1. Introduction
In the last few decades, the development of information technology has led to an increase in the number of individuals working from home. This phenomenon is picking up pace in line with the spread of the coronavirus pandemic, which has pushed workers to Work from Home (WFH). The assimilation of technology affects how people interact with work and life, and it is becoming increasingly important. The boundaries between the domain of work and personal life are becoming significantly blurred, leading to different outcomes, both negative and positive.
Pandemics and prolonged WFH is likely to increase the tension of work and home life; this is characterized by difficulty in coordinating between work and personal life demands that leads to emotional exhaustion (Bhumika, 2020). According to Maddy (2020), the divorce rate during the COVID-19 pandemic has continued to increase worldwide. In line with this issue, the ILO-OECD (2020) reported that women are the most affected by the pandemic, most of them lost their jobs, and had to bear heavy workloads at home during lockdowns which led to an increase in the cases of domestic violence. Technology is considered a convenient means for individuals to switch roles so that the fulfillment of both domains can be carried out flexibly and simultaneously (Harmer et al., 2008). Furthermore, Sapta et al. (2021) explained that technology plays an important role in improving work performance, especially during a pandemic.
In addition, a recent study about WLB in the COVID-19 pandemic provides evidence that several researchers have focused on technology that plays an important role in regulating and accommodating the relationship between the two domains. However, there is another factor which is often overlooked in researching work–life balance, namely cultural factors, yet culture is what shapes individual perceptions of work and personal life (Ollier-Malaterre et al., 2013; Powell et al., 2009). It was also found that cultural backgrounds gave different results related to work– life balance (Yang et al., 2000). In this regard we can refer to “Ugahari”, a traditional concept embraced by the Malaysian society, which we feel what contributes to society’s perception of work and family, which in turn influences individual preferences for WLB. Ugahari is defined as moderation, intermediation and simplicity by adhering to the principle of self-control because you know your limits.
Therefore, this study analyses the role of information and communication technology (ICT) and local wisdom in work–life balance in the era of COVID-19 pandemic. By analysing primary data collected through a questionnaire, this study will empirically examine the impact of technology use and Malaysian local wisdom on work–life balance. The rest of the discussion will be organized as follows: the literature review will highlight prominent research in understanding work–life interrelationship, and from this we will draw the hypotheses used in this research. The following section deals with the data, measurements and methods. After conducting a partial least square analysis, this paper discusses further practical implications and policies for the government and the management. The last section provides concluding statements.
2. Literature Review
2.1. Conceptualizing the Work–Life Balance
The term Work–Life Balance is still a matter of debate among researchers. The main problem stems from the word “balance”, how it is measured and assessed, whether an individual can be said to have a balance between work and life if she can share their time equally between work and personal life. Another problem arises concerning the objectivity of WLB measurements, and whether the balance felt by an individual applies to other individuals (Burke, 2004). In this regard Kalliath and Brough (2008) reviewed keywords to describe the meaning of WLB; namely the satisfaction or pleasant experiences that arise when individuals fulfil the expectations of both work and personal life roles in such a way as to minimize the conflicts that can occur. To gain a more comprehensive understanding of the WLB concept, Clark (2000) offers the border theory.
The border in the WLB framework is defined as the boundaries between work domains and personal life domains, which can be physical, temporal and psychological boundaries (Clark, 2000). The physical border relates to where one of the roles appears, whether it is situated at work or outside the workplace. The temporal border concerns the time when the role occurred. The last border is psychological, where the boundaries are influenced by the behaviour and emotional patterns of the individual (Allen et al., 2014). In other words, physically, the individual is in a certain domain, for example, the workplace, but psychologically, they still behave as if engaged in personal life.
In order to provide a comprehensive understanding of work-life balance, this study includes two dimensions, namely: Permeability (The degree in which elements from one domain can enter another domain both psychologically or behaviorally involved in another role) (Desrochers & Sargent, 2004). Flexibility (The level at which individuals assume they can move easily between domains (Matthews & Barnes-Farrell, 2010). Different degrees of flexibility and permeability result in four types of work-life balance: Integration (The extent to which individuals can transfer influence, values, and skills, boundaries of work life, alongside their personal and family needs. Interference (interference between roles where the demand for time and pressure in the work place interferes with family responsibilities, and vice versa (Caudroit et al., 2011). Autonomy is the extent to which the work provides freedom and independence to the individual in completing his work (Lin & Ping, 2016). Segmentation limitation or isolation between roles is carried out by individuals both physically and psychologically so that one role does not result in conflict with other roles (Nam, 2014).
