Moderating Effect of Self Efficacy and Workload to Work Environment-Work Engagement Relationship Of Hotel Employees In Malang City

Author info »

Abstract

Work engagement is a problem that challenges human resource managers because of the world general decline in employee engagement. In Indonesia alone 77% of employees do not have a work engagement; even 15% of them actively carry out job disengagement, which is certainly detrimental to the company due to decreased employees’ productivity. Therefore, this study also wants to examine the moderating effect of workload and self-efficacy on the influence of the work environment on work engagement of hotel employees in Malang. The results showed that the work environment had a significant positive effect on work engagement. From the results of the MRA, only workload which significantly moderates the influence of the work environment on work engagement. While the self-efficacy, only acts as a predictor moderation, which means it is more appropriate as a predictor of work engagement than a moderating variable. From the results of this study, it is advisable for subsequent researchers to further examine individual factors (such as self-efficacy, self-esteem, optimism) as an independent variable/predictor of work engagement, especially for work contexts that involve human service providers. Furthermore, JD-R framework is also suggested to use in examining work engagement.

Keywords

Work environment. Self-efficacy. Workload. Quasi moderator. Moderated regression analysis. JD-R

Introduction

Within the last decade, work engagement remains a challenge for all business organizations throughout the world. A survey conducted by Gallup Daily Tracking in 2015, found that only 13 per cent of employees worldwide are tied to organizations (Imperatory, 2018). Employee engagement data is even lower when the survey was conducted in Indonesia in 2014 (Gallup, 2014). The number of Indonesian employees who are tied to the organization is only 8 per cent. The majority of Indonesian employees were found to be independent of the organization (77%), and even actively did disengagement (15%). Unfortunately, employees who do not have work attachments, both those who are not engaged, especially those who are actively disengaged will ultimately harm the organization, because it will result in decreased work productivity.

Previous research found that work engagement has a strong relationship to employee performance; even the relationship is stronger than job satisfaction, job involvement and organizational commitment (Schaufeli, 2013). Employees who have work attachments contribute to the tasks for which they are responsible, optimal in solving problems, establishing relationships with others and being able to develop innovation (Simone et al, 2016; Gallup in Vazirani; 2007: 4). In addition, employees who are tied to their jobs will help increase business income, as well as reduce expenses such as labour costs (Swanberg et al., 2011) and tend to remain in the company (Vazirani 2007: 6).

Armstrong (2009: 340) identified five factors that can influence work engagement, one of which is the work environment. A supportive and inspirational work environment described by Armstrong can have an impact on employee engagement. Furthermore, Kaswan (2017: 569) asserts that the work environment can produce a dramatic impact on morale, enthusiasm for the task, and productivity. The working environment conception in this study refers to several opinions such as Kaswan (2017: 568), Sedarmayanti (20029: 21) and Nitisemito in Sunyoto (2015: 38), where the work environment is interpreted as something around workers when doing their work. Indicators commonly used to measure the work environment in aspects of employee employment are work regulations, lighting, air circulation, noise levels and safety (Nitisemito in Sunyoto; 2015: 38).

Support for opinions stating that the work environment influences work engagement appears in sharing research conducted by Aliyah (2017); Thompson (2016); Park and Lee (2018) which shows that there is a significant positive effect between work environment and work engagement. Christian et al. (2011) also found that work conditions such as air temperature, noise, and the environment that endanger health are negatively related to work engagement.

The influence of the work environment on work engagement will be strengthened or weakened by one's personal resources, which consists of selfefficacy and self-esteem (Xhanthopoulou, in Chaudhary, et. al., 2012).

The position of self-efficacy as a moderating variable was proposed by Xanthopoulou in Chaudhary et al. (2012) which explains that personal resources (self-efficacy and self-esteem) as moderators of the influence of job resources and work engagement can be tested. Several other studies such as those conducted by Liu et al. (2017) show that self-efficacy has managed to be a significant moderating variable on the effect of perceived organizational support on work engagement. Another study by Chaudhary et al. (2012) shows that self-efficacy significantly moderates the relationship between human resource development climate and work engagement.

