In the early 20th century, the relationship between work and personal life was largely unquestioned. However, this view shifted in the 1970s due to increasing female workforce participation in Western countries (
Rajalakshmi, 2012
). Recent research highlights that work-life balance (WLB) has become a critical issue in emerging economies, with women’s employment in Iran rising to 22 percent (
Schwab et al., 2016
) and traditional family roles evolving as dual-earner households become more common (
Karimi, 2009
). (
Valcour, 2007
) notes that individuals now juggle various responsibilities such as parenting, spousal duties, and caregiving, making the integration of professional and personal lives essential. Job-related stress can lead to burnout and diminished well-being, prompting organisations to support employees in managing their work-life responsibilities.
WLB has become a significant concern for both employees and organisations, as imbalances can negatively affect work performance and personal life (
Garg & Dawra, 2017
). (
Clark, 2000
) defines WLB as achieving satisfaction and effectiveness at work and home with minimal role conflict, while
Kirchmeyer (2000)
emphasizes the distribution of resources like time and energy across life domains.
Greenhaus and Allen (2011)
highlight the importance of satisfaction in both work and personal responsibilities. Additionally, WLB depends on an individual’s capacity to manage diverse roles such as career, personal life, and community engagement (
Haar, 2013
;
Pasamar & Valle, 2015
). According to
Yuile et al. (2012)
, WLB occurs when both work and non-work obligations are effectively managed.
Understanding the interaction between work and family responsibilities is essential for managing human resources effectively. Researchers and practitioners have increasingly focused on WLB due to changing family dynamics and the rise in dual-career couples and single-parent households (
Kaya & Karatepe, 2020
;
Nicklin et al., 2019
). Social shifts, such as increased female workforce participation and elder care responsibilities, have heightened the need for WLB practices (
Butts et al., 2013
). The COVID-19 pandemic further emphasized the importance of WLB, with a 74 percent drop in life satisfaction (
Yang et al., 2020
). Organisations must implement WLB measures to help employees manage work and personal roles (
Beauregard & Henry, 2009
).
Common WLB practices include flexible work hours, remote working, job sharing, part-time roles, compressed schedules, and emergency paid leave (
Butts & Krysan, 2012
). These practices allow employees to balance various responsibilities more effectively (
Kailasapathy et al., 2014
). Prior studies have linked WLB with job satisfaction, career success, and organisational commitment (
Carlson et al., 2009
;
Saraih et al., 2019
).
Hakanen and Schaufeli (2012)
found a positive relationship between work engagement and life satisfaction, while
Aryee et al. (2005)
highlighted WLB’s connection to organisational commitment and job satisfaction. Effective WLB practices boost organisational efficiency and promote employee autonomy in balancing professional and personal duties (
Becker & Huselid, 2006
;
Felstead et al., 2000
).
Research also indicates a strong link between organisational identity and employee well-being (
Matthews et al., 2014
). Studies have examined how WLB affects job satisfaction, anxiety, and depression (
Brough et al., 2014
;
Haar et al., 2014
). Despite growing interest, gaps remain in understanding the broader effects of WLB (
Greenhaus & Allen, 2011
;
Hall et al., 2013
). This study aims to address these gaps by examining WLB’s influence on job satisfaction and WLB satisfaction, with organisational identity as a potential mediator.
The findings could help organisations understand how WLB practices enhance employee satisfaction. Focusing on the banking sector in a developing economy, this research aims to contribute to WLB literature in emerging markets. While WLB practices are well-studied in developed nations (
Munn & Chaudhuri, 2016
), there is a lack of research in countries like India and Bangladesh (
Munn & Lee, 2014
). This study specifically examines how WLB impacts job satisfaction, WLB satisfaction, and organisational identity in the context of Bangladeshi culture.
2. Literature Review2.1. The Social Exchange Theory
Social exchange theory (
Blau, 1964
) is based on the principle of reciprocity, which is, again, based on two assumptions: 1) people should keep the ones who have helped them in their mind and help them, and 2) people should not injure those who have helped them (
Gouldner, 1960
). This theory suggests that employees perceive positive actions for the benefit of employees as an indication that the organisation cares about them (
Blau, 1964
). Therefore, supportive formal or informal organisational practices can create a feeling of obligation among employees to reciprocate by exhibiting healthy behaviors, such as job satisfaction (
Cropanzano & Mitchell, 2005
). Based on this reasoning, we contend that WLB practices can improve employee job satisfaction and work-life balance satisfaction.
Social exchange theory relies on the principle of reciprocity (
Gouldner, 1960
), which posits that employees are morally obligated to contribute to their employer in exchange for the benefits they receive, such as work-family policies. It is imperative to investigate these reciprocal relationships between employers and employees, as employers may decide to reduce or eliminate benefits such as work-family policies due to a lack of reciprocity. Additionally, social exchange involves reciprocal exchanges where the exact return for employees’ contributions is not predetermined. This theory provides a framework for comprehending the relationship between WLB practices and employee outcomes (
Allen, 2001
;
Haar & Roche, 2010
;
Haar & Spell, 2004
).
