Academy of Accounting and Financial Studies Journal (Print ISSN: 1096-3685; Online ISSN: 1528-2635)

Research Article: 2021 Vol: 25 Issue: 5

Emotional Exhaustion and Deviant Misbehaviours: Effects of Job Stressors and Emotional Intelligence Among Insurance Salespersons

Natasha Tageja, Research Scholar, Amity University, Noida

Vijit Chaturvedi, Associate Professor, Amity University, Noida

Namita Rajput, Professor, Sri. Aurobindo College, University of Delhi

Abstract

The unique nature of a sales job subjects sales executives to extreme pressures resulting in impacting their mental and physical well-being and sometimes inducing negative coping behaviours. The purpose of this research is to study the impact of specific job stressors (role-based stressor and techno-based stressor) on emotional exhaustion which results in salesperson’s frontline deviance behaviour. The research also aims to determine the impact created by emotional intelligence as a significant personality trait to attenuate the ill effects of these specific job stressors on emotional exhaustion. The sample consisted of 205 sales executives involved in direct sales of insurance products from 3 private insurance firms. A structural equation modelling technique was applied to establish causality between job stressors and emotional exhaustion ultimately resulting in frontline deviance behaviour. Findings indicate that both role-based stressors and techno-based stressors had significant direct effects on emotional exhaustion and the more emotionally exhausted a salesperson is, the higher the chances of indulging into frontline deviance behaviour. Emotional intelligence acts as a significant moderator between techno stress and emotional exhaustion.

Keywords

Namita Rajput, Professor, Sri. Aurobindo College, University of Delhi

Introduction

The occupation of a salesperson in a boundary spanning role has undergone extreme changes which exposes them to ever increasing demands (Boles et al., 1997, Rizzo & House, 1972). The absolute necessity of a service driven organization to maintain close contact with their customers places salespeople in a highly stressful position within the organization (Ryding, 2010). Also, in an industry which sells intangible products like insurance, generally using a push strategy (financial companies make efforts in reaching the customers for its products due to their complex and intangible nature) subsequently require a high degree of contact between their customer and sales employees (Buttle, 1993; Parasuraman et al., 1985, Al-diwry et al., 2020). Moreover, increasing economic pressures to outperform competition, meet targets, diminishing lines between work-family, constant challenges posed by new technology and increasing digitalisation and high-quality service expectations of customers contribute significantly to job stress (Day et al., 2010). Two of the work environment variables that are peculiar to salesperson’s stress are role stress, given that its embedded nature in a sales job (Verbeke et al., 2011) and technostress given that the use of technology (example automated CRM softwares, ICT tools, availability over emails, calls, etc.) is inseparable from boundary spanners (Mariadoss et al., 2014; Tarafdar et al., 2007). It is because of these reasons that health practitioners and researchers have come to recognize job stress as a very common syndrome among sales professionals.

The consequences of job stress may be both positive and negative, however the probability of a negative outcome increases as the exposure and intensity of stress increase. However, it is also true that the outcome depends upon how a particular stressor situation is perceived by an individual. Researchers have well established this fact that a particular situation may be appraised as stressful by one person whereas not by another (Tomaka et al., 1993). This can be understood through the works of Lazarus & Folkman (1984) in their cognitive appraisal theory. The most common outcomes of job stressors include health related (anxiety, blood pressure, etc.), intentions to quit, job dissatisfaction, lack of motivations, etc. and inevitably result in loss of millions of dollars spent on account of these.

The fact that stressors in a workplace can cause to alter, modify or cause disturbance in the normal functioning of the person and impact emotional well-being usually results in what is known as emotional exhaustion (Spector & Fox, 2005). Emotional exhaustion is believed to be a part of a broader concept of job burnout which is a state of mental, physical and emotional exhaustion that results from chronic stress experienced over prolonged periods (Lewin & Sager, 2007). Emotional exhaustion is the depletion of physical and emotional resources due to subjugation of oneself to prolonged periods of job stress perceived by an employee in his work sphere (e.g., inadequate resources, lack of decision latitude, work overload) (Maslach & Jackson, 1981). studies suggest that most sales associates tend to engage in more transitory coping mechanisms (Swimberghe et al., 2014). With fewer resources and limited choice of mobility, a sales executive is likely to resort to deviant behaviors. However, deviant behaviors are categorized into three broad categories-organizational deviance (behaviors defying organizational set standards), interpersonal deviance (undesirable behaviors targeted at members of the organization) and frontline deviance- “behaviors targeting a firm’s external stakeholders” (Jelinek & Ahearne, 2006). To date, literature is dominated by concepts that study the direct and indirect effects of job stressors on a variety of outcomes but only a few studies have considered empirically validating the effects of stressors and their interaction with personality traits on negative behavioural outcomes. Moreover, there is dearth of research accounting for causes of counterproductive behaviours at work and the extent to which personality traits like emotional intelligence, self-efficacy, type-A behaviour, etc. impact such negative behavioural outcomes within the framework of emotional exhaustion.

