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Article

Does Work-Life Balance Moderate the Relationship between Career Commitment and Career Success? Evidence from an Emerging Asian Economy

by
Usama Najam
1,
Umar Burki
2,* and
Wajiha Khalid
3
1
Faculty of Business and Accountancy, University of Malaya, Kuala Lampur 50603, Malaysia
2
Department of Business, History and Social Sciences, University of South-Eastern Norway, 3603 Kongsberg, Norway
3
Department of Business Administration, Air University Multan Campus, Multan, Punjab 60000, Pakistan
*
Author to whom correspondence should be addressed.
Adm. Sci. 2020, 10(4), 82; https://doi.org/10.3390/admsci10040082
Submission received: 24 August 2020 / Revised: 30 September 2020 / Accepted: 30 September 2020 / Published: 14 October 2020
(This article belongs to the Special Issue Servant Leadership and Followers’ Well-Being)
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Versions Notes

Abstract

:
This study examines the relationship between career commitment and employee career success (objective and subjective success) in middle-level employees working in the service sector. Further, the study investigates the moderating effect of work-life balance on the relationship between career commitment and career success. By analyzing data from 360 middle level working employees, our empirical results show that career commitment has a positive and significant effect on the objective and subjective career success of employees. Work-life balance positively moderates the relationship between career commitment and subjective career success, whereas it fails to moderate the relationship between career commitment and objective career success. The study contributes by providing a better understanding of the employee’s perception of career commitment and career success and their management in emerging markets. Avenues for future research are identified.

1. Introduction

Researchers argue that personnel career success and career commitment is vital for organizations and individual’s growth (Sullivan and Baruch 2009; Feldman and Ng 2007; Ng et al. 2005). Management literature (Burke 2006; Yean and Yahya 2013; Spurk et al. 2019) shows more focus on different appreciative types of job-related practices in organizations that enhance employees’ career success. Similarly, organizational policies such as human resource practices play a vital role in an employee’s career success (Kumar and Rajendran 2018). Literature accentuates that career enhancement effects organizational strategies such as frequent organizational shifts and networking bring about career success (De Janasz and Forret 2008). Current research argues that career success is embedded in a social environment and includes an employee’s personal life and job-related factors. Therefore, it is essential to avoid examining career success in isolation (e.g., Ocampo et al. 2018).
Previous research (e.g., Seierstad and Kirton 2015) indicates a positive relationship between career commitment and career success. Career commitment (CC) as an antecedent for career success Carson and Bedeian (1994) demonstrates that career commitment is an employee’s motivation toward a chosen job. Alnıaçık et al. (2012) defined career commitment as an employee’s behavior to accept a job responsibility, seek new experience, and work settings to accomplish career goals. Research (Ballout 2009; Srikanth and Israel 2012) defines career success as an individual success is in his/her career and comprises of subjective career success factors (e.g., satisfaction, growth, etc.) and objective career success (e.g., salary level, promotion, etc.). Objective career success comprises concrete results, for example pay and advancement and appreciation in the work environment (Judge et al. 1995). In comparison, subjective career success refers to a person’s personal view of success and reflected by occupational achievement, fulfillment with one’s job, and vocational training (Judge et al. 1995; Aryee et al. 1994).
Work-life balance (WLB) is a person-centered approach, and each person has a unique work-life balance approach (Kossek et al. 2014). According to each person’s career and life stage, it varies because of individual values, goals, and aspirations (Greenhaus and Allen 2011). Work-life balance is also referred to as a relationship between job times or space of work with additional life-related factors (Felstead et al. 2002). Literature also shows that in the presence of self-efficacy, individuals having high levels of career commitment achieve better career success (Ballout 2009).
When organizations provide a decent work-life balance, employees achieve better career success (Haar et al. 2014). Management literature (Haar et al. 2014; Kossek et al. 2014) refers to the work-life balance as an individual’s ability to properly balance one’s life roles. The work-life balance effects individual work outcomes, perceptions, and beliefs that may affect employees’ career attitudes (Lyness and Judiesch 2014; Kossek et al. 2014). Similarly, it affects the career success of individuals. Career success demands an individual employee to devote and manage their work-life in a more self-directed manner (Lee et al. 2016; Mas-Machuca et al. 2016). It is vital to examine the social contexts in measuring career success factors related to employee work-life balance (Ferreira et al. 2020). Similarly, the associations between career commitment, career success, and work-life balance are likely to have different meanings in emerging Asia economies.
Prior research endorses a positive relationship between career commitment and career success (Carson et al. 1999; Day and Allen 2004). However, these studies only measure career commitment to subjective career success and completely ignore objective evaluation. Furthermore, research on subjective career evaluation fails to incorporate social norms of career success, such as individual salary or promotional history (Dries et al. 2009). It is essential to measure parallel how career success subjectively and objectively is affected by employees’ career commitment for a better holistic view. Hence, this study intends to fill this research gap by measuring career commitment’s impact on career success by incorporating both subjective and objective career success dimensions. Another vital gap in the career success literature is the absence of the boundary constraint condition. Relevant literature underscores that work-life balance significantly affects the employees’ career success (Lyness and Judiesch 2008; Sturges and Guest 2004). This study fills this research gap by examining the moderating effect of work-life on the relationship between career commitment and career success (objective and subjective success).
This study focuses on the role of career commitment and work-life balance on an employee’s career success in the middle-management levels. There is a lack of literature on how employees’ work-family balance interacts with other predictors of career success (Ocampo et al. 2018), which is the main research question of this study. The authors attempt to contribute to this research gap. Further, they investigate the moderating role of work-life balance on the relationship between career commitment and career success.
In terms of contributes, this study augments in several ways. First, the study’s research context is an emerging Asian economy, which provides a better insight into work-related and other social factors affecting career success. Further, organizational management styles, work environment culture, and the relation between work and family have different meanings in Asian societies regarding career success (Thornton and Fricke 1987). Second, our study’s results would show whether Western management theories maintain their validity in an Asian management setting. Hence, this study follows Cooke’s (2018) argument about exploring the role of other factors that may affect human resource theoretical models and their outcomes. Third, the authors do not know other studies that examined the moderating role of work-life balance on the relationship between career commitment and career success. Hence, this paper examines the moderating role of work-life balance on the twin dimension of career success (subjective career success and objective career success).
The remainder of the paper is as follows. The next section describes the conceptual model and the formulated hypotheses. Next, we explain the empirical setting, data collection techniques, and validity of the measures, and the empirical results. The paper concludes with a discussion, research limitations, and directions for future research.