2.2. Organisational Identity Theory
According to the Social Identity Approach (
Haslam, 2004
), when employees categorise themselves as members of a specific organisation, they tend to appropriate the organisation’s values and aims as their own and see themselves as interchangeable with other members of the organisation (
Ashforth & Mael, 1989
). Thus, assuming that employees feel a strong sense of belonging in their organisation, and if this membership is psychologically relevant (salient) in a given context, they should show favoritism towards their organisation, in terms of more satisfaction, collaboration, and extra-role behaviors (
Ashforth et al., 2013
).
Identification with one’s own organisation, indeed, increases the likelihood that employees will show more extra-role performance, commitment, and job satisfaction among other outcomes (
Lee et al., 2015
;
Ng & Allen, 2018
). The degree to which an employee identifies with a group, will, for instance, determine how well she/he will correctly interpret the received support from in-group members (
Hair Jr et al., 2014
). Also mentioned, (
Häusser et al., 2020
) hypothesised that group- and individual-level identifications could interact with each other, and this interaction could affect employees’ attitudes and behaviors.
The concept of work-life balance (WLB) plays a vital role in managing employees’ responsibilities across work, home, and other life domains. Work-life balance (WLB) refers to an individual’s perception that work and non-work activities are compatible and promote growth in accordance with an individual’s current life priorities (
Greenhaus & Allen, 2011
). It reflects the ability to effectively manage and fulfil responsibilities across both domains. Employers implement various WLB strategies, including flexible work hours, task sharing, part-time roles, compressed schedules, remote working, and emergency paid leave (
Butts & Krysan, 2012
;
Perrigino et al., 2018
). Though these practices vary by organisation, research indicates that they positively influence organisational commitment and employee attitudes while reducing turnover intentions. WLB also enhances job performance and helps employees better manage both organisational and family duties (
Haar & Roche, 2010
). Studies suggest that achieving WLB increases life satisfaction by allowing individuals to engage in meaningful personal and professional activities (
Brough et al., 2014
;
Carlson et al., 2009
).
According to
Syrek et al. (2022)
, WLB represents the absence of conflict between life roles. A poor balance can lead to work-life conflict, negatively impacting employee health and organisational productivity. Meta-analyses and reviews reveal that WLB practices foster positive job attitudes, enhance organisational commitment, and lower turnover rates (
Butts & Krysan, 2012
;
Kossek et al., 2011
). These practices boost employee performance and contribute to overall well-being, including life satisfaction and increased loyalty (
Dizaho & Othman, 2013
).
Work-life balance satisfaction (WLBS) refers to an individual’s subjective evaluation of how well their work and personal life demands are balanced and how satisfied they are with this balance (
Valcour, 2007
). It reflects perceived success in fulfilling both work and non-work roles without significant conflict or strain. Research highlights the organisational benefits of effective WLB interventions, such as reduced work-family conflict, stronger organisational citizenship behaviors, greater commitment, and improved job satisfaction (
Baral & Bhargava, 2010
;
Kelliher et al., 2019
). Employer support for WLB positively affects employee engagement and retention (
Baral & Bhargava, 2010
;
Kelliher et al., 2019
).
Baral and Bhargava (2010)
emphasise that WLB initiatives ensure employees’ well-being and support their non-work needs. WLB remains crucial across cultures, influencing individual wellness (
Kossek et al., 2014
;
Lyness & Judiesch, 2014
). Based on this, the following hypothesis is proposed:
H1: Work-life balance (WLB) practices will positively relate to Work-life Balance Satisfaction (WLBS).
3.2. Work-Life Balance (WLB) Practices and Job Satisfaction (JS)
Job satisfaction (JS) is defined as “a pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences” (
Locke, 1976
). It encompasses factors such as work conditions, pay, interpersonal relationships, and opportunities for advancement. Employee happiness and engagement rise when organisations implement successful WLB practices. Employees can only be delighted with their employment when they integrate their personal and professional lives (
Alias et al., 2018
). It is stated as ‘the employees’ views of their working environment, relationships among colleagues, salary, and promotion opportunities’ (
Belias et al., 2015
). Organisations that effectively embrace work-life balance programmes show a gain in employee satisfaction and loyalty, asserts
Arif and Farooqi (2014)
. Organisations increasingly comprehend the close relationship between employee happiness and business, which underscores the necessity of concentrating on developing legislation that supports work and personal concerns (
Arif & Farooqi, 2014
).
