International Journal of Human Capital Management, Vol. 2 (2), December 2018 International Journal of Human Capital Management, Vol. 7 (1), June 2023 86 | P a g e International Journal of Human Capital Available online at Management http://journal.unj.ac.id/unj/index.php/ijhcm E-ISSN 2580-9164 Vol. 7, No. 1, June 2023, p 86-103 FACTORS INFLUENCING EMPLOYEE’S WELL-BEING AND JOB PERFORMANCE: THE PERSPECTIVE OF STATE-OWNED ENTERPRISE EMPLOYEE Muhammad Ihsan Mustika Universitas Indonesia Muhammad.ihsan15@ui.ac.id Fanny Martdianty Universitas Indonesia fanny.martdianty@ui.ac.id ABSTRACT State-Owned Enterprises (SOEs) play a crucial role in ensuring stability and control in Indonesia's economy, especially before and after the COVID-19 pandemic. The pandemic COVID- 19 has accelerated the digitization of public and private sector activities in Indonesia and other countries. To adapt to the accelerated digitization caused by the pandemic, SOEs must continue to grow and develop to achieve their targets and goals. The intended goal of this study is to inquire into the impact of technostress, perceived organizational support (POS), total reward systems (TRS), and work-life balance (WLB) on job performance, as mediated by employee well-being (study of SOEs employee). This research employs a quantitative approach to investigate the direct and indirect impacts of the dependent variable through the utilization of the Structural Equation Modelling (SEM) technique. The study focuses on a sample of 263 respondents who are employees of State-Owned Enterprises (SOEs). This research highlights the role of perceived organizational support as a key driver of job performance mediated by employee well-being. The findings emphasize the significance of effectively engaging all generations, particularly Generation Y and Generation Z, within SOEs to strengthen job performance and accomplish organizational success. Furthermore, the study uncovers that employee well-being acts as a full mediator in constructing the connection between the variables under consideration and job performance. This finding emphasizes the importance for companies to continuously maintain perceived organizational support, ensuring that employees feel their well-being is being taken care of and their contributions are valued, especially for the younger generations (Generation Y and Z) who are the successors within the company. Keywords: Employee Well-Being, Job Performance, Perceived Organizational Support, Technostress, Total Reward Systems, Work-Life Balance Received: 5 May 2023 Accepted: 19 June 2023 Publish: June 2023 http://journal.unj.ac.id/unj/index.php/ International Journal of Human Capital Management, Vol. 7 (1), June 2023 87 | P a g e How to Cite: Mustika, M.I, & Martdianty, F. (2023). Factors Influencing Employee’s Well-Being and Job Performance: The Perspective of State-Owned Enterprise Employee. International Journal of Human Capital Management, 7 (1), 86-103. https://doi.org/10.21009/IJHCM.07.01.7 INTRODUCTION State-Owned Enterprises (SOEs) play a crucial role in ensuring economic control and stability in Indonesia, both before and after the COVID-19 pandemic (Kementrian BUMN, 2021). The pandemic has accelerated digitalization efforts globally, necessitating SOEs to adapt and undergo digital transformation to meet the evolving demands of the digital era (Deloitee, 2020; OECD, 2020). Sun et al. (2022) added that SOEs are a key pillar of a country's economy, and the implementation of exceptional development has an immediate impact on the reforming process of the SOEs. Under the leadership of Erick Thohir, the Minister of State-Owned Enterprises, the reform of SOEs has gained prominence, aiming to streamline operations and align them with the demands of the digital era performance (Liputan 6, 2022; Medcom, 2021). In this dynamic landscape, optimizing performance, increasing productivity, and fostering innovation are crucial for SOEs to achieve quality development and maintain healthy business competition. Understanding the factors that influence employee well-being and job performance within the context of SOEs becomes paramount. This paper explores key elements that shape job performance in SOEs, including technostress, perceived organizational support, work-life balance, and total reward systems. Organizational performance, which is the accumulation of individual performance, can be negatively affected by negative relationships in its implementation process and positively affected by the process of achieving organizational goals. A substantial amount of research has been performed to understand the factors affecting job performance, including the effects of excessive technology use that can lead to technostress(Singh et al., 2022; Spagnoli et al., 2020), perceived organizational support (POS) (Jeong & Kim, 2022; Zhang et al., 2022), work- life balance (Abdirahman et al., 2020; Rahim et al., 2022), and total reward systems (TRS) that are obtained from work(Gbande, 2016; Rai et al., 2019; Tarigan et al., 2022). The changes in work styles and digitization faced by every company in Indonesia require SOEs companies to be able to keep up and adapt to these changes. Technostress, which arises from excessive technology use, has emerged as a critical factor impacting job performance and employee well-being. As digital technology becomes increasingly integrated into work environments, employees may experience anxiety, fatigue, and decreased productivity(Spagnoli et al., 2020). Mitigating