Beyond the Borderlines: Redefining Work-Life Balance for Women in Bangladesh’s Evolving Private Sector

This article examines work-life balance (WLB) for women in the private sector in Bangladesh who are facing traditional barriers and structural constraints. It identifies how family support, self-expectation, and organizational culture collectively influence WLB. A Structural Equation Modeling (SEM) was done in this study using Smart-PLS 4.0 and the study reveals that all three predictors significantly affect WLB, with family support being the most important predictive factor. The findings suggest that balance can be achieved through social and institutional cooperation, rather than only individual effort. The study has implications for the advancement of gender-sensitive policies and sustainable work-life integration in developing settings.

Introduction

Work-life balance (WLB) is a global issue, with an increased number of women involved in the workforce. UN UN Women (2024) estimated that the participation of women in the labor force rose from 36% in 2017 to 42.8% in the year 2022. Cultural norms, company-wide procedures, and social pressure influence how we juggle the two balls. In developed economies, flexible work arrangements and institutional support enable women to balance competing demands (Ranaet al., 2024). However, for women in countries such as Bangladesh, their challenges are increasing because of an inflexible job environment, less standard family support, and traditionally restrained familial responsibilities (Akanjiet al., 2020).

In the Bangladeshi corporate sector, especially in banking, mobile telecommunications, and corporate businesses, women increasingly face difficulties balancing WLB. Two-thirds of women in the formal economy are employed part-time, while 82.4% of men have full-time jobs (Khatun, 2014), demonstrating continued gender differences in working conditions. Heavy loads and long hours with flexibility can lead to stress and poor health. Family or work support can help reduce these pressures, but personal expectations in life mediate them (Sharminet al., 2024). However, there is a dearth of empirical research on the simultaneous influence of internal and external variables on women’s WLB in Bangladesh, which may undermine several relationships.

The objective of this study is to explore the joint impacts of family support, personal life expectations, and workplace culture and support on WLB among women in the private sector of Bangladesh. The research findings contribute to the theoretical knowledge base, influence socially responsible organizational and national-level policy decisions, and offer guidance on practical actions that organizations may implement to improve employee well-being, satisfaction, and retention.

Literature Review

Theoretical Underpinning

This research is grounded in the Work/Family Border Theory (Clark, 2000), which argues that work and family are distinct contexts delimited by physical, temporal, and psychological boundaries. People are border-crossers who seek to articulate these realms through their borders’ porosity and negotiability. Family and work support are facilitators that make border crossing more manageable, while personal attitude influences the way in which individuals negotiate and balance family and work-life roles.

Fundamental Catalysts Influencing Women’s Work-Life Balance and Their Subsequent Impacts

Family leverage, personal life expectancies, and organizational culture together determine women's capacity to achieve and maintain work–life balance (Bobbioet al., 2022). Emotional support, practical assistance, and advice with rolekeeping are offered by the family in caring for individuals with role strain. A lack of family understanding increases role conflict and psychological stress, negatively impacting work performance and mental health (Susantoet al., 2022; Rahimiet al., 2023; Yaminet al., 2025). Likewise, women's individual life expectations- career aspirations, lifestyle objectives, and self-fulfillment criteria are shaping more than ever before the way they use their time and energy. Attainable aspirations matched to resources provide a balance of satisfaction across domains, while unrealistic or overambitious aspirations may lead to frustrated expectations, stress, and role overload (Rangarajan, 2018; Hasnatet al., 2025). Work culture mediates balance to at least some extent because supportive work cultures (with flexible hours, familyfriendly policies, and management that is understanding) reduce burnout and enhance organizational commitment (Sharmin & Luna, 2015). In contrast, inflexible work arrangements heighten work–family conflicts and decrease general well-being. Thus, a supportive work environment facilitates and alleviates the interface of professional and personal roles for women (Bradleyet al., 2023; Nishuet al., 2025).

Table I provides categories of key variables that have the potential to impact women’s work-life balance. Each variable is described with accompanying literature citations and a corresponding survey.

