Page 1732
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Balancing Work – Life and Personal – Life Expectancies: Insights from
Public and Private Sector Banks
Prof. S. Rajani
1
, Dr. N. Neeraja
2
1
Senior Professor, MBA Department, Gayatri Vidya Parishad College for Degree and PG Courses,
Rushikonda, Visakhapatnam.
2
Assistant Professor, MBA – Business Analytics Department, Gayatri Vidya Parishad College for
Degree and PG Courses, Rushikonda, Visakhapatnam.
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150500136
Received: 11 May 2026; Accepted: 16 May 2026; Published: 09 June 2026
ABSTRACT
Banking sector is strength for the economic development of any country and the women is playing an important
role in functioning of the banking sector. At present, banks are creating more opportunities for women
employees. Most of the women prefer jobs in banks because they are more attractive and comfortable. Currently,
women employees are facing challenges in fulfilling the responsibilities both in professional life and work life.
The present study is to know about the personal life expectations and work-life expectations of women
employees working in the public and private sector banks in Visakhapatnam. A sample of 120 respondents was
selected using simple random sampling. Data were collected through structured questionnaires based on a five-
point Likert scale. Statistical tools including descriptive statistics, ANOVA, and multiple regression analysis
were employed. The findings reveal significant differences in expectations across sectors and demographic
categories. Regression analysis further indicates that age, marital status, work experience, and type of bank
significantly influence work–life and personal–life expectations. The study provides managerial insights for
designing gender-sensitive workplace policies.
Keywords: Work-life balance, Banking sector, Women employees, Personal life expectations, Work-life
expectations, Regression analysis, Self – management.
INTRODUCTION
Work-life balance plays an important role in day-to-day life. Managing work-life balance is challenging for
women employees working in banking sector because of more work in the workplace it can affect personal life
directly and making complicated to complete household activities. Work-life balance differs from person to
person. Currently, most of the women employees are finding themselves in leading teams, being in important
decision-making roles and creating strategies for organizations they work with. Employees are increasingly
recognizing the important of promoting a balanced life style, offering flexible working arrangements and
wellness programs.
With increased participation of women in leadership, operations, and strategic roles, managing professional
responsibilities alongside personal commitments has become increasingly complex.
In India, the banking sector—comprising public and private institutions—has undergone structural
transformation characterized by technological integration, performance targets, and competitive pressures. These
changes have intensified workload and accountability, especially for women employees who often shoulder dual
responsibilities at workplace and home. Self-management, therefore, becomes essential in maintaining
equilibrium between personal and professional domains. This study examines the work-life and personal-life
expectations of women employees in public and private sector banks and statistically evaluates the influence of
demographic factors on these expectations.
Page 1733
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Challenges that are faced by the women employees at their workplace
Even though we are having gender equity at the workplace, women employees continue to navigate workplaces
shaped by deep-rooted discrepancy that impact their daily work lives. Women employees frequently encounter
barriers at workplace which will impact their personal life and work-life. The challenges that are faced by women
employees at the workplace are unequal pay, under representation in leadership and discrimination. These
hindrances can impact their financial stability, career growth and well-being. In the past, women used to give
importance in inclusivity, collaboration, creativity and compassion, which are used for driving innovation and
navigating complex situations.
Now-a-days organizations are providing more benefits to support workers with caregiving responsibilities,
including paid maternity leave, paternity leave and child care services. The benefits are useful for the women
employees who continue to bear the majority of family caregiving duties.
Even though flexible work policies are increased, women often face stigma or bias in using them. Due to this
they face career setbacks such as missed promotions or slower commitment. Half of the companies provide
emergency child care services in 2024. 80% of the organizations offer benefits for fertility treatments and
adoption or surrogacy. 80% of employees say flexibility has improved in the last decade.
At present, women employees are freely expressing the need of flexible work options, mentorship programming,
leadership development, citing remote arrangements as a primary factor in maintaining their focus, productivity
and well-being.
Key initiatives include:
Family-friendly policies (ex: maternity, paternity leave, childcare etc.)
Flexible work arrangements.
Return-to-work programs for employees returning from extended leave.
Frequent promotion of benefits encouraging their use to reduce stigma.
Why does work-life imbalance occur?
Work-life imbalance occurs when the demands of work and personal life are not managed in a proper way.
There are some of the reasons to cause poor work-life balance like excessive workload, lack of time management,
inadequate delegation, absence of flexibility, insufficient boundaries, commuting hassles, neglecting self-care,
unsupportive work environment, unclear priorities, over committing, technology overload, financial stress,
health issues, lack of boundaries in remote work, job insecurity, poor communication, limited access to
resources, lack of social support, ignoring hobbies and interests.