2.2. The Role of ICT on Work–life Balance
The industrial revolution 4.0 that is currently happening is marked by the development of information technology that allows all activities to be carried out anytime and anywhere, without any time and space limitations. When viewed from the perspective of border theory, the existence of ICT encourages the shift in roles between domains to become more frequent (Duxbury & Smart, 2011; Hill et al., 2003; Middleton, 2008; Towers et al., 2006). Thus the boundaries between the domains are unclear and blurred. The impact for the work domain is that it is easy for workers to accomplish a lot with a minimum intensity of activity (Katz & Aakhus, 2001). This means that ICT can be a convenient intermediary for individuals to change roles. It is not surprising that many workers complete their tasks in the car or even in bed while watching TV. This is what encourages business people to provide smart work infrastructure or information technology-based infrastructure that can encourage workers to improve their work performance (Ingsih et al., 2020; Kim & Kim, 2015).
Regardless of its positive impact on life, the presence of ICT also impacts increasing work pressure from managers or superiors who expect that workers are always ready to work whenever and wherever the opportunity is available (Towers et al., 2006). In line with the digitization of work, it has led to a phenomenon where workers perform their duties round the clock, such as responding to emails, mobile phones and laptops, allowing work to be done 24/7 (Waller & Ragsdell, 2012). In this regard, Nam (2014) states “Work and life tend to increasingly intertwine rather than exist as separate spheres in this age of technology driven connectedness”. From this statement, it is clear that information technology plays an important role in shaping the boundary characteristics between domains, whether permeable or flexible. Thus the hypothesis that can be built is:
H1: The use of ICT has a positive effect on permeability.
H2: The use of ICT has a positive effect on flexibility.
As previously explained, technology plays a role in facilitating individuals to cross boundaries between domains, by managing their permeability and flexibility with continuous integration–segmentation (Golden & Geisler, 2007). Duxbury and Smart (2011) found that workers who frequently use mobile technology often find themselves engaged in two roles simultaneously by synchronizing the physical and virtual environment simultaneously. In other words, for some people, information technology is a suitable means of integrating roles. Also, the flexibility provided by technology allows workers to have autonomy or freedom in determining when and how to complete their work (Breaugh, 1985; Lin & Ping, 2016). However, at the same time, Carlson et al. (2000) argue that technology can cause disruption, especially in personal life, where work demands often invade and dominate the domain of personal life, which creates tension between the two domains.
On the other hand, some workers prefer to use technology to help segmentation between roles by dedicating technology to their respective goals, for example, workers who tend to have two means of communication, one for family needs and the other for work needs. Those who prefer segmentation with strong work and family boundaries view the use of work-related ICT as a loss of personal time. Thus, individuals with strong segmentation preferences strive to maintain the boundaries between the two domains and are more likely to limit information technology during non-working hours. Conversely, those who have weak segmentation preferences tend not to limit the use of ICT even when they are in the domain of personal life (Yang et al., 2019). Thus the developed hypotheses are:
H3: The use of ICT positively affects Work–Life integration.
H4: The use of ICT positively affects Work–Life autonomy.
H5: The use of ICT positively affects Work–Life interference.
H6: The use of ICT negatively affects Work–Life segmentation.
2.3. The Role of Culture on Work–life Balance
Culture is defined by Geertz et al. (1973) as a pattern of meaning transmitted historically through symbols in a system that is inherited and expressed in a symbolic form as a means for humans to communicate and develop knowledge and attitudes, norms and views on life. At this point, it is known that culture influences individual attitudes and views of the phenomena of life (Kitayama & Park, 2010). In line with this, Ashforth et al. (2000) stated that cultural factors play an important role in shaping individual perceptions of the relationship between work and personal life through the values, norms and beliefs that develop in society. In this regard Ahmad et al. (2021) found that national culture plays a significant role in shaping job satisfaction in the workplace.
The influence of culture on WLB can be seen from a study conducted by Yang (2005) where individualistic countries such as America prefer to keep the domains of work and personal life strictly separate, while Eastern countries like China tend to integrate the boundaries between work and personal life. For the American society, the conflict between roles must be avoided because it can threaten the harmonization of the two domains. On the other hand, the Chinese consider conflicts between domains to be natural and see this as a life lesson to strengthen work life along with the personal life (Yang et al., 2000). In line with this, Aycan (2011) stated that the communal culture of countries in Asia views work and personal life as two different but complementary things, while Anglo-Saxon countries view both domains as a threat to other domains, because of the segmentation of roles more common in these countries.
