The Mediating Role of Job Satisfaction on Gen Z Employees Turnover Intention

ABSTRACT


INTRODUCTION
According to Badan Pusat Statistik (2020), generation Z is classified as residents born in the range 1997-2012, occupying the highest composition with a percentage of 27.94% compared to other generations.In Indonesia, employment has begun to be filled by workers from Generation Z, who are also predicted to dominate the workforce as well as being the foundation for organizations and the nation when experiencing a demographic bonus in 2030 and can be categorized as an opportunity to accelerate economic growth because they are at their productive age (Tamengkel & Rumawas, 2022).
Based on turnover intention survey data from 2019-2020 by Mercer (2022), workers in Indonesia who make voluntary turnover were at 8.3% in 2019, which is the highest percentage from the data, then in 2020, at a percentage of 6.3% which is the second highest level after Vietnam which is at a percentage of 7.3%.Workers in Indonesia who make voluntary turnover are at a percentage of 5.0% in 2019, then face a two-fold increase in 2020, which is at 10.8%.
The drastic increase in turnover intention in 2020 was caused by the outbreak of the COVID-19 pandemic, which spread to Indonesia and several other countries, thus affecting all lines of human life, including in the economic sectors (Lulu et al., 2021).According to Yuniasanti, Binti Abas, and Hamzah (2019), high employee turnover intention can affect and reduce employee performance.The stronger the employee's inclination to relocate, the higher costs should the company brace, both in hiring and training new employees.However, according to Deloitte (2022), Gen Z tends to change jobs relatively quickly and at a higher rate than previous generations.This is evidenced by 40% of Gen Z respondents choosing to switch jobs within two years and 35% of Gen Z respondents even willing to leave their current jobs even if no alternative employment is available.Many reasons lead to turnover intention among employees, including business factors such as financial situation, promotion system, type of management, career planning, fairness in the distribution of compensation, workload, organizational environment, work stress, depression, fatigue, and the effect it has on job satisfaction.Therefore, it becomes imperative to investigate the factors influencing turnover intentions, especially among the dominant Generation Z workforce (Dalgic & Akgunduz, 2022).
Therefore, this study aims to research the relationship between work stress, workload, and employee turnover intentions, which tend to have an indirect relationship with job satisfaction; given the limited research on turnover intention among Generation Z employees, the research that will be conducted aims to explore the impact of work stress and workload on turnover intentions with job satisfaction as a mediation role in Generation Z employees.

Research Design
The research to be conducted is the causal-comparative research type.Based on Maheshwari et al.'s causal-comparative research, it is a research problem formulation that seeks to inquire about the relationship between two or more variables.In this research, there are independent variables, dependent variables, and mediating variables (Namazi, 2016).
Based on the level of problems in this study, there is a causal relationship between work stress and workload on the dependent variable, employee turnover intentions, and job satisfaction to mediate the relationship between the independent and dependent variables.

Population and Sample
The target population for this study is the Z-generation workforce.The researcher used the J. F. J. Hair et al. (2014) method, namely 1:10, which means that 10 respondents' answers represent 1 statement.Therefore, the number of statements in this study is 41, with a minimum of 410 respondents.422 questionnaires will be distributed to avoid data errors or misunderstandings.In this case, the researcher selects a sample according to the following criteria: (1) Indonesian Citizen (WNI), (2) has an age range of 18-26 years, and (3) an employee.Therefore, some of the items analyzed in this study have a relationship with the IJEMI e-ISSN:2716-2338

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Lim & Dini (The Mediating Role of Job Satisfaction on Gen Z Employees Turnover Intention) impact of work stress and workload on turnover intention with job satisfaction as a mediation role in Generation Z employees in Indonesia.

Data Collection Techniques
The data collection instrument in this study was distributing questionnaires online using Form, which would then be transferred again to Excel to re-examine the results of the data that had been received; this method is also employed by (Masykuroh & Muafi, 2021) (Irawanto et al., 2021) and (Rahma et al., 2021).

Data Analysis Techniques
According to Anees et al. (2020), this method is a two-step process involving measurement evaluation and structural model assessment.In this study, the researcher Therefore, the method for validating measurement models and testing hypotheses and analysis in this research will use the Partial Least Square-Structural Equation Model (PLS-SEM) Version 3.2.9application since it was considered more appropriate in the phase of developing theories regarding potential relationships between variables and indicator variables (Astrachan et al., 2014).