Table I. Definition of Operational Variable and Measurement

Variables	Concept	Code	Items	References
Family support	Emotional, practical, and instrumental assistance from family members that helps women manage household responsibilities and reduce work–life conflict. (Setyoriniet al., 2023)	FS1	I feel supported by my family when I experience stress related to work	Setyorini et al . (2023)
		FS2	My family provides practical help with household tasks or allows me to focus on work
		FS3	My family encourages me to pursue my career goals and celebrate my professional achievements
		FS4	Family members adjust their routines to accommodate my work schedule when necessary
		FS5	I receive helpful guidance and advice from my family to balance work and personal life
Personal life expectations	Individual goals, priorities, and standards that guide women in managing responsibilities, setting boundaries, and achieving satisfaction across work and personal domains. (Shahet al., 2025)	PLE1	I am satisfied with the amount of time I can dedicate to my personal life outside of work	Shah et al . (2025)
		PLE2	I expect to spend quality time with my family without work-related interruptions
		PLE3	I anticipate having sufficient time for leisure activities and personal interests
		PLE4	I prioritize maintaining my physical and mental health through personal time
		PLE5	I expect to engage in personal development activities, such as education or hobbies, during my personal time
Workplace support and WLB policies	Organizational norms, values, flexibility, and resources that create a supportive environment, enabling women to balance professional and personal roles effectively. (Lee & Shin, 2023)	WCS1	I believe my organization values my contributions and cares about my well-being	Lee and Shin (2023)
		WCS2	My supervisor provides the guidance and resources I need to perform my job effectively.
		WCS3	The work-life balance policies offered by my organization are accessible and meet my needs
		WCS4	I feel motivated and committed to my work because of the support I receive from my organization and supervisor
		WCS5	The culture within my organization promotes a healthy balance between work and personal life
Women’s work-life balance	Women’s work–life balance involves juggling career and personal life successfully, fostering well-being, job satisfaction, and stronger engagement with their organization. (Hasanet al., 2021)	WWLB1	My daily schedule allows me to balance professional tasks and personal commitments effectively	Hasan et al . (2021)
		WWLB2	I am able to maintain my well-being while meeting the demands of my job
		WWLB3	I feel satisfied with the current balance between my work and personal life
		WWLB4	I can manage unexpected challenges at work without negatively affecting my personal life
		WWLB5	I have effective strategies to handle stress from both work and personal life

Conceptual Framework

Fig. 1 presents the conceptual framework of the study and illustrates the hypothesized relationships between dependent and independent variables.

Fig. 1. Conceptual framework of the antecedents influencing women’s work–life balance in the private sector. Source: Authors’ own work.

Research Methodology

Ethics Statement

This study was approved by the Research Committee of the institution because it required human subjects. Informed consent was obtained from all participants during writing. Participants were informed that every question was optional and that no personally identifiable information would be collected, thus ensuring total anonymity.

Sample and Data Collection

The detailed sample characteristics are presented in Table II. The sampling frame included female employees working in private-sector firms across banking, telecommunication, and corporate services in Dhaka, Chattogram, and Sylhet. Firms were selected purposively based on their representation of major employment sectors for women in Bangladesh. In addition, the sample is mostly made up of early-career respondents aged 30–35 years (27%), dominated by married individuals in the majority (55%), and a substantial amount of work experience between two and four years (33%), representing both finitely-balanced psychologically healthy groups that are mature professionally.

Table II. Sample Characteristics

Characteristics	Frequency	Percent
Age
Below 30 years	89	25%
30–35 years	96	27%
36–40 years	87	25%
Above 40 years	82	23%
Marital Status
Single	159	45%
Married	195	55%
Years of working Experience
Less than 2 years	78	22%
2–4 years	117	33%
4–6 years	84	24%
Above 6 years	75	21%

Data Analysis

Smart-PLS (version 4.0) was used to conduct the SEM test and analysis. This method is applicable and suitable for the current study because it permits the analysis of several dependent relationships simultaneously and incorporates latent constructs (Byrne, 2016). PLS-SEM is more powerful than CB-SEM given its strong statistical power resulting from more efficient parameter estimates (Hairet al., 2017). This is a more robust analysis that can be used with data that are not normally distributed (Hairet al., 2017). As suggested by Kline (2023), a sample size of 100-150 is needed to obtain meaningful results using SEM; therefore, the sample size has sufficient power for analysis.

Result Analysis

Common Method Bias (CMB) Test

To assess potential common method bias, the full collinearity approach proposed by Kock (2015) was employed in SmartPLS. In Table III, the variance inflation factor (VIF) values for all indicators ranged between 3.698 and 6.369. Although several values exceeded the ideal threshold of 3.3, all remained below the conservative limit of 10.0 (Hairet al., 2021), suggesting that multicollinearity and CMB are not severe enough to threaten the validity of the model. Nevertheless, this indicates a moderate level of shared variance that should be interpreted cautiously.

Table III. Common Method Bias (CMB)

	VIF
FS1	4.711
FS2	4.472
FS3	3.698
FS4	5.192
FS5	3.824
PLE1	4.795
PLE2	6.369
PLE3	5.825
PLE4	5.890
PLE5	4.782
WCS1	3.899
WCS2	4.320
WCS3	5.351
WCS4	4.568
WCS5	4.789
WWLB1	3.961
WWLB2	5.279
WWLB3	3.759
WWLB4	4.060
WWLB5	4.434

Results of the Measurement Model

Fig. 2 displays the measurement model used in the analysis. To assess the reliability and validity of the cognitive construct, this study conducted a full-scale analysis on the measurement model (Table IV), where strong indicator reliabilities and internal consistency were found with Cronbach’s alpha coefficients above the recommended threshold level of 0.80 (Hairet al., 2021), signifying construct robustness. Methodological stringency was observed according to Hairet al. (2021), Shmueliet al. (2019), and Sarstedtet al. (2014). Composite reliability (CR) also supported internal consistency as per the recommended standards. Convergent validity was tested through the AVE, which represents how much of the variance a construct accounts for its measurement error (Saunderset al., 2019; Sarstedtet al., 2014); and should have an ideal value greater than or equal to 0.50 (Hairet al., 2021; Shmueliet al., 2019; Rahmanet al., 2023). All constructs surpassed these values, with AVE values ranging above 0.843, given that the construct representativeness and measurement model validity were fully validated by established methodological standards.

