Relationship among family, work engagement, and turnover intention form J-DR perspective: exploring family’s dual role as source of conflict and support

Abstract

Family serves as a job resource that can improve employees’ work engagement. However, increased work engagement can potentially trigger work-family conflict and lead to employees’ withdrawal, even employees turnover. It is necessary to explore family functions to fill the existing theoretical and practical gap. Therefore, the present study aims to analyze the relationship among family, work engagement, and turnover intention by considering the family as a sources source of both conflict and support. To this end, this study surveyed non-manager and staff-level employees in pharmaceutical companies in Indonesia. Analyzed using SEM covariance procedure with AMOS 23 software, this study found that family plays dual roles in affecting employees’ work engagement. Increased work engagement was found to result in a lower turnover intention yet increasing work-family conflict. Increased sales, working hours, and targets are among the factors leading to work-family conflict. Work engagement is a double-edged sword that should be handled carefully through communication and stress management interventions. Activities like family gathering programs are also recommended to minimize work-family conflict and improve family support. It is also important to manage the work based on feedback, communication, and capacity building according to standards in the work process in the field of the pharmacy industry.

Keywords:

• family support
• pharmaceutical company
• turnover intention
• work engagement
• work-family conflict

PUBLIC INTEREST STATEMENT

This paper highlighted how the family becomes a resource and job demand that encourages an increase in a person’s absorption (involvement) in work. However, this increase has the potential to create conflicts in the family that can encourage employee withdrawal from work, including leaving the organization. Exploration of two sides of the function of the family needs to be done to meet the theoretical and practical needs. The research analyzes relationships among family, work engagement, and turnover intention from the J-DR perspective, exploring the family’s dual role as a source of conflict and support. The research findings that family plays dual roles in affecting employees’ work engagement. Increased work engagement was found to result in a lower turnover intention yet increasing work-family conflict. Work engagement is a double-edged sword that should be handled carefully through communication and stress management interventions. Activities like family gathering programs are also recommended to minimize work-family conflict and improve family support

1. Introduction

An increase in work engagement is known to potentially lead to a higher possibility of work-family conflict, particularly among staff-level employees whose family lacks an understanding of work dynamics. During the COVID-19 pandemic, job pressures increase as the working pattern heavily relies on information technology. A flexible working hour offered by today’s well-established IT facilities appears to be prone to work-family conflict. The conflict may arise as employees cannot be disturbed during their working-from-home hours or limited IT facilities at home.

Work-family conflict is commonly found in any work environment, including employees in pharmaceutical companies, namely medical representatives (MR), among others. Changes in work hours, demands for communicating with clients at all times, and greater work pressure due to COVID-19 appear to affect work-family conflict. Previous studies suggest that family is the source of both support and conflict to employees’ jobs (Islam et al., 2019; Wang, 2018). Zhou et al. (2020) report a relationship between social support and work-family conflicts. Issues on work-family may encourage companies to optimize HR governance functions to ensure employees keep motivated and stay with the organization, especially those with significant contributions to the organization.

Work-family conflict has drawn huge attention from academics and corporate practitioners. It is seen as an interesting topic in the field of organizational behavior, given its negative effect on the organization and job satisfaction (Fiaz & Qureshi, 2021). Significant roles of the family as both sources of conflict and work resource needs to be investigated further, especially in the pharmaceutical industry. Family becomes a resource and job demand that encourages an increased job engagement yet potentially triggers family conflict that may result in employee withdrawal. The family also serves as a resource for work to support employees in surviving difficult times.

Work-family conflict is reported to be the most common issue faced by employees (Fiaz & Qureshi, 2021). Existing literature on this topic mostly attempt to understand the effect of work-family conflict and employees commitment on job satisfaction (Islam et al., 2019), the relationship among job satisfaction, work stress, work-family conflict, and turnover intention (Chan & Ao, 2018), Lu et al., 2017), the relationship among work-family conflict, turnover intention, and organizational citizenship behavior (I.-A. Wang et al., 2017), and the relationship between work-family conflict and work burnout (Blanco-Donoso et al., 2021).

In the Indonesian context, where most families have a large structure, the family can serve as both sources of conflict and support for employees. In this regard, leaders who support the family are likely to mediate the conflict and family reputation, minimizing the work-family conflict (Liu et al., 2020). Family support is reported to minimize work-family conflict (Haar, 2004). Complex family positions in large family structures like those found in Indonesian families can provide support.