In addition to the collectivistic culture inherent in Asian society, the term “Ugahari”, which comes from the “Nusantara” cultural philosophy of Malaysia and Indonesia, is used to describe a value of cultural aspect that emphasizes that everyone must have something in sufficient quantity but not too much or ‘the right amount is the best and characterizing when to stop doing certain activities to meet the needs of other activities. This is the implication of the idea that we should not take too much because other people and the community would need it. Thus the essence of Ugahari is to achieve happiness through the balance created in daily life and it also includes the subject of work-life balance.
This local wisdom emphasizes the communities not to take things in an excessive manner. For Malaysians, Ugahari is a way of life and a habit of thinking. There is an internal mindset of acceptance and satisfaction in Malaysia and Nusantara which argues that part of the secret to being happy is to be simple in the sense that simplicity is not a deficiency or inability, but has become an inseparable part of the true meaning of happiness in life, in other words If Ugahari is likened to a diet, it can be said that Ugahari is like a balanced diet. Ugahari won’t starve you from eating too little, but it won’t make you bloated from eating too much either. Most importantly, all your nutritional needs are met for your body to be healthy and ideal.
Ugahari and WLB pertain to how individuals are looking for better work-life balance. This can be interpreted in many ways. Ugahari focuses on achieving a balanced life that leads to a happy life. Most countries have their philosophy to accomplish balance and happiness. Sweden has ‘Lagom’ “Not too little. Not too much. Just right”. Denmark has ‘Arbejdsglaedo’ (the Danish way to love your job), Finland ‘Kalsarikanni’ (method of relaxation that is decidedly Finnish) and Iceland has ‘Gluggavedur’ (Iceland optimism). Based on the recent ranking of happiness, all Nordic countries ranked among the top ten world’s happiest countries (Helliwell et al., 2018).
In relation to the work domain, Ugahari’s behavior means ignoring overtime or working outside the specified hours because it indicates that a person is not working effectively during his work time. In addition to working according to portions, prioritizing time to socialize is part of Ugahari’s lifestyle. Thus, this behavior is far from an individualistic lifestyle and is more concerned to group interests and the principle of togetherness. Apart from being used to channel hobbies in a positive way, the time outside of working hours is used to create quality gathering time with relatives, enjoy activities in public spaces, and engage with the surrounding communities. Thus the hypotheses in this study are:
H7: The local wisdom Ugahari negatively determines the Work–life Balance permeability.
H8: The local wisdom Ugahari positively determines the Work–life Balance flexibility.
H9: The local wisdom Ugahari positively affects the types of Work–life Balance integration.
H10: The local wisdom Ugahari positively affects the types of Work–life Balance autonomy.
H11: The local wisdom Ugahari negatively affects the types of Work–life Balance interferences.
H12: The local wisdom Ugahari positively affects the types of Work–life Balance segmentation.
3. Methodology
3.1. Respondents & procedure
This study uses primary data obtained directly from respondents through a questionnaire. The population to be studied are workers with middle management positions in both public and private sectors. The reason for choosing respondents in middle management positions was to focus on the role of respondents as border crossers or border keepers. The public sector is divided into several clusters based on the department, while the private sector is divided into clusters based on the industry category.
The sampling method used in this study is the cluster sampling to select industry departments and categories to be studied and then followed by random sampling to determine which companies to explore. Closed questions are used in this questionnaire, and the options are given using a Likert scale. The items of the questionnaire have been constructed based on strong definition, the determinant of dimension and how to measure every variable. This is very critical in survey research to ensure the items of the questionnaire are related to the main issues which are being studied. The questionnaire is distributed directly to the human resources department which is then distributed to company staff with middle management positions. The survey form can be filled offline using the distributed questionnaire sheet or using the online link at https: https://www.surveymonkey.com/ r/5YGVBCY. In total, out of 638 questionnaires distributed, there were 580 respondents who filled in the questionnaire, but after filtering the data, there were 466 respondents who met the requirements for further analysis. Demographically, respondents who fell in the age group 26–30 years (25.11%) followed by the age range of 31–35 years (22.53%) then the oldest age range was > 55 years (2.15%). When analysed by gender, male respondents dominated with as much as 51.07% and women by 48.93%. In this study, the largest number of respondents came from ethnic Malays with 73.82%, followed by ethnic Chinese 19.96% and Indians with 4.08%.