technostress and providing necessary support to prioritize the mental and psychological health of the workforce is essential for SOEs. Under these circumstances, companies must make their best efforts to maintain the mental and psychological health of their employees. Perceived organizational support (POS) is defined by Karim et al. (2019) as a person's impression of how well their organization is concerned for their welfare and endorses their efforts as employees. With the presence of perceived organizational support, companies can show their concern for their employees, so that employees are not burdened with the work and work environment they face. When employees believe that their organization cherishes their efforts and is concerned about their welfare, it leads to increased employee well-being (Wojtkowska et al., 2017), and improved job (Jeong & Kim, 2022; Zhang et al., 2022). Cultivating a supportive culture that enhances POS should be a focus for SOEs to nurture employee well-being. The changes in work style caused by digital transformation also need to be followed by the benefits or total rewards that employees will receive. SOEs should prioritize developing comprehensive total reward systems programs that are linked with business objectives to foster a International Journal of Human Capital Management, Vol. 7 (1), June 2023 88 | P a g e sense of appreciation and gratitude among employees. Total reward systems (TRS) obtained in a job are also one of the factors that affect employees (Tarigan et al., 2022). Gbande (2016) concludes that total reward systems (TRS) are not only important for productivity improvement, but also affect employee job satisfaction. The COVID-19 pandemic and ongoing digital transformation have led to the emergence of a hybrid work style. Remote work has become normal, work and family matters cannot be separated. Maintaining a healthy work-life balance is another critical aspect influencing employees by fostering a work-life balance culture, SOEs can empower their employees to achieve optimal performance while promoting overall well-being (Hoque et al., 2022; Rahim et al., 2022). On the other hand, Employee well-being is a pivotal determinant in enhancing employee performance (Boulet & Parent-Lamarche, 2022; Lee et al., 2021; Peccei & Van De Voorde, 2019). Notably, Lee et al. (2021) stress that subjective well-being, as a critical indicator of employee well- being, has a positive and substantial link with job performance among Taiwanese and mainland Chinese employees. Moreover, Juchnowicz and Kinowska (2021) emphasize that employee well- being encompasses a state of feeling content, healthy, and happy, permeating all aspects of life, including work activities and job functions that hold significant value. Peccei & Van De Voorde (2019) further elucidate that employee well-being yields positive effects on affective commitment, job satisfaction, and overall organizational performance. In conclusion, as SOEs in Indonesia navigate digital transformation and pursue ongoing business reforms, strategic human resource management strategies are instrumental in driving performance and ensuring employee well-being. Addressing factors such as technostress, perceived organizational support, work-life balance, and total reward systems enables SOEs to create a conducive environment that fosters innovation, productivity, and sustainability. However, when dealing with new-generation employees who have higher interest expectations (Wang et al., 2022), more sensitive psychological constructions (Zhou & Qian, 2021), and further down the road, practical management expertise is still insufficient. This has resulted in an increasing gap between new-generation employees and other generations (generation gap). Additionally, Yu et al. (2022) explained that current research focuses on variables that have a positive impact on the behavior of new-generation employees, such as work-life balance (Harunavamwe & Ward, 2022)and well-being (Harunavamwe & Ward, 2022; Wojtkowska et al., 2017), and there is a lack of systematic research on variables that may have a negative impact on their behavior, such as technostress (Singh et al., 2022) and others. To be able to improve, develop, maintain, and acquire digital talents in achieving company targets and objectives, researchers want to understand what factors influence the well-being and performance of state-owned enterprise (BUMN) employees and whether there are differences in perspectives among generations regarding these factors. Therefore, in this study, researchers want to analyze whether technostress, work-life balance (WLB), perceived organizational support (POS), and total reward systems (TRS) affect job performance mediated by employee well-being for SOEs employees. In the section that follows, each variable used to generate the hypotheses is reviewed in the literature. The quantitative strategy employed in this study is then described in the procedure section. The hypothesis testing procedure is then outlined in the findings and discussion section. The conclusion section summarizes the study's findings, ramifications, drawbacks, and recommendations for further research. LITERATURE REVIEW Technostress, Perceived Organizational Support, Total Reward Systems, Work-Life Balance, and Job Performance Over the last decade, there has been a surge in research interest in technostress (Harunavamwe & Ward, 2022; Singh et al., 2022; Spagnoli et al., 2020; Tarafdar et al., 2015, 2019; Tarafdar & Stich, 2021). In general, stress has been investigated as the outcome of a International Journal of Human Capital Management, Vol. 7 (1), June 2023 89 | P a g e discrepancy among external requirements, personal talents, and the ability to fulfill those requirements (Tarafdar et al., 2011). Research on technostress in organizational contexts is extremely valuable because of its relationship to productivity (Tarafdar et al., 2019) and technology-related job performance (Cahapay & Bangoc II, 2021; Day et al., 2012; Saidy et al., 2022; Tarafdar et al., 2015). H1: Technostress has a negative effect on job performance. Perceived organizational support, as stated by Eisenberger et al. (1986) is related to employees' general impressions of their belief that the company recognizes their contributions and cares about their wellness. Perceived organizational support was defined by Karim et al. (2019) as an individual's view of how significantly an organization cares about its welfare and what it cherishes in its contributions. Several studies have found that perceived organizational support has an impact on organizational work performance (Jeong & Kim, 2022; Zhang et al., 2022). H2: Perceived Organizational Support has a positive effect on job performance. According to Armstrong (2014), a total reward system is a holistic approach to rewarding employees. It involves a combination of various types of rewards, including both financial and non-financial rewards, designed to motivate, retain, and enhance employee performance. A comprehensive rewards system practice can increase the overall effectiveness of recognition and reward programs. Compared to individual reward systems, total reward systems have a stronger impact on individual employees and organizations (Rai et al., 2019; Tarigan et al., 2022). Tarigan et al. (2022) discovered that implementing the total rewards system had a good effect on the model's outcome. H3: Total reward systems have a positive effect on job performance. Organizations must ensure that workers have enough time to complete their duties to their families and their jobs (Abdirahman et al., 2020). Work-life balance is defined Fisher-McAuley et al. (2003) as an individual's attempts to balance the two or more roles that are being played. According to the findings of their research, Hoque et al. (2022) highlighted that work-life balance improves employee performance. Rahim et al. (2022) agree that the work-family culture, as part of the work-life balance, has a favorable impact on personnel job performance. H4: Work-life balance has a positive effect on job performance. Technostress, Perceived Organizational Support, Total Reward Systems, Work-Life Balance, and Employee Well-being When technology is deemed too difficult to be used at work, an employee may suffer techno- complexity or technostress, which has a detrimental influence on well-being (Day et al., 2012). Previous research discovered that someone with higher ranks of technostress is more likely to suffer from psychological tension, from a reduced commitment to endeavor to develop and shows indications of anxiety (Tarafdar & Stich, 2021), has low self-esteem (Korzynski et al., 2021), psychological responses to impairment and fatigue (Afifi et al., 2018), and psychological well- being are negatively affected (Singh et al., 2022). H5a: Technostress has a negative effect on employee well-being. Perceived organizational support is also associated with employee emotions and employee well-being (Wojtkowska et al., 2017). Several studies have found that perceived organizational support has an advantageous impact on elements other than work, such as employee psychological well-being (Harunavamwe & Ward, 2022; Karim et al., 2019; Wojtkowska et al., 2017). Research has shown that employees who receive organizational support perform better, feeling more satisfied with their jobs (Eisenberger et al., 1997). H5b: Perceived Organizational Support has a positive effect on employee well-being. Empirical results show that the total reward system functions as a tool in encouraging employees to increase productivity. On the other hand, Gbande (2016) in his research concluded that total reward systems are not only important for increasing productivity, but also affect International Journal of Human Capital Management, Vol. 7 (1), June 2023 90 | P a g e employee job satisfaction. (Gbande, 2016) discovered that total reward systems had a beneficial effect on employee well-being in his research. H5c: Total reward systems have a positive effect on employee well-being. Work-life balance is one of the most critical concerns that human resource management in firms must handle (Abdirahman et al., 2020). Work-life balance through previous research is known to affect employee well-being (Harunavamwe & Ward, 2022; Irfan et al., 2023; Ivasciuc et al., 2022). In their study, Harunavamwe and Ward (2022) revealed that work-life balance is one of the three variables that have a substantial direct association with the development of workplace flourishing, or can be called employee well-being. H5d: Work-life balance has a positive effect on employee well-being. Employee Well-being and Job Performance Employee well-being, according to Juchnowicz and Kinowska (2021), encompasses characteristics such as life expectancy, income inequality, and environmental elements. Based on previous research, employee well-being could explain patterns of positive influence on Human Resource Management (HRM), welfare, and