REVIEW OF LITERATURE
The banking industry has been widely examined as a high-pressure environment characterized by extended
working hours, stringent compliance requirements, and performance-linked incentives. Empirical research
suggests that such structural features intensify work–family conflict, especially for women employees who often
carry disproportionate domestic responsibilities.
For instance, a study published in Administrative Sciences found that work–life balance significantly influences
job commitment and personal well-being among women bankers, while excessive working hours negatively
affect family satisfaction (Khan et al., 2022). Similarly, Ganapathi (2016) observed that women employees in
private sector banks experience greater job strain compared to their counterparts in public sector institutions due
to performance-driven cultures.
Comparative analyses indicate notable sectoral variations. Rajan and Rani (2024a) reported that married women
employees in public sector banks demonstrated relatively better balance outcomes due to structured working
Page 1734
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
hours and supportive leave policies. In contrast, private sector employees reported higher stress levels linked to
competitive targets and limited autonomy.
Garg and Sharma (2020) argue that Human Resource Information Systems (HRIS) can streamline work
processes, reduce administrative burdens, and enhance flexibility in banking institutions. Their findings suggest
that technological integration can indirectly contribute to better balance outcomes by improving time
management and workflow efficiency.
Further empirical evidence highlights that perceived organizational support positively influences employee
satisfaction and psychological well-being. Rajan and Rani (2024b) found that stress management initiatives
significantly moderate the relationship between workload and personal-life satisfaction among women in public
sector banks. These findings align with the JD–R model, reinforcing the buffering role of organizational
resources.
The relationship between work–life balance and job satisfaction has received considerable empirical validation.
Kaushik and Guleria (2020) conceptualized WLB as a predictor of employee performance and satisfaction,
suggesting that balanced employees exhibit higher productivity and organizational commitment.
Kumar and Sujatha (2023) examined women employees in public sector banks and found a strong positive
correlation between balance perception and job satisfaction. Their results indicate that emotional well-being and
reduced role conflict significantly enhance professional engagement.
Similarly, Dhungel (2022), in a study of women in the banking industry, reported that improved balance practices
contribute to lower turnover intentions and higher organizational loyalty. These findings underscore the strategic
importance of WLB initiatives in sustaining workforce stability within the service sector.
Gender remains a critical dimension in WLB research. Women employees often encounter dual-role pressures
arising from workplace expectations and societal norms regarding caregiving responsibilities. Chandana and
Jain (2025) highlight that women in banking frequently experience role overload due to professional
commitments coupled with domestic expectations.
Prathiba and Raja (2023) observed that married women employees face heightened strain during peak
operational periods, particularly in private sector banks where performance metrics are stringent. Nambiar
(2025) further emphasizes that psychological well-being is closely associated with institutional support systems,
especially maternity leave provisions and flexible scheduling options.
These findings collectively suggest that gender-sensitive HR policies are essential to achieving sustainable
work–life integration.
Several studies have compared public and private sector banking institutions to assess differences in work–life
balance outcomes. Walia (2020) reported that public sector banks generally provide more stable working
conditions, structured hours, and predictable workloads, thereby facilitating better work–life integration.
Conversely, private sector banks often demonstrate higher productivity expectations and extended operational
hours, which intensify work–family conflict.
Rajan and Rani (2024a) empirically confirmed that public sector employees reported higher balance scores
compared to private sector counterparts. However, private sector institutions were found to offer greater career
progression opportunities, creating a trade-off between professional advancement and personal life equilibrium.
Objectives
To comprehend about the personal life expectations and work-life expectations of women employees
working in banks.
Page 1735
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
To make a comparative analysis of practices adopted in public and private sector banks to achieve work-
life balance among women employees.
To assess the influence of demographic variables on work–life and personal–life expectations.
To provide suitable suggestions for an appropriate work-life balance in banking sector for women
employees.
Hypothesis
Sector-Based Hypotheses
H01: There is no statistically significant variation in work-life expectations among women employees working
in public sector banks.
H02: There is no statistically significant variation in work-life expectations among women employees working
in private sector banks.
H03: There is no statistically significant difference between public and private sector women employees
regarding work-life expectations.
Similarly, personal-life expectations may vary across sectors due to workload, flexibility policies, and
organizational culture.
H04: There is no statistically significant variation in personal-life expectations among women employees
working in public sector banks.