Different research results found by Chaudhary et al. (2017) by comparing in two different countries, it proves that self-efficacy does not succeed in becoming a moderator variable in the relationship between human resource development climate and work engagement. Referring to the different finding of the study, the position of self-efficacy as an interesting moderator variable to be tested. Therefore, the researcher will then examine whether the self-efficacy in this study has succeeded in becoming a significant moderator variable or not on the effect of the work environment on work engagement.

Schwarzer and Jerusalem (in Rizal, 2015) define self-efficacy as a feeling of being able to do work, better abilities, happy challenging work and job satisfaction. The existence of self-efficacy will be able to promote work engagement and a positive social work environment (Consiglio et al., 2016: 126) Employees who have high self-efficacy, will be persistent in working. In contrast to employees who have low self-efficacy, employees will give up on their abilities. Self-efficacy is a person's belief about his success in doing a job (Kreitner and Kinicki, 2014: 125) or managing prospective situations (Bandura, 1995: 2). In different terms Luthan (2006: 338) refers to self-efficacy as a belief in the ability to mobilize the motivation, cognitive aspects and actions needed at work.

In several previous studies, especially relating the burnout and work engagement, self-efficacy was found to be a predictor of work engagement (Halbesleben, 2010) and had a positive influence on work engagement (Makikangas in Bakker, Demerouti & Sanz-Vergel, 2014). Self-efficacy was also found to be able to reduce the negative effects of a less supportive work environment so that it was able to become a buffer to reduce burnout (Bakker et al., 2014). In his study, Makikangas (in Bakker et al., 2014) argues that an individual who has high self-esteem has a certain way of adjusting to reality. Individuals who have high self-esteem will be able to accept mistakes and setbacks as something natural and tend to see life as something they can influence and they can act in it. Self-efficacy is included in the individual factors that become antecedent work engagement.

In addition, in the perspective of job demands and job resources (JD-R) analysis which results in burnout and work engagement, it is generally found that both individual job resources such as self-efficacy, work autonomy, are able to be predictors or antecedents of work engagement and negatively related (reduce) burnout. While job demands, such as a less conducive work environment and excessive workload have a significant positive effect on burnout and negatively affect work engagement. Even so, the effect of job demands is stronger on burnout than work engagement (Bakker et al., 2014). Even in a study conducted by Schaufeli & Bakker (2004) found that job resources are exclusive predictors of work engagement, although they also include job demands as predictors of work engagement in their studies. However, several other studies found that job demands such as excessive workload, less conducive work environment also correlated and were predictors of work engagement although not as strong as job resources (Christian et al., 2011; Halbesleben in Bakker et al., 2014). Furthermore, Hakanen et al. (in Bakker et al., 2014) also found in their research that investigated how high job demands and high job resources experienced by Finnish dentists that a high variation of professional skills would be able to increase the work engagement of these doctors when burdened the work perceived by dentists in Finland was high. In addition, variations in their professional skills are also able to minimize the negative impact of workload on work engagement.

From several studies on work engagement, it appears that self-efficacy in the lower-order individual factors group can reduce the influence of negative job demands (such as a high-risk work environment, role ambiguity, role conflict, role stress, tiring events, stressful events, pressure work) towards work engagement. While the workload that falls into the category of job demands, can increase burnout and reduce engagement or negatively affect work engagement. Therefore, workloads, especially those perceived to be excessive by employees, will also affect work engagement.

Workload is defined as a collection of task requests or work (task demand), as a form of business in the form of activity or achievement (Gartner & Murphy, 1979; Gawron, 2008). Job requests are the goals of an organization to be achieved. In fulfilling a task request, a person usually has the time allowed to do the task and also the level of performance of the task completed. Gartner and Murphy (1979) state that realistically, it will be difficult for someone to exceed 100% of their workload, even though there is research that says otherwise. Even so, the task assigned to someone could have exceeded 100%. Greenglass, et al., (2001) conducted a study of nurses whose workload exceeded 100%, and this was one of the factors causing stress consistently to nurses in all lines of the hospital. Workload is the main significant prediction of negative mental development, lack of job satisfaction, and burnout for nurses.