Workplace flexibility has a major impact on job satisfaction (
Kumari, 2012
;
Yanala et al., 2023
). Businesses that promote work-life balance are generating happy social citizens in addition to a pleased workforce. Work-life balance policies, such as job sharing, flexible scheduling, remote work, and task management flexibility, are meant to give employees autonomy over their working hours and a sense of fulfillment from carrying out and finishing their tasks without regard to location or time constraints. In this way, having a contented and happy workforce result in higher contributions within organisations (
Arif & Farooqi, 2014
). For firms, acquiring and sustaining valuable human capital is a challenge (
Viljoen, 2022
).
Dhamija et al. (2019)
believe that when job aspects and needs are satisfied, employee job satisfaction arises. According to
Alias et al. (2018)
, workers who are employed by companies that strongly support work-life balance are happier in their positions than those who work for companies that do not distinguish between work and personal life.
Job satisfaction provides workers with extra opportunities to meet family obligations, which leads to a high degree of family-related satisfaction (
Voydanoff, 2005
). In addition, WLB practices minimise psychological strain and allow people to please their family and their jobs. WLB techniques favor job satisfaction due to a more positive outlook and stress reduction (
Bloom et al., 2009
). Employees who experience WLB practices are more satisfied with their jobs.
Bowling et al. (2010)
revealed in a meta-analysis that work satisfaction has a favorable connection with family functioning, happiness, positive affect, and the lack of negative affect. They suggested that global JS had a greater link with life satisfaction. Although work-life balance satisfaction (WLBS) and job satisfaction (JS) are positively related, they represent distinct evaluative domains. WLBS refers to an individual’s subjective assessment of how well they are able to manage the demands of work and personal life, and their satisfaction with this balance (
Valcour, 2007
). In contrast, JS concerns an employee’s emotional evaluation of various aspects of their job, including tasks, work environment, and career prospects (
Locke, 1976
). While WLBS can influence JS, particularly through reduced work-life conflict, the two constructs are conceptually separate: WLBS spans both personal and work domains, whereas JS is specific to the workplace. Acknowledging this distinction ensures clarity in model specification and construct validity.
Prior research has studied the links between WLB and employee’ satisfaction (
Brough et al., 2014
;
Haar et al., 2014
), demonstrating that employees who experience balance are more content with their employment and lifestyles. Building on this research, we argue that employees who experience work-life balance (WLB) are likely to report higher satisfaction. This argument is based on the concept that attaining balance reduces tensions between work and personal life, nurturing a greater sense of harmony. Additionally, individuals engaged in meaningful and diverse activities may experience greater overall job and life satisfaction. Previous research indicated that WLB is positively connected to career satisfaction (
Saraih et al., 2019
) and job satisfaction (
Carlson et al., 2009
;
Haar, 2013
). Balanced individuals might sense lower stress and high satisfaction with their jobs (
Warner & Hausdorf, 2009
). Thus, it is hypothesised that work-life balance and job satisfaction are positively and strongly associated.
H2: Work-life balance (WLB) practices will positively relate to Job Satisfaction (JS).
3.3. The Mediating Role of Organisational Identifications (OI)
Organisational Identification (OI) is defined as “the perception of oneness with or belongingness to an organisation, where individuals define themselves in terms of their membership in the organisation” (
Mael & Ashforth, 1992
). It reflects a psychological attachment that influences attitudes and behaviors within the workplace. According to the Social Identity Theory (
Haslam & Ellemers, 2005
), when employees classify themselves as members of a certain organisation, they tend to take the organisation’s values and purposes as their own and perceive themselves as interchangeable with other members of the organisation. Since organisational identification shows the relationship between people and their organisation, it is ‘potentially capable of explaining and predicting many important attitudes and actions in the workplace’ (
Edwards, 2005
). According to
Lee et al. (2015)
and
Ng and Allen (2018)
, employees who identify with their organisation are more likely to exhibit extra-role performance, dedication, and job satisfaction, among other outcomes. Employees with work passion dedicate extensive time to work-related tasks and activities; they remain overtime, actively participate in organisational life, and regard work as a vocation (
Vallerand, 2003
). Because employees are often confined inside the setting and context of the organisation, organisational life becomes a part of an individual’s life, leading to a higher feeling of identification with the organisation (
Mageau et al., 2009
).
Allen (2001)
argued that firms that assist families may boost WLB as well as the commitment to the company since employees are more drawn to jobs that include flextime and work-life advantages. Additionally, a strong organisational identification makes coworkers more connected, which increases the possibility that employees will identify with the organisation and be more likely to work together (
Avanzi et al., 2015
;
Junker et al., 2019
;
van Dick & Haslam, 2012
). Employees with greater degrees of OI internalise the aims and values of the organisation and are thus more motivated to direct efforts toward the organisational objectives (
Efraty & Wolfe, 1988
). These individuals will display a cooperative manner of functioning and exhibit a significant lot of effort (
Carmeli et al., 2007
).