organizational performance (Peccei & Van De Voorde, 2019). Of the four factors described earlier, employee well-being is also crucial in terms of enhancing job performance (Boulet & Parent-Lamarche, 2022; Lee et al., 2021; Peccei & Van De Voorde, 2019). According to Colquitt et al. (2019), performance can be formally defined as the value of all actions taken by employees that can have a positive or negative impact on the achievement of organizational goals. Therefore, organizations require high-performing employees to achieve their goals, vision, and mission, and to gain a competitive advantage (Thevanes & Mangaleswaran, 2018). H6: Employee well-being has a positive effect on job performance. Employee Well-being as Mediation Aside from having an advantageous effect on job performance from employee well-being, it is known that employee well-being is affected by factors such as technostress (Singh et al., 2022; Spagnoli et al., 2020), perceived organizational support (Harunavamwe & Ward, 2022; Wojtkowska et al., 2017), total reward systems (Gbande, 2016), and work-life balance (Harunavamwe & Ward, 2022). Accordingly, this study will examine the indirect impacts of technostress, perceived organizational support, total reward systems, and work-life balance affecting job performance, with employee well-being serving as an intervening variable. Figure 1. Conceptual Model International Journal of Human Capital Management, Vol. 7 (1), June 2023 91 | P a g e H7a: Technostress has a negative indirect effect on job performance mediated by employee well-being. H7b: Perceived organizational support has a positive indirect effect on job performance mediated by employee well-being. H7c: Total reward systems have a positive indirect effect on job performance mediated by employee well-being. H7d: Work-life balance has a positive indirect effect on job performance mediated by employee well-being. METHODOLOGY To assess both the indirect and direct effects of independent variables on the dependent variable, researchers employed a quantitative research technique with a verification strategy in this study. As a result, this study employs a verification technique to assess the effect of technostress, perceived organizational support, total reward systems, and work-life balance affecting job performance and employee well-being among SOEs employees. Sampling Technique and Samples The method of non-probability sampling, especially purposive sampling in judgment sampling, was used in this investigation. It involves selecting sample members based on specific criteria or characteristics determined by the researcher. As previously explained, the sample criteria to be analyzed in this study are employees of SOEs companies located in JABODETABEK and have worked for one year, so that the respondents can represent the existing population with qualified knowledge of the company's current conditions. Hair et al. (2019) categorized the minimum sample size into four groups. One of these categories includes models with seven constructs or fewer, with a simple commonality of at least 0,5 and identifiable constructs. For such models, a minimum sample size of 150 is recommended. So, taking the number of samples stated by Hair et al. (2019) into account, the number of samples to be analyzed in the present investigation is 263 respondents. Data Collection The steps of data gathering are carried out by providing questionnaires in the form of a survey to study respondents. The questionnaire is made up of numerous questions that are constructed in order to elicit direct replies from respondents. Technostress is measured from research instruments that have been carried out by Tarafdar et al. (2007). The research tool is evaluated based on five dimensions that can explain Technostress: techno-complexity, techno- overload, techno-insecurity, techno-invasion, and techno-uncertainty. The Perceived Organizational Support Survey (SPOS), which consists of 8 question items, will be used to assess perceived organizational support in this research. The Perceived Organizational Support Survey (SPOS), which consists of 36 question items, was established as a measure of Perceived Organizational Support commitment due to the assumption that Perceived Organizational Support is an antecedent of organizational commitment (Eisenberger et al., 1986). Total reward systems variable will be measured using research instruments conducted by Hareendrakumar et al. (2021). The research instrument will be measured through 3 dimensions, namely compensation, benefits, and recognition. In research done by Hareendrakumar et al. (2021), total question indicators comprise 11 question items. Hayman (2005) study tools were used by the researcher to assess work-life balance. Hayman (2005) created a psychometric tool to assess work-life balance in organizations, which included 15 questionnaire questions tested across three dimensions: Work Interference with Personal Life (WIPL), Personal Life Interference with Work (PLIW), and Work Personal Life Enhancement (WIPL). International Journal of Human Capital Management, Vol. 7 (1), June 2023 92 | P a g e Employee well-being will be assessed using the PERMA model, which consists of five indicators: P stands for positive emotion, E stands for engagement, R stands for positive connections, M stands for mean, and A stands for accomplishments (Seligman, 2011). In this study, researchers will use the PERMA model designed by (Butler & Kern, 2016) with the number of