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The Impact of Technology on Work Life Balances with Reference to
Female Workers, Especially Team Leaders from Selected Garments in
Ampara District
S.M.I. Jahan
1*
, E.G Shehan Sandaruwan
2
1
Department of Interdisciplinary Studies, Faculty of Engineering, South Eastern University of Sri
Lanka
2
Department of Human Resource Management, Faculty of Management, University of Peradeniya Sri
Lanka
*Corresponding Author
DOI:
https://dx.doi.org/10.47772/IJRISS.2025.910000595
Received: 26 October 2025; Accepted: 04 November 2025; Published: 19 November 2025
ABSTRACT
In today's digital age, technology plays an essential role in work practices and employee well-being, especially
in dynamic and stressful industries such as the apparel sector. This research examines the impact of new
technologiesthe Internet of Things (IoT), cloud computing, 3D printing, automation facilities, and big data
analyticson work-life balance (WLB) of female team leaders from selected garment factories in Ampara
District, Sri Lanka. Sample size 86 was selected from the population through random sampling. The data was
collected through structured questionnaires and analyzed using SPSS using reliability tests, descriptive
statistics and regression analysis. Results showed that IoT, cloud computing, automation facilities, and big data
analytics positively and significantly affected work-life balance, whereas 3D printing was the only technology
not positively and significantly related in this case. Regression analysis showed that new technologies
explained 61.9% of the variance accounted for WLB with IoT being the strongest predictor. In summary, these
results highlight the importance of increased use of advanced technologies in the apparel sector which can
enhance flexibility, provide support to stress, and enhance well-being. 3D printing cannot negatively affect
WLB, however, as the use of 3D printing is not sufficiently utilized in operations. The study is an important
contribution to the knowledge gaps regarding technology's contribution to maintaining a work life balance,
specifically female workers in Sri Lanka's apparel industry. The study recommends that organizations focus on
IoT, cloud computing, automation, big data analytics, and in the future: 3D printing as means of enhancing
retention and satisfaction.
Keywords: Apparel sector, Technology, and work life balance
INTRODUCTION
In the fast-changing digital environment of today, technology has become a vital aspect of human life, altering
the way we work, communicate, and engage socially. Technology's influence on work-life integration is one of
its most significant effects. Work-life balance is raising concern among employees and employers in the
apparel industry, ultimately for three reasons: women's involvement in the workplace, nuclear families, and the
dual-working concept, all contributing to an imbalance in work and family obligations due to dynamic work-
culture and lifestyle changes. Work-life balance has become a strategic concern for HR management and a
significant underpinning of employee retention strategy.
This research paper looks at the relationship between technology, which encompasses personal computers,
mobile phones, and other elements of information and communication technology (ICT) on employees work-
life balance. Although many different policies and flexible scheduling were introduced, an increased workload,
and work performance, which demands much of their job led to work-life imbalance. Therefore, advancement
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in technologies can provide support to the employees to have a healthy workplace but it can also discourage
employees from taking advantage of those options offered. (Coggin, 2012) concluded that the researcher
evidenced greater use of technological applications in the apparel industries which also facilitate them to work
at home, and not just the opportunity to work at home. Most of the organizations in the apparel sector in Sri
Lanka were able to work from home during the uprising of COVID-19 pandemic as they have been advancing
their technology. However, the current discovery contradicts some previous research that indicated a weak
relationship proposed between Work-related technologies and WLB.
Problem Statement
Information and communication technology has become a key ingredient in many countries? Science and
technology development and, as a result, there is a greater demand for them globally. Major industry players
are finding it increasingly difficult to keep pace with the worldwide demand and technology. This opens up Sri
Lanka to become a world ICT destination of choice, being able to cope with this growing worldwide demand.
Therefore, Lakshani, (2020) concluded that a strong positive relationship exists between Work-related
technology usage on WLB by generation y employees: evidences from executive level employees in the Sri
Lankan apparel industry. Stokes (2019) also indicated a statistically significant relationship between
technology tools used for work and life tasks, and technology-assisted supplemental work during the workday.
The findings presented in this paper, indicate some inconsistency with some previously published findings that
point to a weak relationship between technologies and WLB (Coggin, 2012).