Identification occurs when employees perceive the organization’s identity as appealing. The larger an organization’s image is perceived by its members, the greater their level of identification. For this process to take place, it is crucial to cultivate a shared objective, active engagement, and a common narrative between the organization and the individual. When individuals identify themselves with the organisation’s organisations, the degree of work satisfaction improves, motivation increases, and the turnover rate lowers (
Zhou et al., 2017
). It is usually claimed in the research that organisational identification is directly related to favorable work performance (
He & Brown, 2013
). Suppose the management of the organisation assures that the employees identify with the organisation and connect to the organisation with a sense of loyalty and belonging. In that circumstance, the employees are happier with the tasks they perform (
Akova & Hasdemir, 2019
).
There is a vast body of evidence on the advantages of group memberships, and identifying with the organisation has been consistently related to better workplace outcomes, predicting positive organisational citizen behavior (
Christ et al., 2003
). An increasing body of knowledge, social identification, and group engagement promote overall well-being and work satisfaction (
Haslam et al., 2009
). For instance,
van Dick and Haslam (2012)
present empirical and meta-analytical evidence that relates strong organisational identification to improved work satisfaction and reduced stress levels (
Van Dick et al., 2008
). This shows that organisational identification equips individuals with more resources to deal with the issues they experience jointly, resulting in more favorable working outcomes.
It can be seen from the literature that WLB practices influence individual attitudes and behavior not only directly but also indirectly via some motivational and socio-psychological processes (
Kehoe & Wright, 2013
). According to social identity theory, people are eager to affiliate themselves with renowned social groups to increase their self-esteem (
Abrams & Hogg, 1988
). Thus, increased organisational identification is likely to result in actions that benefit the organisation and its employees (
Brown et al., 2006
). Although existing literature explores the relationship between organizational identity and work satisfaction, no study has examined the mediating role of organizational identification in the link between work-life balance (WLB) and job satisfaction (JS), as well as WLB and work-life balance satisfaction (WLBS). This research aims to address this gap. Grounded in social exchange theory, we propose that organizational identification (OI) serves as a key mechanism in understanding the impact of WLB practices on both WLBS and JS. Based on this, we formulate the following hypotheses.
H3: Organisational identification mediates the relationship between work-life balance practices and Work-life Balance Satisfaction (WLBS).
H4: Organisational identification mediates the relationship between work-life balance practices and job satisfaction (JS).
The research model is shown in
Figure 1
.
Figure 1. Conceptual model.
4. Methodology4.1. Participants and Procedure
The banking industry in Bangladesh employs approximately 195,141 individuals, with 126,991 working in over fifty private commercial banks (
Bangladesh Bank, 2020-21
;
Roy et al., 2024
). This study focused on full-time employees from various private commercial banks across multiple major cities in Bangladesh, including Dhaka, Khulna, Chittagong, Sylhet, and Rajshahi. A convenience sampling technique was used to facilitate participant access due to time and logistical constraints. Although non-probability sampling may limit generalizability, efforts were made to reduce sampling bias by approaching banks of different sizes and geographic regions. Formal letters were sent to a randomly selected set of private banks in these cities, and upon receiving managerial approval, survey questionnaires were distributed during working hours to employees from diverse departments and hierarchical levels. A cover letter accompanied each questionnaire, clearly outlining the purpose of the study and ensuring confidentiality and anonymity of responses. A total of 850 questionnaires were distributed, from which 566 were returned, yielding a 66.6% response rate. After data screening, 528 valid responses were retained for final analysis.
To support the data collection process, five experienced research assistants were engaged. Their responsibilities included identifying accessible participants, administering the questionnaires, and retrieving completed responses. The final sample was diverse in terms of age, gender, job roles, and geographic location, enhancing the representativeness of the findings within the private banking sector in Bangladesh.
Data was collected between June and November 2023. This period followed the height of the COVID-19 pandemic, during which most organisations, including banks in Bangladesh, had resumed full on-site operations. Although the immediate disruptions caused by the pandemic had largely subsided, residual shifts in employee expectations regarding workplace flexibility and work-life balance may have influenced participant perceptions. These contextual factors should be considered when interpreting the findings, particularly those related to organisational support and employee well-being.
Although the sample included employees from multiple private commercial banks, preliminary inquiries and discussions with HR managers during the approval process suggested that core human resource policies and work-life balance programs were broadly similar across institutions. Most banks adhered to common regulatory standards set by the Bangladesh Bank and followed comparable frameworks for leave entitlements, working hours, and employee welfare initiatives. While minor procedural differences may exist, substantial variation in WLB practices across banks is unlikely to have significantly influenced the results.
4.2. Measures
A five-point Likert scale was used to measure the questionnaire, with response options ranging from 1 (strongly disagree) to 5 (strongly agree).
WLB practices (WLBP)
To measure WLB practices, this study used an eight-item scale (
Judge et al., 1994
;
Syrek et al., 2013
). A sample item, “I am satisfied with my balance between work and private life.” Cronbach’s alpha coefficient for this scale was 0.908, indicating high internal consistency.