question items used, namely 15 question items.The job performance of SOEs employees will be measured through individual work roles (Griffin et al., 2007) which consists of 9 question items. Individual work role behaviors will focus on individual task behaviors to measure Job performance. Data Analysis Structural equation modeling (SEM) techniques are used to analyze the relationship between variables and figure out the direct or indirect effect of the independent variables and the dependent variable from technostress, perceived organizational support, total reward systems, and work-life balance with job performance mediated by employee well-being for SOEs employees. The analysis was carried out in this study utilizing the Lisrel 8.80 calculation program to produce correct calculation results and to facilitate faster and more exact data processing, as well as SPSS to conduct descriptive analysis. After the SEM analysis was carried out, this research will be analyzed more in the K- independent samples different test. K-independent samples were used in this study to determine the differences between each generation from the perspective of technostress, perceived organizational support, total reward systems, and work-life balance. The result of the analysis would show whether generations may have the same or identical or different perspectives. RESULTS AND DISCUSSION Results Based on the analysis the respondents, the profile characteristics of the 263 respondents worked in the Telecommunications and Media industry cluster with a total of 85 respondents (32,23%), followed by the Financial industry cluster of 50 (19,01%), Energy, Oil & Gas industry 31 (11,79%), Plantation & Forestry industry 30 (11,41%), and 8 other industry 67 (25,48%). When viewed from the year of birth or generation, Generation Y (1981 – 1994) represents the highest number of respondents 128 (48,67%), followed by Generation Z (1995 – 2010) 85 (32,32%), and Generation X (1981 – 1994) represents the lowest number of respondents 50 (19,01%). Furthermore, measurement model testing was performed to confirm the chosen model's goodness of fit for further study. The structural model fit test revealed that the model has a good fit, as evidenced by absolute fit indices, RMSEA of 0,067 (RMSEA 0,07) and SRMR of 0,068 (SRMR 0,08). And also, incremental fit indices (NFI, RFI, CDI, and IFI), with each indicator considered good if the incremental fit indices are greater than 0,94 (Hair et al., 2019). The analysis of the model fit reveals that each indicator has values above their marginal values, with NFI at 0,96, RFI at 0,96, CFI at 0,98, and IFI at 0,98, indicating that the structural model has a very good fit. Therefore, it can be concluded that the overall structural model used has a good relationship between latent variables. International Journal of Human Capital Management, Vol. 7 (1), June 2023 93 | P a g e Table 2 Convergent Validity Testing Result Variable Item SLF Error Validity Test CR ≥ 0,7 AVE ≥ 0,5 Reliability Test Technostress TSComp 0,52 0,73 Valid 0,8334 0,5655 Reliable TSOver 0,89 0,21 Valid TSIns 0,68 0,54 Valid TSInv 0,86 0,26 Valid Perceived Organizational Support POS1 0,86 0,25 Valid 0,9165 0,6503 Reliable POS2 0,90 0,18 Valid POS3 0,88 0,22 Valid POS4 0,83 0,32 Valid POS5 0,63 0,60 Valid POS6 0,69 0,52 Valid Total Reward Systems TRSC 0,94 0,13 Valid 0,9332 0,8238 Reliable TRSB 0,96 0,07 Valid TRSR 0,82 0,33 Valid Work-Life Balance WIPL 0,92 0,16 Valid 0,8010 0,6717 Reliable PLIW 0,71 0,50 Valid Employee Well- Being EWP 0,83 0,31 Valid 0,9469 0,7816 Reliable EWE 0,82 0,33 Valid EWR 0,89 0,21 Valid EWM 0,94 0,11 Valid EWA 0,93 0,13 Valid Job Performance JP1 0,87 0,25 Valid 0,9597 0,7069 Reliable JP2 0,85 0,28 Valid JP3 0,86 0,26 Valid Table 1 Structural Model Fit Test Goodness of Fit Indicator Cut-off Value Goodness of Fit Value Conclusion Absolute Fit Indices GFI GFI > 0,9 0,84 Marginal Fit RMSEA RMSEA < 0,07 0,063 Good Fit SRMR SRMR ≤ 0,08 0,068 Good Fit Incremental Fit Indices NFI NFI > 0,94 0,96 Good Fit NNFI NNFI > 0,94 0,98 Good Fit RFI RFI > 0,94 0,96 Good Fit CFI CFI > 0,94 0,98 Good Fit IFI IFI > 0,94 0,98 Good Fit International Journal of Human Capital Management, Vol. 7 (1), June 2023 94 | P a g e JP4 0,86 0,26 Valid JP5 0,85 0,28 Valid JP6 0,90 0,19 Valid JP7 0,90 0,19 Valid JP8 0,81 0,35 Valid JP9 0,77 0,41 Valid The construct validity was assessed based on the standardized loading factors (SLF) of the formed model. Constructs with SLF values meeting the minimum standard of SLF ≥ 0,5 were deemed valid and suitable for further analysis. The reliability of the measurement model was evaluated using two indicators of convergent validity: average variance extracted (AVE) with AVE values ≥ 0,5, and construct reliability (CR) with CR values ≥ 0,7 (Hair et al., 2019). The re- specified measurement model was evaluated based on construct validity in terms of both validity and reliability. Table 2 shows the outcomes of this investigation. The t-value and p-value will be used to evaluate the significance of the influence of variables on the study hypothesis based on the findings of the structural model analysis. Criteria for the significance of the effect between latent variables will be compared with the value of t-table = ± 1,645 (one-way hypothesis) with the acceptance rate of the research hypothesis, t-value ≥ 1,645 or t-value ≤ - 1,645 and reject otherwise and the hypothesis can be accepted if the p-value ≤ 0,05 and reject other values. A negative t-value