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Organizational climate, that is, the atmosphere surrounding an organization, unites features with individual, organizational, and environmental characteristics that affect the behaviors of individuals within the organization. Burnout is accepted as a syndrome that often occurs in people who work together with others. Faculty members in universities are potential burnout candidates due to their relationships with many students, employees, and administrators. To reduce burnout of the faculty members, it is crucial to maintain a healthy organizational climate. It is also projected that discrepancies in organizational climate can manifest differently between public and private universities. So, the purpose of this study is to examine the effect of organizational climate on the burnout of faculty members at both state and private universities. By using the survey method, 984 responses were collected from faculty members. A covariance-based structural equation modeling was constructed to test the reliability and validity of both the measurement and the structural model. The results of the study supported the hypotheses mostly and indicated that all dimensions of organizational climate negatively influenced faculty members’ emotional exhaustion. While the balanced workload, clarity of task, cohesion, and the ethical dimensions within the organizational climate produced a negative effect on the depersonalization of faculty members, the lack of clarity of task and ethical dimensions contributed negatively to the diminished personal accomplishment. In addition, the study demonstrated that state university faculty members having cohesion dimension of organizational climate were less likely to be exhausted emotionally, whereas cohesion among private university faculty members negatively influenced the depersonalization. Theoretical and practical implications regarding organizational climate dimensions and burnout levels of faculty members were discussed. Keywords organizational climate, burnout, faculty member, state universities, and private universities Faculty members, as teachers of higher education, are Introduction also exposed to burnout. Their relationships with many stu- Burnout is described as “a psychological syndrome that is dents, staff, and administrators make them prime candidates characterized as a negative emotional reaction to one’s job as for burnout (Blix et al., 1994). They also tackle with many a consequence of extended exposure to a stressful work envi- issues including “pressures, conflicts, demands, and too few ronment” (Marek et al., 2017; Maslach et al., 2001; Maslach emotional rewards, accomplishments, and successes” & Jackson, 1984; Yildirim & Dinc, 2019). According to this (Harrison, 1999, p. 26), as well as having unrealistic goals definition, employees who work in stressful jobs are more and expectations which are set for them without their input likely to display higher levels of burnout. In addition, burn- and becoming frustrated in achieving professional growth out has been observed in individuals who have high ideals and many interactions with other people (Evers et al., 2005). American University of the Middle East, Kuwait One of the most stressful professions is frequently cited as Arthur J, Bauernfeind College of Business, Murray State University, KY, teaching (Kyriacou, 2001; Naghieh et al., 2015) with the USA need for intensely personal interactions with people, espe- Corresponding Author: cially students and other teachers who also suffer from high Muhammet Sait Dinc, Department of Human Resource Management, stress, which creates a higher level of burnout, absenteeism, American University of the Middle East, P.O. Box: 220 Dasman, 15453, and eventual exit from the teaching profession (Betoret, Kuwait. 2006; Chang, 2009; Jepson & Forrest, 2006). Email: Muhammet.Dinc@aum.edu.kw Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open (Lackritz, 2004). Faculty members who encounter the issues 2018). This has newly created a competitive environment above are more likely to have burnout; those with higher lev- between private and state universities, causing new chal- els of burnout can display their intention toward turnover as lenges to universities as well as to academic staff. While pri- well as poor job performance, and absenteeism (Blix et al., vate universities have demanded that their faculties produce 1994; Singh et al., 1998). So, burnout is a losing situation productivity in research as well as provide quality education within faculty members as well as universities as a whole. and participation in administrative duties such as committee One of the countries which have been suffering from burn- memberships, faculty members in state universities have out is Turkey. According to a study that included workers from been exposed to increased teaching and service load demands 35 European countries, the highest burnout scores among the (Demir et al., 2015). These demands within both private and non-EU countries were found in Turkey (Schaufeli, 2018). state universities have the potential to damage “personal and The employees that suffered most from burnout in Turkey professional competencies of faculty members, reduce their have been teachers and academic staff. In the literature of edu- productivity and lead to burnout experiences” (Sabagh et al., cation, recent studies that have focused on the burnout of 2018, p. 132). The potential implications can produce haz- teachers and faculty members show that one out of three ardous effects on faculty members’ performances, student teachers experience burnout syndrome, with 10% leaving this learning, and, finally, institutional productivity (M. Byrne profession every year (Can & Tiyek, 2015). Due to these seri- et al., 2013). In this regard, investigating the factors prevent- ous effects of burnout, it has become crucial to research meth- ing the likelihood of faculty burnout at both private and state ods that reveal insights on how to reduce or prevent the universities has been crucial. OC is one of these factors. probability of burnout and to identify the main factors of fac- Thus, the purpose of this study is to explore the impact of OC ulty burnout in Turkey. While there is ample research examin- dimensions on the burnout levels of faculty members within ing the burnout, literature focusing on faculty burnout within both state and private universities in Turkey. universities in Turkey has been severely limited (Okray, 2018). This article is structured in the following manner. Much of this research has concerned factors influencing burn- Following a review of the literature on burnout and OC, out of faculty members, such as age, gender, academic title, hypotheses are proposed, based on the relevant literature. teaching load, and marital status (Demir et al., 2015; Kulavuz- After the “Research Methodology” section describes the sur- Önal & Tatar, 2017), personal characteristics and emotional vey administration and systems used to measure variables in intelligence (Arslan & Acar, 2013; Taşlıyan et al., 2014), orga- the study, the results of the model are presented. Finally, the nizational citizenship behavior and organizational silence discussion section explains the theoretical and managerial (Çankır, 2017; Kahya, 2015). As Maslach and Jackson (1981) implications of the study, reveals the limitations, and offers proposed that the primary reasons for burnout were workplace suggestions for future research. factors rather than the personal characteristics exhibited by employees, the focus of this study has been placed on the main Theoretical Framework and workplace factor that might reduce the burnout of academi- Hypotheses Development cians: organizational climate. Organizational climate (OC) is defined as “a set of measur- Burnout able properties of the work environment, perceived directly or indirectly by the people who live and work in this environment Freudenberger first described the concept of burnout in 1974 and assumed to influence motivation and behavior” (Litwin & as “a state of exhaustion that results from failure, attrition, Stringer, 