H05: There is no statistically significant variation in personal-life expectations among women employees
working in private sector banks.
H06: There is no statistically significant difference between public and private sector women employees with
respect to personal-life expectations.
Demographic-Based Hypotheses
Work-life balance perceptions are often shaped by individual demographic characteristics. Therefore, the study
further examines the influence of age, marital status, educational qualification, and work experience.
H07: Age does not significantly influence work-life expectations of women employees in the banking sector.
H08: Marital status does not significantly influence personal-life expectations of women employees in the
banking sector.
H09: Work experience does not significantly affect perceptions of work-life balance among women employees.
H10: Educational qualification does not significantly influence work-life expectations among women
employees.
RESEARCH METHODOLOGY
Simple random sampling method is used for the survey of the study. It is a probability sampling technique. The
study adopts a descriptive and analytical research design. Data is collected through questionnaires, emails and
personal interviews from 120 respondents from the different public and private sector banks of Visakhapatnam
district and try to find out the women employees personal life expectations and work-life expectations. In the
questionnaire, Likert’s 5-point scale is used to determine scores, where respondents were asked to rate each
Page 1736
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
attribute on 5 point scale ranging from strongly agree to strongly disagree. Secondary data were gathered from
journals and published sources.
Methodological Justification
The study employed both ANOVA and multiple regression analysis to address distinct but complementary
research objectives. ANOVA was utilized to examine mean differences in work–life and personal–life
expectations across public and private sector banks. This technique enabled identification of statistically
significant group-level variation. Subsequently, multiple regression analysis was conducted to assess the
predictive influence of demographic and institutional variables on expectation constructs. Regression allowed
estimation of the magnitude, direction, and explanatory power of independent variables, thereby providing
deeper insight into causal relationships. The combined use of these techniques enhanced analytical robustness
and strengthened the explanatory validity of the study.
Statistical Tools
Descriptive statistics (Mean and Standard Deviation)
One-way ANOVA
Multiple Linear Regression
Limitations of the study
The study was conducted only in the Visakhapatnam district hence the data cannot be compared with
other areas.
The analysis is made based on the information provided by the respondent which is subjected to bias.
The result analysis applicable only to the certain period.
Research Gap
Although numerous studies have examined work–life balance among women employees in the banking sector,
most prior research has primarily focused on general stress factors, organizational policies, or overall job
satisfaction. Limited attention has been given to the integrated examination of both work-life expectations and
personal-life expectations within the same empirical framework.
Further, earlier studies have largely concentrated on either public sector or private sector banks independently,
without offering a comparative perspective between the two sectors. The structural differences in workload,
performance targets, flexibility policies, and organizational culture between public and private banks may create
distinct expectation patterns among women employees, yet empirical comparative evidence remains insufficient.
Moreover, demographic determinants such as age, marital status, and work experience have often been discussed
descriptively, but few studies have statistically tested their influence using inferential techniques. Particularly in
the context of Visakhapatnam district, there is a lack of region-specific empirical evidence assessing how
demographic variables shape work-life and personal-life expectations among women employees.
Three major gaps remain:
1. Limited comparative analysis between public and private sector banks.
2. Insufficient integration of work–life and personal–life expectations within a single empirical model.
3. Lack of statistical testing of demographic predictors using inferential methods such as regression
analysis.
Additionally, region-specific studies in Visakhapatnam district remain scarce. The present study addresses these
gaps through a structured comparative and predictive approach.
Page 1737
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Data Analysis and Interpretation
There are 12 public sector banks and 21 private sector banks in India. Out of 12 public sector banks some of the
banks that are selected in Visakhapatnam for study are SBI, Union Bank of India, UCO bank, Bank of India and
Bank of Baroda. Out of 21 private sector banks, some of the banks that are selected for the study are Axis bank,
ICICI bank, and HDFC bank.
The sample size of both the public and private sector banks is 120. The demographic characteristics considered
for the study include age, marital status, educational qualification, work experience, designation, and type of
bank.