The negative effects of overwork do not only affect the type of nurse's work. DeFreese & Smith (2013) also found that workload is also one indicator in the calculation of burnout and also the level of engagement for the athlete profession. There is a lot of pressure on the athlete so that when the athlete is unable to adapt to the demands of sporting activity demand it will cause an inability to adapt to burnout. In athletes, the case of burnout is one of the responses to the inability to adapt due to stress-related to exercise activities and competitions or competitions. Workload itself is part of the areas of worklife (areas of work-life). The work-life area is a component that is able to predict the level of burnout and engagement of a person towards an organization or job. The area of work-life includes six dimensions in addition to workload, namely control, respect, community, justice, and values (Leiter & Maslach, 2004). Thus it can be interpreted that the existence of workload is able to predict one's level of engagement.

From the various reviews and findings of previous studies that are still diverse, this study is interested in testing the role of moderation of two variables, namely self-efficacy (which is included in individual job resources) and workload (which is included in situational job demands) on the influence of the work environment on work engagement in hospitality industry employees in the city of Malang.

Malang is one of the major cities in East Java, which is famous for its various interesting tourist and culinary destinations. Along with the growing and developing tourism destinations in the region of Malang and surrounding areas, also impact on the needs of hotels and lodging. Data of the Association of Indonesian Hotels and Restaurants (PHRI) of Malang in 2017 showed that the number of hotels in Malang totalled to 105, starting from lodging classes to five-star hotels. The Culture and Tourism Office (Disbudpar) of Malang City, released visitor/tourist data in Malang City during 2018 totalling 15,034 foreign tourists and 4.8 million domestic tourists. Based on these data it appears that the need for lodging or hotels in the city of Malang is still high, the occupancy rate of hotels in the city of Malang is quite high and is never lonely. As a result, employees are required to always be available and excellent in serving customers, considering the hospitality industry is one of the players in the hospitality industry that prioritizes service. So that a high level of work engagement is needed as other service professions are found to have a high level of work engagement such as teachers, nurses, doctors, police. Therefore, it is interesting to investigate the work engagement of hotel employees in relation to the work environment, self-efficacy, and workload they experience.

Based on the discussions that have been submitted, the research proposes several research hypotheses:

H1: The work environment has a significant effect on the work engagement of Malang city hotel employees

H2: Self efficacy significantly moderates the influence of the work environment on the work engagement of Malang city hotel employees

H3: Workload significantly moderates the influence of the work environment on the work engagement of Malang city hotel employees.

Method

This research was conducted with a quantitative explanatory approach. Analysis for the verification of hypotheses performed using inferential statistical calculations, regression and moderating regression analysis (MRA). The variables that are the focus of this study are the work environment, work engagement, self-efficacy, and workload. Work environment variable (X) as an independent variable, work engagement (Y) as the dependent variable, self-efficacy (Z1) and work load (Z2) are respectively positioned as moderator variables. The relationship model between variables is presented in figure 1 (Figure 1).

Figure 1. Model of Relationships between Variables.

The population in this study are hotel employees in the category of 3-star hotels and local networks in Malang. The selection of this category is based on consideration of data accessibility opportunities, and hotels in that category have the principle of labour efficiency is highly prioritized so that the potential for workload emergence is quite large. Samples taken from the population are endeavoured to be representative enough to be able to represent the condition of the population. The questionnaires distributed in this study amounted to 210. And the number of returned questionnaires amounted to 148. This means that only 70% of the returned questionnaires or the response rate of respondents was only 70%.