3.2. Analytical approach
This study uses SEM-PLS (Partial Least Squares) to analyse the data obtained from the questionnaire. Where PLS-PM is considered a soft modelling approach in the absence of strong assumptions, such as sample size and measurement scale required and provides sequential estimates, subset by subset, of loading and structural parameters (Vinzi et al., 2010). According to Hair et al. (2016), the first important step is to take in PLS-SEM is to make a path diagram that describes the research hypothesis and displays the relationship between the variables to be examined. Therefore the path diagram in this study is depicted in Figure 1.
Figure 1: Structural Equation Design of the Research
Then the PLS-SEM analysis was carried out in two stages, namely the outer model and inner model (Hair et al., 2016). The outer model, namely the specification of the relationship between latent variables and their indicators, also known as the outer relation or measurement model, defines the characteristics of a construct with its manifest variables. Convergent validity of the measurement model with the reflective indicator model is assessed based on the correlation between the item score / component score and the construct score calculated by PLS. The reflective size is said to be high if it correlates more than 0.70 with the construct to be measured. However, for research in the early stages of developing a measurement scale the loading value of 0.5 to 0.60 is considered sufficient (Chin, 1998). Discriminant validity of the measurement model with reflective indicators is assessed based on the cross loading measurement with the construct. If the construct correlation with the item of measure is greater than the measure of the other constructs, it will show that the latent construct predicts the size of the block better than the other block sizes. Furthermore, the evaluation of the outer model is done by looking at convergent validity with a rule of thumb > 0.70 and the average variance extracted (AVE) value must be greater than 0.5 (Vinzi et al., 2010).
Finally, composite reliability by looking at the Cronbach’s Alpha value for the condition is > 0.70. Meanwhile, the inner model is the specification of the relationship between latent variables (structural model), also known as the inner relation, which describes the relationship between latent variables based on the substantive theory of research. Without losing its general characteristics, it is assumed that the latent variable and indicator or manifest variable are zero and unit variance is equal to one, so that the location parameter (constant parameter) can be omitted from the model. One of the inner model evaluations can be done with R-squared with the conditions that the values of 0.67, 0.33 and 0.19 indicate that the model is strong, moderate and weak (Chin, 1998). Related to this, Hair et al. (2016) added that the cut off for R-squared was > 0.10. In addition, the PLS model is also evaluated by looking at the predictive relevance Q-square for the constructive model. The Q-square measures show how well the observed values are generated by the model and also the parameter estimates. The value of Q-square > 0 indicates that the model has predictive relevance, while the Q-square < 0 model is built.
4. Results
The structure of this research report uses recommendations from Chin that uses a two-step approach (Vinzi et al., 2010); the first focuses on the results of the measurement model and the second focuses on the results of the structural model.
This first section will explain the evaluation of the measurement model to test the validity and reliability of each question item that reflects the latent variable (Table 1). Ideally, this section evaluates how accurate or reliable a measure is when viewed from its convergent and discriminatory validity. Because the indicators in this study are reflective, the evaluation uses the loading factor, AVE, Cronbach’s alpha value and composite reliability. See Table 1 below.
Table 1: Measurement Model Evaluation
Table 1: Continued
The first step in evaluating the model that has been built is to test that the manifest variable of a construct has a high correlation with its latent variable. This validity test can be seen from the loading factor value as shown in Table 1. It is known that the loading value on each manifest variable has a value greater than the required cut-off point. While the construct validity can be seen in the discriminant validity using the Fornell-Larcker Criterion, as shown in Table 2. It can be seen that the latent constructs predict indicators in their block better than the indicators in other blocks. Furthermore, another way used to test discriminant validity is by looking at average variance extracted (AVE). In Table 1, the AVE value is greater than the required value, meaning that the variance of all indicators can be captured by the latent variable (Vinzi et al., 2010).
Table 2: Fornell-Larcker Criterion
As presented in Table 1, uni-dimensional latent constructs can be measured well by each indicator, as indicated by the Cronbach’s alpha value > 0.70 which means that there is internal consistency or reliability of the construct size, which is characterized by a closely related set of items that compose the construct as a group (Dakduk et al., 2019). Because Cronbach’s alpha tends to underestimate in measuring reliability, composite reliability is used to get a closer approximation from the table, all constructs have a score that exceeds 0.70 as the limit set by Chin (1998).