Table 1: Demographic Profile of Respondents (N = 120)
Variable
Category
Frequency
Percentage
Age
20 – 30 years
30
25.0%
31 – 40 years
46
38.3%
41 – 50 years
28
23.3%
Above 50 years
16
13.4%
Marital Status
Married
78
65.0%
Unmarried
34
28.3%
Others
8
6.7%
Education
Graduate
40
33.3%
Post Graduate
62
51.7%
Professional
Qualification
18
15.0%
Work Experience
Below 5 years
32
26.7%
5–10 years
40
33.3%
11–15 years
26
21.7%
Above 15 years
22
18.3%
Type of Bank
Public
60
50.0%
Private
60
50.0%
Interpretation
Majority of respondents (38.3%) belong to the age group of 31–40 years and only 13.4% of the respondents are
above 50 years. 65% of the respondents are married women employees. More than half (51.7%) of the
respondents are post-graduates and only 15% of the respondents are having Professional Qualification. Equal
representation was ensured from public and private sector banks.
Model 1: Predicting Work-Life Expectations
A multiple linear regression analysis was conducted to examine whether demographic and institutional variables
significantly predict Work–Life Expectation (WLE) scores among women employees in the banking sector.
Page 1738
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
The regression equation estimated was:
WLE=β0+β1(Age)+β2(Marital Status)+β3(Experience)+β4(Education)+β5(Type of Bank)+ε
Table 2: Multiple Regression Results – Work-Life Expectations
Variable
Beta
t-value
Age
0.312
3.45
Marital Status
0.276
2.98
Work Experience
0.214
2.41
Education
0.109
1.32
Type of Bank
0.287
3.12
R²=0.48
F=21.67
p < 0.001
This indicates that the model provides a good fit to the data and that the independent variables collectively
explain a substantial portion of variation in work–life expectations.
Interpretation of R² and Model Fit
An R² value of 0.48 suggests that 48% of the variance in work–life expectation scores is explained by age,
marital status, work experience, education, and type of bank.
In social science research, an R² close to 0.50 is considered moderately strong, indicating that demographic and
institutional factors play a meaningful role in shaping work–life expectations.
The significant F-statistic confirms that the regression model as a whole is statistically reliable.
Interpretation of Individual Predictors
1. Age (β = 0.312, p = 0.001)
Age is a significant and positive predictor of work–life expectations.
A one-unit increase in age is associated with a 0.312 increase in WLE score.
Older employees tend to report higher work–life expectations.
This may reflect increased family responsibilities, caregiving roles, or career-stage transitions that heighten
expectations for balance.
2. Marital Status (β = 0.276, p = 0.004)
Marital status significantly predicts work–life expectations.
Married employees exhibit higher expectations compared to unmarried employees.
This suggests that dual-role responsibilities intensify the need for institutional support.
Page 1739
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
The finding aligns with role conflict theory, where multiple role demands elevate expectations for work-life
integration.
3. Work Experience (β = 0.214, p = 0.018)
Work experience is a significant positive predictor.
Employees with greater experience demonstrate higher expectations.
Senior employees may expect more autonomy, flexibility, and supportive policies.
This suggests that expectations evolve with tenure and organizational exposure.
4. Education (β = 0.109, p = 0.189)
Education is not statistically significant.
Although positively related, its effect is weak and insignificant.
Educational attainment alone does not substantially influence work–life expectations.
This implies that institutional environment and life-stage variables are more influential than academic
qualifications.
5. Type of Bank (β = 0.287, p = 0.002)
Type of bank is a strong and significant predictor.
Employees in private sector banks (dummy coded 1) show significantly higher work–life expectations
compared to public sector employees.
This may reflect higher performance pressure and longer working hours in private banks.
This variable demonstrates structural institutional differences in shaping employee expectations.
Among all predictors, age and type of bank show relatively stronger standardized beta values, indicating their
substantial contribution to explaining variation in work–life expectations.
Demographic maturity and institutional structure jointly influence expectations more than educational level.
Model 2: Predicting Personal-Life Expectations
A second regression model was estimated to assess predictors of Personal–Life Expectation (PLE) scores.
Regression Equation:
PLE=β0+β1(Age)+β2(Marital Status)+β3(Experience)+β4(Education)+β5(Type of Bank)+ε
Table 3 : Regression Results – Personal-Life Expectations
Variable
Beta
t-value
Significance
Age
0.298
3.21
0.002
Marital Status
0.354
3.88
0.000
Work Experience
0.190
2.09
0.039
Page 1740
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Education
0.082
1.01
0.315
Type of Bank
0.265
2.74
0.007
R²=0.52
F=24.83
p < 0.001
Interpretation of R² and Model Fit
The R² value of 0.52 indicates that 52% of the variation in personal-life expectations is explained by the
included predictors.
This suggests that demographic and institutional variables have even stronger explanatory power for
personal-life expectations than for work–life expectations.
The statistically significant F-statistic confirms overall model adequacy.