The authors through this research recognize that-1) a person’s environment consists of many sources of stress (knowns as stressors), 2) when these stressors are viewed individually, they may or may not produce deleterious effects contingent on coping resources, and 3) collectively they would restrain a person’s coping resources leading to emotional exhaustion (Fogarty et al., 2000). Thus, it becomes prudent to analyse the relationship between job stressors (role stressors and techno-based stressors), emotional exhaustion, emotional intelligence, and frontline deviant behaviour which is the objective of this current study.

Literature Review

The distinct characteristics and demands of a sales job distinguish itself from other jobs as it involves considerable travel requirements, meeting new and existing clients, making sales presentation, meeting and exceeding performance quotas, ensuring 24*7 availability to answer customer queries, facing the challenges of new technology (in the form of new CRM softwares and ICT tools for data entry, storage, customer networking) making it all the more stressful than ever before.

The perception of a specific stressor in the environment involves a two-step appraisal process- a primary appraisal to assess the potential damage, harm and risk created by a specific stressor on one’s wellness. A secondary appraisal of the assessment of resources and abilities available with an individual to overcome the demands placed by a stressor (Folkman et al., 1986). Job stress results when an employee perceives higher demands in his environment as threatening or damaging and lower availability of resources to deal with them. An individual experiencing prolonged job stress would put in more efforts to deal with negativity resulting out of constant appraisal of the situation (Hobfoll, 1989). This may lead to emotional weariness. In a desire to strike back and to overcome exhaustion salespersons may retaliate in kind wherein they may not vent out their frustration on the organization or its members directly. Instead resort to behaviors that may scar an organizations image in front of external customers. Such behvaiors are known as frontline deviance behaviors. Hence due to his low degree of contact with company officials and co-workers, and increased connectivity with customers the authors consider only frontline deviant misbehaviours.

Role-Stress, Techno-Stress and Emotional Exhaustion

The role theory posits that role-based stress is dominated by three main components: role ambiguity, role conflict and role overload. Role Ambiguity is defined as the lack of clarity in information pertaining to one’s role perceived by an individual in the organization. Role conflict is the degree to which there is incompatibility among one’s role-based expectations. And role overload is the excess of role-based expectations over one’s ability to fulfil them.

The direct effects of perceived role stress on job burnout, in general, and role overload on emotional exhaustion, in particular, have been confirmed in a number of studies (Singh et al., 1994, Boles et al., 1997, Yip et al., 2008). In a study conducted by Lewin & Sager (2007), a model proposing antecedents of job burnout of which emotional exhaustion is a predominant variable was put to test and it was found that a high perceived role overload resulted in higher levels of emotional exhaustion. Yet another study conducted by Sharma (2002) among Indian executives belonging to public and private sector found role-based stressors to be significant predictors of emotional exhaustion and overall job burnout. Therefore,

H1: The higher the levels of role-based stressors (RA, RC and RO) among salesperson, the higher emotional exhaustion they experience