After obtaining the validity of the measures used to represent each construct, the next step is to provide evidence that supports the theoretical model as proposed in the previous discussion. In this study, it was found that the R-square was classified as weak even though it passed the cut-off point of 0.1, however, the Q-square value in Table 3 shows a number more than 0, which means that the model of observed values has been reconstructed properly so that the model has relevant predictions. Furthermore, the table also shows that the validity of the model built is moderate. Thus even though there is a small relationship, it is reliable.
Table 3: Structural Model Evaluation
Furthermore, the path significance determination in the structural model is carried out through the PLS algorithm, taking into account the bootstrap process, which involves random sampling from the original data set to determine the significance level of the path coefficients (see Table 4) (Hair et al., 2016). Overall, with the T-Statistic value of 1.645 and a confidence interval of 90%, all exogenous variables tested for endogenous variables have a significant effect. However, there are variables with different directions from the hypothesis. ICT turned out to show a significant positive direction towards segmentation. Ugahari on permeability and integration was previously considered to have a negative impact, has turned out to have a positive impact.
Table 4: Outcomes of Structural Equation Model Analysis
*Significance at t-value ≥ 1.96 with p ≤ 0.05, **Significance at t-value ≥ 1.645 with p ≤ 0.1.
5. Discussion
After the enactment of the Malaysian government’s mobile control order on 18 March 2020, encouraging industry players to work from home (WFH), the presence of technology in the WFH programme has made the house a digital workplace. Of course, this has an impact on individual preferences for the management of the work domain and personal life. This influence can be seen in the perspective of the use of ICT during a pandemic which can help workers manage their work and personal life domains flexibly, meaning that they can freely do their jobs while maintaining the balance of their personal life domains. Interestingly, the results of this study show different results from Nam (2014) who found that ICT and permeability were negatively related, while in this study the opposite was found in that ICT and permeability had a positive coefficient. This means that the intensity of internet use is a significant predictor of flexibility and permeability, with a positive direction. The consequence is that work– to–life permeability is positively related to work–to–life flexibility, and life–to–work permeability is also positively related to life–to–work flexibility.
This situation encourages individuals to integrate the domain of their family and personal life, which is marked by blurring the boundaries between the two domains (Ashforth et al., 2000; Nam, 2014; Pheng & Chua, 2018) so that the patterns and behaviour of individuals in carrying out their roles tend to be similar. This is understandable because in a pandemic like situation, the home becomes a place to work and a place to socialize with other family members. In line with this, the use of ICT during WFH allows communication or work demands to enter non-working space or time, or conversely the communication of demands from the family domain interferes with the job demands. As a result, there is often tension between domains. This tension arises because of competition for limited resources (e.g. time) and limits workers from managing non-domain responsibilities of their work (Beham et al., 2011; McGinnity & Whelan, 2009). On the other hand, the role of ICT has a positive effect on the work domain, as workers can independently determine their schedule and style of work due to the high work flexibility offered by WFH. However, autonomy does not mean working in isolation without guidance and supervision, although an autonomous workplace is based on the transparency and integrity of workers. Lastly, regarding the role of segmentation, it was found in this study that ICT and segmentation have a positive effect, but with low t-value, this indicates that individuals often do rapid role switching rather than maintaining the boundaries between work and personal life domains. In other words integration is more prevalent than segmentation.
As with ICT, Ugahari plays an important role in managing the boundaries between various domains. Although both have positive effects on flexibility and permeability, the effect of Ugahari has a negative direction on interference. The higher the Ugahari behaviour, the lower the level of tension between the domains. In this regard, Ugahari plays a significant role in the pattern of relationships between domains, where each domain is allotted its own time, each of which should not be excessive, at the same time it demands harmonization between the domain of work and personal life. The logical consequence of this way of life is emphatically compartmentalization of the two domains. In other words, Ugahari encourages role segmentation, where the transition process between roles can be carried out more clearly, which in turn reinforces the symbolic signs of each role, and takes individuals deeper into the roles they play.
6. Conclusion
Based on the empirical analysis as previously described, this research is expected to be able to provide practical insights for government and company leaders. In order to maximize the role of technology and encourage “Ugahari” behaviour in workers’ efforts to achieve WLB. Thus the government and company leaders need to develop relevant policies to encourage a balance between the work and the personal life domain. For this reason, this study offers recommendations for both the government and company leaders during the implementation of WFH.
