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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue IX, September 2025
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“Empowering Indian Women through Entrepreneurship: A Study
on Kolkata”
Urmi Adhikary, Dr. Saurav Ghosh, Dr. Jyotirmoy Koley, WBES
Department of Commerce & Management, Seacom Skills University, Bolpur, West Bengal, India.
DOI: https://doi.org/10.51583/IJLTEMAS.2025.1409000004
Abstract: This study examines the influence of women's entrepreneurship on their empowerment in Kolkata, India. Women
entrepreneurs in Kolkata, particularly those aged 36–45, are making notable strides in establishing and managing their own
enterprises. Most of these entrepreneurs are married and possess technical education, which is essential for their entrepreneurial
activities. The study utilized both primary and secondary data sources, with primary data collected through a structured
questionnaire and personal interviews with 208 women entrepreneurs using convenience sampling. The findings indicate that
factors such as marital status, educational attainment, and training from organizations such as MSME significantly affect
entrepreneurs' perceptions of business growth and success potential. Married women entrepreneurs encounter unique challenges in
balancing family responsibilities with business demands. The study also underscores the substantial potential of women-led
businesses in job creation, with 53.4% of survey participants employing between 5 and 10 individuals. These results highlight the
need for targeted initiatives and programs to promote women's entrepreneurship and foster business growth in Kolkata.
Policymakers, entrepreneurs, and support organizations can leverage these insights to enhance the overall economic environment
of the region through sustained job creation and business development. Recommendations for women entrepreneurs include
developing strong time-management skills, understanding lending options and financial incentives, and accessing technology and
training programs.
Keywords: Women Entrepreneurship Kolkata, Job Creation, Economic Development, factors influencing the perceived growth
of businesses, etc.
1. Introduction:
Entrepreneurs are individuals who can generate innovative ideas for marketing products or delivering services. This cohort makes
strategic decisions to transform innovation into successful enterprises. In Indian society, where entrenched customs often uphold
male dominance, women entrepreneurs must exert considerable effort to attain equal rights, status, and justice. Indian women are
acknowledged for their accomplishments across various domains and have distinguished themselves by surmounting numerous
social challenges. Businesses led by women employ over 27 million individuals, making a substantial contribution to job creation
and economic growth. According to a Bain and Company survey, over 45% of Indian women in rural areas are motivated to initiate
businesses to gain recognition, and start-ups led by women yield a 35% higher return on investment than those managed by men.
Furthermore, a report by the McKinsey Global Institute suggests that providing women with equal opportunities could potentially
increase India's GDP by $770 billion by 2025. Experts have further elucidated that India's GDP could reach $700 billion by 2025
if more women entered the workforce, thereby increasing the economic growth rate from 7.5% to 9%. However, to realize this
potential, India must address the numerous challenges faced by women, such as limited access to education and employment
opportunities, as well as cultural norms that often prioritize domestic responsibilities over paid work.
The Core Concept of Women Entrepreneurship:
This study aims to enhance awareness and comprehend the significance of women's entrepreneurship and its contribution to global
development and sustainable economic growth. We conducted a comprehensive and systematic review of the literature on female
entrepreneurs. This review addresses the primary challenges encountered by Indian women entrepreneurs, their success narratives,
the motivational factors that drive them, and public perceptions across various age groups regarding women entrepreneurs. Despite
women being a pivotal force in India's economic advancement, the nation still faces considerable challenges in achieving gender
equality and empowering the female workforce. These enterprises have created employment opportunities for millions of people,
thereby contributing to economic growth and job creation. Women-led ventures currently employ over 27 million individuals,
highlighting the substantial role that women play in advancing the economy. Women entrepreneurs in India are categorized into
several groups: (a) Tech Entrepreneurs, (b) Social Entrepreneurs, (c) Rural Entrepreneurs, (d) micro-entrepreneurs, (e) Corporate
Entrepreneurs, (f) Start-up Founders, (g) Franchise Owners, and (h) Small and Medium-sized Enterprises. Although women
entrepreneurs can be classified into distinct segments, it is essential to acknowledge that these classifications are not rigid. Many
women may transition between categories as they advance their entrepreneurial pursuits. Collectively, these categories create a
dynamic and diverse landscape of women’s entrepreneurship, showcasing the limitless potential and influence of women in
business.