The statements in the questionnaire were measured using a semantic differential scale. In this research, the answer format as the respondent's assessment consists of seven categories that reflect the two sides (positivenegative) that confront the statement presented. The work environment measurement instruments in this study used instruments developed by Nitisemito and Sunyoto consisting of 9 measurement instruments concerning aspects of relations between employees, noise levels, work regulations, lighting, air circulation, and security. While the work engagement measurement instrument adopted the instrument developed by Schaufeli et al. (2002) which consisted of 16 measurement instruments of three indicators namely: vigor, dedication, and absorption. Meanwhile, to measure self-efficacy, researchers adopted an instrument developed by Bandura (1995) which included three indicators of self-efficacy measurement, namely: magnitude, generality, and strength. Furthermore, the last, measurement of workload using an instrument developed by Leiter & Maslach (2004) which consists of 10 measurement instruments.

From the results of the test validity and reliability of the instrument, it appears that all of the instruments measuring this research variable are valid and reliable, making it feasible to be used as a measurement tool. The instrument validity test was performed using Factor Analysis with the Factor Loading indicator. The questionnaire question is said to be valid when the Factor Loading value> 0.50. In addition, indicator items will also be said to be valid when the Kaiser-Meyer-Olkin (KMO) value for each variable is ≥ 0.5. The KMO value for the four variables also fulfilled the requirements with a value of ≥ 0.5. So, it can be concluded that all variables and indicator items in this study are said to be valid which means that the questions in the questionnaire are able to explain what is measured by the questionnaire.

While the instrument reliability testing is carried out to test the consistency, stability, predictive power and accuracy of a questionnaire. Questionnaire items are said to be reliable when the Cronbach's Alpha value> 0.6 and the question items that make up the variable have a corrected item-total correlation value> 0.3. Based on the results of reliability testing, it appears that all variable items have a Cronbach's Alpha value> 0.6 and the whole question item has a corrected item-total correlation value> 0.3, so it can be said that all the variables in this study are reliable. The results of the analysis of the validity and reliability of the research instruments are presented in the following tables 1 and 2 (Table 1).

After all the instruments have been tested as valid and reliable, the data analysis used to test the research hypothesis is multiple linear regression analysis using the Moderated Regression Analysis (MRA) method. MRA is used to determine whether the variable self-efficacy and workload variables become significant moderator variables on the influence of the work environment on work engagement. MRA uses an analytical approach that maintains sample integrity and provides a basis for controlling the influence of moderator variables (Table 2).

Results and Discussion

Simple Linear Regression Analysis Results

Simple linear regression analysis in this study was used to determine the magnitude of the influence of the work environment on work engagement. Table 3 below shows the results of simple linear regression analysis to determine the relationship between the work environment as an independent variable and work-engagement as a dependent variable (Table 3).

Regression results are considered feasible if the significant number in the ANOVA table has a value <0.05. The results of the analysis, as presented in the table above show that the significant number is at a value <0.05. This shows that the work environment variable has a significant influence on the workengagement of hotel employees where this study was conducted. From the results of the hypothesis analysis in Table 3, it can be seen that hypothesis 1 (H1) of the study is supported, with an effective value of 0.861 significant at the level of 0.001.

These results support several previous studies such as Anitha (2013) who found that the work environment has a large influence on employee engagement. This study examines managers in small and medium-sized businesses in India who are in lower and middle management positions. Together with relationships with colleagues/teams, the influence of the work environment on employee engagement is able to explain 67.2% of the variation in employee engagement of managers (r2, 0.672). This shows that a conducive work environment is actually able to influence employee engagement. In other terms, employee engagement is the result of various aspects that exist in the work environment.

This study also confirms the results of previous studies from Harter, Schmidt, and Hayes (2002); May, Gilson, & Harter (2004); and Rich, Lepine, & Crawford (2010) who found that the work environment was a significant factor affecting the level of employee engagement. This can be explained because if management maintains and develops a supportive and conducive work environment, companies usually practice practices that care about the needs and feelings of their employees, provide positive feedback and encourage employees to voice their desire to develop new skills that will encourage them to be better able to overcome work problems (Deci & Ryan, 1987).

In the context of hotel employees in Malang, the working environment perceived by employees is in a good category, so that in accordance with previous research findings, a good work environment is an aspect that supports the work involvement of hotel employees in Malang.