Organisational identification (OI)
OI was assessed using a six-item scale developed by
Saks and Ashforth (1997)
. A sample statement is, “When someone criticises the enterprise, it feels like a personal insult”. The Cronbach’s alpha coefficient for this scale was 0.922.
Job Satisfaction (JS)
Job satisfaction (dependent variable) was measured using five items measured by
Churchill Jr et al. (1974)
. A sample statement is “I feel that my job is satisfying”. The Cronbach’s alpha coefficient for this scale was 0.923.
Work-life Balance satisfaction (WLBS)
To assess work-life balance satisfaction (dependent variable), a scale by
Syrek et al. (2013)
, which consists of the five items reflecting employees’ satisfaction with their achieved balance between work and private life. A sample item is: “I am satisfied with my balance between work and private life.” Cronbach’s alpha coefficient for this scale was 0.934, reflecting excellent reliability.
Control variable
Following the empirical investigation (
Roy et al., 2023
;
Roy et al., 2024
) employees’ education, age, gender, marital status and occupational role were considered as control variables.
4.3. Data Analysis
After the questionnaires were collected, the responses were coded and analyzed using the Statistical Package for Social Sciences (SPSS) version 27 and IBM SPSS AMOS version 24. The hypotheses were then tested using covariance-based structural equation modeling (CB-SEM) as the statistical tool. The use of this statistical tool owes to its popularity and preference over tools such as regression (
Bollen, 1989
;
Dartey-Baah & Addo, 2019
); because of its ability to test hypothesised relationships as well as factor structures of the latent variables simultaneously (
Gefen et al., 2000
;
Hair et al., 2016
). As a second generational statistical tool, SEM deals with two main models; the structural model which entails the proposed relationships between the independent (exogenous) and the dependent (endogenous) latent variables, and secondly, the measurement model which comprises the loadings of the items on their respective constructs (
Gefen et al., 2000
).
Thus, combining these two models allows errors in the observed variables and factors analysis to be included simultaneously in testing the model for proposed hypothesised relationships between constructs (
Dartey-Baah & Addo, 2019
;
Gefen et al., 2000
). Concerning the mediation analysis, although the
Baron and Kenny (1986)
approach has been widely used for testing mediation over the years, it has been criticised for missing some true indirect effects thus resulting in Type II errors in research (
MacKinnon et al., 2007
). The mediation was thus tested by calculating the indirect effect estimates and subsequently testing the estimates for significance. SEM can test such complex relationships among variables (
Dartey-Baah & Addo, 2019
;
Hair Jr et al., 2014
;
Gefen et al., 2000
;
Kenny, 2012
).
As such, the structural models were evaluated to estimate the indirect effects of work-life balance (WLB) on work-life balance satisfaction (WLBS) and job satisfaction (JS) through organizational identity (OI). These estimates were then tested for significance using the percentile bootstrapping confidence interval method.
4.4. Demographic Analysis
The demographic analysis of the respondents offers a detailed profile of the bank employees surveyed to assess the effects of WLB practices on WLBS and JS. The sample showed a notable gender disparity, with 69.5 per cent males and 30.5 per cent females. Age distribution indicated a predominantly younger workforce, as 73.1 per cent of respondents were between 20 and 40 years old, while 26.9 per cent fell within the 41 to 55 age range, suggesting an early- to mid-career demographic. In terms of educational background, a significant majority of 85.6 per cent held a master’s degree, 14.0 per cent had a bachelor’s degree, and only 0.4 per cent held qualifications below a bachelor’s degree. Marital status analysis revealed that 83.1 per cent of respondents were married, while 16.9 per cent were unmarried. Family responsibilities were also a notable factor, as 72.7 per cent of participants reported having more than two dependents, and 27.3 per cent had one to two dependents, highlighting the potential influence of family obligations on their work-life balance needs. The sample included a diverse range of occupational roles, such as branch manager, senior officer, officer, and junior officer, ensuring a well-rounded representation of the banking workforce in Bangladesh. This variation in respondent demographics enhances the representativeness of the sample, offering valuable insights into the interplay of work-life balance, job satisfaction, and personal satisfaction across the industry.
5. Results5.1. Preliminary Analysis
The dataset was initially examined for missing values and their patterns, as systematic missing data could impact the validity of the findings (
Sekaran & Bougie, 2016
). Out of 566 responses, 31 cases exhibited random missing values and were subsequently excluded from the analysis. The remaining 535 responses were then assessed for outliers using the Mahalanobis distance test at a significant level of p < 0.000. Based on this, 7 responses with extreme values were removed (
Kline, 2011
).
