance among salespeople affects individual and interpersonal outcomes. For example, how does salesperson workplace deviance affect one's sales performance, customer satisfaction, or sales manager's perceptions? The personal selling workplace deviance literature is rife with opportunities to explore and this study attempts to provide a better understanding of this malevolent, perplexing, but all too common workplace phenomenon.
Burton R. Risinger Endowed Professor of Marketing
Louisiana Tech University
Instructor of Marketing
Louisiana Tech University
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Table 1 Standardized Confirmatory Factor Analysis (CFA) Loading Estimates Item Item Description NOD DEP [[xi].sub.1] [xi]2 NOD Taken property from work 0.692 without permission. NOD Spent too much time 0.504 fantasizing or daydreaming instead of working. NOD Come in late to a sales 0.832 meeting without permission. NOD Neglected to follow your 0.763 boss's instructions. NOD Discussed confidential 0.903 company information with an unauthorized person. NOD Used an illegal drug or 0.877 consumed alcohol on the job. NOD Put little effort 0.592 into your work. Dep. I was bothered by things 0.716 that usually don't bother me. Dep. I did not feel like eating; 0.657 my appetite was poor. Dep. I felt that I could not shake 0.837 off the blues even with help from my family or friends. Dep. I felt that I was just as - good as other people. (1,2) Dep. I had trouble keeping my mind - on what I was doing. (1) Dep. I felt depressed. 0.879 Dep. I felt that everything 0.659 I did was an effort. Dep. I felt hopeful about - the future. (1,2) Dep. I thought my life had 0.803 been a failure. Dep. I felt fearful. (1) - Dep. My sleep was restless. 0.716 Dep. I was happy. (1,2) - Dep. I talked less than usual. 0.654 Dep. I felt lonely. 0.855 Dep. People were unfriendly. 0.756 Dep. I enjoyed life. (1,2) - Dep. I had crying spells. 0.738 Dep. I felt sad. 0.889 Dep. I felt that people 0.778 dislike me. Dep. I could not get "going." 0.755 LSP I would rate my performance on sales commissions earned. LSP I would rate my performance on exceeding sales objectives and targets. LSP I would rate my performance on generating new customer sales. LSP I would rate my performance on generating current customer sales. LSP Overall, I would rate my performance compared to the typical salesperson in my firm. EE Working with customers is really a strain for me. (1) EE I feel I am working too hard for my customers because they're too demanding. EE Working with my sales manager directly puts heavy-duty stress on me. EE I feel emotionally drained by the pressure my sales manager puts on me. EE I feel I work too hard trying to satisfy non-sales employees of the company. EE I feel burned out from trying to meet top management's expectations. Average Variance 0.560 0.589 Extracted (AVE) Construct Reliability 0.896 0.952 Cronbach's Alpha 0.889 0.953 Item Item Description LSP EE [xi]3 [[xi].sub.4] NOD Taken property from work without permission. NOD Spent too much time fantasizing or daydreaming instead of working. NOD Come in late to a sales meeting without permission. NOD Neglected to follow your boss's instructions. NOD Discussed confidential company information with an unauthorized person. NOD Used an illegal drug or consumed alcohol on the job. NOD Put little effort into your work. Dep. I was bothered by things that usually don't bother me. Dep. I did not feel like eating; my appetite was poor. Dep. I felt that I could not shake off the blues even with help from my family or friends. Dep. I felt that I was just as good as other people. (1,2) Dep. I had trouble keeping my mind on what I was doing. (1) Dep. I felt depressed. Dep. I felt that everything I did was an effort. Dep. I felt hopeful about the future. (1,2) Dep. I thought my life had been a failure. Dep. I felt fearful. (1) Dep. My sleep was restless. Dep. I was happy. (1,2) Dep. I talked less than usual. Dep. I felt lonely. Dep. People were unfriendly. Dep. I enjoyed life. (1,2) Dep. I had crying spells. Dep. I felt sad. Dep. I felt that people dislike me. Dep. I could not get "going." LSP I would rate my performance 0.743 on sales commissions earned. LSP I would rate my performance 0.838 on exceeding sales objectives and targets. LSP I would rate my performance 0.869 on generating new customer sales. LSP I would rate my performance 0.907 on generating current customer sales. LSP Overall, I would rate my 0.919 performance compared to the typical salesperson in my firm. EE Working with customers is - really a strain for me. (1) EE I feel I am working too hard 0.526 for my customers because they're too demanding. EE Working with my sales manager 0.902 directly puts heavy-duty stress on me. EE I feel emotionally drained 0.945 by the pressure my sales manager puts on me. EE I feel I work too hard trying 0.729 to satisfy non-sales employees of the company. EE I feel burned out from trying 0.836 to meet top management's expectations. Average Variance 0.735 0.643 Extracted (AVE) Construct Reliability 0.933 0.897 Cronbach's Alpha 0.930 0.894 (1) Item deleted from scale. (2) Reverse scored item.
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|Author:||Amyx, Douglas; Jarrell, Larry|
|Publication:||Journal of Managerial Issues|
|Date:||Sep 22, 2016|
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