1968, p. 1). OC is the atmosphere that surrounds an loss of energy and power, or unfulfilled wishes on human organization. This atmosphere affects the moral levels of the internal resources” (Freudenberger, 1974, p. 160). For the last organization members as well as the intensity of their good- 20 years, many researches have been done in different busi- will, feeling, and belonging. A positive OC in universities ness areas. The most common definition of burnout is the enables faculties to be satisfied with their jobs, increase their definition made by Maslach and Jackson (1986), which per- productivity, and thus prevent their burnout. In this regard, ceives burnout as a three-dimensional concept. These three there has been a scarcity of research concerning the relation- dimensions are named as emotional exhaustion, depersonali- ship between the dimensions of OC and the consequent burn- zation, and personal accomplishment. Emotional exhaustion out level. Also lacking are empirical studies exploring these refers to the depletion of emotional and physical resources relationships at state and private universities separately. where the individual feels a lack of the necessary energy to State universities have been considered expert at provid- perform the work. Depersonalization refers to an uncaring ing higher education through experienced academics for the and negative attitude toward different aspects of the job, and last decade, but the number of private universities that pro- related to the lack of connection with the job at emotional and vide better educational opportunities and infrastructures has cognitive level. Personal accomplishment refers to feelings of increased enormously. The increased demand by students, incompetency, lack of achievement, and productivity at work. the deficiency of state universities regarding research and Maslach and Jackson (1984) suggest that the dimensions are teaching are some of the reasons for this upsurge (Dinc, not dependent on each other and they could occur at any time. Dinibutun et al. 3 Reports in the literature state that sources of stress are Cohesion refers to the level of mutual trust and respect generally related to burnout in occupations that serve the between employees and management (Koys & DeCotiis, public (Maslach & Jackson, 1981). It has been observed that 1991). Respect combined with friendly relations among individuals with high ideals who also have many interactions employees, both inside and outside an organization, with other people suffer from burnout (Evers et al., 2005). expresses the degree of mutual support and assistance they Faculty members at universities that have a relationship with provide. a large number of students, staff, and administrators are Ethics refers to the way in which official and written ethi- prime candidates for burnout, and those faculty members cal rules, which are valid within an organization, expresses who sustain higher levels of burnout have more tendency to how sensitively the management complies with these rules change their jobs (Blix et al., 1994). To prevent and reduce and sanctions that are to be applied to their employees if they burnout, understanding its determinants is very important do not follow them. This aspect of climate assists employees (Lambert et al., 2013). However, in the last three decades, an to identify ethically appropriate actions within an organiza- integrated model of burnout has described the dimensions of tion (Koys & DeCotiis, 1991). the relationships between the potential antecedents and out- Participation expresses the relationship between manager comes of burnout and burnout with its dimensions (B. M. and employee in decision-making and a transparent and flex- Byrne, 1994). A study that was conducted in the context of ible discussion environment (Eberhardt & Shani, 1984). education suggested that burnout studies should concentrate solely on the impact of environmental factors (Friedman, Theoretical Foundation 1991). In addition, burnout is the result of the interaction between the work environment and the individual; it has The Job Demands–Resources theory (Demerouti et al., 2001) been discussed in the prior burnout literature that the solu- has become one of the leading approaches in predicting ante- tions to burnout should be sought in the social environment cedents of burnout. According to Demerouti et al. (2001), job of the workplace (Leiter & Maslach, 1988; Maslach, 1999). demands are social, organizational, and physical aspects of Therefore, the focus of this study as one of these work- the job that require continuous mental or physical efforts related environmental factors is the OC. and, therefore, are related to potential psychological or phys- ical problems such as exhaustion. To the contrary, job resources are aspects of an occupation that (1) diminish job Organizational Climate demands at associated mental or physical costs, (2) stimulate OC “represents the worker’s perceptions of his objective an employee’s development, and (3) assist in achieving work situation, including the characteristics of the organi- work-related goals (Demerouti et al., 2001, p. 501). The Job zation he works for and the nature of his relationships with Demands–Resources theory suggests that “excessive job other people while doing his job” (Churchill et al., 1976, p. demands lead to strain and burnout that, in turn, leads to poor 324). There are many studies in the literature concerning performance. Burnout is, therefore, expected to fully or par- OC that concentrate on the shared and learned perceptions tially mediate the relationship between job demands and that arise from formal and informal organizational poli- maladaptive outcomes” (Demerouti et al., 2001; Sabagh cies, practices, and procedures (Sparrow & Gaston, 1996). et al., 2018). This mediation process is designated as the The following variables regarding OC are investigated in health impairment process in the Job Demands–Resources this study: managerial competence, balanced workload, theory. It suggests that lack of resources will cause a higher clarity of task, cohesion among coworkers, ethics, and level of exhaustion and burnout, while an abundance of job participation. resources is presumed to decrease the negative effect of job Managerial competence includes the attitude and behav- demands on burnout levels (Demerouti et al., 2001; Sabagh iors shown by managers toward employees, which includes et al., 2018; Schaufeli & Taris, 2014). Empirical studies keeping their promises and communicating with their strongly support the suggestion that job demands (e.g., work employees (Rogg et al., 2001). overload, control, value) and job resources (e.g., participa- Balanced workload relates to the extent to which a suffi- tion, supervisor support) predict burnout (Maslach & Leiter, cient amount of time is required by employees to perform 1997; Schaufeli & Taris, 2014). In the present study, the Job their tasks in accordance with predetermined performance Demands–Resources theory is relied on as the guiding standards (Koys & DeCotiis, 1991). The ability of employ- framework to explain the relationship between OC dimen- ees to work without feeling time constraints, allowing suffi- sions and faculty burnout levels. cient time to solve problems related to their work and the required volume of work combined, creates the weight of Relationship Between Organizational Climate their workload. and Burnout Clarity of Task means that employees know exactly what is expected of them concerning their jobs (Eberhardt & Several studies in the literature have supported the relation- Shani, 1984). ship between OC and burnout (Cordes et al., 1997; Dinc 4 SAGE Open et al., 2020; Kaya et al., 2010; Lubranska, 2011; Maidaniuc- Hypothesis 2a (H2a): Balanced Workload has a signifi- Chirila & Constantin, 2017; Martinussen et al., 2007; cant negative effect on Emotional Exhaustion. Yildirim & Dinc, 2019; Vallen, 1993). A strong correlation Hypothesis 2b (H2b): Balanced Workload has a signifi- between OC and burnout was described in a study conducted cant negative effect on Depersonalization. on the service sector (Lubranska, 