Interpretation of Individual Predictors
1. Age (β = 0.298, p = 0.002)
Age significantly influences personal-life expectations.
Older employees report higher personal-life expectations.
This reflects increasing non-work responsibilities such as childcare and eldercare.
2. Marital Status (β = 0.354, p < 0.001)
Marital status emerges as the strongest predictor in this model.
The highest beta coefficient (0.354) indicates substantial influence.
Married women demonstrate significantly higher personal-life expectations.
This reinforces the centrality of family roles in shaping personal-life demands.
3. Work Experience (β = 0.190, p = 0.039)
Work experience is significant but weaker compared to age and marital status.
Experienced employees may expect greater flexibility to manage personal commitments.
4. Education (β = 0.082, p = 0.315)
Education again shows no significant predictive power.
This confirms that personal-life expectations are more influenced by social and familial factors than by
academic background.
5. Type of Bank (β = 0.265, p = 0.007)
Type of bank significantly affects personal-life expectations.
Employees in private banks report stronger personal-life expectations.
This may indicate greater work pressure creating higher demand for balance.
Page 1741
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Table: Hypothesis-Wise Acceptance/Rejection
Hypothesis
Statement
Result
Decision
H1
Age significantly influences work–life expectations.
β = 0.312, p = 0.001
Accepted
H2
Marital status significantly influences work–life expectations.
β = 0.276, p = 0.004
Accepted
H3
Work experience significantly influences work–life expectations.
β = 0.214, p = 0.018
Accepted
H4
Education significantly influences work–life expectations.
β = 0.109, p = 0.189
Rejected
H5
Type of bank significantly influences work–life expectations.
β = 0.287, p = 0.002
Accepted
H6
Age significantly influences personal-life expectations.
β = 0.298, p = 0.002
Accepted
H7
Marital status significantly influences personal-life expectations.
β = 0.354, p < 0.001
Accepted
H8
Work experience significantly influences personal-life
expectations.
β = 0.190, p = 0.039
Accepted
H9
Education significantly influences personal-life expectations.
β = 0.082, p = 0.315
Rejected
H10
Type of bank significantly influences personal-life expectations.
β = 0.265, p = 0.007
Accepted
Table 4: Distribution of respondents from the Public sector banks according to their opinion on Work –
Life Expectations
Statement
Opinion of Respondents
SA
A
N
DA
SDA
I get fair treatment from my superiors
13
(21.7)
16
(26.7)
10
(16.7)
14
(23.3)
7
(11.6)
I want to work for a maximum of 9 hours.
19
(31.7)
16
(26.7)
8
(13.3)
8
(13.3)
9
(15.0)
I want to have flexible targets.
14
(23.3)
22
(36.7)
10
(16.7)
9
(15.0)
5
(8.3)
I want have good relationship with colleagues
18
(30.0)
14
(23.3)
11
(18.3)
11
(18.3)
6
(10.0)
I look forward to receive adequate training when new
systems are introduced.
17
(28.3)
15
(25.0)
13
(21.7)
4
(6.7)
11
(18.3)
Mean
16.2
16.6
10.4
9.2
7.6
Standard Deviation
2.59
3.13
1.82
3.70
2.41
Note: In the above table we have done the descriptive statistics like Mean and Standard deviation.
Percentages are written in the brackets.
H01: There is no significant difference in the opinion of respondents on work-life expectations of women
employees working in the Public sector banks.
Page 1742
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Table 5: ANOVA for Work – Life Expectations in Public sector banks
WLB
ANOVA
Sum of Squares
DF
Mean Squares
F
Significance
Between
Groups
342.8
4
85.7
10.90330789
0.00007
Within Groups
157.2
20
7.86
Total
500
24
Interpretation: The above table depicts that at 95% confidence intervals for the groups, p < 0.05 (0.00007 <
0.05), the critical value for degrees of freedom (4, 20) is 2.866. F
cal
> F
critical
i.e., 10.9 > 2.866. Hence the null
hypothesis H0 is rejected and it can be concluded that there is a significant difference in the opinion of
respondents on Work – Life Expectations of women employees working in the public sector banks.
From the table 4 we can see that 36.7% of the respondents from the public sector banks agree that they want to
have flexible targets and only 8.3% of the respondents said that they don’t want to have flexible targets. 6.7% of
the respondents said that employees are looking forward to receive adequate training when new systems are
introduced and 28.3% of the respondents said that employees are looking forward to receive adequate training
when new systems are introduced.