RESULTS AND DISCUSSION
In conducting the hypothesis testing to examine the relationships between variables in a research model, data will be collected from 422 respondents (176 men and 246 women) by distributing questionnaires online on social media.Data dissemination and collection was carried out within a period of 3 months from March to May 2023, with a total of 301 people as workers, 88 people as civil servants, and 33 people as entrepreneurs.
PLS-SEM is used because this research focuses on predicting endogenous variables.First, the measurement model must be evaluated by examining internal consistency, convergent validity (CV), and discriminant validity (DV) (J.F.Hair et al., 2017).This evaluation was carried out using a composite reliability score (CR).This study shows that the CR scores of all constructs exceed 0.700, indicating high internal consistency of the scale used in this study (Shuttleworth, 2014).Next, factor loadings and average variance extract (AVE) were measured to evaluate the CV construct.CV is the extent to which a variable is positively associated with alternative measures of the same construct (Perry Hinton, 2017).Factor loadings must be 0.708 or greater, and 0.700 must be considered sufficiently suitable.The scale value of 0.500 must also be fulfilled by the AVE score of all constructs, thus indicating that the CV is acceptable.

a. Model Measurement
Discriminant validity (DV) shows how much a construct differs from other constructs according to empirical standards (Larcker, 1981).The DV test in this analysis is assisted by Fornell and Larcker's guidelines, which note that the square root of the meaning of AVE must be greater than the association with the squares of other constructs (J.F.Hair et al., 2017).The DV results will be shown in Table 2. square root for each construct is greater than the correlations between constructs in the model (Larcker, 1981).Based on the data processing table above, the results of the discriminant validity test are valid and meet the criteria.

b. Structural Model Test
J.F. Hair et al. (2017) stated that the importance of a study's direct and indirect impact was tested by utilizing the bootstrapping feature on SmartPLS.To produce t-values and standards to validate statistical validity, the bootstrapping procedure was carried out for 5,000 interactions.Bootstrapping makes no claims about the side distribution of the data or the shape of the distribution of the variables in comparison; it can also be used using a finite sample size (Fauzi, 2022).The values in bootstrapping show the direction and influence of each latent variable on one another.The structural model test results show that in hypothesis 1, the influence of work stress on turnover intention among Gen Z is significant.This is evident from the mean value of 0.774 and p-value of 0.000.This research indicates that work stress can indeed affect employee's desire to change jobs.The same findings were also shown by reference (Lebang & Ardiyanti, 2021).
In Hypothesis 2, it is evident that the influence of work stress on job satisfaction among Gen Z is significant.This is supported by a mean value of 0.167 and a p-value of 0.007.This indicates that work stress can indeed affect employees' job satisfaction.In their study, Prilia Diah Nita ( 2022) also stated that work stress positively influences employee job satisfaction.
In hypothesis 3, the relationship between workload and turnover intention among Gen Z employees has no significant effect.This is indicated by the mean value of -0.020 and p-value of 0.680.Workload does not significantly impact turnover intention, suggesting that workload is not a primary factor affecting employee's decisions to change jobs.Previous research by Wibowo Akbar et al. (2021) also revealed that workload did not significantly influence turnover intention.
In hypothesis 4, the influence of workload on job satisfaction among Gen Z is considered significant due to a mean value of 0.127 and p-value of 0.048.Therefore, this result indicates a significant relationship between workload and job satisfaction among Gen Z employees.
Physical workload can lead to fatigue, work errors, and decreased productivity.In hypothesis 5, the results of the direct effect test indicate that job satisfaction significantly influences turnover intention among Gen Z, with a mean value of 0.133 and p-value of 0.000.Therefore, job satisfaction significantly impacts turnover intention among Gen Z employees.Research by Fajar et al. (2022) also proves that workload negatively and significantly affects job satisfaction.

c. Test the Mediation Variable
This study uses bootstrapping on the SmarPLS application to test the significance of the indirect effect and confirm the mediation of job satisfaction in the relationship between work stress, workload, and employee turnover intentions.Table 4 shows that job satisfaction significantly mediates work stress on employee turnover intentions.In contrast, job satisfaction cannot significantly mediate the relationship between workload and employee turnover intentions.