Fig. 2. Measurement model.

Table IV. Convergent Validity

Constructs	Items	Loadings	Cronbach's alpha	Composite reliability	Average variance extracted (AVE)
FS	FS1	0.927	0.954	0.965	0.845
	FS2	0.917
	FS3	0.909
	FS4	0.936
	FS5	0.907
PLE	PLE1	0.929	0.965	0.973	0.876
	PLE2	0.947
	PLE3	0.944
	PLE4	0.939
	PLE5	0.922
WCS	WCS1	0.911	0.957	0.967	0.853
	WCS2	0.919
	WCS3	0.938
	WCS4	0.927
	WCS5	0.921
WWLB	WLB1	0.911	0.953	0.964	0.843
	WLB2	0.937
	WLB3	0.907
	WLB4	0.916
	WLB5	0.921

As noted by Shmueliet al. (2019), discriminant validity is an important issue in PLS-SEM path analysis because it ensures that the latent variables are statistically different, which in turn represents innate theoretical structures. The findings reported in Table V reveal that discriminant validity is obtained because strict demands regarding the Heterotrait-Monotrait Ratio (HTMT) are met. According to Shmueliet al. (2019) and Hairet al. (2021), the HTMT measure is a useful index for analyzing the transferability of two latents. To determine discriminant validity, the HTMT values must be below 1. The results of this research meet these needs and indicate that they are consistent with the theoretical criterion-related validity requirements, offering strong evidence for discriminant validity.

Table V. Discriminant Validity (HTMT Ratio)

	FS	PLE	WCS	WWLB
FS
PLE	0.044
WCS	0.056	0.169
WWLB	0.553	0.443	0.375

Hypothesis Testing

Direct hypothesis testing (Table VI) showed that Family Support (β = 0.493), Personal Life Expectation (β = 0.476), and Workplace Culture and Support (β = 0.412) all significantly and positively influence women’s work-life balance (p = 0.000), with family support having the strongest effect, highlighting its pivotal role alongside personal expectations and workplace culture.

Table VI. Direct Hypothesis Testing

No.		Original sample (O)	Sample mean (M)	Standard deviation (STDEV)	T statistics (|O/STDEV|)	P values	Remarks
H1	FS -> WWLB	0.493	0.493	0.034	14.461	0.000	Supported
H2	PLE -> WWLB	0.476	0.476	0.035	13.585	0.000	Supported
H3	WCS -> WWLB	0.412	0.413	0.035	11.731	0.000	Supported

Discussion

Women’s work-life balance was influenced by a combination of family support, personal expectations, and workplace culture. Potent family support leads to emotional security and a sense of obligation, which helps women navigate their work lives with less stress (Akanjiet al., 2020). Reasonable personal expectations allow them to relate their dreams and goals to the available time and energy, enhancing fulfillment instead of frustration. Women are also able to strike a balance between their roles because of flexible and friendly work (Bradleyet al., 2023). In collectivist cultures like Bangladesh, family plays a central role in individual well-being and decision-making (Hofstede, 2001). Therefore, strong family networks offer emotional and practical resources that buffer work stress and promote balance more effectively than individual or organizational factors. This cultural embeddedness explains why family support emerged as the most dominant predictor in the model. Theoretically, the results support Clark’s (2000) work/family border theory in that balance is accomplished through both relational and institutional collaboration rather than individual effort alone. From a practical standpoint, this study highlights that it is important for organizations to implement inclusive family-friendly policies and for women to have adaptive personal expectations. In summary, this understanding calls for a comprehensive approach to advancing gender equality and healthy female workers in Bangladesh’s emerging private sector.

Conclusion and Recommendation

In the private sector of Bangladesh, this study suggests that women’s work–life balance is a function of family support, personal expectations, and workplace culture. Harmony comes from social and institutional teamwork and not the efforts of just one person. Women’s health and retention in the workplace opportunities exist to invest in supportive family networks and more flexible organizational policies. The cross-sectional nature of the study and self-reported data restrict causal inference, and the population scope is limited to private-sector employees. Future research could also use longitudinal or mixed methods to investigate evolving trends in work–life integration. The involvement of public sector workers and people with a range of gender identities would also enhance our understanding of how social context and institutional practices influence sustainable work–life balance.

Conflict of Interest

The authors affirm they have no conflict of interest.