2011). A recent study also Hypothesis 2c (H2c): Balanced Workload has a significant discovered that OC is strongly and negatively correlated negative effect on Diminished Personal Accomplishment. with burnout in public organizations (Pecino et al., 2019). With regard to studies focusing on OC dimensions and job Clarity of Task concerns the knowledge by employees con- burnout levels, Cordes et al. (1997) showed that a lack of the cerning expectations of their job performance. Lack of clar- subordinate-manager relationship as well as an attempt to ity regarding job performance has been found to result in achieve success in a job with insufficient resources, inade- emotional exhaustion and depersonalization (Cordes et al., quate management, and coordination problems, all result in 1997; Kim, 2008). Lack of task clarity and role ambiguity emotional exhaustion and depersonalization. In another were reported to lead to lower perceived accomplishment study, it was demonstrated that stressful relationships with and greater depersonalization within the university environ- supervisor increased emotional exhaustion (O’driscoll & ment (Ghorpade et al., 2011). For instance, in a large-scale Schubert, 1988). In the context of higher education, research- study of 1,067 academics in Netherland, lack of task and role ers found that OC is negatively connected to the burnout of clarity was shown to predict greater emotional exhaustion faculty members (Anbar & Eker, 2008; Maidaniuc-Chirila & (Van Emmerik, 2002). These previous findings suggest the Constantin, 2016; Taka et al., 2016). For example, in a study following hypothesis: of 300 academics in China (Zhong et al., 2009), the role of management predicted total burnout scores. Also, findings in Hypothesis 3a (H3a): Clarity of Task has a significant a study conducted on academic staff in South Africa showed negative effect on Emotional Exhaustion. that higher levels of support from one’s superiors predicted Hypothesis 3b (H3b): Clarity of Task has a significant lower levels of reported burnout (Tytherleigh et al., 2008). negative effect on Depersonalization. Based on the literature discussed above, the following Hypothesis 3c (H3c): Clarity of Task has a significant hypothesis is posited: negative effect on Diminished Personal Accomplishment. Hypothesis 1a (H1a): Managerial Competence has a sig- Cohesion is defined as the level of mutual trust and respect nificant negative effect on Emotional Exhaustion. between employees and management. Cohesion can only be Hypothesis 1b (H1b): Managerial Competence has a sig- established within a university if faculty members and man- nificant negative effect on Depersonalization. agement mutually support each other. A lack of cohesion Hypothesis 1c (H1c): Managerial Competence has a among colleagues results in emotional exhaustion and deper- significant negative effect on Diminished Personal sonalization (Cordes et al., 1997) and predicts total burnout Accomplishment. scores (Zhong et al., 2009). Findings from the studies con- ducted in South African and Dutch universities noted that Balanced workload is the extent to which sufficient time is greater support from one’s organization as well as one’s col- provided to faculty members to perform their tasks, accord- leagues reduced reported burnout by academic staff ing to predetermined performance standards. The workload (Tytherleigh et al., 2008; Van Emmerik, 2002). Drawing on required at a university represents the relative amount of this literature, the following hypotheses are posited: time which is dedicated to teaching, research, service, and professional development of faculty members (Gonzalez & Hypothesis 4a (H4a): Cohesion has a significant nega- Bernard, 2006). Studies in the literature found that high tive effect on Emotional Exhaustion. workload was a positive predictor of faculty burnout Hypothesis 4b (H4b): Cohesion has a significant nega- (Barkhuizen et al., 2014; Navarro et al., 2010). For exam- tive effect on Depersonalization. ple, in a study conducted with 265 university faculty mem- Hypothesis 4c (H4c): Cohesion has a significant nega- bers in the United States, the amount of burnout showed a tive effect on Diminished Personal Accomplishment. significant correlation to the number of students taught, the time invested in various activities, and numerous student The aspect of ethics within the OC is an instrument that evaluations (Lackritz, 2004). Another study result demon- shapes the ethical nature of the organization by creating strated that faculty members with a more balanced work- norms and expectations guiding behavior (Schneider & load, experiencing lighter teaching loads, reported Reichers, 1983). Therefore, this climate dimension helps significantly lower levels of emotional exhaustion in com- members to determine ethically appropriate actions within parison with those with heavy teaching loads (Gonzalez & an organization. In the literature, the relationships between Bernard, 2006). Based on the above literature, the follow- organizational ethics and employees’ outcomes have become ing hypotheses are suggested: fundamental issues (Dinc & Plakalovic, 2016; Kaya et al., Dinibutun et al. 5 2010). Research findings showed that employees who felt stressed as a result of insincerity within organizational values combined with the conflict of ethical understandings, in turn, were led toward burnout (Maslach et al., 2012; Maslach & Leiter, 1997). Based on this literature, the following hypoth- esis is postulated: Hypothesis 5a (H5a): Ethics has a significant negative effect on Emotional Exhaustion. Hypothesis 5b (H5b): Ethics has a significant negative effect on Depersonalization. Hypothesis 5c (H5c): Ethics has a significant negative effect on Diminished Personal Accomplishment. Participation refers to the working relationship between Figure 1. Proposed model. managers and employees within the decision-making pro- cess. Participation in decision-making influences the possi- when the associations are hypothetical or not observable bility of burnout, resulting in an increased sense of personal directly (Williams et al., 2009). CB-SEM follows a maxi- accomplishment in particular (O’driscoll & Schubert, 1988). mum likelihood estimation by reproducing a covariance In the higher education context, it was found that participa- matrix to minimize the difference between the observed and tion in decision-making predicted greater perceived accom- the estimated covariance matrix without focusing on the plishment (Pretorius, 1994). Drawing on this literature, the explained variance (Hair et al., 2011). CB-SEM offers many following hypothesis is posited: benefits compared with first generation statistical approaches such as regression analysis, which do not directly allow the Hypothesis 6a (H6a): Participation has a significant neg- assessment of measurement characteristics, so that the latent ative effect on Emotional Exhaustion. variables must be converted to the average of individual Hypothesis 6b (H6b): Participation has a significant neg- measures. Therefore, CB-SEM-based approaches include the ative effect on Depersonalization. evaluation of individual measures (Astrachan et al., 2014; Hypothesis 6c (H6c): Participation has a significant neg- Hair et al., 2010). ative effect on Diminished Personal Accomplishment. The proposed model illustrated in Figure 1 shows the proposed association between OC and Burnout. The latent Private universities differ from state universities in terms of variable, OC, had six subdimensions, including Managerial infrastructures and educational opportunities. The demands Competence, Balanced Workload, Clarity of Task, and expectations of administrations of private universities Cohesion, Ethics, and Participation, while the latent vari- concerning research productivity and providing quality edu- able, Burnout, had three subdimensions including cation also differ from state universities. Due to these differ- Emotional Exhaustion, Depersonalization, and Diminished ences, the perceptions of academic staff employed in private Personal Accomplishment. and state universities regarding their organizations have