H6
Work Stress -> Job Satisfaction -> Turnover Intention 0,021 2,843 0,005 Significant H7 Workload -> Job Satisfaction -> Turnover Intention 0,018 1,489 0,137 Insignificant In hypothesis 6, the influence of work stress on turnover intention with job satisfaction as a mediating variable is considered significant.This is evident from the mean value of 0.021 and p-value of 0.005.In this study, job satisfaction mediates the relationship between work stress and turnover intention.This is because as work stress increases, job satisfaction tends to decrease, which can lead to a higher level of turnover intention among employees.These results indicate the same findings as the study conducted by Lebang Ardiyanti (2021) but are the opposite of the study conducted by (Prasetio et al., 2019).
In Hypothesis 7, the influence of workload on turnover intention with job satisfaction as a mediating variable is deemed insignificant, with a mean value of 0.018 and a p-value of 0.137.
In this study, the role of job satisfaction is considered unable to mediate the relationship between workload and turnover intention.This is because a high workload does not necessarily impact job satisfaction among employees and does not necessarily lead to an intention to change jobs.Therefore, high workload, affecting job satisfaction, is not considered the primary reason why Generation Z employees have a desire to switch jobs; these results indicate the same finding as the study conducted by (Fajar et al., 2022) and (Prilia Diah Nita, 2022).

d. Test the Coefficient of Determination
By the criteria of J.F. Hair et al. (2017), the R squares value is categorized as vital if it is more than 0.75, moderate if it is less than 0.50, and weak if it is less than 0.25.

CONCLUSION
Based on 422 respondents whom Generation Z employees filled in, the results of this study indicate that work stress significantly affects employee turnover intentions and job satisfaction.
The workload does not significantly affect employee turnover intentions, which means workload is not the main factor influencing employees' decisions to change jobs.However, workload significantly affects job satisfaction, implying that a high workload without good feedback can lead to low employee performance satisfaction.Job satisfaction is stated to significantly influence employee turnover intentions, signifying that if employees feel dissatisfied with their work, it can be a reason for employee turnover intentions to occur.
Job satisfaction is also a mediating variable in the relationship between work stress and workload on employee turnover intentions.This can happen because the higher the job stress, the lower the job satisfaction, causing a high intention of employee turnover.However, job satisfaction cannot mediate the relationship between workload and employee turnover intentions because high workloads do not necessarily affect employee job satisfaction, which impacts employee turnover intentions.Therefore, workload is not one of the reasons

5.
e-ISSN: 2716-2338 IJEMI Vol.4,No.3, September 2023, pp.243~253 employs the Structural Equation Model (SEM) statistical method to analyze the correlation between variables, between variables and indicators, and direct measurement errors to obtain a comprehensive model representation.SEM has two types: Covariance-Based Structural Equation Modeling (CB-SEM) and Partial Least Square Path Modeling (PLS-SEM).
choose to change jobs.The test results show a low R Square value, which is 0.073 or 0.73%.This means that other variables outside of this study influence job satisfaction by 99.27%.

Table 1 .
Model Measurement (Factor Loadings, Composite Reliability (CR), and AverageBased on the processed questionnaire data, 37 question indicators from the variables are considered valid, while 5 question indicators from the variables are categorized as invalid.This is because the factor loading values for these indicators did not reach the threshold of 0.6, and removing these variables was necessary to preserve the overall data quality.Specifically, for job satisfaction, the outer loading was as follows: Job satisfaction 2 had a loading of 0.587, job satisfaction 3 had a loading of 0.570, job satisfaction 4 had a loading of 0.216, job satisfaction 11 had a loading of 0.173, and job satisfaction 15 had a loading of 0.478.Therefore, the results of this model measurement test exclude these five question indicators that were deemed invalid.
Joseph F. Hair Jr et al. (2014)of Job Satisfaction on Gen Z Employees Turnover Intention)As for the results for each tested variable, an average variance extracted (AVE) value was obtained that meets the convergent validity standard.According toJoseph F. Hair Jr et al. (2014), the convergent validity scale can be assessed through AVE, and the AVE threshold value is expected to be at least less than 0.5.Therefore, based on the data analysis results, it can be concluded that each variable has met the convergent validity standard.

Table 3 .
Structural Model Test Results

Table 5 .
Coefficient Determination Test ResultsTable5shows that the R squares value for the endogenous variable of job satisfaction is 0.073, which means that Work Stress and Workload can explain job satisfaction by 0.73%.In comparison, the remaining 99.27% is explained by other variables not included in the model.243~253 included in the model.Therefore, if, according to the criteria of previous researchers, an R squares value of more than 0.75 indicates a prediction result in the strong category, this endogenous variable is categorized as vital.
The R squares value for the endogenous variable employee turnover intention is 0.648, which means that Work Stress and Workload can explain the employee turnover intention variable by 64.8%.In comparison, the remaining 35.2% is explained by other variables not IJEMI Vol.4,No.3, September 2023, pp.

Table 6 .
Quality Index Test ResultsBased on Table6, the calculation of the quality index test obtained GoF results of 0.493, meaning the value is greater than 0.36.Therefore, this value is categorized as a strong or large model fit.The following is the result of calculating the Goodness of Fit Index (GoF) using the