First, it needs to be understood that ICT can both be a blessing and a curse to personal life, the reason for this is that it provides flexibility and high permeability to indivi- duals, so that tensions between domains often occur. Thus, policyholders need to understand the impact before making policies. Second, the Malaysian cultural trait of Ugahari has a positive impact on achieving a balance between work and life domains, but this local wisdom often does not get enough attention in realizing a better work and family life. Thus, the culture needs to be strengthened and reiterated. Third, there is a need for policies that direct individuals to reduce boundary permeability, which encourages inter-domain interruption, so that a good understanding of policymakers is needed to recognize more specific WLB patterns as personal preferences. Although integration preferences are considered to have more positive consequences for WLB (Nam, 2014), segmentation preferences are needed in an effort to reduce the intrusion that occurs.
The use of ICTs during the WFH policy has allowed individuals to have high flexibility and permeability. This situation has two important consequences, namely role integration, which is marked by fading the boundaries of work and personal life, and the high frequency of transitions between boundaries. Furthermore, increasing flexibility and permeability at the same time often creates interference between work and personal life domains, this disturbance arises as a result of the high frequency of interruptions coming from one domain to another. Even so, the resulting tension was successfully suppressed by Ugahari behaviour, by segmenting each role according to its size. Thus, we argue that the two variables ICT and Ugahari both play an important role in managing work and personal life boundaries. Although ICT encourages individuals to work whenever and wherever, Ugahari behaviour limits this so that it is not excessive. The two domains can relate harmoniously to achieve balance in work and personal life.
*Acknowledgements:
This study was funded by the Fundamental Research Grant Scheme (FRGS) Under Reference Code; FRGS/1/2019/SS08/UMT/02/3. We would like to thank the Ministry of Higher Education of Malaysia for financial support.
1First Author and Corresponding Author. Associate Professor in Financial Economics, Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, Malaysia [Postal Address: PA113, 1st Floor, FPEPS, 21030 Kuala Terengganu, Terengganu, Malaysia] Email: suhal@umt.edu.my
2Associate Professor in Labour Economics, Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, Malaysia.Email: suriyani_md@umt.edu.my
3Professor of Faculty of Social Sciences and Humanity, Universiti Kebangsaan Malaysia, Malaysia. Email: norjef@ukm.edu.my
4Ph.D. Candidate, Graduate Research Assistant, Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, Malaysia. Email: aji_ie@ub.ac.id
References
- Ahmad, A. R., Hassan, A., Alhammadi, Y., & Jameel, A. S. (2021). National Culture , Leadership Styles and Job Satisfaction: An Empirical Study in the United Arab Emirates*. Journal of Asian Finance, Economics and Business, 8(6), 1111-1120. https://doi.org/10.13106/jafeb.2021.vol8.no6.1111
- Allen, T. D., Cho, E., & Meier, L. L. (2014). Work-Family Boundary Dynamics. Annual Review of Organizational Psychology and Organizational Behavior, 1(1), 99-121. https://doi.org/10.1146/annurev-orgpsych-031413-091330
- Ashforth, B. E., Kreiner, G. E., & Fugate, M. (2000). All in a day's work: Boundaries and micro role transitions. Academy of Management Review, 25(3), 472-491. https://doi.org/10.5465/AMR.2000.3363315
- Aycan Z. (2011). Cross-Cultural Approaches to Work-Family Conflict. In: Korabik, K., Lero, D. S., & Whitehead, D. L. (Eds.). Handbook of Work-Family Integration: Research, Theory, and Best Practices (pp. 353-370). Elsevier Science. https://books.google.co.id/books?id=JXiphWwbVxsC
- Beham, B., Drobnic, S., & Prag, P. (2011). Work demands and resources and the work-family interface: Testing a salience model on German service sector employees. Journal of Vocational Behavior, 78(1), 110-122. https://doi.org/https://doi.org/10.1016/j.jvb.2010.07.008
- Bhumika, B. (2020). Challenges for work-life balance during COVID-19 induced nationwide lockdown: exploring gender difference in emotional exhaustion in the Indian setting. Gender in Management: An International Journal, 35(7/8), 705-718. https://doi.org/10.1108/GM-06-2020-0163
- Breaugh, J. A. (1985). The Measurement of Work Autonomy. Human Relations, 38(6), 551-570. https://doi.org/10.1177/001872678503800604
- Burke, R. J. (2004). Work and Family Integration. Emerald Insight, 27(1), 89-107. https://doi.org/10.110802610150810844965 https://doi.org/10.110802610150810844965
- Carlson, D. S., Kacmar, K. M., & Williams, L. J. (2000). Construction and Initial Validation of a Multidimensional Measure of Work-Family Conflict. Journal of Vocational Behavior, 56(2), 249-276. https://doi.org/https://doi.org/10.1006/jvbe.1999.1713
- Caudroit, J., Boiche, J., Stephan, Y., Le Scanff, C., & Trouilloud, D. (2011). Predictors of work/family interference and leisure-time physical activity among teachers: The role of passion towards work. European Journal of Work and Organizational Psychology, 20(3), 326-344. https://doi.org/10.1080/13594320903507124
- Chin, W. (1998). The partial least squares approach for structural equation modeling. In: Marcoulides, G. A. (Eds.), Modern methods for business research (pp. 295-336). Psychology Press.