In addition to this, (Hubbard, 2016) stated that Fifty-seven percent of participants indicated that they perceive
an imbalance between work and life due to ICTs while 61% indicated that they believe ICTs help to facilitate
the work-life balance. These percentages came from the descriptive statistics of the composite score which was
developed from the survey items asking about work-life balance and also instructional faculty perceptions of
work-life balance were approximately normally distributed with a slight negative skew. The slight negative
skew of instructional faculty perceptions toward work life balance, as indicated in the research, might have a
couple underlying reasons. Research performed by (Postman, 1982) has indicated that in the contemporary age
technology plays a significant role in obtaining a work-life balance. In this Apparel industry that is providing
direct employment to over 300,000 workers in Sri Lanka (Export Development Board, 2021). As indicated by
Rajapakshe (2018), the apparel industry employs about 15% of the workforce and female workers account for
85% of the workforce. Even though apparel has a lot of advantages, the industry faces many challenges; one of
these is dealing with the problem of high employee turnover.
In addition, most of the studies divulged possible reasons for the identified factors that affect work-life balance
without reference to gender. Meanwhile, Sri Lankan apparel sector, usually cited for WLB inconsistencies
(Embuldeniya, 2015; Dissanayake & Ali, 2013) was considered an appropriate context to explore the identified
research gap. Research outcomes would shed some light on the influences of technology on work life balance
with reference to women workers, specifically team leaders from selected garments in the Ampara District.
Research Questions
1. What is the effect of internet of things (IoT) on work life balance?
2. What is the effect of cloud computing on work life balance?
3. What is the effect of 3D printing on work life balance?
4. What is the effect of automation tools on work life balance?
5. What is the effect of big data analytics on work life balance?
Research Objectives
The main objective is based on the impact of technology on work life balance with reference to female
workers, especially team leaders from selected garments in Ampara District.
1. To study the level of technology and work life balance in apparel sector?
2. Identify the relationship and effect of the technology on work life balance in the apparel sector.
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LITERATURE REVIEW
Work Life Balance
Work-life balance is defined as "the degree to which an individual is engaged in - and satisfied with - his or her
work role and family role, both of which are equally important" (Greenhaus, Collins, & Shaw, 2003). Work-
life conflict occurs when work and life are incompatible, such that work-related behaviours impede time with
family and time with the family interferes with work (Harris, Harris, and Marrett, 2011). There are various
forms of the term, such as work-family conflict and work-family balance that more specifically refer to how an
individual' family and work lives interact. Overall, the focus of this work is to study the personal lives of
employees in general.
Internet of things (IoT)
The application of IoT technology in the industrial value chain sets the stage for Industry 4.0. IoT is a
comprehensive ecosystem of tools and services that must work cooperatively to provide a complete
proposition. IoT has much potential and possible benefits in the textile and fashion retail industry; it allows
more insights into customer needs and wants, better product assortment choices, better recommendations,
better design (patterns, shapes, etc.), innovation, and more, which leads to new business risks and opportunities
that need to be managed and governed appropriately (Chen, 2021).
Cloud Computing
Cloud computing has the potential to reduce IT operations and management costs (Damodaram, 2010). Cloud
computing is a relatively new kind of internet technology that uses remote servers for data storage and
computing. It offers resources, software products, and information on-demand to different devices and
optimizes energy consumption (Ionescu, 2015).
3D Printing
3D printing is a process of producing three-dimensional objects created by laying down successive layers of
material according to a computer-generated design. In garment factories, this will be used to build up layers of
materials to create a three-dimensional part of a garment. When 3D printing is used in garment production, you
can test the quality and performance measure of the product before committing to mass production which
saves excess expense and waste (Percival, 2010). 3D printing is a capital and technology-intensive process
which relies on little low-skilled labour, so for the future of apparel production, developed economies may
have a productive advantage (Vanderploeg, 2017).