dif- The summary of the sample, Exploratory Factor Analysis, fered. Several studies have shown that the perceptions of fac- Confirmatory Factor Analysis, and the Structural Equation ulty members working within private and state universities Modeling for testing the hypothesis are described in the differ significantly regarding the dimensions of their learn- methodology section. ing organization (Balay, 2012; Dinc, 2018). Based on the literature, the following hypothesis is suggested: Research Design and Instrumentation Hypothesis 7 (H7): The impact of Organizational Climate on Burnout Syndrome differs according to the type of A three-page questionnaire with three sections was used to university. collect data for the study. The first section included questions about OC adapted from the scales developed by Rogg et al. (2001), Koys and DeCotiis (1991), and Eberhardt and Shani Research Methodology (1984). The second section contained questions on burnout, A covariance-based structural equation modeling (CB-SEM) adapted from the Maslach Burnout Inventory developed by was employed to test the proposed hypotheses. CB-SEM Maslach and Jackson (1981). It included three components: methodology, which is a multivariate analytical methodol- “emotional exhaustion,” ‘personal accomplishments,’ and ogy, can be used to test and estimate the complex causal “depersonalization.” The items of these variables are shown associations among the latent variables simultaneously even in Table 1. Finally, the last section consisted of demographic 6 Table 1. Measurement Table. Organizational climate Source Cronbach’s alpha Managerial competence Rogg et al. (2001) (α = .89) 1. “My manager is easy to talk to about job related problems” 2. “My manager backs me up and lets me learn from my mistakes” 3. “Managers follow through on commitment” 4. “Managers clearly communicate work objectives and responsibilities” 5. “Managers take action on new ideas provided by employees” 6. “Work is fairly distributed to employees” 7. “Employees trust each other” 8. “Managers consistently treat everyone with respect” Balanced workload Koys & DeCotiis (1991) (α = .94) 9. “I always seem to have plenty of time to get everything done” 10. “I have just the right amount of time and workload to do everything well” 11. “I do not feel that I am always working with time constraints on my job” 12. “My coworkers and I always find time for long-term problem solving” Clarity of task Eberhardt & Shani (1984) (α = .86) 13. “On my job I have no doubt of what is expected of me” 14. “There is not any uncertainty in my job” 15. “I clearly know what level of work performance is expected from me in terms of amount, quality, and timeliness of output” 16. “This institution always provides necessary resources to be successful for employees” Cohesion Koys & DeCotiis (1991) (α = .92) 17. “Employees pitch in to help each other out” 18. “Employees tend to get along with each other” 19. “Employees take a personal interest in one another” 20. “There is a lot of team spirit among employees” Ethics Koys & DeCotiis (1991) (α = .95) 21. “Our institution has a formal, written code of ethics” 22. “Our institution enforces a code of ethics” 23. “Our institution has policies regarding ethical behavior” 24. “In our institution, unethical behavior is not tolerated” 25. “Behaviors that result in personal gain but do not comply with ethical behavior are condemned” 26. “Behaviors that result in institutional gain but do not comply with ethical behavior are condemned” (continued) 7 Table 1. (continued) Organizational climate Source Cronbach’s alpha Participation Eberhardt & Shani (1984) (α = .90) 27. “The decisions at this institution are taken in an open discussion environment in which the employees also participate” 28. “The decision-making approach in this institution is more flexible than centralized” 29. “While making decisions, employees’ concerns, and opinions are also evaluated” 30. “In this institution, importance is given to human relations and teamwork” Burnout Emotional exhaustion Maslach & Jackson (1981) (α = .89) 1. “I feel emotionally drained by my work” 2. “I feel used up at the end of the workday” 3. “I feel fatigued when I get up in the morning and have to face another day on the job” 4. “Working with people all day is really a strain for me” 5. “I feel burned out by my work” 6. “I feel frustrated by my job” 7. “I feel I’m working too hard on my job” 8. “Working with people directly puts too much stress on me” 9. “I feel like I’m at the end of my rope” Depersonalization Maslach & Jackson (1981) (α = .77) 10. “I feel I treat some recipients as if they were impersonal ‘objects’” 11. “I’ve become more callous toward people since I took this job” 12. “I worry that this job is hardening me emotionally” 13. “I don’t really care what happens to some recipients” 14. “I feel recipients blame me for some of their problems” Personal accomplishment Maslach & Jackson (1981) (α = .74) 15. “I can easily understand how my recipients feel about things” 16. “I deal very effectively with the problems of my recipients” 17. “I feel I’m positively influencing other people’s lives through my work” 18. “I feel very energetic” 19. “I can easily create a relaxed atmosphere with my recipients” 20. “I feel exhilarated after working closely with my recipients” 21. “I have accomplished many worthwhile things in this job” 22. “In my work, I deal with emotional problems very calmly” 8 SAGE Open questions such as age group, gender, marital status, academic The summary of the demographic variables is shown in title, institution type, and duration of employment. Table 2. The results indicated that 57% of the participants The items of the constructs were in English. Therefore, were female, and 43% were male; 61.4% were married; the survey questions in the English language were translated 56.3% worked in a private university, 43.7% worked in a into the Turkish language using a back-translation methodol- state university; 7.7% were associate professors, 16.9% were ogy (Brislin, 1986). The survey items were investigated by full professors, 21.2% were assistant professors; almost 6% experts and professors in this field before distribution to the were younger than 25 years old, and 25.4% were older than participants to ensure the content and the face validity of the 45; and finally, 40.1% had between 1 and 5 years of experi- constructs. All items were measured on a 5-point Likert-type ence, while 10.8% had more than 20 years of experience. scale, where one represents strongly disagree, while five rep- resents strongly agree. The final form of the survey was then Exploratory Factor Analysis distributed. Before testing the hypothesis, the items were subjected to Exploratory Factor Analysis (EFA) to find the underlying Sample and Data Collection Procedure factor structures. To extract the factors, Principal Axis The study targeted academicians from private and state uni- Factoring (PAF) analysis as the factor extraction method and versities in Istanbul, Turkey. The total number of faculty Promax as the factor rotation were employed. The EFA members in Istanbul was retrieved from the Council of results are provided in Table 3. Initially, 52 items from the Higher Education, which lists 6,572 academicians within adapted scales were subject to EFA, from which nine items private universities and 12,656 academicians within state were eliminated from the analysis due to low or cross factor universities. The total number of academic staff in Istanbul loadings. As a result, 43 items were left for further analysis, was 19,228 (Council of Higher Education, 2019). with seven items measuring Personal Accomplishment, six The survey instrument was developed using an online sur- items measuring Ethics, Managerial Competence, and vey tool (Survey Gizmo); the web link of the survey was Emotional Exhaustion, four items measuring Cohesion, distributed to all academic members in the sample via e-mail. Balanced Workload, and Depersonalization, and three items As the target population was huge, it was not possible to measuring Participation and Clarity of Task. In addition, the deliver the surveys by hand to