indicates that the latent variable has a negative influence on other latent variables, whereas a positive value indicates the reverse. The structural model analysis, as shown in Figure 2 and Table 3, demonstrates that the independent variables, such as technostress, perceived organizational support, total reward systems, and work-life balance, have no substantial direct influence on job performance. This is evident from the t-value and p-value results, which do not meet the established standards. However, it is worth noting that the variable of technostress does have a significant influence on the mediating variable of employee well-being, indicated by a path coefficient of -0,14 (t-value = Figure 2. Structural Model Path Diagram International Journal of Human Capital Management, Vol. 7 (1), June 2023 95 | P a g e -179 and p-value = 0,0372). This suggests that technostress negatively affects employee well- being. Employee well-being is also influenced by perceived organizational support, total reward systems, and work-life balance, with sequential path coefficients of 0,57 (t-value = 6,93 and p- value = 0,0000), 0,15 (t-value = 2,11 and p-value = 0,0178), and 0,16 (t-value = 1,99 and p-value = 0,0000). These three variables exhibit positive path coefficients and t-values, implying that perceived organizational support, total reward systems, and work-life balance have a beneficial influence on employee well-being. Furthermore, the employee well-being, which serves as a moderator in this study, has a considerable impact on job performance. The value of the path coefficient is 0,66 (t-value = 7,59, p-value = 0,0000), indicating that employee well-being has a positive influence on job performance. When the mediating function of employee well-being in the effect of technostress, perceived organizational support, total reward systems, and work-life balance on job performance is examined further, it is discovered in Table 4 that the employee well-being variable has a totally mediating role. As a result, it is possible to conclude that the impact of technostress, perceived organizational support, total reward systems, and work-life balance upon job performance are mediated by employee well-being. Table 3 Research Hypothesis Analysis H Path Path Coefficient t-value p-value Conclusion H1 Technostress  Job Performance 0,09 1,03 0,1519 Positive & Statistically Not Significant H2 Perceived Organizational Support  Job Performance -0,05 -0,53 0,2982 Negative & Statistically Not Significant H3 Total Reward Systems  Job Performance -0,02 -0,23 0,4091 Negative & Statistically Not Significant H4 Work-Life Balance  Job Performance -0,04 -0,43 0,3337 Negative & Statistically Not Significant H5a Technostress  Employee Well- Being -0,14 -1,79 0,0372 Negative & Statistically Significant H5b Perceived Organizational Support  Employee Well-Being 0,57 6,92 0,0000 Positive & Statistically Significant H5c Total Reward Systems  Employee Well-Being 0,15 2,11 0,0178 Positive & Statistically Significant H5d Work-Life Balance  Employee Well-Being 0,16 1,99 0,0237 Positive & Statistically Significant H6 Employee Well-being  Job Performance 0,66 7,59 0,0000 Positive & Statistically Significant International Journal of Human Capital Management, Vol. 7 (1), June 2023 96 | P a g e The total effect variable approach of Hair et al. (2019) will be used to quantify the total effects of technostress, perceived organizational support, total reward systems, and work-life balance upon job performance. The indirect effect on mediation will be calculated by multiplying the independent variable's path coefficient on the mediating variable (Path A) by the path coefficient of the mediating variable on the dependent variable (Path B). Table 4 shows the results of the indirect influence in this study, and the path coefficient values of the technostress variable, perceived organizational support, total reward systems, and work-life balance regarding job performance show the direct influence of the independent variables on the dependent variable. To calculate the overall influence of the technostress variable, perceived organizational support, total reward systems, and work-life balance affecting job performance, sum the direct and indirect effects of each variable independently. According to Table 5, perceived organizational support had the largest overall effect on job performance factors. As a result, it is possible to conclude that the variable perceived organizational support is a latent variable that has the largest impact on improving the work performance of SOEs employees. Discussions The changes in work styles resulting from the COVID-19 pandemic and current digital transformation manifest in hybrid work arrangements, where employees are continuously engaged with technology for both work and personal purposes, which can contribute to excessive technology use. Excessive technology use can lead to technostress. However, the findings of this study differ from previous research, where technostress negatively affected job performance (Cahapay & Bangoc II, 2021; Day et al., 2012; Saidy et al., 2022; Tarafdar et al., 2015). Contrary to expectations, the study revealed that technostress does not exert a significant influence on job performance. Surprisingly, the analysis demonstrated positive path coefficients, indicating that higher levels of technostress were associated with increased job performance. However, these Table 5 Total Effect of Independent Variables on Dependent Variables