The intensive use of technology has penetrated the walls of every organization and every occupation. The sales job too involves the use of sales automated software and ICTs (information and communication technology). The premise of socio technical theory is that increased use of technology in an organization to bring in more efficiency and quality has added more stress to employees work lives (Trist, 198; Speier & Venkatesh, 2010; Fatima, 2021). However, not everyone is tech savvy, rather technology (ICTs and CRM software) is believed to induce strain, nervousness and anxiety among its users. Moreover, the inability to cope with demands of new technology, new digital tools and software can cause what is called technostress. Thus, technostress is the imbalance that results out of demands created by technology in the workplace and resources available to deal with them. Constantly evolving technology nowadays calls for 24*7 availability over calls, mails, e-mails, etc. among customer representatives and sales executives to fulfil customer needs, a phenomenon called technology invasion. Moreover, changing technical aspects of workplace asks for new technology or constantly updating software creating additional pressures on salespersons to learn the complex software or leading to much of their time lost on training on new software leaving lesser time for sales calls better known as technology complexity. It has been observed that technology when used at optimum levels would act as a job resource producing positive outcomes for both employees and organization, but beyond optimum levels it creates job strain and may even cause exhaustion (Ayyagari et al., 2011).

Thus, the current study considers all three aspects of techno stress (Tarafdar et al, 2011) particularly relevant in sales literature-technology invasion, technology complexity and technology overload as components of techno- stress.

H2: The higher the levels of techno stressors (TC, TO and TI) among salesperson, the higher emotional exhaustion they experience

Emotional Exhaustion and Frontline Deviance Misbehaviour

Prolonged stress among individuals escalates negative emotions and depletes the already low count of resources available to him ultimately resulting in emotional exhaustion (Babakus et al., 1999). Thus, emotional exhaustion primarily represents lack of energy and sensations caused by excessive psychological pressures usually faced by individuals who are in customer-oriented jobs (Singh et al., 1994). Thus, the negative emotional state of an employee because of emotional exhaustion directs counterproductive behaviours resulting in workplace deviance behaviours as a part of the coping process meant to rectify the inconsistencies between the demands and available resources to close the gap between the two (Averill, 1983). Further, the possibility of engaging in such behaviours is high for a salesperson working outside office, having too heavy a workload (in terms of quality and quantity), having high autonomy, and being unsupervised for most of the time in a field.

Because he has fewer resources, he would devote all his time to meet short term goals and concentrate on fulfilling key performance indicators than on building client relationships (Cordes & Dougherty, 1993). This would lead him into acting for his own self good even if it means acting against the organization indulging into undesirable behaviours, sometimes even thefts (Kulas et al., 2007). This coping strategy sometimes induces deviant behaviours.

H3: The higher the levels of emotional exhaustion among salesperson, the greater would be the frontline deviant behavior.

Linking EI, Emotional Exhaustion and Frontline Deviance Misbehaviour

EI is defined as the competency of an individual to identify, regulate and comprehend emotions of self and others (Salovey & Mayer, 1990). Researchers have consistently argued that EI is a more important personality trait than IQ in predicting success in the organizational set up. The selling environment involves higher degree of buyer-seller interactions, and expects customer driven adaptive sales behavior which requires sales executives to constantly adapt their emotions to meet client needs. As per Humpel & Caputi (2001) “emotions form an important part of the overall reaction to stress and burnout”. Therefore, the modulation of emotions by employees helps in maintaining a positive stance ultimately encouraging productive work behaviours. Thus, salespersons with high EI are likely to be less vulnerable to stress induced negative outcomes like job burnout, emotional exhaustion, depression, negative affect and are likely to engage in productive behaviours including less likelihood of indulging into frontline deviant behaviours (Shkoler & Tziner, 2017).

H4: A higher emotional intelligence among salespersons would lead to lower levels of emotional exhaustion

H5: A higher emotional intelligence among salespersons would lead to lower levels of frontline deviance misbehavior

EI in sales literature has widely been recognized for its direct ability to predict sales outcomes such as sales performance but very limited number of empirical studies exist to support this premise. Rather, EI has been well established as a moderator in a number of sales researches. The works of McFarland et al. (2016) based on the appraisal theory of emotions have shown that a salesman’s emotional intelligence can buffer the deleterious effects of role stress on three salesperon’s outcomes—emotional exhaustion, customer-oriented selling, and sales performance. Further, recent research has evinced that trait EI when viewed as a valuable resource in coping with emotions has attenuated stressor-mental well-being related outcomes (Landa et al., 2008). The following hypotheses is proposed:

H6: Emotional intelligence attenuates the relationship between role stress and emotional exhaustion