Following this, the normality of the data was tested by evaluating the skewness and kurtosis values. All values were within the acceptable range of ±1 for skewness and ±3 for kurtosis (
Byrne, 2016
), indicating normal distribution. Lastly, Harman’s single-factor test was conducted as recommended by
Podsakoff et al. (2003)
to assess common method bias. The test revealed that a single factor accounted for 47.16% of the variance, which is below the critical threshold, suggesting that common method variance was not a major concern (
Fuller et al., 2016
).
5.2. Descriptive and Confirmatory Factor Analysis
To ensure the validity and reliability of the measurement model, a Confirmatory Factor Analysis (CFA) was conducted in accordance with the guidelines of
Hair et al. (2010)
,
Kline (2011)
, and
Hu and Bentler (1999)
. The model fit was assessed using multiple indices, including χ2/df < 3.0, Comparative Fit Index (CFI) ≥ 0.90, Tucker–Lewis Index (TLI) ≥ 0.90, Root Mean Square Error of Approximation (RMSEA) ≤ 0.08, and Standardised Root Mean Square Residual (SRMR) ≤ 0.10. The results indicated that the measurement model fit the data well, with χ2/df = 2.464, CFI = 0.959, TLI = 0.954, RMSEA = 0.053, and SRMR = 0.040 (see
Table 1
). To further support the robustness of the model, the proposed four-factor structure was compared with alternative configurations (three-factor, two-factor, and one-factor models). The hypothesised four-factor model demonstrated a significantly better fit than the more parsimonious alternatives (see
Table 1
).
Following this, descriptive statistics and discriminant validity were examined to assess the distinctiveness of the study constructs. As shown in
Table 2
, the mean and standard deviation (SD) values were as follows: work-life balance (WLB) (M = 3.23, SD = 0.899), work-life balance satisfaction (WLBS) (M = 3.22, SD = 1.062), job satisfaction (JS) (M = 3.08, SD = 1.081), and organisational identification (OI) (M = 3.28, SD = 1.083). These results provide insight into the central tendencies and variability of the measured variables. Discriminant validity was evaluated using the Fornell–Larcker criterion, where the square root of the AVE for each construct exceeded the corresponding inter-construct correlations. Additionally, the Heterotrait–Monotrait (HTMT) ratio values for all construct pairs remained below the conservative threshold of 0.85, further confirming adequate discriminant validity (see
Table 2
).
In addition to discriminant validity, convergent validity was assessed by examining standardised factor loadings, composite reliability (CR), and average variance extracted (AVE). All item loadings exceeded the recommended cut-off of 0.50, supporting item adequacy. CR values ranged from 0.908 to 0.934, while AVE values ranged from 0.55 to 0.70, thereby satisfying the criteria for convergent validity (see
Table 3
). Collectively, these results confirm that the measurement model demonstrates strong psychometric properties, providing a sound basis for further hypothesis testing.
Note: CFI = Comparative Fit Index; TLI = Tucker–Lewis index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Root Mean Squared Residual; WLB = Work-life balance; OI = Organizational identification; WLBS = Work-life balance satisfaction; JS = Job satisfaction; Four-factor model: Baseline model; Three-factor model: WLBS and JS were combined into one factor; Two-factor model: WLB and OI were combined into one factor and WLBS and JS were combined into another factor; One-factor model: All variables combined.
<xref ref-type="bibr" rid="scirp.143398-"></xref>Table 2. Mean, standard deviation, correlations.
Variables
M
SD
WLB
WLBS
JS
OI
WLB
3.2301
0.89962
0.742
0.520
0.504
0.485
WLBS
3.2238
1.06233
0.523
0.838
0.690
0.694
JS
3.0849
1.08110
0.492
0.701
0.810
0.780
OI
3.2812
1.08347
0.507
0.69
0.787
0.815
Note: N = 528, Underlined and bold elements in diagonal are the square root of AVE. Values below the diagonal elements are the correlations between constructs. Italicized values above diagonal elements are the HTMT ratios. WLB = Work-Life Balance; WLBS = Work-Life Balance Satisfaction; JS = Job Satisfaction; OI = Organizational Identification.
<xref ref-type="bibr" rid="scirp.143398-"></xref>Table 3. Factor loading, Cronbach’s alpha, Composite reliability (CR), and Average Variance Extracted (AVE).
The proposed structural model was tested using 5,000 bootstrap samples, with each hypothesis evaluated independently to ensure precise inference. Detailed statistical outcomes are presented in
Table 4
and
Figure 2
.
First, Hypothesis 1 (H1) posited that work-life balance (WLB) positively influences work-life balance satisfaction (WLBS). The results confirmed this relationship, with WLB exerting a significant positive effect on WLBS (β = 0.241, SE = 0.045, CR = 5.313, p < 0.01). This finding substantiates the notion that employees who perceive a balanced integration between work and personal life report higher satisfaction regarding this balance.