faculty members and collect percent of total variance accounted for each factor ranged them back again. Therefore, the convenience sampling between 1.59 and 34.08, with Ethics being the highest and approach, which is a common nonprobability approach Clarity of Task being the lowest. The nine factors together (Vehovar et al., 2016), was used to collect data. The survey accounted for 61.02%, which is higher than the recom- was sent to 12,509 participants; 7,816 participants were from mended threshold value of 60% (Hair et al., 2010; Hinkin, state universities, and 4,693 participants were from private 1998). Also, the Eigenvalues of the constructs after rotation universities. The e-mail addresses of the academic staff were ranged between 4.03 and 10.35. The descriptive statistics of accessed from the websites of the respective universities. the items with Mean and Standard Deviations are also pro- These members were sent a follow-up notice electronically 2 vided in the same table. Moreover, the Kaiser–Meyer–Olkin weeks later. After approximately 4 weeks, a second follow- (KMO) test statistics revealed that the sample data was ade- up was sent to participants via e-mail. When respondents quate for the EFA (KMO = 0.951), while Bartlett’s Test of completed the online survey, they were able to click on a Sphericity test statistics indicated that the variables of inter- button labeled “Submit Responses.” A note of thanks then est sufficiently related to each other to enable running the appeared on the screen, and the responses were registered in EFA (Bartlett’s Test of Sphericity = 28338.92, df = 903, p the appropriate data file. The participants were required to value = .001). The convergent validity was met, as the items answer all questions: They were not allowed to move to the within each of the extracted nine factors were highly associ- next question if the current one was not answered. As a ated. In addition, the discriminant validity was satisfied as result, there were no missing values in the obtained sample the factors were distinct and uncorrelated where the items data set. A total of 430 participants from the state universities had high loadings within each factor, and there were no responded, being a 5.50% return rate, while 554 participants major cross-loadings between factors. Finally, the reliability from the private universities responded, having an 11.80% measures using Cronbach’s alpha ranged between .71 and return rate. As a result, 984 participants in total responded to .94, which were greater than the cutoff value of 0.70 (Cortina, the survey, with a 7.86% return rate. Based on the table 1993; Cronbach, 1951; Hair et al., 2010). developed by Sekaran (2000), which indicates the minimum sample size that can represent the population, the minimum Confirmatory Factor Analysis (CFA) sample size for the state universities was 375, and the mini- mum sample size for the private universities was 364, to rep- Following the EFA, the nine latent variables in a single model resent the target population. Thus, the 984 sample size were subject to Confirmatory Factor Analysis (CFA) to inves- adequately represented the target population of this research tigate the reliability and validity, as well as the model-fit of (Sekaran, 2000). the constructs (Fornell & Larcker, 1981). The model-fit Dinibutun et al. 9 Table 2. Summary of Demographic Variables. Variable Categories Frequency Percent Gender Female 561 57.00 Male 423 43.00 Total 984 100.00 Marital status Single 380 38.60 Married 604 61.40 Total 984 100.00 Institution State university 430 43.70 Private university 554 56.30 Total 984 100.00 Academic title Professor 166 16.87 Associate professor 76 7.72 Assistant professor 209 21.24 Lecturer, PhD 51 5.18 Lecturer, MSc 148 15.04 Research assistant, PhD 49 4.98 Research assistant, MSc 285 28.96 Total 984 100.00 Age 20–25 years 57 5.80 26–30 years 214 21.70 31–35 years 228 23.20 36–40 years 105 10.70 41–45 years 130 13.20 Older than 46 years 250 25.40 Total 984 100.00 Experience Less than 1 year 90 9.10 1–5 years 395 40.10 6–10 years 225 22.90 11–15 years 118 12.00 16–20 years 50 5.10 More than 21 years 106 10.80 Total 984 100.00 performance measures, which indicated how well the factor the validity of the constructs (Hair et al., 2010). In Table 5, structure accounts for the associations between the variables the correlation coefficients between each pair of the latent in the sample data as well as the standardized regression variables, the descriptive statistics, the average variance weights and t-statistics of the latent variables’ items, are extracted (AVE) values, the composite reliability (CR), the shown in Table 4. For the CFA, the maximum likelihood esti- Cronbach’s alphas, and the square root of AVEs on the diago- mator was selected during the CFA analysis. The results nal of the correlation matrix are given. The correlation analy- revealed that χ /df was 2.07, the comparative fit index (CFI) sis also indicated that there was no high bivariate correlation was 0.97, the incremental fit index (IFI) was 0.97, the Tucker– between each pair of the latent variables. The reliability of Lewis index (TLI) was 0.96, the relative fit index (RFI) was the constructs was satisfied as the Cronbach’s alpha scores 0.964, the goodness of fit index (GFI) was 0.93, and the root (ranges between 0.71 and 0.94) and CR (ranges between mean square error of approximation (RMSEA) was 0.033. 0.81 and 0.95) were more than the suggested threshold value The provided measure of model-fit performance values was of 0.70 (Bari et al., 2019; Nunnally & Bernstein, 1994). In completely satisfied, based on the suggested cutoff values addition, the values of AVE ranged between 0.52 and 0.85, (Bagozzi &Yi, 1988; Hu & Bentler, 1999). Thus, the model- which indicated that the convergent validity was met as the fit measurements showed a good fit of the proposed model. values of AVE were above the recommended value of 0.50 (Bari et al., 2019; Hair et al., 2010; Meng & Bari, 2019). Finally, the discriminant validity was satisfied as the square Measurement Model root of AVE values (range between 0.72 and 0.92) at the Before testing the hypothesis using SEM, it was crucial to diagonal of the correlation matrix was well above any inter- investigate the internal consistency and reliability as well as correlation values of the latent variables. 10 SAGE Open Table 3. Exploratory Factor Analysis. Factor Items Factor loadings Variance (%) Cumulative variance (%) Eigenvalues M SD Ethics OC_eth3 0.94 34.08 34.08 10.14 3.58 1.08 (α = .94) OC_eth2 0.92 3.70 1.05 OC_eth1 0.84 3.74 1.09 OC_eth4 0.83 3.63 1.12 OC_eth5 0.73 3.46 1.12 OC_eth6 0.69 3.35 1.12 Managerial OC_mc1 0.83 5.13 39.21 10.70 3.32 1.04 competence OC_mc5 0.78 3.10 0.87 (α = .89) OC_mc3 0.76 3.28 0.90 OC_mc2 0.74 3.06 1.04 OC_mc8 0.71 3.47 1.00 OC_mc6 0.55 2.66 1.06 Cohesion OC_coh2 0.92 3.93 43.14 8.09 3.52 0.91 (α = .90) OC_coh3 0.87 3.38 0.95 OC_coh4 0.76 2.95 0.99 OC_coh1 0.71 3.05 1.00 Balanced workload OC_bw2 0.93 3.35 46.49 7.53 2.96 0.99 (α = .87) OC_bw1 0.92 3.05 1.03 OC_bw3 0.63 2.86 1.03 OC_bw4 0.60 3.08 0.88 Participation OC_part2 0.89 1.81 48.30 8.50 2.65 1.11 (α = .91) OC_part3 0.81 2.56 1.07 OC_part1 0.80 2.70 1.05 Clarity of task OC_ct1 0.83 1.59 49.89 8.47 3.62 0.96 (α = .86) OC_ct3 0.80 3.64 0.99 OC_ct2 0.78 3.32 1.05 Emotional exhaustion BO_ee5 0.89 6.47 56.39 10.35 2.29 1.06 (α = .92) BO_ee3 0.87 2.20 1.08 BO_ee2 0.86 2.72 1.08 BO_ee1 0.85 2.63 1.13 BO_ee9 0.69 1.91 1.03 BO_ee6 0.49 2.72 1.10 Depersonalization BO_dper2 0.89 2.01 58.37 7.06 2.06 0.98 (α = .79) BO_dper3 0.73 2.08 1.11 BO_dper1 0.62 1.54 0.80 BO_dper4 0.46 1.63 0.81 Personal BO_pad5 0.56 2.65 61.02 4.03 2.07 0.67 accomplishment BO_pad2 0.56 2.06 0.60 (diminished) BO_pad3 0.55 2.10 0.86 (α = .71) BO_pad1 0.52 2.36 0.69 BO_pad6 0.51 2.29 0.79 BO_pad7 0.49 2.36 0.79 BO_pad4 0.48 2.11 0.77 Note. “α” represents Cronbach’s alpha; Kaiser–Meyer–Olkin Measure of Sampling Adequacy = 0.951; Bartlett’s Test of Sphericity = 28338.92, df = 903, p value = .001. The results of SEM are provided in Table 6. According to Structural Equation Modeling the revealed results, Managerial Competence