2. Conceptual Model and Hypotheses

Career commitment and work-life balance play a vital role in developing firms’ human resource practices. Career commitment demands a strong sense of identification, active involvement, development, and persuasion in career goals (Srikanth and Israel 2012). Career commitment allows individuals to assess one’s motivation and make an action to pursue their career. Existing researchers (Vandenberghe and Basak 2013; Crompton and Lyonette 2006) examine the role of career commitment and work-life balance on career success in the Western context. Furthermore, a bit of research examined the role of career commitment and work-life balance on career success in the Asian context. Ballout (2009) showed that self-efficacy moderates the relationship between career commitment and career success. Our model identifies that individuals must commit to their careers, because it will lead them toward their career success and provide a balance between their work and life helps to strengthen or weaken this relationship. Figure 1 illustrates our research model.

2.1. Career Commitment and Career Success

Career success is an essential variable in career research. It is an individual’s career experience (Arthur et al. 2005). Arthur et al. (2005) defined career success as a work-related outcome desired by an individual that they accomplished during work experience over time. Career success is also defined as a person’s preference and capability to attain positive degree work and outcomes for their career (Verbruggen 2012). Career scholars (e.g., Judge et al. 1995; Verbruggen 2012) agreed that career success is comprised of both a subjective and an objective side. Subjective career success refers to an individual’s perception of a career. Mostly, it operationalized growth or recognition in job or career satisfaction (Heslin 2005). Objective career success comprises of the concrete or tangible result; for instance, a pay rise, promotions, and advancement (Dries et al. 2009). Therefore, individuals and organizations need to understand their success’ subjective and objective goals and their effects.
Prior research supports the relationship of a career commitment to career success. For instance, Sultana et al. (2016) indicate that employees’ commitment to their careers plays a crucial role in their career success because employees can control their careers. Srikanth and Israel (2012) shows that career commitment predicts career success because commitment leads individuals toward favorable career outcomes. Alnıaçık et al. (2012) show that career motivation has a positive correlation with job satisfaction. Ballout (2009) indicates that career commitment is positively associated with career success. Employees who show better career commitment achieve more career success. Hence, we propose:
Hypothesis 1 (H1):
Career commitment has a positive effect on subjective career success.
Hypothesis 2a (H2a):
Career commitment has a positive effect on objective career success (promotions).
Hypothesis 2b (H2b):
Career commitment has a positive effect on objective career success (salary).