Moderated Regression Analysis (MRA)

The moderated regression analysis (MRA) method is used to determine whether the self-efficacy variable and the workload variable become significant moderator variables on the influence of the work environment on workengagement. Table 4 below shows the results of the MRA analysis to determine the effect of moderation from the self-efficacy and workload variables on the relationship of the work environment to work-engagement (Table 4).

The self-efficacy variable gives a parameter coefficient in the form of T-count of -1.950 with a significance level of 0.053 (> 0.05). Meanwhile, the workload variable gives a parameter coefficient in the form of T-count of -2.756 with a significance level of 0.007 (≤ 0.05). From the results of the analysis, it can be said that workload has a moderating influence on the relationship of the work environment and work-engagement. While the MRA test results on the effect of self-efficacy moderation indicate that self-efficacy does not have an effect as a moderating variable on the relationship of work-environment and workengagement.

a. The moderating effect of self-efficacy

This analysis is used to determine whether the self-efficacy variable is able to be a significant moderator variable on the influence of the work environment on work-engagement. The analysis shows that 1 (Work environment Work Engagement) is significant (0,000), 2 (Self Efficacy Work Engagement) is significant (0,000). However, when the work environment is interacted with self-efficacy to test the effects of self-efficacy moderation, the results are not significant (3 = 0.053> 0.05). From the results of this test, it appears that the second hypothesis is not supported. This means that the hotel staff's selfefficacy does not become a moderating variable of the influence of the work environment on hotel employee work engagement in Malang.

This shows that the self-efficacy variable in the pattern of the relationship between work environment and work-engagement functions as a moderating predictor (Arnold, H, 1982), meaning that the self-efficacy variable only plays a predictor (independent) variable in the relationship model formed in the study this. A variable can become pure moderation if the pattern of influence between the independent variable and the dependent variable is not significant, and after adding it to the moderating variable the effect between the independent and dependent variable becomes significant.

This can be seen from the results of the linear regression analysis in Table 1 which shows that independently, self-efficacy does significantly influence the work engagement of hotel employees. The effect of self-efficacy on work engagement is also quite large. If judging from the results of this analysis it appears that self-efficacy is more appropriate to be observed as a variable causing works engagement as suggested by several previous researchers (Bakker et al., 2014; Makikangas et al., 2013; Xhantopoulou et al., 2009; Halbesleben, 2010) which generally found that self-efficacy and various other individual factors were positively related to work engagement. This explains that if individuals have personalities who believe that they are able to overcome problems, then they will have a way to adapt and be able to minimize the negative impacts of their work environment.

However, the findings of this study are quite interesting, that when self-efficacy interacts with the work environment, the effect on work engagement becomes negative, although the results are not significant. This indicates that although a hotel employee who has confidence that he is able to complete the job well if they interact with colleagues, supervisors, and also the physical working environment they experience, it will affect the work engagement. Here it is seen that external factors of a person have a large enough influence to change oneself, especially the work environment. Surely this finding is interesting to be further confirmed in other future studies both in the context of hotels and other industries.

b. Workload moderation effect

From the results of testing the hypothesis of the influence of moderation in Table 4, it shows that the effect of moderating workload is significant for the influence of the work environment on work engagement. From these results, it can be concluded that hypothesis 3 of the study is supported. The direction of influence of workload moderation is negative. That is, the workload can reduce the positive influence of the work environment on work engagement.

The results of this study are in line with the findings of previous studies which found that workload will indeed independently influence the reduction of individual work engagement (Bakker et al., 2014; Christian et al., 2011; Halbesleben, 2010). Although in the context of their research, the workload that enters the realm of job demands affects burnout (fatigue) at work rather than work engagement. However, these studies also found other facts that job demands, including workloads, can reduce employee engagement.