Overview of Women Entrepreneurship in India:
In the Indian business context, women entrepreneurs are increasingly establishing their presence in diverse economic sectors. They
make substantial contributions to areas such as agriculture, manufacturing, trade, and various services. The five leading economic
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sectors in which women entrepreneurs are notably active include agriculture (34.3%), manufacturing (29.8%), trade (18.23%), other
services (5.38%), and accommodation and food services (2.77%). Globally, women represent 43% of entrepreneurs. With an
emphasis on inclusivity and diversity, women aged between 40 and 59 are at the forefront of entrepreneurial activities. Significantly,
ten women-owned companies achieved unicorn status in the first half of 2019, highlighting the capabilities and potential of Indian
women entrepreneurs. This trend of women's entrepreneurship in India is anticipated to continue its growth trajectory, with
government initiatives and support programs playing a pivotal role in fostering this development. The rise of digital platforms and
e-commerce has further empowered women entrepreneurs by offering them new opportunities to present their products and services
to a broader audience. As more women overcome barriers and achieve business success, they serve as role models and mentors for
the next generation of aspiring female entrepreneurs, thereby creating a positive cycle of empowerment and economic growth.
II. Review of Literature:
The following literature review section presents a synthesis of the most pertinent and recent studies.
Suryavanshi and Iqbal (2024) assert that the growth and success of a nation are intrinsically linked to the socioeconomic
empowerment of its citizens. Microfinance is widely recognized as an effective instrument for socioeconomic development and
poverty alleviation, particularly in disadvantaged and underserved regions. Empowerment of women through microfinance is a
topic of considerable scholarly discussion and analysis, with women identified as the primary beneficiaries. The authors focused
on the impact of microfinance on women's empowerment within our country, acknowledging both the challenges and the positive
and negative evidence associated with this empowerment. By examining the key factors and implications, they underscore the
relationship between microfinance and women's empowerment.
Kumar and Shobana (2023) examined the traditional roles of women and the challenges they encounter in establishing their own
businesses. The socioeconomic context, coupled with policy changes, has facilitated the emergence of women entrepreneurs in
recent years. The involvement of women in the workforce contributes to job creation and enhances the GDP. The societal
significance of women entrepreneurs as role models promotes gender equality and empowers women.
Divekar and Mali (2022) investigated the challenges encountered by women entrepreneurs, with a particular focus on marketing
and sales within Micro and Small Enterprises (MSEs) owned by women. They conducted a systematic review of the marketing
strategies implemented over the past decade in India. Women-led MSEs face numerous challenges, including issues related to
finance, education, family pressure, and male dominance. From a business perspective, marketing is a significant challenge for
women entrepreneurs. A plan is formulated for future research in this area.
Roychoudhury (2022) examined three fundamental dimensions of women's empowerment: educational attainment, labour market
participation, and governance. Education plays a pivotal role in female entrepreneurs' skill development in India. Additionally,
workforce involvement is a critical component of women's empowerment, as women encounter low labour participation rates in
the job market.
Resource-Based View (RBV) analyze how women entrepreneurs’ access and utilize resources, such as microfinance, to build their
businesses and achieve empowerment. RBV emphasizes the importance of resources in achieving competitive advantage and can
be applied to understand how women entrepreneurs leverage resources to overcome challenges.Theories like Kabeer's framework,
emphasizes the importance of agency, resources, and achievements in women's empowerment, can provide a nuanced understanding
of the complex processes involved in women's empowerment. This framework highlights the need for women to have autonomy,
self-belief, and the power to influence decision-making.Oxfam's Conceptual Framework on Women's Economic Empowerment
emphasizes the importance of women's rights to control and benefit from resources, assets, income, and their own time. It also
highlights the need for women to have autonomy and self-belief to make changes in their lives.
To strengthen the paper, several theoretical frameworks can be integrated to provide a deeper understanding of women's
empowerment and entrepreneurship.
Objectives of the Study:
The objective of this study is to investigate the influence of women's entrepreneurship on women’s empowerment in Kolkata.
III. Research Methodology:
This empirical study has utilized both primary and secondary data sources. Primary data have been collected through a structured
questionnaire, while secondary data have been obtained from various articles, journals, and research publications. The research has
been conducted in the district of Kolkata. The structured questionnaire has been distributed, and personal interviews have been
conducted with women entrepreneurs using the convenience sampling technique. In total, 208 respondents completed the
questionnaire. The survey has been conducted between November 2024 to December 2024. The frequency tables, simple
percentages, and statistical tools such as the chi-square test and independent sample t-test have been employed to analyse the data,
with the assistance of the SPSS package (version 26), to derive logical conclusions.