only had a sig- The CB-SEM methodology was utilized to test the research nificant negative association with Emotional Exhaustion hypotheses. There was no multicollinearity issue among the (p < .05); Balanced Workload had a significant negative independent variables as the variable inflation factors (VIFs) relationship with Emotional Exhaustion (p < .001) and were all less than the suggested (Hair et al., 2010) cutoff Depersonalization (p < .001); Clarity of Task had a signifi- value of 10 (ranging between 1.48 and 2.47). cant negative association with Emotional Exhaustion Dinibutun et al. 11 Table 4. Confirmatory Factor Analysis. Latent variables Items Standardized regression weights t-statistics Ethics OC_eth6 0.78 Scaling OC_eth5 0.79 29.02 OC_eth4 0.82 24.95 OC_eth3 0.94 28.86 OC_eth2 0.94 27.03 OC_eth1 0.84 24.92 Managerial competence OC_mc8 0.76 Scaling OC_mc6 0.75 23.54 OC_mc5 0.78 24.96 OC_mc3 0.78 24.67 OC_mc2 0.70 21.29 OC_mc1 0.76 23.90 Cohesion OC_coh4 0.88 Scaling OC_coh3 0.83 24.94 OC_coh2 0.81 24.47 OC_coh1 0.81 26.15 Balanced work OC_bw4 0.98 Scaling OC_bw3 0.64 14.17 OC_bw2 0.87 21.75 OC_bw1 0.83 21.25 Participation OC_part3 0.92 Scaling OC_part2 0.88 40.73 OC_part1 0.85 37.73 Clarity of task OC_ct3 0.79 Scaling OC_ct2 0.82 26.62 OC_ct1 0.84 27.20 Emotional exhaustion BO_ee9 0.64 Scaling BO_ee6 0.76 19.56 BO_ee5 0.90 23.54 BO_ee3 0.88 22.16 BO_ee2 0.84 19.96 BO_ee1 0.88 21.51 Depersonalization BO_dper4 0.54 Scaling BO_dper3 0.82 13.97 BO_dper2 0.78 13.99 BO_dper1 0.60 14.02 Personal accomplishment (diminished) BO_pad7 0.55 Scaling BO_pad6 0.66 12.55 BO_pad5 0.65 13.09 BO_pad4 0.49 11.26 BO_pad3 0.62 12.39 BO_pad2 0.48 10.85 BO_pad1 0.45 6.54 2 2 Note. χ (784) = 1620.1.01, χ /df = 2.07, comparative fit index = .97, incremental fit index = .97, Tucker–Lewis index = .96, relative fit index = .94; goodness of fit index = .93 root mean square error of approximation = .033. (p < .001), Depersonalization (p < .001), and Personal negative association with Emotional Exhaustion (p < .001). Accomplishment (p < .001); Cohesion had a significant neg- The results showed that H3 and H5 were fully accepted, ative association with Emotional Exhaustion (p < .05) and while H1, H2, H4, and H6 were partially accepted. Depersonalization (p < .05); Ethics had a significant nega- Moreover, 44.5% of the variance in Emotional Exhaustion, tive relationship with Emotional Exhaustion (p < .001), 20.6% of the variance in Depersonalization, and 14.7% of Depersonalization (p < .001), and Personal Accomplishment the variance in Personal Accomplishment were explained by (p < .001); finally, Participation only had a significant the variances in Managerial Competence, Balanced 12 SAGE Open Table 5. Correlation Analysis and Reliability Measures of the Variables (N = 984). Variables L1 L2 L3 L4 L5 L6 L7 L8 L9 1 Ethics 0.87 2 Managerial competence .56** 0.80 3 Cohesion .47** .59** 0.88 4 Balanced work .38** .52** .37** 0.84 5 Participation .52** .59** .44** .37** 0.92 6 Clarity of task .48** .57** .43** .47** .46** 0.88 7 Emotional exhaustion −.51** −.52** −.42** −.51** −.49** −.49** 0.85 8 Depersonalization −.39** −.33** −.29** −.30** −.30** −.33** .58** 0.78 9 Personal accomplishment −.30** −.24** −.19** −.15** −.20** −.30** .35** .34** 0.72 AVE 0.76 0.64 0.77 0.71 0.85 0.78 0.73 0.61 0.52 Composite reliability 0.95 0.91 0.93 0.91 0.95 0.91 0.94 0.86 0.81 Cronbach’s alpha 0.94 0.89 0.90 0.87 0.91 0.86 0.92 0.79 0.71 M 3.57 3.15 3.23 2.99 2.64 3.52 2.41 1.83 2.19 SD 0.96 0.79 0.84 0.83 0.99 0.88 0.92 0.73 0.46 Note. The elements on the diagonal are the square root of AVE, while the elements off-diagonal are the correlations between the latent variables. AVE = average variance extracted. Bold values are the square root of AVE scores. They are not coefficients of correlation. There is no sgnificance level assciated with the square root of AVE scores. **p < .01. Table 6. Structural Equation Modeling Results. Hypothesis Paths Beta t-stat Result H1a Managerial competence → emotional exhaustion −0.07* 1.95 Accepted H1b Managerial competence → depersonalization −0.02 0.66 Rejected H1c Managerial competence → personal accomplishment −0.03 0.82 Rejected H2a Balanced workload → emotional exhaustion −0.26*** 8.58 Accepted H2b Balanced workload → depersonalization −0.12*** 3.54 Accepted H2c Balanced workload → personal accomplishment −0.005 0.21 Rejected H3a Clarity of task → emotional exhaustion −0.14*** 4.29 Accepted H3b Clarity of task → depersonalization −0.12*** 3.04 Accepted H3c Clarity of task → personal accomplishment −0.19*** 4.60 Accepted H4a Cohesion → emotional exhaustion −0.08* 2.31 Accepted H4b Cohesion → depersonalization −0.07* 1.95 Accepted H4c Cohesion → personal accomplishment −0.05 1.53 Rejected H5a Ethics → emotional exhaustion −0.19*** 5.30 Accepted H5b Ethics → depersonalization −0.24*** 5.18 Accepted H5c Ethics → personal accomplishment −0.21*** 4.95 Accepted H6a Participation → emotional exhaustion −0.13*** 3.89 Accepted H6b Participation → depersonalization −0.01 0.38 Rejected H6c Participation → personal accomplishment 0.02 0.66 Rejected 2 2 2 Note. R = .445; R = .206; R = .147. EmotionalExhaustion Depersonalization PersonalAccomplishment *p < .05. **p < .01. ***p < .001. Workload, Clarity of Task, Cohesion, Ethics, and Participation to compare the proposed model between state and private (see the footnote in Table 7). universities as the grouping variable. As previously shown, the sample size of the state universities was 430, while the sample size of the private universities was 554. The compari- Comparison of Models Between State and son of the proposed model is given in Table 7. Accordingly, Private Universities the results indicated that Balanced Workload had a signifi- The same proposed model was tested by comparing state cant negative association with Emotional Exhaustion and universities with private universities. Thus, a multigroup Depersonalization in both state and private universities. In analysis based on bootstrapping results was utilized addition, Clarity of Task had a significant negative Dinibutun et al. 13 Table 7. Comparison of the Proposed Model Between State Universities and Private Universities. Beta t-values Beta t-values Paths (private) (private) (state) (state) Managerial competence → emotional exhaustion −0.056 1.20 −0.08 1.23 Managerial competence → depersonalization −0.01 0.08 −0.03 0.39 Managerial competence → personal accomplishment −0.03 0.50 −0.01 0.01 Balanced workload → emotional exhaustion −0.30*** 8.31 −0.19*** 3.95 Balanced workload → depersonalization −0.13*** 2.92 −0.11* 2.10 Balanced workload → personal accomplishment 0.07 1.27 −0.06 1.06 Clarity of task → emotional exhaustion −0.18*** 4.41 −0.09* 1.95 Clarity of task → depersonalization −0.12* 2.27 −0.11* 1.95 Clarity of task → personal accomplishment −0.16* 2.62 −0.25*** 4.33 Cohesion → emotional exhaustion −0.06 1.61 −0.10* 1.96 Cohesion → depersonalization −0.11* 2.12 −0.03 0.41 Cohesion → personal accomplishment −0.04 0.84 −0.06 0.81 Ethics → emotional exhaustion −0.22*** 4.81 −0.15* 2.51 Ethics → depersonalization −0.29*** 4.30 −0.18* 2.62 Ethics → personal accomplishment −0.24*** 4.16 −0.18*** 2.96 Participation → emotional exhaustion −0.12* 2.81 −0.14* 2.43 Participation → depersonalization −0.01 0.18 −0.01 0.12 Participation → personal accomplishment −0.09 1.56 0.150* 2.41 *p < .05. **p < .01. ***p < .001. Table 8. The Coefficients’ Difference Between State and Private Universities. β – β t-value Private State Paths (|Private – State|) (Private vs. State) Managerial competence → emotional exhaustion 0.03 0.32 Managerial competence → depersonalization 0.02 0.25 Managerial competence → personal accomplishment 0.03 0.30 Balanced workload → emotional exhaustion 0.10 1.73 Balanced workload → depersonalization 0.02 0.27 Balanced workload → personal accomplishment 0.14 1.62 Clarity of task → emotional exhaustion 0.09 1.28 Clarity of task → depersonalization 0.01 0.12 Clarity of task → personal accomplishment 0.09 1.10 Cohesion → emotional exhaustion 0.04 0.59 Cohesion → depersonalization 0.08 1.04 Cohesion → personal accomplishment 0.02 0.21 Ethics → emotional exhaustion 0.07 