Table 6: Distribution of respondents from the Private sector banks according to their opinion on Work –
Life Expectations
Statement
Opinion of Respondents
SA
A
N
DA
SDA
I get fair treatment from my superiors
16
(26.7)
19
(31.7)
13
(21.7)
7
(11.6)
5
(8.3)
I want to work for a maximum of 9 hours.
20
(33.3)
19
(31.7)
5
(8.3)
11
(18.3)
5
(8.3)
I want to have flexible targets.
14
(23.3)
21
(35.0)
10
(16.7)
8
(13.3)
7
(11.6)
I want have good relationship with colleagues
18
(30.0)
14
(23.3)
12
(20.0)
10
(16.7)
6
(10.0)
I look forward to receive adequate training when new
systems are introduced.
17
(28.3)
15
(25.0)
13
(21.7)
11
(18.3)
4
(6.7)
Mean
17
17.6
10.6
9.4
5.4
Standard Deviation
2.24
2.97
3.36
1.82
1.14
Note: In the above table we have done the descriptive statistics like Mean and Standard deviation.
Percentages are written in the brackets.
H02: There is no significant difference in the opinion of respondents on work – life expectations of women
employees working in the Private sector banks.
Page 1743
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Table 7: ANOVA for Work – Life Expectations in Private sector banks
WLB
ANOVA
Sum of Squares
DF
Mean Squares
F
Significance
Between Groups
543.2
4
135.8
22.86195286
0.0000003
Within Groups
118.8
20
5.94
Total
662
24
Interpretation: The above table depicts that at 95% confidence intervals for the groups, p < 0.05 (0.0000003 <
0.05), the critical value for degrees of freedom (4, 20) is 2.866. F
cal
> F
critical
i.e., 22.86 > 2.866. Hence the null
hypothesis H0 is rejected and it can be concluded that there is a significant difference in the opinion of
respondents on Work – Life Expectations of women employees working in the private sector banks. From the
table 6 we can see that 31.7% of the respondents from the private sector banks agree that they are getting fair
treatment from the superiors and only 8.3% of the respondents strongly disagree that they are getting fair
treatment from the superiors. 30% of the respondents said that employees are having good relationship with the
colleagues and 20% of the respondents are neutral and only 10% of the employees strongly disagree that they
are not having good relationship with the colleagues.
Table 8: Distribution of respondents from the Public sector banks according to their opinion on Personal
– Life Expectations
Statement
Opinion of Respondents
SA
A
N
DA
SDA
I need time for refreshment.
19
(31.6)
16
(26.7)
13
(21.7)
7
(11.7)
5
(8.3)
I need time for sleep.
19
(31.6)
21
(35.0)
4
(6.7)
11
(18.3)
5
(8.3)
I want to enjoy family trips at least once in year during
vacation.
22
(36.7)
14
(23.3)
9
(15.0)
10
(16.7)
5
(8.3)
I want some personal time to squander with my
family.
14
(23.3)
18
(30.0)
11
(18.3)
10
(16.7)
7
(11.7)
I want to spend some time with my children.
13
(21.7)
14
(23.3)
18
(30.0)
11
(18.3)
4
(6.7)
I want to spend some quality time for myself.
23
(38.3)
19
(31.6)
11
(18.3)
3
(5.0)
4
(6.7)
I love to indulge in social engagement.
17
(28.3)
19
(31.6)
9
(15.0)
7
(11.7)
8
(13.3)
Mean
18.1
17.3
10.7
8.4
5.4
Standard Deviation
3.8
2.7
4.3
2.9
1.5
Note: In the above table we have done the descriptive statistics like Mean and Standard deviation.
Percentages are written in the brackets.
Page 1744
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
H03: There is no significant difference in the opinion of respondents on personal – life expectations of women
employees working in the public sector banks.
Table 9: ANOVA for Personal – Life Expectations in Public sector banks
WLB
ANOVA
Sum of Squares
DF
Mean Squares
F
Significance
Between Groups
862.8571429
4
215.7142857
21.34778511
0.00000002
Within Groups
303.1428571
30
10.1047619
Total
1166
34
Interpretation: The above table depicts that at 95% confidence intervals for the groups, p < 0.05 (0.00000002
< 0.05), the critical value for degrees of freedom (4, 30) is 2.68. F
cal
> F
critical
i.e., 21.347 > 2.68. Hence the null
hypothesis H0 is rejected and it can be concluded that there is a significant difference in the opinion of
respondents on Personal – Life Expectations of women employees working in the public sector banks. From the
table 8 we can see that 38.3% of the respondents from the public sector banks strongly agree that they want to
spend some quality time for themselves and only 5% of the respondents disagree that they don’t want to spend
some quality time for themselves. 23.3% of the respondents agree that they want to spend some quality time
with their children, only 6.7% of the respondents strongly disagree that they don’t want to spend some quality
time with their children and 30% of the respondents are in a dilemma that whether they want to spend or don’t
want to spend the time with children.