H7: Emotional intelligence attenuates the relationship between techno- stress and emotional exhaustion

image

Research Methodology Research Background and Data Collection

The sampling frame consisted of salespersons employed in 3 private life insurance firms engaged in direct B2C sales selling insurance instruments in Delhi NCR region. The choice for this sampling unit was the highly stressful nature of their jobs. The firms were selected based on highest market capitalization and sales revenue generated over the last 3 years. A structured questionnaire consisting of self-reported measures was shared via an email with 300 sales executives at randomly selected branches of these insurance firms. Responses were sought anchored on a likert scale of strongly disagree to strongly agree. Out of 217 completed questionnaires received, 12 questionnaires were considered unusable due to missing data. Thus, a response rate of 68% was achieved. The percentage of males was 65% whereas females constituted 35% of the sample, majority of the respondents were relatively young falling in the age group of 18-30 years (33%) and 30-50 years (38%) while remaining belonged to the above 50years group. The mean age of the sample was 39.2 years.

Measures

Role stressors: Role stressors like role ambiguity and role conflict were measured using the short version standardized scale from House, Rizzo, and Lirtzman's (1970). Using the short versions were consistent with the approach adopted in Klein and Verbeke (1999), and in McFarland et al. (2015) and other studies validating the use of short version. Sample items from this scale included, “I work with two or more groups who operate quite differently”, “ I know what my responsibilities are”, etc. Role overload was measured using 5 item scale from Beehr et al., (1976). A example of an item from this scale includes, “My work load is too heavy”.

Techno stressors: Techno based stressors were measured using 9 items adapted from Ragu-Nathan et al. (2008)’s scale representing of technology overload, technology complexity and technology invasion.

Emotional Intelligence: This construct was measured the 14-item scale from using Genos inventory (the concise version) (Gignac, 2010).

Emotional Exhaustion: The MBI inventory by Maslach & Jackson (1981) containing the emotional exhaustion subscale with 9-items was used. This construct was scored on a seven-point frequency scale ranging from “never” to “daily.”

Frontline Deviant Behavior: This scale utilized from Jelinek & Ahearne (2006) included 4-items scored on a seven-point likert scale. An example of an item used for this scale is “I used deceptive tactics while selling to prospects or customers”.

Measurement Model Analysis

Data was analysed using structural equation modelling using the AMOS software version 26.0 utilising the maximum likelihood estimation method. All the relevant constructs of this study were measured from salesperson’s perspective taken from previously validated sales literature. Composite scores were calculated for each construct and all the summed scores were then mean centred to remove any multicollinearity between them (Shieh, 2011). Further to proceed with analysis, firstly all items representing each construct were examined using item to total correlation to account for any inconsistencies contributing to poor fit of the model and item loadings below 0.4 were removed. This resulted in a reduced questionnaire with 31 items in total. All factors loaded significant on corresponding constructs. Next, to assess the reliability of each construct measures, composite reliabilities (CR) and average variances extracted (AVE) were estimated using (Fornell & Larcker’s, 1981). AVE and CR for each construct were found to exceed the acceptable minimum cut off criteria (CR >0.7 and AVE>0.5; & CR>AVE). The composite reliability of all constructs ranged between 0.68 to 0.79 and AVE values lie between 0.58 to 0.63 (Bagozzi & Yi, 1988). Cronbach’s alpha for each of the construct ranged between demonstrating acceptable reliability as presented in Table 1. A confirmatory factor analysis was carried out for the main variables of the study without including the interaction terms (McFarland et al., 2016) resulting in a good model fit. The credibility of chi-square statistics to study fit of the model is highly debatable amongst researchers (Schlermelleh-Engel et al. 2003, Vandenberg 2006), thus the following fit measures were used GFI=0.89, TLI=0.96, CFI=0.970, RMSEA=0.30 all of which demonstrated good fit (Barrett, 2007). No post hoc modification was done as the data fitted well to the proposed model. After establishing goodness of fit for the measurement model, the structural model was put to test with paths indicating the proposed hypotheses. Table 1 demonstrates means, standard deviations, and correlations among the main constructs.