0.93 Ethics → depersonalization 0.10 1.05 Ethics → personal accomplishment 0.05 0.64 Participation → emotional exhaustion 0.02 0.33 Participation → depersonalization 0.00 0.02 Participation → personal accomplishment 0.24*** 2.84 *p < .05. **p < .01. ***p < .001. relationship with emotional exhaustion, depersonalization, and personal accomplishment at both private and state uni- and personal accomplishment in both groups. Moreover, versity levels. Finally, Participation had a significant nega- Cohesion had a significant negative relationship with deper- tive association with emotional exhaustion at both the private sonalization in the private university group, while it had a and state university levels. significant negative relationship with emotional exhaustion The difference between the betas of the state and private at the state university level. Ethics had a significant negative universities and the corresponding t-statistics are shown in association with emotional exhaustion, depersonalization, Table 8. The results indicated that there was a significant 14 SAGE Open difference between the coefficients of the groups in testing supervisory roles in academic life are positive predictors of the association of participation with personal accomplish- both Emotional Exhaustion and Depersonalization of faculty ment, while there was no statistically significant difference members, teaching load, the amount of time required for between any other coefficients of the state and private grading, office hours, service time, the number of service universities. activities, and the overall time spent as a faculty member are positively correlated with Emotional Exhaustion (Lackritz, 2004). However, the study did not find a negative effect aris- Discussion ing from the Balanced Workload and Cohesion dimensions The findings of this study show that the Managerial on the decreased personal accomplishment level of burnout Competence and Participation dimensions of OC have a sig- experienced by faculty members. At the decreased personal nificant and negative influence on the emotional exhaustion accomplishment stage of burnout, a person feels like a fail- level of faculty members’ burnout. The ability of managers to ure. Lack of relationship between this level of burnout by communicate effectively, combined with their attitudes and faculty members and the Balanced Workload and Cohesion behaviors toward employees, is vital to provide a positive OC indicates that fairness by the administration in terms of deliv- for employees. This type of climate creates a transparent ery in teaching and service loads, accompanied with respect organization and encourages employees to participate fully in and friendly relations among the academic members does the decision-making process. These two dimensions are criti- not reduce feelings of failure in their jobs by faculty mem- cal, especially in the higher education institutions, in which bers. Therefore, Hypotheses 2 and 4 are partially accepted. the productivity of the academic staff is vital. Psychological Another finding in the study demonstrates that the Clarity health is crucial to create productivity. According to the of Task dimension of OC has an important negative effect on results of the study, faculty members who held positive per- the emotional exhaustion, depersonalization, and diminished ceptions of Managerial Competence in their administrators personal accomplishment level of burnout experienced by and were invited into a Participation opportunity in the deci- faculty members. Clarity of Task means that employees sion-making processes, within both the state and private uni- know exactly what is expected from them on the job. versities, were less likely to be exhausted emotionally. This Universities are educational institutions where all the rules result is consistent with the findings of Tytherleigh et al. and regulations are well written and documented. Therefore, (2008) and Van Emmerik (2002), which indicate that high academic staff always know what is expected, clearly, espe- levels of support from one’s superiors will predict lower lev- cially in teaching and research activities. Thus, the study els of reported burnout. The result of Pretorius’s (1994) study, shows that faculty members who perceived a higher clarity showing that participation in decision-making was signifi- of task within the state and private universities were less cantly correlated with perceived accomplishment in South likely to demonstrate emotional exhaustion, depersonaliza- African academics, is consistent with the findings of this tion, or experience a decreased personal accomplishment study. On the other hand, these two dimensions of OC did not level of burnout. Several study results that are in line with influence the depersonalization and the decreased personal this finding have indicated that lack of task clarity and role accomplishment level of burnout in the study. Therefore, ambiguity would lead to lower perceived accomplishment Hypotheses 1 and 6 are partially accepted. and greater depersonalization (Ghorpade et al., 2011) and The findings of the study also indicated that the Balanced greater emotional exhaustion (Van Emmerik, 2002) in a uni- Workload and Cohesion dimensions of OC affected the emo- versity environment. Therefore, Hypothesis 3 is accepted. tional exhaustion and depersonalization levels of faculty Furthermore, the study demonstrates that the Ethics dimen- burnout negatively. Workload refers to the absolute amount sion of OC has a significant negative impact on emotional of work required and the time frame within which that work exhaustion, depersonalization, and the diminished personal must be completed (Cooper et al., 2001). Cohesion is mutual accomplishment level of job burnout. Ethics in OC is the sensi- trust and respect between employees. Employees who have tivity of management to comply with official and written ethi- friendly relations with their coworkers in an organization cal rules which are valid within the organization. Employees possess a sense of support and security. The study findings who have a positive perception regarding the ethicality of their demonstrated that faculty members who reported higher lev- organizations are less likely to show burnout symptoms. els of the Balanced Workload and Cohesion OC dimensions Faculty members who reported receiving higher levels of ethi- within both state and private universities were less likely to cal sensitivity within the state and private universities were less report emotional exhaustion and a depersonalization level of likely to report experiencing emotional exhaustion, deperson- burnout. These findings are consistent with several studies alization, and a decreased personal accomplishment level of which found that workload and time pressure are strongly burnout at work. This result is consistent with Maslach et al.’s related to burnout, in particular, to the dimension of exhaus- (2012) and Maslach and Leiter’s (1997) research findings, tion (Leiter et al., 2010; Maslach et al., 2001; Reid et al., which showed that employees felt stressed by insincerity 1999; Vesty et al., 2018; Yildirim & Dinc, 2019). This speci- within organizational values as well as conflict with ethical fies that while the total numbers of students in teaching and understanding, which in turn lead to burnout. In addition, Dinibutun et al. 15 Siegall and McDonald’s (2004) findings that found person- Thompson & Rose, 2011), there has been a gap in terms of organization value congruence to be negatively correlated with linking OC dimensions to burnout levels. At the same time, emotional exhaustion and depersonalization levels of burnout there was a scarcity of research examining these relation- among U.S. faculty are in line with the results of this study. ships among academic staff within universities. This study Therefore, Hypothesis 5 is accepted. tries to fill these gaps in the literature. This research indi- Moreover, regarding differences between the perceptions cates that clarity of task and the ethical dimensions of OC of faculty members who work in either the state or private were significant