Table 7: Distribution of respondents from the Private sector banks according to their opinion on Personal
– Life Expectations
Statement
Opinion of Respondents
SA
A
N
DA
SDA
I need time for refreshment.
20
(33.3)
25
(41.7)
8
(13.3)
5
(8.3)
2
(3.3)
I need time for sleep.
22
(36.7)
18
(30.0)
11
(18.3)
5
(8.3)
4
(6.7)
I want to enjoy family trips at least once in year during
vacation.
14
(23.3)
25
(41.7)
9
(15.0)
6
(10.0)
6
(10.0)
I want some personal time to squander with my
family.
14
(23.3)
16
(26.7)
10
(16.7)
16
(26.7)
4
(6.7)
I want to spend some time with my children.
15
(25.0)
12
(20.0)
21
(35.0)
2
(3.3)
10
(16.7)
I want to spend some quality time for myself.
17
(28.3)
22
(36.7)
11
(18.3)
5
(8.3)
5
(8.3)
I love to indulge in social engagement.
13
(21.7)
23
(38.3)
6
(10.0)
13
(21.7)
5
(8.3)
Mean
16.4
20.1
10.9
7.4
5.1
Standard Deviation
3.41
4.95
4.81
5.06
2.48
Note: In the above table we have done the descriptive statistics like Mean and Standard deviation.
Percentages are written in the brackets.
Page 1745
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
H04: There is no significant difference in the opinion of respondents on personal – life expectations of women
employees working in the private sector banks.
Table 8: ANOVA for Personal – Life Expectations in Private sector banks
WLB
ANOVA
Sum of Squares
DF
Mean Squares
F
Significance
Between Groups
1086
4
271.5
14.91758242
0.0000008
Within Groups
546
30
18.2
Total
1632
34
Interpretation: The above table depicts that at 95% confidence intervals for the groups, p < 0.05 (0.0000008 <
0.05), the critical value for degrees of freedom (4, 30) is 2.68. F
cal
> F
critical
i.e., 14.917 > 2.68. Hence the null
hypothesis H0 is rejected and it can be concluded that there is a significant difference in the opinion of
respondents on Personal – Life Expectations of women employees working in the private sector banks. From the
table 7, we can see that 41.7% of the respondents from the private sector banks agree that they need time for
refreshment and only 31.6% of the respondents from the public sector banks say that they need time for
refreshments. 36.7% of the respondents strongly agree that they need time to sleep so that stress will be reduced
and they can complete the work in time, only 6.7% of the respondents strongly disagree that they no need time
to sleep.
FINDINGS
The empirical analysis provides several important insights into the work–life and personal–life expectations of
women employees in public and private sector banks.
1. Sector-Based Differences
The ANOVA results indicate statistically significant variation in both work–life and personal–life expectations
within public and private sector banks. This demonstrates that expectation patterns are not uniform and differ
across institutional settings. Women employees in private sector banks reported relatively higher expectations,
particularly regarding flexibility, fair treatment, manageable working hours, and personal time. This may be
attributed to higher performance pressures and competitive work environments in private banking institutions.
Public sector employees, while benefiting from structured working hours and relatively stable policies, also
exhibited significant expectation variation, especially concerning training opportunities and flexibility in targets.
2. Demographic Influence on Work–Life Expectations
Multiple regression analysis revealed that demographic factors play a substantial role in shaping work–life
expectations:
Age emerged as a significant positive predictor, indicating that expectations increase with life stage
progression.
Marital status significantly influenced expectations, with married employees reporting higher demands
for balance-supportive policies.
Work experience also showed a positive and significant relationship, suggesting that tenure enhances
awareness and expectation of institutional support.
Education, however, did not demonstrate a statistically significant influence.
Type of bank significantly predicted expectations, confirming structural differences between public and
private sector institutions.
Page 1746
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
The model explained 48% of the variance in work–life expectations, indicating moderate explanatory strength.
3. Demographic Influence on Personal–Life Expectations
The second regression model showed even stronger explanatory power (R² = 0.52) for personal–life
expectations.