2.2. The Moderating Role of Work-Life Balance

Individual behavioral attitudes depend on the human’s ability to manage their life because individuals change their attitudes consistent with the work and life environment (Barnett and Hyde 2001). We argue that work-life balance is central in affecting the relationship between career commitment and career attitudes. Research (Kossek et al. 2014) finds that many employees valued work-life balance in their lives, which affects individual perceptions and beliefs about personal career attitudes. Better living and career goals balance motivate employees toward more job commitment (Poulose and Susdarsan 2014).
The literature on commitment and career success reports mixed results. For instance, studies (Maeran et al. 2013; Adams et al. 1996) found a negative relationship between work-life balance and job satisfaction. Other research studies (Shujaat et al. 2013) report a positive relationship between work and non-work balance regarding employee career and job satisfaction. Malik et al. (2010) findings suggest an insignificant effect between work-life balance and job satisfaction. Such opposing results show that work-life balance affects an employee’s behavior towards career success. Inconclusive results underline the need to examine the moderation effect of work-life balance and its impact on career success.
When employees demonstrate a commitment to their career, this commitment will help them achieve subjective career success (Barnett and Hyde 2001). This balance is vital for individuals’ subjective career success (Gálvez et al. 2020). Employees who have high work-life balance have firm control over work, life, and less conflict (Delecta 2011). In contrast, employees with a low balance between work and family showed dissatisfaction at work and diminishing family involvement (Delecta 2011). In the presence of high work-life balance, employees seek career success in subjective and objective areas. Hence, we propose:
Hypothesis 3 (H3):
Work-life balance positively moderates the relationship between career commitment and subjective career success.
Hypothesis 4a (H4a):
Work-life balance positively moderates the relationship between career commitment and objective career success (promotions).
Hypothesis 4b (H4b):
Work-life balance positively moderates the relationship between career commitment and objective career success (salary rises).

3. Methodology and Measurement

To test our proposed model, we applied a qualitative approach to test the effect of career commitment on career success and test the moderating effect of work-life balance. Therefore, to test our theoretical model empirically, we selected middle-management employees working in Pakistan’s service sector. We applied a cross-sectional survey method to collect the data and sent the self-administered questionnaires to the target respondents. We collected data (1) by visiting the organizations, (2) mailing the questionnaire, and (3) by courier. The respondents (managers and executives) worked in the service sector firms, mainly in telecommunication firms, IT firms, and the banking sector. The key respondents worked as managers and business executives, and the selected firms offer working individuals numerous opportunities to excel in their careers. The respondents had master’s degrees in their respective fields, were well conversant with the research problem, and had a good command of English. We visited the selected companies to ensure that they meet the selection criteria. We distributed four hundred and twenty (420) questionnaires to diverse middle-management persons working in the service sector. During the data collection process, we applied personal connections to achieve the maximum number of respondents. In the end, we selected received three hindered and sixty (360) useable responses, providing us an excellent response rate of 85%.
A cover letter stated the academic purpose of research to examine the employee’s career success achieved through career commitment and balancing their life with work. We applied a five-point Likert scale to measure all the items of our constructs. We took measures to counter the potential issues related to common method bias. First, we used the procedural remedies to control the variance by assuring the respondents about the study’s confidentiality and anonymity to the minimum respondent’s bias (Chang et al. 2010). Second, we used the statistical remedies by conducting a common latent factor test to impute the means after extracting the unexplained variance on a single latent factor using Amos. Since all the measures were self-reported, there has been a chance of common method bias. The composite variables were extracted by incorporating the unexplained variance explained by the common latent factor to deal with the common method bias (see Table 1).