- Clark, S. C. (2000). Work/Family Border Theory: A New Theory of Work/Family Balance. Human Relations, 53(6), 747-770. https://doi.org/10.1177/0018726700536001
- Dakduk, S., Gonzalez, A., & Portalanza, A. (2019). Learn about structural equation modeling in smartPLS with data from the customer behavior in electronic commerce study in Ecuador (2017). In SAGE Research Methods Datasets Part 2. SAGE Publications, Ltd. https://www.doi.org/10.4135/9781526498205
- Desrochers, S., & Sargent, L. D. (2004). Boundary/Border Theory and Work-Family Integration 1. Organization Management Journal, 1(1), 40-48. https://doi.org/10.1057/omj.2004.11
- Duxbury, L., & Smart, R. (2011). The "Myth of Separate Worlds": An Exploration of How Mobile Technology has Redefined Work-Life Balance. In: Kaiser, S., Ringlstetter, M. J., Eikhof, D. R., & Cunha, M. e (Eds.), Creating Balance? International Perspectives on the Work-Life Integration of Professionals (pp. 269-284). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-16199-5_15
- Geertz, C. (1973). The Interpretation Of Cultures. Basic Books. https://books.google.com.my/books?id=BZ1BmKEHti0C
- Golden, A. G., & Geisler, C. (2007). Work-life boundary management and the personal digital assistant. Human Relations, 60(3), 519-551. https://doi.org/10.1177/0018726707076698
- Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications. https://books.google.co.id/books?id=Xn-LCwAAQBAJ
- Harmer, B., Pauleen, D. J., & Schroeder, A. (2008). Cause or cure: Technologies and work-life balance. ICIS 2008 Proceedings - Twenty Ninth International Conference on Information Systems, May 2014.
- Hill, E. J., Ferris, M., & Martinson, V. (2003). Does it matter where you work? A comparison of how three work venues (traditional office, virtual office, and home office) influence aspects of work and personal/family life. Journal of Vocational Behavior, 63(2), 220-241. https://doi.org/10.1016/S0001-8791(03)00042-3
- Helliwell, J., Layard, R., & Sachs, J. (2018). World Happiness Report 2018, Sustainable Development Solutions Network. https://s3.amazonaws.com/happiness-report/2018/WHR_web.pdf
- ILO-OECD. (2020). The impact of the COVID-19 pandemic on jobs and incomes. https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_756331.pdf
- Ingsih, K., Prayitno, A., Waluyo, D. E., Suhana, S., & Ali, S. (2020). The Effect of Training , Information Technology , Intellectual and Emotional Intelligence on Teachers' Performance. Journal of Asian Finance, Economics and Business, 7(12), 577-582. https://doi.org/10.13106/jafeb.2020.vol7.no12.577
- Kalliath, T., & Brough, P. (2008). Work-life balance: A review of the meaning of the balance construct. Journal of Management & Organization, 14(3), 323-327. https://doi.org/10.5172/jmo.837.14.3.323
- Katz, J. E., & Aakhus, M. (2002). Perpetual Contact: Mobile Communication, Private Talk, Public Performance. Cambridge University Press. https://books.google.co.id/books?id=Wt5AsHEgUh0C
- Kim, H., & Kim, O. (2015). The Effect of Smart Work Quality on Collective Intelligence and Job Satisfaction. Journal of Distribution Science, 13(5), 113-120. https://doi.org/10.15722/JDS.13.5.201505.113
- Kitayama, S., & Park, J. (2010). Cultural neuroscience of the self: Understanding the social grounding of the brain. Social Cognitive and Affective Neuroscience, 5(2-3), 111-129. https://doi.org/10.1093/scan/nsq052
- Lin, P. T. J., & Ping, L. C. N. (2016). Perceived Job Autonomy and Employee Engagement as Predictors of Organizational Commitment. Undergraduate Journal of Psychology, 29(1), 1-16.