Variable Direct Effect Indirect Effect Total Effect Technostress 0,09 -0,0924 -0,0024 Perceived Organizational Support -0,05 0,3762 0,3262 Total Reward Systems -0,02 0,0990 0,0790 Work-Life Balance -0,04 0,1056 0,0656 Table 4 Mediating Effects of Employee Well-Being H Path Path A Path B Indirect Effect Conclusion H7a Technostress  Employee Well-being  Job Performance -0,14 0,66 -0,0924 Full Mediation H7b Perceived Organizational Support  Employee Well-being  Job Performance 0,57 0,66 0,3762 Full Mediation H7c Total Reward Systems  Employee Well-being  Job Performance 0,15 0,66 0,0990 Full Mediation H7d Work-Life Balance  Employee Well-being  Job Performance 0,16 0,66 0,1056 Full Mediation International Journal of Human Capital Management, Vol. 7 (1), June 2023 97 | P a g e findings are consistent with the research conducted by several other researchers where technostress was found to have no significant effect and had a positive path (Aziz et al., 2023; Maipita et al., 2023; Tarafdar et al., 2019). These findings indicate that employees in this study demonstrate the ability to effectively cope with and overcome technostress, mitigating its negative impact on the performance of SOEs employees. The presence of the new generation (Generation Y and Generation Z) with their unique work styles and innovative technology utilization presents a challenge that motivates employees to innovate, work creatively, and improve performance. Furthermore, the structural model analysis results indicate that perceived organizational support, total reward systems, and work-life balance were not found to have a significant direct influence on job performance and even exhibited negative path coefficients. These findings are supported by previous research, where perceived organizational support (Alshaabani et al., 2021; Liu et al., 2019; Sameer, 2022), total reward systems (Li et al., 2023), and work-life balance (Gaikwad et al., 2021; Isa & Indrayati, 2023) were found to have no significant effect with negative path coefficients. The findings suggest that perceived organizational support can be leveraged by employees to engage in task procrastination and non-work-related activities, potentially impacting their performance. Furthermore, Generation Z employees perceive lower total reward systems and feel undervalued by the company, resulting in a negative influence on their performance within State-Owned Enterprises (SOEs). The impact of technostress on employee well-being, as found in the structural model analysis, has a statistically significant and negative influence on employee well-being.In line with existing literature (Singh et al., 2022; Tarafdar & Stich, 2021), excessive technology use has varied effects on employees' psychological well-being. In the context of this study, these findings underscore the importance of addressing technostress in the work environment. Companies need to pay attention to balanced technology use and provide appropriate support to employees in effectively managing technology to reduce the negative impact of technostress on psychological well-being. This research provides a significant contribution to understanding the relationship between technostress and employee well-being in the evolving digital era of SOEs. The structural analysis results indicate that perceived organizational support has a positive and significant influence on employee well-being and has the greatest impact in enhancing the employee well-being of SOEs. These findings are consistent with previous research stating that perceived organizational support is positively related to factors outside of work, such as employees' psychological well-being and life satisfaction (Aggarwal-Gupta et al., 2010; Harunavamwe & Ward, 2022; Wojtkowska et al., 2017). These studies support the social exchange perspective in workplace relationships: employees are more likely to succeed in their jobs when they believe that their superiors and the organization as a whole support them and meet their needs (Karim et al., 2019). The significance of enhancing organizational support to promote employee well-being is underscored. Active involvement of leaders and supervisors in providing adequate support is crucial. Concrete measures, such as reducing technology-related stress and ensuring technical support, can alleviate stress and improve work-life balance. Introducing flexible working hours with a commitment to timely completion of tasks can aid employees. The research also found that total reward systems have a significant influence on employee well-being. This is consistent with previous research indicating that total reward systems serve as a tool to motivate employees to increase productivity and have a positive impact on employee well-being (Gbande, 2016; Hulkko-Nyman et al., 2014; Salleh et al., 2020). The study emphasizes the necessity of aligning total reward systems with the changing work styles brought about by digital transformation. It highlights the significance of providing appropriate and relevant total rewards to enhance employee well-being. Adopting a holistic approach that includes both financial and non-financial components in reward and recognition strategies shows promise in improving employee well-being and organizational effectiveness. In the current context, where dynamic changes in the workplace and a shift towards more flexible ways of working are becoming dominant, it is important for organizations to consider International Journal of Human Capital