Lee and Ashforth (1996) also found in their research on the context of human service providers (teachers, nurses, police, consultants, and social workers) that workload, stressful events, work pressure, role conflict, role ambiguity, role conflict and role stress will be causing burnout, especially when employees do not get social support and have a good relationship with supervisors. Whereas if they have good social support (relationships with coworkers), support from superiors, and also regularly receive positive feedback (reflecting the existence of a conducive working environment), then burnout will not occur, despite workloads, emotional demands, their physical demands are high (Bakker et al., 2005). From the findings of this study and some previous research findings, it can be seen that the workload is indeed able to reduce the positive influence of the work environment on the work engagement of hotel employees in Malang.

Even so, the results of the analysis also show that the workload variable only functions as a quasi-moderator or pseudo moderator (Arnold H, 1982). This means that the workload variable has a role as a variable that moderates the effect of the work environment on work engagement, and at the same time acts as a predictor variable (independent) that has an influence on the independent variable (work-engagement).

Conclusions and Suggestions

From the results of the following research analysis and discussion, it appears that the work environment has a significant positive effect on work engagement, so the first hypothesis is supported. In addition, the results of the study also showed that self-efficacy and workload have a significant influence on work engagement partially. Even if analyzed using MRA, only the workload variable can significantly reduce the positive influence of the work environment on work engagement. Although the influence of workload moderation is also just a quasi-moderator. Therefore, only hypothesis 3 of the study is supported. While hypothesis 2 is not supported.

Based on the results of this research discussion, it is recommended for further research to confirm the effects of workload moderation on the influence of the work environment on employee work engagement in both the hospitality context and other contexts. The next suggestion is to use the JDR (Job Demands and Job Resources) framework as a work engagement research framework because by using this framework, future research can better capture whether it is true that job resources are able to reduce the effect of negative job demands on work engagement.

Ethical Statements

Funding: Not applicable

Compliance with Ethical Standards

Conflict of interest: The authors declare that they have no conflict of interest.

Human and Animal Rights: This article does not contain any studies with human or animal subjects performed by any of the authors.

Informed Consent: Informed consent was obtained from all individual participants included in the study.

Availability of data and material: Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Code availability: Not applicable

References

Alarcon G. 2011. A meta-analysis of burnout with job demands, resources, and attitudes. J. Vocat. Behav. 79:549-62.

Anitha J. (2013). International Journal of Productivity and Performance Management Determinants of employee engagement and their impact on employee performance. International Journal of Productivity and Performance Management Leadership &amp Organization Development Journal Journal of Managerial Psychology, 63(3), 308–323. https://doi.org/10.1108/IJPPM-01-2013-0008.

Armstrong, M. 2009. Armstrong’s Handbook of Human Resource Management Practice. 11thedition. United Kingdom: Kogan Page.

Arnold H., (1982) Moderator Variables, A Clarification on Conceptual, analytic and psychometric issues. Organizational Behavior and Human Performance, 29, 1943-1974.

Bakker AB, Demerouti E, Euwema MC. 2005. Job resources buffer the impact of job demands on burnout. J. Occup. Health Psychol. 10:170-80.

Bakker, A.B., Demerouti, E., Sanz-Vergel, A.I. 2014. Burnout and Work Engagement: The JD-R Approach. Annu. Rev. Organ. Behavior, 1: 389-411.

Bandura, A. 1995. Self-Efficacy in Changing Societies. Cambridge: University Press DeFreese, J. D. & Alan L. Smith. 2013. Areas of Worklife and the Athlete Burnout- Engagement Relationship, Journal of Applied Sport Psychology, 25:2.

Christian MS, Garza AS, Slaughter JE. 2011. Work engagement: a quantitative review and test of its relations with task and contextual performance. Pers. Psychol. 64:89-136.

Gallup, G. 2014. State of The Global Workplace: Employee Engagement Insights for Business Leaders Worldwide. Gallup Survey Report: 1-34.

Gartner, W.B. and Murphy, M.R. Concepts of workload. In Hartman, B.O. and McKenzie, R.E. (Eds.). 1979. Survey of methods to assess workload. AGARD-AG-246.

Gawron, Valerie J., 2008. Human Performance, Workload, and Situational Awareness Measures Handbook. Boca Raton: Taylor & Francis.