Automation
The current applications of this technology is in stitching automotive interiors, but it can subsequently be
incorporated into clothing and other fabric products to produce higher quality products, gain a competitive
edge, and decrease labour expenses (Chowdhury, 2020). In several aspects, the automation technologies are
superior to human operators in efficiency, accuracy, affordability, and trustworthiness, and remains to be seen
whether they take away the majority of human operators. Automation has fully exchanged human operators in
some systems and partially in others, however the terminologies of completely exchanging with a human
operator are at odds with appearances for number operating level and additional value level in garment
factories (Akhtar, 2022).
Big data analytics
Big data analytics is a technology that allows the collection, manipulation, and analysis of vast amounts of
varied data over the supply chain to produce knowledge and information (Rad, Oghazi, Palmié, Pashkevich,
Patel, & Sattari, 2022). In daily operations, the apparel industry predominantly uses big data analytics to make
important corporate decisions with customers, clients, and leaders (Nithya, Kusuma, & Muragaiah, 2022).
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METHODOLOGY
The study's goal is to evaluate the influence of technology on work life balance regarding female workers,
mostly team leaders from selected garments in the Ampara district. The researcher carefully selected a sample
of 86 female team leaders from a population of 104 in the selected garments in Ampara district, Sri Lanka. The
samples were randomly selected and the sample size was determined by using Krejcie and Morgan table. The
respondents had a good grasp of the study's purpose and were asked to respond to qualitative questions to
collect data. In summary, the study aims to examine technology impacts on work life balance. The results of
this study provide many valuable insights to support work life balance in working environment.
CONCEPTUAL FRAMEWORK
Starting point of the survey altogether 92 questionnaires was given among that only 86 was properly filled and
returned. This study therefore, intends to focus on 86 different age groups. The self-administered questionnaire
each respondent examined included closed-ended questions using a Likert scale from zero to one. We asked
each research planner potential subject to statistically analyze our data using SPSS. A literature reviewed based
on hypothetico-deductive method resulted in following alternative hypotheses being operationalized, like
Cohen (2013) regression analysis.
Figure 1: Conceptual Model
H1a: There is an impact between internet of things (IoT) and work life balance.
H2a: There is an impact between cloud computing and work life balance.
H3a: There is an impact between 3D Printing and work life balance.
H4a: There is an impact between automation tools and work life balance.
H5a: There is an impact between big data analytics and work life balance.
Data Analysis and Results
Reliability Analysis
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Table I: Reliability Analysis
Cronbach's Alpha for technology rated high overall above 0.7, thus it is highly acceptable. As the obtained
Cronbach's Alpha is considered high, permission to delete items is zero. In other words, the tool used by this
study has achieved the acceptable internal consistency desired and stable for all statistical variables.
Sample Profile
Descriptive statistical analysis was run on respondents’ demographic variables. The results are shown in the
table.
Table Ii: Sample Profile
Demographic Variable
frequency
(%)
Marital Status
Married
32
37.2
Unmarried
54
62.8
Age Group
Below 35
63
73.3
35 and Above
23
26.7
Education
Ordinary level
33
38.4
Advanced level
10
11.6
Diploma
43
50.0
Experience
1 to 5 Years
67
77.9
Less than 1Year
19
22.1
Among 86 respondents, everyone identified as female--the respondents had an entirely homogeneous
demographic profile. With respect to marital status, while the majority of respondents were unmarried (54
respondents), there were also 32 who stated they were married. We note that 73.3% of respondents were less
than 35 years old and 26.7% were at least 35 years old. In terms of education, 38.4% of respondents had
completed education at the ordinary level, while only 50.0% of respondents had completed education at the
diploma level, 11.6% of respondents had completed education at an advanced level. In terms of work
experience, the highest number of respondents, which was 67 respondents, had 1 to 5 years of experience, with
19 respondents stating they had less than a year of experience.
Univariate Analyses
Table Iii: Univariate Analyses
N
Mean
Std. Deviation
Internet of Things
86
3.71
.749
Cloud Computing
86
3.60
.783
3D Printing
86
3.83
.712
Variables
Cronbach’s Alpha
Items
internet of things (IoT)
cloud computing
3D Printing
automation tools
data analytics
Work Life Balance
0.765
0.787
0.783
0.781
0.767
0.804
4
4
5
4
5
10
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Automation Tools
86
3.82
.794
Data Analytics
86
3.60
.783
Work Life Balance
86
3.77
.452
Valid N (listwise)
86
This provides a summary of results of descriptive statistics of research variables, mean, standard deviation of
dependent and independent variable. All of only research variables has been found high level mean value.