3.1. Measures and Control Variables

This study modified the existing scales to measure the dependent, independent, and control variables. Career commitment (CC) measures individual feelings towards one’s job. We selected four items from Blau (1989). Work-life balance refers to the balance of managing work and non-work life effectively. We selected five items from Gröpel and Kuhl (2009). Career success is measured by subjective success and objective success. For subjective career success (SCS), we used the sixteen items developed by Shockley et al. (2016). These items measure the level of recognition, quality work satisfaction, growth, and development that individuals achieved during their careers. Objective career success is measured by using two proxies, salary level and promotion (Heslev 2005). The salary level reflects the increase in the respondent’s salary overtime in career. In contrast, the promotion level indicates the level of promotion that an individual received during their career.
We incorporated work experience, marital status, and gender as control variables in our theoretical model. Work experience represents the number of years an individual has been working in a job and reflects the level of commitment and motivation towards the job and its impact on an individual’s career success. We integrated a natural logarithm of the number of years doing a job in an organization to account for this effect. Marital status and gender are the two dummy variables. Marital status identifies whether a respondent is married or single. This control variable measures the impact of an individual’s marital status on career success. Similarly, gender reflects the number of male and female employees working in the service sector (Ng et al. 2005).

3.2. Validation of Construct

We checked the convergent validity of multi-item constructs (CC, SCS, WLB). First, we performed an exploratory factor analysis (EFA). Each measurement item loaded on their respective constructs (between 0.50–0.90), providing convergent validity for the theoretical model. Cronbach’s alpha for all the constructs ranged from 0.681 to 0.819, indicating suitable reliability for measurement scales (Nunnally and Bernstein 1994). We applied AMOS 22 to verify the internal consistency and reliability of the measurement model. Our confirmatory factor analysis (CFA) test showed satisfactory fit indices for our data. The X2/df (Chi square/degree of freedom ratio) = 1.91, and other fit indices (CFI = 0.923, IFI = 0.924, TLI = 0.910, RMSEA (Root mean square error of approximation) = 0.050, and PCLOSE (Probability of close fit and should be insignificant > 0.05) = 0.454) values provided an acceptable fit (Hu and Bentler 1999) for our model. Table 2 provides the information regarding respective constructs, their items, and their Cronbach’s alpha value. Table 3 shows the correlation matrix of the model.

4. Empirical Analysis and Results

4.1. Structural Equation Modeling

By using AMOS 22, we test the proposed hypotheses. The results revealed a satisfactory structural equation model fit, as indicated by the ratio (CMIN/DF = 3.1) and the fit indices (CFI = 0.912, IFI = 0.924, TLI = 0.559, and RMSEA = 0.055). The results provide support for the hypotheses H1, H2a, and H2b. Career commitment is positively related to subjective career success (β = 0.388, p < 0.001), number of promotions (β = 0.157, p < 0.05), and salary level (β = 0.154, p < 0.01).

4.2. Moderation Analysis

To test for interaction effects, we centered and introduced interaction terms into our model. The work-life balance had a significant but negative moderating effect on the relationship between career commitment and subjective career success (b = −0124, p < 0.001), supporting H3, while it had no significant moderating effect on the relationship between career commitment and objective career success, lending no support to both H4a and H4b.
Figure 2 and Figure 3 show significant interaction. These graphs show that in the presence of low WLB, career commitment among employees leads toward low subjective career success. In contrast, high career commitment among employees will result in high subjective career success. While in the presence of high work-life balance, low career commitment will result in more career success, and high commitment toward career will result in higher subjective career success. The graph also shows that the lines get intercepts after some time, and the results become reverse. In this case, high work-life balance and high commitment towards a career will result in low subjective career success. If employees want to enjoy career success, then their work-life balance gets affected (see Table 4).