Work engagement is one of the under researched variables in the relationship between work-family conflict and turnover intention. Its concept and measurement are closely related to work resources in job demand-resources theory (JD-R; Lee et al., 2018). Work engagement supports ongoing physical and psychological efforts in the workplace (Shi & Gordon, 2019). Schaufeli et al. (2019) define work engagement as a positive, satisfying work-related state of mind characterized by vigor, dedication, and absorption. However, Tirastittam et al. (2020) criticized that work engagement by definition is not convincing. Bakker and Demerouti (2018) state that most studies adopting individual-level approaches report differences in the average level of work engagement between individuals due to working conditions, personal characteristics, and behavioral strategies. Kisahwan (2020) emphasizes the need for more studies to test work engagement as a mediation variable for turnover intention. Work engagement plays a significant role in promoting organizational success.

It is necessary to examine the mediating role of work engagement in turnover intention and family’s dual functions (i.e., as sources of conflict and support) based on the theoretical and practical needs. Harun et al. (2020) suggest that the effects of stress on work-family conflict, work engagement, and turnover intention have not been fully explored and understood. Theoretical and practical knowledge is needed as the basis for the development and sustainability of managerial practices to reduce the losses of work engagement to family conflicts, as well as high employee turnover. Stress management interventions and family-friendly policies to minimize conflict and employee work-family support, as Wang put forward (Wang, 2018), can be developed with due regard to the external work dynamics. Ensuring the sustainability of such programs requires a conceptual foundation and empirical evidence, which will be presented by this study. The contribution of the present study includes a framework for companies to develop intervention programs to minimize conflict work-family conflict while conducting critical evaluations of their effectiveness from a cost-benefit perspective. In addition, this study describes the position of work engagement as a mediation variable for turnover intention. The goal of the study was to analyze the relationship among family, work engagement, and turnover intention from the JD-R theory perspective by considering the family’s dual functions, i.e., a source of both conflict and support.

2. Literature review and hypotheses

2.1. Work engagement mediates the influence of family conflict and works on turnover intentions

Work-family conflict is known to adversely affect employees’ mental health, leading to lower work engagement and increased turnover intentions. Liu et al. (2020) and Chen et al. (2018) state that work-family conflict has a direct influence on turnover intentions. Lee et al. (2018) suggest from JD-R’s perspective that works engagement is a mediation for turnover intention. Employee withdrawal is related to the intention to leave the organization due to conflicts between work and family. Harun et al. (2020) and Cao et al. (2020) add that the work engagement function as mediation for turnover intention. Wang (2018) said, work and family conflicts reduce work engagement and increase turnover intentions. The JD-R model reveals a dual psychological process in employees. Islam et al. (2019) state that family conflict defines weak family support due to decreased work engagement and increased turnover intention. In this regard, the proposed hypotheses are as follow:

H1: Family and work conflicts affect work engagement.

H2: Family and work conflicts affect turnover intentions.

H3: Work engagement mediates family and work conflicts on turnover intentions.

2.2. Work engagement mediates family support as a resource for turnover intentions

Following the JD-R model, work engagement is the core component that connects job resources and positive outcomes (Bakker & Demerouti, 2018; Wang, 2018). Family support is one of the job resources of an employee. Job resources are reported to affect work engagement (Lesener et al., 2019). The JD-R model explains how two types of resources both work and personal can lead to work engagement (Majumdar and Kumar 2020, Han et al., 2020). The role of the family, among others, provides social support, a pivotal factor in employment (H.-j. Wang et al., 2020; Wang, 2018). Kiema‐Junes et al. (2020) argue that family support serves as a resource for work. Family relationship support describes the structure of social networks that encourages a person to stay with his/her organization (Zhou et al., 2020). Family support is positively related to the psychological needs of employees and negatively relates to the intention to leave the organization. Family support may minimize work-related stress and keep employees’ working spirit to cope with high-pressure work. Therefore, this study expects that:

H4: Family support affects work engagement.

H5: Family support affects turnover intentions.

H6: Work engagement mediates the effect of family support on turnover intention.

The conceptual framework of this study can be described in Figure 1 as follows

Figure 1. Conceptual framework.