Marital status was the strongest predictor, highlighting the centrality of family responsibilities.
Age remained a significant determinant.
Work experience had a positive but comparatively weaker effect.
Education again showed no significant influence.
Type of bank significantly affected personal-life expectations, suggesting institutional context
influences personal time demands.
4. Educational qualification alone does not significantly determine expectation patterns, indicating that structural
and social factors outweigh academic credentials in shaping balance expectations.
Suggestions
Based on the empirical findings, the following policy and managerial recommendations are proposed:
1. Flexible Work Design
Banks, particularly private sector institutions, should introduce structured flexibility mechanisms such as:
Flexible working hours
Compressed work weeks
Hybrid work arrangements
Target-based performance evaluation instead of time-based monitoring
These initiatives can reduce role conflict and improve employee satisfaction.
2. Family-Supportive Policies
Given the strong influence of marital status and family responsibilities:
Childcare support facilities
Extended maternity and parental leave
Emergency leave provisions
Elder-care assistance programs
Should be institutionalized to support women employees across life stages.
3. Career-Stage Based Interventions
Since age and experience significantly influence expectations, banks may implement:
Mentorship programs for mid-career employees
Leadership development opportunities for senior women employees
Career counseling and stress management workshops
Such initiatives can enhance self-management capabilities.
Page 1747
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
4. Sector-Specific HR Strategies
Private sector banks should focus on reducing excessive performance pressure and promoting psychological
well-being, while public sector banks may enhance innovation and flexibility in policy execution.
5. Institutional Support Systems
Organizations should strengthen:
Employee Assistance Programs (EAPs)
Mental health counseling services
Training on time management and self-regulation
Transparent grievance redressal systems
A supportive organizational climate can mitigate stress and improve retention.
CONCLUSION
The study provides empirical evidence that work–life and personal–life expectations among women employees
in the banking sector are significantly influenced by both demographic characteristics and institutional context.
Sectorial differences between public and private banks contribute to distinct expectation patterns, reflecting
variations in workload intensity, policy flexibility, and organizational culture.
Regression findings confirm that age, marital status, work experience, and type of bank are key determinants of
expectation levels, while educational qualification does not significantly predict balance perceptions. Personal-
life expectations appear to be more strongly shaped by demographic variables than work–life expectations.
The results emphasize that achieving sustainable work–life integration requires a dual approach: strengthening
individual self-management capacities and implementing gender-sensitive organizational policies. Institutions
that proactively address these dimensions are more likely to enhance employee well-being, productivity, and
long-term organizational commitment.
Overall, the study contributes to the growing literature on gender and work–life balance by offering a
comparative and predictive perspective within the Indian banking sector. The findings have practical
implications for human resource management, policy formulation, and institutional reform aimed at promoting
equitable and sustainable workplace environments.
REFERENCES
1. Khan, S., Thomas, G., Kunbhar, B. A., & Mohamed, N. H. M. (2022). Impact of work–life balance on
working women in the banking sector. Administrative Sciences, 13(1), 7.
https://doi.org/10.3390/admsci13010007
2. Rajan, A. M., & Rani, R. S. (2024). An empirical study of work–life balance among married women
employees of public and private sector banks in Thiruvananthapuram district. ShodhKosh: Journal of
Visual and Performing Arts, 5(6), 3691–3699.
3. Walia, P. (2020). Work life balance of bank employees: A comparison. Indian Journal of Commerce and
Management Studies.
4. Prathiba, A., & Raja, M. (2023). A study on work life balance of women employees in banking sector with
reference to Thoothukudi. Journal of Research Administration, 5(2), 1689–1699.
5. Nambiar, R. R. (2025). Work-life balance and well-being of women bank employees: A comparative study
of public and private sector banks. Asian Journal of Management and Commerce, 6(1), 1145–1149.
6. Ganapathi, R. (2016). A study on work life balance and job satisfaction of women employees working in
new private sector banks. Journal of Management Research and Analysis, 3(3), 126–130.
Page 1748
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
7. Kumar, V. J., & Sujatha, S. (2023). The impetus of work–life balance on job satisfaction among women
employees in public sector banks in Kerala. International Conference Proceedings.
8. Dhungel, S. (2022). Work life balance among women employees in service sector with special reference
to banking industry in Kathmandu Valley. The Mega Journal.
9. Rajan, A. M., & Rani, R. S. (2024). Impact of work life balance and stress management among women
employees of public sector banks in Thiruvananthapuram district. Frontiers in Health Informatics, 13(5).