5. Discussion and Conclusions

This research’s main objective was to find out the relation of career commitment on career success, including both dimensions, subjective career success and objective career success, in the service sector of Pakistan. With that, we also examine the moderating role of work-life balance in the hypothesized direct relationships (see Table 5).
Our results support that career commitment positively affects subjective and objective career successes (i.e., promotion and salary). The findings are consistent with previous studies (Ballout 2009; Colakoglu 2011; Sultana et al. 2016) and augment the logic that career commitment brings positive extrinsic and intrinsic outcomes for employees.
The role of work-life balance as a moderator positively moderates the relationship between career commitment and subjective career success (subjective as well as objective career success). The hypothesis was accepted in case of subjective career success. Therefore, work-life balance moderates the relationship between career commitment and subjective career success in such a way that at a low level of work-life balance, there is low impact of career commitment on career success. However, as work-life balance increases, the impact from career commitment to career success increases to a point afterward; a very high level of career commitment would not increase the career success any further instead, try to dampen it (see Figure 2).
Our results are consistent with previous studies (Amin et al. 2016; Lyness and Judiesch 2008; Qu and Zhao 2012; Yadav and Dabhade 2014). The hypothesis (H3) is supported under the role theory approach (Adams et al. 1996), which underlines that at some levels, a high balance between work and life will decrease the success level among employees. In the case of objective career success (H4a and H4b), we found out an insignificant relationship of work-life balance between career commitment and objective career success. The primary reason for the negligible moderation effect of WLB on objective career success (salary and promotion) could be due to Pakistan’s job compensation system. Pakistan’s compensation system is based on seniority rather than performance. In Pakistan, the objective measure for career success (salary and promotion) is not much affected by employee performance instead of the employee’s experience and years of work.
This study provides implications for individuals as well as organizations. The findings suggest that individual behavior toward career commitment yields results in the form of subjective career success such as satisfaction, recognition, etc., and for objective career success such as promotions and salary raise. Such career commitment will also beneficial for employees with high work-life balance. Regarding objective career success, career commitment will not have a better pay off effect in the presence of work-life balance. Our finding suggests that when organizations motivate their employees to become more committed in their respective positions, it positively affects the organization’s performance and the improvement of an individual’s subjective and objective career success. Hence, organizations are responsible for creating environments where employees feel motivated and committed toward their job, which generates a win–win outcome for all (Vandenberghe and Basak 2013). If an organization wants its employees to achieve subjective and objective career success, they should develop a deep understanding of factors that affect career commitment.

Limitations, Implications, and Future Recommendation

Like other research studies, this study has limitations. Our analysis focuses on examining the role of a career commitment to achieving a high career success level. Individual measure their career success with other factors such as organization performance, organization status (national vs. international), etc. Our study followed a quantitative research method and used a self-reporting survey questionnaire for collecting data from the service sector employees. Self-reported questionnaire structure results are typically biased. Hence, future research should overcome this limitation by using a multi-actor data approach. Future studies should collect data more comprehensively. Selecting a single sector from individual country limits in interpreting and generalizing the results. Career commitment and career success are crucial for practitioners. Future researchers should apply individual factors such as intelligence, personality, etc., as moderators to better understand the mediating effect in their relationship.

6. Conclusions

This study’s goal has been to contribute to career success and work-life balance from the employees’ perspective. We describe and measure the relationship between career commitment and career success practices. Our findings indicate that career commitment positively affects career success objectives, and work-life moderates some of the career success areas. In terms of contributions, our study examines objective and subjective career success concurrently as an outcome of career commitment in an emerging Asian economy. This study’s findings also provide a better understanding of management practices regarding employees’ career objectives and their commitment to the employer.