3. Method

This survey study involved 310 employees of pharmaceutical companies in Indonesia recruited using a random sampling technique. The work-family conflict (WFC) scale from Carlson et al. (2000) and Liu et al. (2020) were employed, some items read: 1) work keeps me away from family activities more than I want, 2) the time I have to devote to work makes me unable to participate as a responsibility to my family, 3) I have to skip family activities because of the amount of time spent working.

In measuring family support, the family support inventory for workers (FSIW) developed by King et al. (1995) was used. Some items read: 1) members of my family burdening me with things that they should be able to handle themselves (instrumental assistance) and 2) My family wasn’t interested in hearing about my workday (emotional sustenance).

Work engagement in this study was measured using Utrecht Work Engagement Scale (UWES), covering three dimensions, namely vigor, dedication, and absorption, according to Schaufeli et al. (2019). Some items read: 1) vigor is the awareness of employees to feel the energy, strength, desire to work, readiness to continue working for a very long time at a time; 2) dedication as a gift to a more organizational purpose by finding meaning and purpose, enthusiasm for work, inspiration in work, pride in the work done, challenges in work; and 3) absorption as a process of assimilation on the work of the dissertation with a feeling towards the time that passes very quickly while working.

Lastly, the turnover intention was measured using Chen et al.’s (2018) indicators, which describe the turnover intention indicator as follows: 1) actively looking for a new job; 2) often thinking of quitting the current job, and 3) will probably look for a new job the following year.

Respondents were provided with five response options from 1 (strongly disagree) to 5 (strongly agree). We asked for help from HR Department or company representatives to distribute envelopes containing questionnaires. The questionnaire was returned to the researchers’ addresses and social media. The number of questionnaires shared per company plus 10% in anticipation of incomplete answers. The collected data were analyzed using descriptive statistics and Structural Equation Modeling.

4. Results

The following Table 1 displays the result of the goodness of fittest.

Table 1. Overall model fit analysis

Goodness of Fit Parameters	First Parameters	Second Parameters	Cut-off Value	Testing Conclusion
Absolute Fit:
Chi-Square (X^2)/Degree of Freedom	2.664	1.932	< 2.00	Good Fit
P-Value of Chi Square (X^2)	.000	0.000	≥ 0.05	Poor
Root Mean Square Error of Approximation (RMSEA)	0.073	0.055	≤ 0.08	Good Fit
Goodness-of-Fit Index (GFI)	0.921	0.944	> 0.90	Good Fit
Standardized Root Mean Square Residue (SRMR)	0.031	0.029	< 0.08	Good Fit
Expected Cross-Validation Index (ECVI)	0.832	0.665	< Saturated model 0.680	Good Fit
Incremental Fit:
Comparative Fit Index (CFI)	0.956	0.977	> 0.90; > 0.95	Good Fit
Normed Fit Index (NFI)	0.931	0.953	> 0.90; > 0.95	Good Fit
Tucker-Lewis Index (TLI)	0.943	0.968	> 0.90; > 0.95	Good Fit
Incremental Fit Index (IFI)	0.956	0.977	> 0.90; > 0.95	Good Fit
Relative Fit Index (RFI)	0.912	0.936	> 0.90; > 0.95	Good Fit
Adjusted Goodness of Fit Index (AGFI)	0.884	0.913	≥ 0.90	Good Fit
Parsimonious Fit:
Parsimony Goodness of Fit Index (PGFI)	0.623	0.602	> 0.60	Good Fit
Akaike Information Index (AIC)	257.160	205.419	< Saturated model 210.000	Good Fit
Consistent Akaike Information Criterion (CAIC)	418.204	385.409	< Saturated model 707.340	Good Fit

Source: Researcher processed data

Based on Table 1 Overall Model Fit Analysis, there are 14 Good Fit and 1 Poor, then we can conclude that the fit between the data and model is already Good Fit now. The RMSEA is better also now, 0.055, Good Fit. Then we can continue the next is testing: Measurement Model Fit Analysis.