Limitations of Convenience Sampling
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Convenience sampling may introduce sampling bias, as the sample may not be representative of the larger population of women
entrepreneurs in Kolkata. Due to the non-probability nature of convenience sampling, the results may not be generalizable to the
entire population of women entrepreneurs in Kolkata. Potential for Selection Bias: The sample may be biased towards women
entrepreneurs who are more accessible or willing to participate in the study. Rationale for Choosing Convenience Sampling was
chosen due to time and resource constraints, allowing for a more feasible and efficient data collection process. The study aims to
explore the experiences and challenges faced by women entrepreneurs in Kolkata, and convenience sampling provides a suitable
approach for this purpose. Due to the limitations of convenience sampling, the results has been interpreted with caution and not
overgeneralized to the entire population of women entrepreneurs in Kolkata. Future studies have been consider employing more
robust sampling methods, such as probability sampling, to increase the generalizability of the results.
By acknowledging the limitations of convenience sampling and cautioning against overgeneralizing the results, this study provides
a more nuanced understanding of its findings and contributes to the existing body of research on women entrepreneurship in
Kolkata.
Formulation of Hypothesis:
Three sets of hypotheses have been formulated to achieve the research objectives. They are as follows:
Hypothesis-1
H0: There is no association between marital status and balancing family life with the business of entrepreneurs.
H1: There is an association between marital status and balancing family life with the business of entrepreneurs.
Hypothesis-2
H0: There is no relation between education and the perceived growth of the business of entrepreneurs.
H1: There is a relation between education and the perceived growth of the business of entrepreneurs.
Hypothesis-3
H0: There is no difference between the average of the perceived growth of business and the training received by entrepreneurs.
H1: There is a difference between the average of the perceived growth of business and the training received by entrepreneurs.
Data Analysis and Discussion:
The primary data collected from the field survey have been analysed and discussed below. The analysis reveals several key trends
in the surveyed population. Demographic factors such as age, education level, and income appeared to have significant correlations
with the observed behaviours. These findings provide valuable insights into a community's needs and preferences, which can inform
future policy decisions and interventions.
Location of Respondents:
Table-1 Location of Respondents
Location Frequency Percent
Kolkata Main 119 57.5
North Kolkata 23 15.9
South Kolkata 66 26.6
Total 208 100.0
(Source: Field Survey)
Observation: Table 1 above shows that 57.5 % of the surveyed respondents are from Kolkata main,15.9 % of the surveyed
respondents are from north Kolkata & 26.6 % are from south Kolkata.
Marital Status of Respondents:
Table-2 Marital Status of Respondents
Marital status Frequency Percent
Married 139 66.8
Unmarried 42 20.2
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Divorced 27 13.0
Total 208 100
(Source: Field Survey)
Observation: The above table 2 shows that 66.8 % of the surveyed respondents are married, 20.2 % are unmarried 13% are
divorced.
Age Group of the Respondents:
Table-3 Age Group of Respondents
Age Frequency Percent
Below 25 Yrs 0 0
25-35 Yrs 22 10.6
35-45 Yrs 132 63.5
45-55 Yrs 54 14.8
Above 55 Yrs 0 0
Total 208 100.0
(Source: Field Survey)
Observation: In the above table 3, it has been found that 63.5% of the surveyed respondents are in the age group between 36- 45
years, 14.8 % of the surveyed respondents are in the age group between 46-55 years, and 10.6% are in the age group between 26-
35 years.
Education of the Respondents:
Table-4 Education of Respondents
Education Frequency Percent
Below Graduation 16 7.7
Graduation 46 22.1
Post Graduation 57 27.4
Technical 89 42.8
Total 208 100.0
(Source: Field Survey)
Observation: Table 4 above shows that 42.8 % of the surveyed respondents are Technical, 27.4 % of the surveyed respondents are
Post Graduate, 22.1 % are Graduate, and 7.7% are below Graduation level.
Balancing Family Life with Business:
Table-5 Balancing Family Life with Business
Life Balance Frequency Percent
Yes 146 70.2
No 62 29.8
Total 208 100.0
(Source: Field Survey)
Observation: Table 5 above, it has been seen that 70.2 % of the surveyed respondents can balance business with family life,
whereas 29.8% of the surveyed respondents are unable to do so.
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Perceived Success in Business
Table-6 Perceived Success in Business
Perceived Success in Business Frequency Percent
Highly Successful 85 40.9
Moderately successful 123 59.1
Struggling for Existence 0 0
Complete Failure 0 0
Total 208 100.0
(Source: Field Survey)
Observation: Table 6 above shows that 59.1 % of the surveyed respondents are moderately successful, whereas 40.9% are highly
successful.