Management, Vol. 7 (1), June 2023 98 | P a g e work-life balance as a crucial aspect in enhancing employee well-being. A good work-life balance can contribute positively to employee well-being, which, in turn, can have a positive impact on overall employee performance. This research found that work-life balance has a significant influence on employee well-being. These findings are consistent with several previous studies that have shown the impact of work-life balance on employee well-being (Harunavamwe & Ward, 2022; Irfan et al., 2023; Ivasciuc et al., 2022). Human resource management needs to prioritize work-life balance as one of the important issues to be addressed within organizations, especially in efforts to enhance employee well-being. As a mediating variable in this study, employee well-being has a significant and positive influence on job performance. This indicates that the higher the level of employee well-being, the higher their performance. These findings are consistent with several previous studies that highlight the relationship between employee well-being and job performance (Boulet & Parent-Lamarche, 2022; Lee et al., 2021; Peccei & Van De Voorde, 2019). This research emphasizes the importance of fostering positive psychological mindsets to empower employees in diverse and challenging work environments. It provides valuable insights into the relationship between employee well- being and job performance, particularly in the context of dynamic workplace changes and high job demands. Organizations need to prioritize employee well-being, encompassing happiness, health, and relationships, as it plays a significant role in enhancing performance. Implementing strategies and programs, such as health initiatives and work-life balance efforts, can effectively support employee well-being and improve overall organizational performance. In this study, employee well-being plays a role as a mediating variable that connects factors such as technostress, perceived organizational support, total reward systems, and work-life balance with job performance. In other words, the effects of these factors on job performance occur through the influence of employee well-being. Furthermore, using the K-independent samples different test, differences in perceived organizational support were found among generations, with Generation X exhibiting higher levels compared to other generations. Variations in employee well- being levels were also observed across industry sectors, with the Plantation and Forestry cluster showing lower levels. To enhance employee well-being and job performance, it is crucial to prioritize perceived organizational support, particularly in sectors with lower well-being levels. CONCLUSION Researchers have shown considerable interest in exploring factors influencing employee well-being and job performance. However, practical management experiences often fail to address the unique characteristics of the new generation of employees, who possess distinct interests (Wang et al., 2022) and heightened psychological sensitivities (Zhou & Qian, 2021). Consequently, a generational gap has widened between these employees and other generations. Notably, perceived organizational support, the independent variable with the greatest impact on job performance, varies across generations. Generation X (born between 1965 and 1980) exhibits higher levels of perceived organizational support compared to other generations. This finding underscores the continuous need for companies to prioritize perceived organizational support, ensuring that employees perceive their well-being as a priority and their contributions as valuable. This is particularly crucial for younger generations (Generation Y and Z), who represent the future successors within the organization. To navigate an increasingly multigenerational work environment successfully, companies must devise strategies that accommodate the diverse needs and expectations of each generation. To optimize employee performance and enhance company productivity, state-owned enterprises (SOEs) should implement effective human resource strategies that align with organizational goals and foster innovative and sustainable practices. This study explores the impact of various factors on employee well-being and job performance in SOEs. Structural equation modeling analysis revealed that employee well-being fully mediates the relationship between the International Journal of Human Capital Management, Vol. 7 (1), June 2023 99 | P a g e examined variables and job performance. Perceived organizational support exhibited the strongest overall effect on job performance, mediated by employee well-being. This highlights the importance of enhancing organizational support to promote employee well-being. Active involvement of leaders and supervisors in providing essential support to employees is strongly recommended. Measures such as mitigating technology-related stress and ensuring technical assistance availability can effectively reduce technostress and improve work-life balance, thus enhancing overall employee performance. 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Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.775580 Figure 1. Conceptual Model Table 2 Convergent Validity Testing Result Table 1 Structural Model Fit Test Figure 2. Structural Model Path Diagram Table 3 Research Hypothesis Analysis Table 5 Total Effect of Independent Variables on Dependent Variables Table 4 Mediating Effects of Employee Well-Being