Table 1 Means, Standard Deviations and Correlations
  No. of items Means SD 1 2 3 4 5
1 Role based stress 10 3.60 1.01 (0.935)        
2 Techno based stress 9 3.52 1.06 0.184* (0.928)      
3 Emotional Intelligence 10 3.52 0.897 -0.048 -0.267** (0.823)    
4 Burnout 9 3.68 1.51 0.229** 0.344** -0.212** (0.923)  
5 Deviance 3 4.38 1.73 0.213** 0.191** -0.201** 0.282** (0.812)

Results

After running confirmatory factor analysis, the interaction terms (role-based stress* emotional intelligence given by RBEI and techno-based stress* emotional intelligence given by TBEI) were incorporated in the structural model and overall fit was ascertained. The following indices: GFI= 0.87, TLI=0.95, CFI = 0.965, and RMSEA = 0.0451 indicated acceptable fit of the model. Table 1 represents the structural path coefficients of the proposed model. Hypothesis H1 assuming a positive relationship between role-based stress and emotional exhaustion found acceptability (β = 0.369, t-value=3.69, p<0.01) reflecting that frontline sales executives displayed greater emotional exhaustion with increasing levels of perceived role stressors. Similarly, hypothesis 2 was found to be significant at p<0.01 stating that as technology-based stress increased, emotional exhaustion levels also exacerbate. Further, findings also supported that higher emotional exhaustion would translate into greater deviant misbehaviour among salespersons who foresee such behaviours as a measure to maintain performance and control (Shkoler & Tziner, 2017). Hypothesis 4 representing higher emotionally intelligent executives displayed lesser emotional exhaustion reflected by a negative beta value (β= -0.287, p<0.05) was found to be significant. Consistent with the above, employees with high EI are less likely to indulge in frontline deviant behaviours outside the organization (β = -0.285, t-value= -2.113, p≤0.01). Hence, H5 also found support. Finally incorporating interaction terms given by RBEI and TBEI in the model and testing the paths from these interaction terms to burnout, it was found that emotional intelligence was not found to moderate the relationship between role-based stress and emotional exhaustion (H6) whereas, EI mitigated the ill effects of technology created stress on emotional exhaustion with β = -0.106, p<0.01 thus moderating this relationship (H7). Overall, findings of this study supported H1-H3 hypotheses representing the direct effects of stressors on emotional exhaustion and of emotional exhaustion on frontline deviance misbehaviour. Results also reflect upon the importance of emotional intelligence as a necessary coping tool among sales professionals.

Discussion

By examining the negative side of the coping theory, this research is a modest attempt of the authors to understand the negative behaviors that emerge out of a disturbed mental state due to prolonged stress experienced by salespeople. The prevalence of mis selling tactics and unethical behaviors among salespeople in the Indian insurance sector calls for a deeper investigation into the factors in their work environment which drive such deviant behaviors. This research lends credibility to Low et al., (2001) study that customer representatives and sales executives in boundary spanning positions are highly susceptible to emotional exhaustion. This study asserts that frontline deviant behaviors are a by-product of the emotional status of the employee whereas emotional intelligence as a coping resource moderates the effect of stressors on emotional exhaustion, it should be viewed as a powerful tool that can weaken the stress induced negative outcomes among them and enhance their ability to deal with cynicism along with exercising reasonable judgment while they act. It should be noted that emotional exhaustion is a more relevant construct for boundary spanners in face-to-face selling involving high degree of customer contacts and since most of their time is spent on field, it is obvious that negative behaviors in the form of deviance may be directed towards customers to achieve equity within their own mindset. A similar study reiterated this fact that “a dissatisfied employee turns to deviance misbehaviors as a remedy when emotional exhaustion becomes too big a reservoir of frustration to maintain internally” (Yoo & Frankwick, 2013).

Organizations should aims at reducing ambiguity, conflicts arising out of a salesperson’s job role by ensuring clearly defined tasks, expectations from his/her role, communicating clear policies and programs, etc. At the same time, they should aim to ensure that salespeople recruited are ready to handle technical aspects of their work efficiently without being felt burdened by it. This would reduce role-based stress and techno-based stress which are substantial aspects of their work and may lower the risks of emotional exhaustion which has serious implications for organizations, marketing environment, managers, and researchers.

Limitations

Although this research draws conclusions based on causal relationships established based on rigorous literature review yet other reasons for causation cannot and should not be ruled out. This cross-sectional research was carried out among sales executives from 3 private insurance firms which limits its generalization ability to overall industry. It may call out for longitudinal studies to draw more reliable inferences and requires more diverse samples and a larger sample size. Further, sales executives might not report true data on a measure like frontline deviance behaviour which further weakens the generalizing ability of this study.