- Pheng, L. S., & Chua, B. K. Q. (2018). Work-Life Balance in Construction: Millennials in Singapore and South Korea. Springer Singapore. https://books.google.co.id/books?id=OvYHuQEACAAJ
- Maddy, S. (2020). Why the pandemic is causing spikes in breakups and divorces . BBC Worklife. Retrieved June 01, 2021 from https://www.bbc.com/worklife/article/20201203-why-thepandemic-is-causing-spikes-in-break-ups-and-divorces
- Matthews, R. A., & Barnes-Farrell, J. L. (2010). Development and Initial Evaluation of an Enhanced Measure of Boundary Flexibility for the Work and Family Domains. Journal of Occupational Health Psychology, 15(3), 330-346. https://doi.org/10.1037/a0019302
- McGinnity, F., & Whelan, C. T. (2009). Comparing Work-Life Conflict in Europe: Evidence from the European Social Survey. Social Indicators Research, 93(3), 433-444. https://doi.org/10.1007/s11205-008-9437-y
- Middleton, C. (2008). Do mobile technologies enable work-life balance? Dual perspectives on BlackBerry usage for supplemental work. In: Hislop, D. (Eds), Mobility and Technology in the Workplace (pp. 209-224). Taylor & Francis. https://books.google.co.id/books?id=Wol8AgAAQBAJ
- Nam, T. (2014). Technology Use and Work-Life Balance. Applied Research in Quality of Life, 9(4), 1017-1040. https://doi.org/10.1007/s11482-013-9283-1
- Ollier-Malaterre, A., Valcour, M., Den Dulk, L., & Kossek, E. E. (2013). Theorizing national context to develop comparative work-life research: A review and research agenda. European Management Journal, 31(5), 433-447. https://doi.org/https://doi.org/10.1016/j.emj.2013.05.002
- Powell, G. N., Francesco, A. M., & Ling, Y. (2009). Toward culture-sensitive theories of the work-family interface. Journal of Organizational Behavior, 30(5), 597-616. https://doi.org/10.1002/job.568
- Sapta, I. K. S., Muafi, M., & Setini, N. M. (2021). The Role of Technology , Organizational Culture , and Job Satisfaction in Improving Employee Performance during the COVID-19 Pandemic. Journal of Asian Finance, Economics and Business, 8(1), 495-505. https://doi.org/10.13106/jafeb.2021.vol8.no1.495
- Towers, I., Duxbury, L., Higgins, C., & Thomas, J. (2006). Time thieves and space invaders: Technology, work and the organization. Journal of Organizational Change Management, 19(5), 593-618. https://doi.org/10.1108/09534810610686076
- Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications. Springer Berlin Heidelberg. https://books.google.co.id/books?id=PPUbvBUvmWoC
- Waller, A. D., & Ragsdell, G. (2012). The impact of e-mail on work-life balance. Aslib Proceedings, 64(2), 154-177. https://doi.org/10.1108/00012531211215178
- Yang, J., Zhang, Y., Shen, C., Liu, S., & Zhang, S. (2019). Workfamily segmentation preferences and work-family conflict: Mediating effect of work-related ICT use at home and the multilevel moderating effect of group segmentation norms. Frontiers in Psychology, 10(MAR). https://doi.org/10.3389/fpsyg.2019.00834
- Yang N. (2005). Individualism-collectivism and work-family interfaces: A Sino-US comparison. In: Poelmans, S. A. Y. (Eds). Work and Family: An International Research Perspective (pp. 287-318). Taylor & Francis; https://books.google.co.id/books?id=-vN5AgAAQBAJ
- Yang, N., Chen, C., & Choi, J. (2000). Sources of Work-Family Conflict: A Sino-U.S. Comparison of the Effects of Work and Family Demands. Academy of Management Journal, 43. https://doi.org/10.2307/1556390