Ghozali (2011) explains that measurement model fit analysis for validity testing can be done by conducting: 1. Construct Validity Test, 2. Convergent Validity Test, and 3. Reliability Test. In this step, we will do the Construct Validity Test first, by looking at the “C.R. (Critical Ratio)” score than the “P (Probability)”. If the CR is > 1.96 (1.96 is the critical value at the significant level 0.05) and P < 0.05. then the indicator is valid, able to reflect the latent variable. If the “P” score show “***”, it means that the “P” score is significant, targeted < 0.001.

Based on Table 2 Regression Weight, we can see from Amos output, all observed variables have CR score > 1,96 and P score shows “***”, which means < 0,05. We conclusion the result of measurement model fit analysis is fit for construct validity test. Then we can continue the next step with the convergent validity test is testing the indicator whether has a high variance proportion or not. All the items/observed variables/indicator of a latent variable should be converging or share the high variance proportion. To conduct the convergent validity test, it can be done by looking at the “Loading Factor” or the “Standardized Loading Factor/SLF” score. If the SLF scores are high, it shows that the observed variable and its latent variables are converged or valid. It would converge/valid if the SLF score is ≥ 0.70 (Hair et al., 2019).

Table 2. Regression weighs

			Estimate	S.E.	C.R.	P	Label
WE	<—	WFC	.132	.059	2.218	.027	par_14
WE	<—	FS	.821	.134	6.117	***	par_15
TOI	<—	WE	−1.604	.183	−8.760	***	par_11
TOI	<—	FS	−.293	.217	−1.349	.177	par_12
TOI	<—	WFC	−.159	.084	−1.897	.058	par_13
WFC1	<—	WFC	1.000
WFC2	<—	WFC	1.026	.057	18.086	***	par_1
WFC3	<—	WFC	.728	.056	12.905	***	par_2
WFC4	<—	WFC	.888	.054	16.298	***	par_3
WFC5	<—	WFC	1.063	.055	19.482	***	par_4
WFC6	<—	WFC	.790	.059	13.282	***	par_5
WE1	<—	WE	1.000
WE2	<—	WE	1.042	.085	12.232	***	par_6
WE3	<—	WE	.957	.079	12.170	***	par_7
TOI1	<—	TOI	1.000
TOI2	<—	TOI	.878	.039	22.233	***	par_8
TOI3	<—	TOI	.763	.042	18.233	***	par_9
FS1	<—	FS	1.000
FS2	<—	FS	.701	.072	9.732	***	par_16

Source: Researcher processed data

Based on the Table 3 standardized regression weights, all observed variables have the “Standardized Loading Factor/SLF” ≥ 0.70, leading to the conclusion that all the variables are valid. However, there are 3 observed variables, namely: WFC3 is 0.672, WE1 is 0.675, and FS2 is 0.673 that have the SLF score ≤ 0.70. Based on Hair et al. (2007) and Igbaria et al. (1997), those 3 observed variables are still valid (if the SLF score is ≥ 0.05, it means valid). Table 4 shows a summary up of all the validity test results.

Table 3. Standardized regression weights

			Estimate
WE	<—	WFC	.203
WE	<—	FS	.748
TOI	<—	WE	−.797
TOI	<—	FS	−.133
TOI	<—	WFC	−.122
WFC1	<—	WFC	.866
WFC2	<—	WFC	.826
WFC3	<—	WFC	.672
WFC4	<—	WFC	.776
WFC5	<—	WFC	.865
WFC6	<—	WFC	.716
WE1	<—	WE	.675
WE2	<—	WE	.828
WE3	<—	WE	.816
TOI1	<—	TOI	.911
TOI2	<—	TOI	.887
TOI3	<—	TOI	.795
FS1	<—	FS	.782
FS2	<—	FS	.673

Source: Researcher processed data

Table 4. Summary up all the reliability testing results

Latent Variables	CR Score	VE Score	Reliability Conclusion
Work Family Conflict (WFC)	0.94 ≥ 0.70	0.62 ≥ 0.50	Reliable
Family Support (FS)	0.79 ≥ 0.70	0.53 ≥ 0.50	Reliable
Work Engagement (WE)	0.88 ≥ 0.70	0.60 ≥ 0.50	Reliable
Turnover Intention (TOI)	0.94 ≥ 0.70	0.75 ≥ 0.50	Reliable

Source: Researcher processed data

Reliability Testing with Construct Reliability (CR) Test is measuring how reliable and consistent the data. The CR score can be counted with this below formula: $\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{i}\mathrm{a}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}\left(\mathrm{C}\mathrm{R}\right)=\frac{{({\sum }^{s}td.loading)}^2}{{({\sum }^{s}td.loading)}^2+{\sum }^{e}j}$

The CR score ≥ 0.70 means showing good reliability in the latent variable/construct (Hair et al.,2007). However, the 0.60 ≥ CR ≤ 0.70 is still acceptable if the validity testing results for the indicator are valid (Ghozali, 2011).