References

  1. Averill, J.R. (1983). Studies on anger and aggression: implications for theories of emotion. American Psychologist, 38(11), 1145.
  2. Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 831-858.
  3. Babakus, E., Cravens, D.W., Johnston, M., & Moncrief, W.C. (1999). The role of emotional exhaustion in sales force attitude and behavior relationships. Journal of the Academy of Marketing Science, 27(1), 58-70.
  4. Bagozzi, R.P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
  5. Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual differences, 42(5), 815-824.
  6. Beehr, T.A., Walsh, J.T., & Taber, T.D. (1976). Relationships of stress to individually and organizationally valued states: Higher order needs as a moderator. Journal of applied psychology, 61(1), 41.
  7. Boles, J.S., Johnston, M.W., & Hair Jr, J.F. (1997). Role stress, work-family conflict and emotional exhaustion: Inter-relationships and effects on some work-related consequences. Journal of Personal Selling & Sales Management, 17(1), 17-28.
  8. Buttle, F.A. (1993). Selling services: a contingency model. Journal of services marketing.
  9. Cheung, F.Y.L., & Tang, C.S.K. (2012). The effect of emotional dissonance and emotional intelligence on work–family interference. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 44(1), 50.
  10. Cordes, C.L., & Dougherty, T.W. (1993). A review and an integration of research on job burnout. Academy of management review, 18(4), 621-656.
  11. Day, A., Scott, N., & Kelloway, E.K. (2010). Information and communication technology: Implications for job stress and employee well-being. In New developments in theoretical and conceptual approaches to job stress. Emerald Group Publishing Limited.
  12. Fatima, Z. (2021). Salesforce control systems: a review of studies. International Journal of Business Excellence, 23(2), 188-225.
  13. Fogarty, T.J., Singh, J., Rhoads, G.K., & Moore, R.K. (2000). Antecedents and consequences of burnout in accounting: Beyond the role stress model. Behavioral Research in Accounting, 12, 31-68.
  14. Folkman, S., Lazarus, R.S., Gruen, R.J., & DeLongis, A. (1986). Appraisal, coping, health status, and psychological symptoms. Journal of personality and social psychology, 50(3), 571.
  15. Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal        of Marketing Research, 18(1), 39-50.
  16. Gignac, G. (2010). Seven-factor model of emotional intelligence as measured by Genos EI: A confirmatory factor analytic investigation based on self-and rater-report data. European Journal of Psychological Assessment, 26(4), 309.
  17. Hobfoll, S.E. (1989). Conservation of resources: a new attempt at conceptualizing stress. American Psychologist, 44(3), 513.
  18. House, R.J., & Rizzo, J.R. (1972). Role conflict and ambiguity as critical variables in a model of organizational behavior. Organizational Behavior and Human Performance, 7(3), 467-505.
  19. Humpel, N., Caputi, P., & Martin, C. (2001). The relationship between emotions and stress among mental health nurses. Australian and New Zealand Journal of Mental Health Nursing, 10(1), 55-60.
  20. Jelinek, R., & Ahearne, M. (2006). The enemy within: Examining salesperson deviance and its determinants. Journal of Personal Selling & Sales Management, 26(4), 327-344.
  21. Klein, D.J., & Verbeke, W. (1999). Autonomic feedback in stressful environments: How do individual differences in autonomic feedback relate to burnout, job performance, and job attitudes in salespeople?. Journal of Applied Psychology, 84(6), 911.
  22. Landa, J.M.A., López-Zafra, E., Martos, M.P.B., & del Carmen Aguilar-Luzon, M. (2008). The relationship between emotional intelligence, occupational stress and health in nurses: a questionnaire survey. International journal of nursing studies, 45(6), 888-901.
  23. Lazarus, R.S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer publishing company.
  24. Lewin, J.E., & Sager, J.K. (2007). A process model of burnout among salespeople: Some new thoughts. Journal of Business Research, 60(12), 1216-1224.
  25. Low, G.S., Cravens, D.W., Grant, K., & Moncrief, W.C. (2001). Antecedents and consequences of salesperson burnout. European Journal of Marketing.