Subsequently, Hypothesis 2 (H2) predicted a positive relationship between WLB and job satisfaction (JS). The data supported this hypothesis, demonstrating a significant positive effect of WLB on JS (β = 0.11, SE = 0.035, CR = 3.167, p < 0.05). This suggests that an effective work-life balance extends beyond personal satisfaction to influence employees’ overall contentment with their job roles.
The analysis then focused on the mediating role of organisational identification (OI) in these relationships. Regarding Hypothesis 3 (H3), which proposed that OI mediates the effect of WLB on WLBS, the results showed a strong positive path from WLB to OI (β = 0.535, p < 0.01), and from OI to WLBS (β = 0.594, p < 0.01). The indirect effect of WLB on WLBS through OI was statistically significant (β = 0.326, p < 0.01), with bias-corrected confidence intervals [0.243, 0.410] excluding zero. This confirms partial mediation, highlighting OI’s key role in strengthening employees’ satisfaction with their work-life balance.
Similarly, Hypothesis 4 (H4) posited that OI mediates the relationship between WLB and JS. Consistent with this, OI was positively associated with JS (β = 0.609, p < 0.01), and the indirect effect of WLB on JS via OI was significant (β = 0.318, p < 0.01), with confidence intervals [0.254, 0.417] indicating robustness. These findings affirm OI as a critical psychological mechanism that links WLB practices with enhanced job satisfaction.
<xref ref-type="bibr" rid="scirp.143398-"></xref>Table 4. Results of hypothesis testing.
Variables
Bootstraps at 95%
β
S. E
C. R
LL CI
UL CI
WLB -> WLBS
0.241**
0.045
5.313
0.137
0.356
WLB -> JS
0.11*
0.035
3.167
0.021
0.211
WLB -> OI
0.535**
0.052
10.348
0.454
0.626
OI -> WLBS
0.594**
0.048
12.311
0.462
0.717
OI -> JS
0.609**
0.045
13.464
0.512
0.721
Indirect effect
WLB -> OI -> WLBS
0.326**
0.042
7.761
0.243
0.41
WLB -> OI -> JS
0.318**
0.041
7.756
0.254
0.417
WLB -> WLBS
0.241**
0.045
5.313
0.137
0.356
WLB -> JS
0.11*
0.035
3.167
0.021
0.211
Note: *p < 0.05, **p < 0.01. WLB = Work-Life Balance; WLBS = Work-Life Balance Satisfaction; JS = Job Satisfaction; OI = Organizational Identification; SE = Standard error; CR = Critical ratio; BC = Bias-corrected; CI = Confidence interval.
Figure 2. Structural model.
6. Discussion
This study aimed to investigate the impact of WLB practices on employees’ work-life balance satisfaction (WLBS) and job satisfaction (JS), alongside the mediating effect of organisational identity (OI) on the WLB-WLBS and WLB-JS relationships among employees in private commercial banks.
The findings demonstrate a positive influence of WLB on employees’ WLBS. This implies that organisations implementing WLB practices—such as flexible hours, adaptable workstations, teleworking, job-sharing, part-time options, childcare support, maternity leave, and family-oriented holidays—are likely to foster greater satisfaction with work-life balance among employees. This aligns with existing research that highlights a positive association between WLB and WLBS in employees (
Butts & Krysan, 2012
;
Haar & Roche, 2010
). Moreover, achieving work-life balance satisfaction translates into improved job attitudes, heightened organisational commitment, reduced turnover, enhanced employee engagement and retention, minimised work-family conflict, increased organisational citizenship behaviors, strengthened organisational commitment, and greater job satisfaction (
Baral & Bhargava, 2010
;
Kelliher et al., 2019
;
Kossek et al., 2011
).
Further analysis reveals that WLB has a positive effect on employees’ JS, indicating that providing flexible work arrangements, task-sharing options, transitions from full-time to part-time roles, compressed working hours, remote work, and emergency paid leave for dependents can enhance job satisfaction. These practices not only boost employee morale but also promote family well-being, satisfaction, reduced stress, and a broader enjoyment of life (
Bloom et al., 2009
;
Bowling et al., 2010
;
Voydanoff, 2005
). These results are consistent with previous research findings in other sectors (
Hart, 1999
;
Iverson & Maguire, 2000
;
Vansteenkiste et al., 2007
), as well as studies focused on the banking sector in various global contexts (
Deng & Gao, 2017
;
Umans et al., 2018
).
Finally, the study underscores that OI mediates the relationship between WLB and WLBS, and WLBS and JS, suggesting that providing employees with autonomy and freedom in their roles enhances both work-life balance satisfaction and job satisfaction. This outcome is consistent with the established influence of WLB on WLBS and JS in this study and corroborated by prior literature (
Butts & Krysan, 2012
;
Haar & Roche, 2010
). Additionally, the mediating role of OI in WLBS and JS outcomes is well-documented in other studies, further supporting these findings (
Carmeli et al., 2007
;
Kehoe & Wright, 2013
;
Vallerand, 2003
;
van Dick & Haslam, 2012
).