predictors of emotional exhaustion, deper- universities concerning the impact of OC dimensions on their sonalization, and lack of personal accomplishment level of burnout levels, this study finds that faculty members working burnout experienced by faculty members. In addition, at state universities, where there is a Participation OC dimen- Balanced Workload and Cohesion had negative effects on sion, were less likely to report a decreased personal accom- emotional exhaustion, and depersonalization levels, plishment level of burnout in contrast to faculty members whereas Managerial Competence and Participation dimen- within the private universities. This result may stem from the sions solely influenced negatively the emotional exhaus- research context. When a faculty member starts to work at a tion creating the burnout of faculty members. state university in Turkey, it can be inferred that he or she Another contribution of this study to the literature con- becomes a permanent academic staff who may be fired by the cerns exploring the effect of the OC dimensions on burnout university only under very extraordinary conditions. Due to levels within state and private universities separately. this approach, especially experienced faculty members such Whereas few studies in the literature examine the percep- as associate professors or professors in the state universities tions of academic staff about employee behaviors within pri- may not be motivated to focus on personal accomplishment. vate and state universities (Balay, 2012), little research has They are more concentrated on teamwork within their univer- concentrated on linking the dimensions of OC to faculty sities. All of the success stories within their universities to burnout levels within state and private universities. This which they have made enormous contributions by participat- research attempts to fill this gap in the literature. This study ing in the decision-making process may enhance their happi- demonstrates that while faculty members who work within ness and therefore reduce the possibility of a decreased sense the state universities which have a Cohesion OC dimension of personal accomplishment that contributes to burnout and are less likely to be exhausted emotionally, the availability of emotional exhaustion. The study findings showing a nega- Cohesion in the private universities negatively affects the tive relationship between Cohesion in the state universities depersonalization burnout level of faculty members. and the relative emotional exhaustion of faculty members However, the decreased personal accomplishment level of support this. On the contrary, faculty members in the private faculty members within state universities where they were universities must concentrate on their academic and personal involved in the decision-making process was low. This rela- accomplishments in order not to be laid off. Participation in tionship was not found among faculty members who worked meetings and teamwork may be considered to be a waste of within private universities. time for them; therefore, the study found no relationship between Participation in private universities and their Managerial Implications decreased personal accomplishment. In addition, the avail- ability of Cohesion in these universities only reduced the Several implications are arising from this study for admin- depersonalization level of burnout of faculty members. Due istrators in both state and private universities who must be to the aforementioned characteristics of the faculty members concerned about the mental state of their faculty members. in private universities, faculty members who enjoy respect First, these results suggest that state and private universi- and friendly relations with their colleagues are less likely to ties can enhance the health and productivity of their staff have a tendency to dehumanize their students and colleagues, while reducing emotional exhaustion, depersonalization, often delivered by way of a cynical, callous, and uncaring and a sense of a lack of personal accomplishment by attitude. The theoretical and practical implications of the always being sensitive and complying with the official and study are highlighted in the following paragraphs. written ethical rules within the organization and maintain- ing clarity toward what is expected of the faculty concern- ing the tasks in departments and colleges. Another Theoretical Implications implication of the study is the negative effect of the This research has theoretical implications. First, it finds Balanced Workload and Cohesion OC dimensions on emo- support for the relationship between OC and burnout. tional exhaustion and depersonalization, causing burnout Although many empirical studies have researched the rela- of the faculty members in both types of universities. The tionship between OC and burnout (Bronkhorst et al., 2015; teaching load and the number of students under the super- Cordes et al., 1997; Idris & Dollard, 2014; Kaya et al., vision of the faculty members are directly correlated with 2010; Lee et al., 2013; Lubranska, 2011; Maidaniuc- burnout. Therefore, the reduction of the teaching load and Chirila & Constantin, 2017; Martinussen et al., 2007; the number of students can be a preventive tool for faculty 16 SAGE Open members (Lackritz, 2004). With regard to Cohesion in the dimensions of OC influence the reduction of the emotional universities, effective training and socialization, including exhaustion of faculty members. Several dimensions of OC family members, can enhance the faculty members’ rela- such as balance within the workload, clarity of task, cohe- tionships with their colleagues. The final implication con- sion, and ethical dimensions may produce a negative effect cerns the different approaches of the faculty members in on the depersonalization dimension of faculty burnout. state and private universities toward the Cohesion and Finally, lack of clarity of task and the ethical dimensions of Participation dimensions of OC. The study results demon- OC succeeded in decreasing the dimension of diminished strated that while faculty members who work at state uni- personal accomplishment of faculty burnout. The study pro- versities which have a Cohesion OC were less likely to be vides several recommendations for both state and private exhausted emotionally, the availability of Cohesion in the university administrators. private universities did not affect the emotional exhaustion of faculty members, but influenced their depersonalization Declaration of Conflicting Interests burnout level negatively. However, the decreased personal The author(s) declared no potential conflicts of interest with respect accomplishment level of faculty members in the state uni- to the research, authorship, and/or publication of this article. versities, where they were encouraged to participate in the decision-making process, was low. This relationship was Funding not found among faculty members in private universities. The author(s) received no financial support for the research, author- These study findings suggest that private universities ship, and/or publication of this article. should focus more on Cohesion among faculty members at the university, college, and department levels. University ORCID iDs administrators can encourage faculties to do research Sait Revda Dinibutun https://orcid.org/0000-0003-4588-5677 jointly with their colleagues who are working in the same department, to enhance both cohesion and personal suc- Muhammet Sait Dinc https://orcid.org/0000-0002-1146-5474 cess. This can also contribute to reducing the emotional exhaustion of faculty members. The private university References administrators should also concentrate on the participation Anbar, A., & Eker, M. (2008). Work related factors that affect burn- of faculty members in the decision-making process. out among accounting and finance academicians. 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SAGE Open – SAGE
Published: Dec 11, 2020
Keywords: organizational climate,burnout,faculty member,state universities,and private universities
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