With the above formula, we can count the CR score for the latent variables. Another reliability testing is using the Average Variance Extracted (AVE/VE) to complete the CR score. The AVE score can be counted using this below formula:

$\mathrm{V}\mathrm{a}\mathrm{r}\mathrm{i}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{E}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{e}\mathrm{d}\left(\mathrm{V}\mathrm{E}\right)=\frac{{\sum }^{s}td.loadin{g}^2}{{\sum }^{s}td.loadin{g}^2+{\sum }^{e}j}$

The AVE score ≥ 0.50 means showing the good convergent in the latent variable/construct. CR and VE score showing at Table Summary up all the reliability testing results as follows.

Based on the table summary of all the reliability testing results, we can conclude all the latent variables are reliable. As all the variables passed the reliability testing, we can continue to the next testing fit analysis, namely Structural Model Fit Analysis or Hypothesis Analysis. The critical decision in Structural Model Fit or Hypothesis Testing is checking the P-Value with significant level (alpha) at 0.05 or comparing the CR (Critical Ratio) score with t-table (1.96) (Sekaran & Bougie, 2016). Table 5 shows the result for Testing Fit—Structural Model Fit Analysis (Hypotheses Testing).

Table 5. Hypotheses testing

Hypotheses	Path	Standardized Loading	Value	CR Score	Hypotheses Conclusion
1	WE <—WFC	.203	0.027	2.218	Significant
2	WE <—FS	.748	0.000	6.117	Significant
3	TOI <—WE	−.797	0.000	−8.760	Not significant
4	TOI <—FS	−.133	0.177	−1.349	Not significant
5	TOI <—WFC	−.122	0.058	−1.897	Not significant

Source: Researcher processed data

Based on the above results, hypothesis 1 and hypothesis 2 has the CR (Critical Ratio) score > 1.96, P-value have < 0.05 as well, and evaluating the standardized loading factor, all have < 1.00. Therefore, we conclude that all the hypothesis is accepted. Hypotheses 3,4 and 5 rejected

5. Discussions

Although turnover intention among employees who participated in this study was found to be very low (average score of 1.61), there is still potential change in the intention that may significantly affect the organization. It should be noted that an intention can potentially turn into real behavior (e.g., voluntary resignation) or affect employees’ work morale. This can be a strong signal for improving the governance system, including work-family conflict management.

This study found that work-family conflict among respondents was low (average score 2.2). However, the potential work-family conflict may increase as the company demands become higher, especially during the COVID-19 pandemic. During the pandemic, employees are required to work more efficiently be adaptive, and be consistent in implementing several work procedures. Regarding family support, the present study found a fairly high family support (average score 3.91). Social support as social capital may affect work activities, including employees’ psychological condition in facing work dynamics and stressful environment due to COVID-19. Family support as an ongoing resource for employees includes feedback for employees in building hopes and careers in work. Work engagement was found to be in the fairly high category (average score 4.25). Employees of pharmaceutical companies, in general, have positive thoughts to express themselves in the work. Nevertheless, a high work engagement requires stability and improvement amid the stressful COVID-19 pandemic.

The test results with the SEM covariance procedure obtained a picture of the factor weight of each indicator is above 0.5 with a latent variable composite reliability value of 0.79 to 0.94 is greater than the recommended 0.70. Based on the test results, the model in this study meets the fit criteria. The construction of each variable is considered to be by the results of empirical it means articulating reality. The definition structure has empirical indicators that have the potential to be concept indicators as well as explain phenomena despite having fewer parameters and range values. Each parameter is consistent with the theory. The measurements of work-family conflict are in line with (Carlson et al., 2000; Liu et al., 2020). For family support inventory for workers (FSIW) in line with (King et al., 1995; Wayne et al., 2006). The construction of work engagement is in line with the Utrecht Work Engagement Scale (UWES) as stated by (Kisahwan, 2020; Schaufeli et al., 2019). The concept and indicator of turnover intention are in line with (Chen et al., 2018; Kisahwan, 2020). Multidimensional concepts can be developed in accordance with the context of the research. Indicators in accordance with events, and empirical results that are employees in pharmaceutical companies as long as the specific attributes attached to the variable are clearly stated.