  26. Mariadoss, B.J., Milewicz, C., Lee, S., & Sahaym, A. (2014). Salesperson competitive intelligence and performance: The role of product knowledge and sales force automation usage. Industrial Marketing Management, 43(1), 136-145.
  27. Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of organizational behavior, 2(2), 99-113.
  28. McFarland, R.G., Rode, J.C., & Shervani, T.A. (2016). A contingency model of emotional intelligence in professional selling. Journal of the Academy of Marketing Science, 44(1), 108-118.
  29. Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50.
  30. Ragu-Nathan, T.S., Tarafdar, M., Ragu-Nathan, B.S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Information Systems Research, 19(4), 417-433.
  31. Rizzo, J.R., House, R.J., & Lirtzman, S.I. (1970). Role conflict and ambiguity in complex organizations. Administrative Science Quarterly, 150-163.
  32. Ryding, D. (2010). The impact of new technologies on customer satisfaction and business to business customer relationships: Evidence from the soft drinks industry. Journal of Retailing and Consumer Services, 17(3), 224-228.
  33. Salovey, P., & Mayer, J.D. (1990). Emotional intelligence. Imagination, cognition and personality, 9(3), 185-211.
  34. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
  35. Sharma, R.R. (2002). Executive burnout: contribution of role related factors. Indian Journal of Industrial Relations, 81-95.
  36. Shieh, G. (2011). Clarifying the role of mean centring in multicollinearity of interaction effects. British Journal of Mathematical and Statistical Psychology, 64(3), 462-477.
  37. Shkoler, O., & Tziner, A. (2017). The mediating and moderating role of burnout and emotional intelligence in the relationship between organizational justice and work misbehavior. Revista de Psicología del Trabajo y de las Organizaciones, 33(2), 157-164
  38. Shkoler, O., & Tziner, A. (2017). The mediating and moderating role of burnout and emotional intelligence in the relationship between organizational justice and work misbehavior. Revista de Psicología del Trabajo y de las Organizaciones, 33(2), 157-164.
  39. Singh, J., Goolsby, J.R., & Rhoads, G.K. (1994). Behavioral and psychological consequences of boundary spanning burnout for customer service representatives. Journal of Marketing Research, 31(4), 558-569.
  40. Spector, P.E., & Fox, S. (2005). The Stressor-Emotion Model of Counterproductive Work Behavior.
  41. Speier, C., & Venkatesh, V. (2002). The hidden minefields in the adoption of sales force automation technologies. Journal of Marketing, 66(3), 98-111.
  42. Swimberghe, K., Jones, R.P., & Darrat, M. (2014). Deviant behavior in retail, when sales associates “Go Bad”! Examining the relationship between the work–family interface, job stress, and salesperson deviance. Journal of Retailing and Consumer Services, 21(4), 424-431.
  43. Tarafdar, M., Tu, Q., Ragu-Nathan, B.S., & Ragu-Nathan, T.S. (2007). The impact of technostress on role stress and productivity. Journal of management information systems, 24(1), 301-328.
  44. Tomaka, J., Blascovich, J., Kelsey, R.M., & Leitten, C.L. (1993). Subjective, physiological, and behavioral effects of threat and challenge appraisal. Journal of personality and social psychology, 65(2), 248.
  45. Trist, E.L. (1981). The evolution of socio-technical systems (Vol. 2). Toronto: Ontario Quality of Working Life Centre.
  46. Vandenberg, R.J. (2006). Introduction: statistical and methodological myths and urban legends: where, pray tell, did they get this idea?.
  47. Verbeke, W., Dietz, B., & Verwaal, E. (2011). Drivers of sales performance: a contemporary meta-analysis. Have salespeople become knowledge brokers?. Journal of the Academy of Marketing Science, 39(3), 407-428.
  48. Yip, B., Rowlinson, S., & Siu, O.L. (2008). Coping strategies as moderators in the relationship between role overload and burnout. Construction Management and Economics, 26(8), 871-882.
  49. Yoo, J., & Frankwick, G.L. (2013). Exploring the impact of social undermining on salesperson deviance: An integrated model. Journal of Personal Selling & Sales Management, 33(1), 79-90.
Get the App