Greenglass, Esther R., Ronald J. Burke, & Lisa Fiksenbaum. 2001. Workload and Burnout inNurses. Journal of Community and Applied Social Psychology, vol. 11, 211-215.

Halbesleben JRB. 2010. A meta-analysis of work engagement: relationships with burnout, demands, resources, and consequences. See Bakker & Leiter 2010, pp. 102-111.

Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-Unit-Level Relationship Between Employee Satisfaction, Employee Engagement, and Business Outcomes: A Meta-Analysis. Journal of Applied Psychology, 87(2), 268–279. https://doi.org/10.1037//0021-9010.87.2.268.

Hewitt A. 2017. 2017 Trends in Global Employee Engagement, (Online), (http://www.aon.com/unitedkingdom/attachments/trp/2017-Trends-in-Global-Employee-Engagement.pdf).

Imperatori, B. (2017). Engagement and Disengagement at Work Drivers and Organizational Practices to Sustain Employee Passion and Performance (First). Springer. https://doi.org/10.1007/978-3-319-51886-2_1.

Kahn, W. A. 1990. Psychological Conditions of Personal Engagement and Disengagement at Work. Academy of Management Journal, (Online), 33 (4):692-724.

Kaswan. 2017. Psikologi Industri & Organisasi: Mengembangkan Perilaku Produktif dan Mewujudkan Kesejahteraan Pegawai di Tempat Kerja. Bandung: Alfabeta.

Kreitner, R. & Kinicki, A. 2014. Organizational Behavior. Jakarta: Salemba Empat Leiter, M. P.,&Maslach, C. 2004. Areas of worklife: A structured approachtoorganizational predictors of job burnout. In P. L. Perrewe & D. C. Ganster (Eds.), Research in occupational stress and wellbeing. Oxford, UK: Elsevier.

Lee RT, Ashforth BE. 1996. A meta-analytic examination of the correlates of the three dimensions of job burnout. J. Appl. Psychol. 8:123-33.

Luthans, F. 2006. Perilaku Organisasi. Edisi 10. Yogyakarta: Andi.

Macey, W. H., & Schneider, B. (2008). The Meaning of Employee Engagement. Industrial and Organizational Psychology, 1(January), 3-30. https://doi.org/10.1111/j.1754-9434.2007.0002.x.

Mäkikangas A, Feldt T, Kinnunen U, Mauno S. 2013. Does personality matter? Research on individual differences in occupational well-being. In Advances in Positive Organizational Psychology, Vol. 1, ed. AB Bakker, pp. 107–43. Bingley, UK: Emerald.

Rich, B. L., Lepine, J. A., & Crawford, E. R. (2010). Job Engagement : Antecedents and Effects on Job Performance. Academy of Management Journal, 53(3), 617-635.

Schaufeli, W., dkk. 2002. The Measurement of Engagement and Burnout: A Two Sample Confirmatory Factor Analytic Approach. Journal of Happiess Studies, (Online), 3: 71-92

Schaufeli, W.B., Martinez, I.M., Pinto, A.M., Salanova, M., & Bakker, A.B. 2002. Burnout and Engagement in University Students: A Cross-National Study. Journal of Cross-Cultural Psychology: 33: 5:464-481.

Sedarmayanti. 2009. Sumber Daya Manusia dan Produktivitas Kerja. Bandung: CV Mandar Maju.

Sunyoto, D. 2015. Penelitian Sumber Daya Manusia Teori, Kuesioner, Alat Statistik, dan Contoh Riset. Jakarta: CAPSWursanto, I. 2005. Dasar-Dasar Ilmu Organisasi. Edisi II. Yogyakarta: Andi.

Xanthopoulou D, Bakker AB, Demerouti E, Schaufeli WB. 2009a. Reciprocal relationships between job resources, personal resources, and work engagement. J. Vocat. Behav. 74:235-44.

Author Info

Received: 05-Jan-2023 Accepted: 06-Feb-2023 Published: 13-Feb-2023