Based on the identified results there is no negative variance of error, this information means according to the results, very low standard error coefficients and correlations between estimation coefficients are obtained at the model level. Test results showed that hypotheses 1 and 2 were accepted while hypotheses 3, 4, and 5 were rejected. The results of influence testing for mediation variables showed that the value of Z is greater than Z calculated means that work engagement mediates the influence of work family conflict and family support on turnover intention. This finding is consistent with Liu et al. (2020) and Chen et al. (2018) who report no direct effect of work-family conflict on turnover intention (Cao et al., 2020; Harun et al., 2020; Lee et al., 2018; Wang, 2018). This shows that the family is a resource for work. Work and family are at a low level with the JD-R model, family support is a working power in line with (Lesener et al., 2019; Majumdar & Kumar, 2020; Han et al., 2020; Kiema‐Junes et al., 2020).

The role of work engagement as a mediation variable is accepted even though it is not in full or perfect (perfect mediation). The results of the study further emphasize that the position of work engagement is very strategic for the company’s efforts in reducing turnover intentions and making the company a desirable place to work. Function work engagement strategies as stated (Kisahwan, 2020). Work engagement is self-expression, cognitive and emotional based on its experience interacting with family as a resource for work as well as a source of pressure that triggers personal disengagement.

Work engagement is a rational psychological experience and is mediated by individual perception. Therefore, companies through their HR governance system need to ensure that employees get family support and are free from work-family conflict issues. Companies need to pay attention and design programs to develop personal resources that drive work engagement. The companies need to actively identify and evaluate individuals’ feelings about the family environment, including resilience when facing work-family conflict. It is also necessary to develop family support for the work and achievements of employees. Companies need to build communication both formally and nonformal to ensure employees’ high work engagement to minimize turnover intentions. The company through its communication system and HR governance should maintain employees’ high work engagement through human resource practices to support employees through families. Work engagement does not only denote individuals’ positive response to work-related knowledge and experience but also serves as a mental representation of employees’ work and their work environment.

The company’s success in improving work engagement through formal and informal interactions with employees’ families may represent the company’s understanding of the employee’s mental aspects and their well-being. As Schaufeli et al. (2019), Bakker and Demerouti (2018) point out, personal resources play a pivotal role in determining their ability to express themselves physically, cognitively, and effectively at work and prevent them to stay with the organization.

Human resources management plays a critical role in ensuring the family role as employees’ work and personal resource through communication and coordination. This is important to balance employees’ work and family roles. The company needs to design structural configurations including adhocracy by involving the employee’s family through representatives to be part of work engagement management. The company can also establish non-formal direct communication to gain an intersubjective understanding between the company and the family through the HR division, increasing the capacity of medical representatives to continue to work with high work engagement, including educating about pharmaceuticals to doctors and pharmacies with low turnover intentions.

5.1. Limitations

Respondents were limited to non-manager employees with large family structures such as in Indonesia. The exploration of family positions in this study was viewed from a JD-R perspective. Fiaz and Qureshi (2021) present work-family conflicts as interesting subjects in the field of organizational behavior.

6. Conclusion

Work engagement is found to mediate the effect of work-family conflict and family support on turnover intention. Changes in employee turnover intention appear to be mitigated by their work engagement. There is a need to develop non-formal communication with families to manage stress. It is also necessary to organize family gathering programs to reduce work-family conflict. Further research is needed to explore job resources that can increase the work engagement of employees from different fields.

Acknowledgements

The authors would like to thank Telkom University for Research Center, Bandung, Indonesia, for sponsoring this publication.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Alex Winarno

Alex Winarno graduates of the Doctoral Program in Management Science at the Indonesian of Education University. Currently as an Assistant Professor at the Department of Business Administration, Faculty of Business and Communication, Telkom University, Bandung, Indonesia. Research interest in domain management subdomain organizational behavior and human resources management.

For 15 years he held a structural position at Telkom University. E-mail: [email protected]