Author Contributions

All the authors contributed equally in this research article regarding conceptualization, methodology, formal analysis, and writing the original draft of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Admsci 10 00082 g001 550
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. The moderation effect I.
Figure 2. The moderation effect I.
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Figure 3. The moderation effect II.
Figure 3. The moderation effect II.
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Table
Table 1. Respondents profiles.
Table 1. Respondents profiles.
CharacteristicsPercentage
Industry
Telecommunication24.4
Banks62
IT13.6
Total100
Gender
Male74.4
Female25.6
Total100
Work Experience
0 to 3 years33.6
4 to 9 years45.8
9 to 12 years20.6
Total 100
Marital Status
Single46.8
Married49.5
Others3.7
Total100
Table
Table 2. Description of items and validity measures.
Table 2. Description of items and validity measures.
ConstructsResponded on a 5-Point Likert Scale Where 1 Indicated Strongly Disagrees and 5 Indicated Strongly Agree.
Subjective Career Success (SCS)
12 items, α = 0.819		SCS1: “My supervisors have told me I do a good job.”
SCS2: “Organizations I worked for have recognized me as a good performer.”
SCS3: “I have been recognized for my contributions.”
SCS4: “I am proud of the quality of the work I have produced.”
SCS5: “I have met the highest standards of quality in my work.”
SCS7: “Decisions that I have made have impacted my organization.”
SCS8: “The organizations I have worked for have considered my opinion regarding important issues.”
SCS9: “Others have taken my advice into account when making important decisions.”
SCS10: “I have chosen my own career path.”
SCS13: “I have continuously improved by developing my skill set.”
SCS14: “My career is personally satisfying.”
SCS16: “I have found my career quite interesting.”
Work-Life Balance (WLB)
05 items, α = 0.681		WLB1: “Because of my work, I have no free time”
WLB2: “Because of my work, I neglect my family”
WLB3: “Because of my work, I neglect my friends”
WLB4: “I have enough time for my friends.”
WLB5: “I have enough time for my family (partner, parents, children),”
Career Commitment (CC)
04 items, α = 0.788		CC2: “I want a career in this job.”
CC4: “If I had all the money I needed, I would still want to be in this job.”
CC5: “I do not want to leave my job as I enjoy doing it.”
CC6: “This is my ideal job for my life work.”
Objective Career success ITEMS NAMEWe measure objective career success through the absolute value (number of promotions and a salary increase). Respondents reported the number of times they received a promotion, and the difference between the starting salary and current salary showed the salary increase.
Work Experience 1 itemA natural logarithm of the number of years an individual is doing a job in an organization.
Marital Status 1 itemThe number of employees who are where unmarried coded as 1, married coded as 2, and others coded as 3.
Gender 1 itemA dummy variable, where males were coded as 1, and females coded as 2.
Table
Table 3. Correlation matrix.
Table 3. Correlation matrix.
SCSOCS1OCS2WLBCCLogWMG
SCS1
OCS10.0191
OCS20.144 **0.147 **1
WLB0.209 **−0.015−0.131 *1
CC0.421 **0.0900.135 *0.142 **1
LogW0.0530.513 **0.193 **−0.112 *0.0861
M−0.0090.199 **0.0920.0170.410.405 **1
G−0.149 **−0.074−0.135 *−0.035−0.069−0.145 **−0.0511
Mean2.472.1162.111.432.632.341.571.25
SD0.3321.5372.840.3020.6121.300.5830.436
N360360360360360360360360
Note: OCS1 = objective career success 1, OCS2 = Objective career success 2, M = Martial Status, G = Gender, ** p < 0.01, * p < 0.05.
Table
Table 4. Moderation analysis result.
Table 4. Moderation analysis result.
VariablesDependent Variables
Subjective Career SuccessObjective Career Success (Promotions)Objective Career Success (Salary)
Control Variables
Gender−0.186(.065) ***−0.259(.185)−22.54(8.7)
Marital Status−0.009(0.49)0.524(0.136) ***11.466(6.57) **
Independent Variables
Career Commitment0.388 (0.028) ***0.157(0.095) **0.154 *
Moderator
Work-Life Balance0.142(0.031) ***−0.029(0.99)−0.155 ***
CC*WLB−0.124(0.020) ***0.003(0.65) −0.030(0.39)
*** p < 0.001, ** p < 0.05, * p < 0.01.
Table
Table 5. Hypothesis result.
Table 5. Hypothesis result.
HypothesisResults
H1: Career commitment has a positive effect impact on subjective career success.Supported
H2a: Career commitment has a positive effect on objective career success (promotions).Supported
H2b: Career commitment has a positive effect on objective career success (salary)Supported
H3: Work-life balance positively moderates the relationship between career commitment and subjective career success.Supported
H4a: Work-life balance positively moderates the relationship between career commitment and objective career success (promotions).No support
H4b: Work-life balance positively moderates the relationship between career commitment and objective career success (salary).No support

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Najam, U.; Burki, U.; Khalid, W. Does Work-Life Balance Moderate the Relationship between Career Commitment and Career Success? Evidence from an Emerging Asian Economy. Adm. Sci. 2020, 10, 82. https://doi.org/10.3390/admsci10040082

AMA Style

Najam U, Burki U, Khalid W. Does Work-Life Balance Moderate the Relationship between Career Commitment and Career Success? Evidence from an Emerging Asian Economy. Administrative Sciences. 2020; 10(4):82. https://doi.org/10.3390/admsci10040082

Chicago/Turabian Style

Najam, Usama, Umar Burki, and Wajiha Khalid. 2020. "Does Work-Life Balance Moderate the Relationship between Career Commitment and Career Success? Evidence from an Emerging Asian Economy" Administrative Sciences 10, no. 4: 82. https://doi.org/10.3390/admsci10040082

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