Regression Analysis
Regression analysis is a quantitative statistical analytical technique used to assess relationships between a
dependent variable and one or more independent variables. In this study, the predictive variables were internet
of things, cloud computing, 3D printing, automation tools, data analytics and the outcome variable was the
work life balance.
Table Iv: Model Summary Of The Regression
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.787
a
.619
.595
.287
The R value was 0.787, which means there is a strong positive relationship between the dependent variable and
the independent variable. Additionally, the R-square value was 0.619, which means that 61.9% of the variation
in Work Life Balance can be described by Internet of Things, Automation Tools, Cloud Computing, 3D
printing, and Data Analytics.
Table V: Anova
The p-value from ANOVA table is less than 0.001, which means that at least one of the five variables depends
on Work Life Balance.
Table Vi: Coefficient Regression
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
10.731
5
2.146
26.011
.000
b
Residual
6.601
80
.083
Total
17.332
85
Coefficients
a
Model
Unstandardized Coefficients
t
Sig.
B
Std. Error
1
(Constant)
1.807
.187
9.647
.000
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The equation: Work Life Balance = 1.807+ 0.493(Internet of Things) + 0.343(Cloud Computing) + 0.116(3D
Printing) + 0.253(Automation Tools) + 0.129(Data Analytics)
Therefore, with every unit increase in the internet of things, the work life balance will increase by 0.493, with
all the other variables held constant. For every unit increase in cloud computing, the work life balance increase
will increase by 0.343, with all the other variables held constant. And for every unit increase in 3D printing,
the work life balance will increase by 0.116, with all the other variables held constant. Similarly, for every unit
increase in automation tools, the work life balance will increase by 0.253. And also for every unit increase in
data analytics, the work life balance will increase by 0.129, with all the other variables held constant. In
addition, the coefficient results shows that the Internet of Things, Cloud computing, Automation Tools, and
Data Analytics are positive significant influence over the apparel sector females team leader work life balance
in Ampara district. This is consistent with results from (Alcácer. & Cruz-Machado, 2019), and it shows
automated systems that add value to the different stages of processes do so in a way to provide more flexible
working and increase efficiency within the manufacturing sector. However, 3D printing is not significant in
predicting the work life balance in Ampara district.
CONCLUSION
It has been found in this research that the collective factors all have a strong relationship to work life balance.
The findings of this research could be used to improve the understanding of the relationship between the
context of advanced technological tools and work-life balance - for female team leaders in the apparel sector in
Ampara district in particular. All forms of advanced technological tools had a significant and positive effect on
work-life balance; these included the Internet of Things (IoT), cloud computing, automation tools, and data
analytics. The IoT was overall the most significant theoretically, which demonstrated to be a major contributor
to effective and flexible workflows. Cloud computing and automation tools significantly enhance operations,
efficiency and primarily reduce stress relating to work life balance.
Interestingly, the study found that 3D printing, although becoming an increasingly relevant technology in the
industry, does not have a significant relationship with work-life balance in this sector. This indicates that its
use may be limited or not fully utilized in the work processes of the apparel industry in the Ampara district.
The findings suggest that the apparel industry should focus on developing strategic emerging technologies
before considering the use of 3D printing to increase value; advancements in work-life balance will improve
employee satisfaction, efficiency, and the overall well-being of employees. Additionally, to build value in the
apparel sector, organizations should concentrate on using IoT, cloud computing, automation tools, and data
analytics; whereas 3D printing can be explored as a possible way to add value to the overall industry after
adopting these other technologies. However, the study only examines some of the technologies used by the
industry, and it is also recommended that further studies investigate the use of other relevant technologies in
the industry and the service sectors.
REFERENCES
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3.392
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Cloud Computing
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2.836
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3D Printing
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2.534
.015
Automation Tools
.253
.064
3.977
.000
Data Analytics
.129
.049
2.613
.000
a. Dependent Variable: Work Life Balance
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