6.1. Practical Implications
This study underscores the critical role of employees’ organisational identification behaviors within organisations, particularly in fields that are economically driven, such as the banking sector. Notably, it highlights the positive impact of organisational work-life balance (WLB) initiatives on employees’ overall work-life satisfaction and job satisfaction. The findings suggest that the banking industry should prioritise providing employees with meaningful avenues to achieve a healthy work-life balance. Given the high-stress nature of banking roles, employees often feel confined within the demands of their professional lives.
Implementing effective WLB practices can enhance employees’ motivation, job involvement, and commitment, while reducing burnout, as supported by prior studies (
Baral & Bhargava, 2010
;
Butts & Krysan, 2012
;
Kelliher et al., 2019
;
Kossek et al., 2011
). Furthermore, a well-balanced work-life arrangement fosters increased employee productivity and dedication to the organisation, thereby benefiting both the individuals and the institution as a whole.
6.2. Theoretical Implications
The findings of this study provide a nuanced perspective on the relationships between work-life balance (WLB), work-life balance satisfaction (WLBS), job satisfaction (JS), and organisational identification (OI), with a particular emphasis on the Asian context. Specifically, the research identifies an indirect effect of WLB on both WLBS and JS through the mediating role of OI, underscoring the broader impacts of WLB initiatives.
This study offers several theoretical contributions. Firstly, it expands the existing literature on WLB and OI by emphasising the indirect influence of WLB practices on enhancing WLBS and JS. The findings corroborate the view that effective WLB contributes to heightened levels of positive employee satisfaction. Furthermore, while conducting an extensive review of the literature, a notable gap was identified in research specifically examining the relationships between WLB, WLBS, and JS. This study’s unique contribution thus advances the understanding of how WLB influences WLBS and JS in this regional setting, filling an important gap in current research.
6.3. Limitations and Future Directions
This study has certain limitations regarding the generalisability of its findings across the Bangladeshi banking sector, primarily due to the sample and convenience sampling technique employed. This limitation aligns with observations in the literature, where some scholars (
Simon, 2011
;
Sudeshna & Datt, 2016
) argue that quantitative studies may not fully represent the target population regardless of the sampling method. However, despite this limitation, the study’s findings remain relevant and credible for application within the banking sector.
Additionally, the study relied on self-reported measures for the variables, which may have introduced response bias. Future research would benefit from integrating multiple methods to assess these variables, such as supervisor ratings and behavioral measures, to enhance accuracy and reduce potential bias.
A further limitation is the study’s focus on a single industry (banking). This specific context may limit the applicability of the findings to other industries. Expanding future research to encompass a broader range of industries could provide insight into the generalisability of these results. Additionally, future studies could adopt qualitative methods to explore underlying factors influencing the relationships observed between WLB, WLBS, JS, and OI.
7. Conclusion
This study explores the influence of work-life balance (WLB) practices on employees’ work-life balance satisfaction (WLBS) and job satisfaction (JS), while also examining the mediating role of organisational identification (OI) on WLB-WLBS and WLB-JS relationships. The findings confirm that effective WLB practices such as flexible work arrangements, part-time roles, remote work, and family-oriented support positively impact both WLBS and JS. Moreover, the study affirms the mediating role of OI, highlighting that employees who identify strongly with their organisation are more likely to derive satisfaction from both their work and their personal lives. The results indicate that when organisations foster a supportive and flexible environment, employees are more engaged, less stressed, and more satisfied with their jobs. Organisational leaders, especially in high-pressure sectors like banking, may adopt these practices not only to improve job satisfaction but also to reinforce employees’ identification with the organisation. By investing in meaningful WLB initiatives and promoting a sense of belonging, institutions can effectively enhance both employee well-being and organisational outcomes.
Funding Statement
The author received no financial support for the research, authorship, and/or publication of this article.
Biographies
Dr. Ishita Roy is an Associate Professor at the Department of Management Studies in Gopalganj Science and Technology University, Gopalganj, Bangladesh. She received her PhD from Gopalganj Science and Technology University, Gopalganj, Bangladesh. She published several papers in peer-reviewed international journals. Her areas of research interest include Human Resource Management, Leadership, Organizational Behavior, Work-life Balance Practices and Subjective well-being.
Acknowledgements
The author is grateful to the anonymous referees of the journal for their insightful and constructive comments, which significantly enhanced the quality of this manuscript. Special thanks are extended to Dr. Md. Sahidur Rahman and Dr. Md. Shamsul Arefin for their invaluable guidance and support throughout the research process, particularly in study design and coordination of data collection. The author also acknowledges the contributions of Rawshan Islam, Tanmoy Karmakar and Choyan Halder whose dedicated efforts in data collection and screening were instrumental. Sincere appreciation is also extended to all others who assisted in the fieldwork and data collection process. Their support played a vital role in the successful completion of this study.
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