Perceived Growth of Business Over Past Years
Table-7 Perceived Growth of Business in Past Years
Perceived Growth of Business Frequency Percent
Very low 20 9.6
Low 30 14.4
Moderate 50 24.0
High 60 28.8
Very High 48 23.1
Total 208 100.0
(Source: Field Survey)
Observation: Table 7 states that out of 208 surveyed respondents, 28.8% perceived growth of business as high, 24.0% as moderate,
23.1% as Very High, 14.4% as low, and 9.6% as Very Low. These percentages indicate the individual proportion of entrepreneurs
who perceive their business growth at different levels.
Training Received by Entrepreneurs from MSME- DI
Table-8 Training Received by Entrepreneurs
MSME- DI Training Received Frequency Percent
Yes 55 26.4
No 153 73.6
Total 208 100.0
(Source: Field Survey)
Observation: Table 8 above, it has been observed that 73.6 % of the surveyed respondents did not receive MSME DI Training,
whereas 26.4% of the respondents received MSME DI Training.
Business Experience:
Table-9 Business Experience
Business Experience Frequency Percent
More than 5 years 104 50.0
Less than 5 years 104 50.0
Total 208 100.0
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(Source: Field Survey)
Observation: From Table 9, it can be observed that women entrepreneurs' business experience is divided into two categories:
50.0% have less than five years of experience, and 50.0% have more than five years of experience. The percentages show an equal
split, with 50.0% in each category, indicating a balanced distribution of business experience.
Employment Generation:
Table-10 Employment Generation
No of Employees Frequency Percent
1-5 77 37.0
5-10 111 53.4
10-20 14 6.7
Above 20 6 2.9
Total 208 100.0
(Source: Field Survey)
Observation: From table 10 above, it has been observed that 53.4 % of the surveyed respondents employed 5-10 employees, 37%
employed 1-5, .6.7 % of the respondents employed 10 to 20 employees, and 2.9 % of the surveyed respondents employed more
than 20 employees.
Hypothesis Testing:
Chi-Square Test: The chi-squared test is a statistical method employed to ascertain whether a significant association exists between
two categorical variables. This evaluates the discrepancy between the observed and expected frequencies. In this context, the test
is used to examine the potential association between marital status (a categorical variable) and the ability to balance family life with
business responsibilities (another categorical variable). The null hypothesis (H0) posits the absence of an association, while the
alternative hypothesis (H1) suggests the presence of an association. The Chi-Square test facilitates the decision on whether to reject
H0.
Hypothesis-1
H0: There is no association between marital status and balancing family life with the business of entrepreneurs.
H1: There is an association between marital status and balancing family life with the business of entrepreneurs.
Table-11
Cross Tabulation Between Marital Status and Balancing Family Life with the Business of Entrepreneurs
Balancing Family with the Business
Total Yes No
Marital
Status
Married Number 86 53 139
% of Total 41.3% 25.5% 66.8%
Unmarried Number 39 3 42
% of Total 18.8% 1.4% 20.2%
Divorced Number 21 6 27
% of Total 10.1% 2.9% 13.0%
Total Number 146 62 208
% of Total 70.2% 29.8% 100.0%
(Source: Compiled by Researchers)
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Table-12
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 15.655 2 0.000
Likelihood Ratio 18.434 2 0.000
Linear-by-Linear Association 8.343 1 0.004
No of Valid Cases 208
(Source: Compiled by Researchers)
Interpretation: The Pearson Chi-Square p-value is 0.000, indicating statistical significance at the 5% level (p-value < 0.05). This
result demonstrated a statistically significant association between marital status and the ability to balance family life with business
responsibilities. The findings suggest that entrepreneurs' marital status is related to their capacity to effectively manage family and
business obligations. The statistical significance of this association leads to the rejection of the null hypothesis (H0) and acceptance
of the alternative hypothesis (H1), which posits a relationship between marital status and balancing family life with business. These
findings imply that marital status influences entrepreneurs' ability to balance family and business responsibilities. This association
has implications for entrepreneurship support programs and policies, providing valuable insights for entrepreneurs, policymakers,
and support organizations to better understand the relationship between marital status and entrepreneurial success.
Hypothesis-2
H0: There is no relation between education and the perceived growth of business of entrepreneurs.
H1: There is a relation between education and the perceived growth of business of entrepreneurs.
Table-13 Cross-tabulation between Education and the Perceived Growth of Business
Perceived Growth of Business Over the Past Year
Total Very Low Low Moderate High Very High
Education
Level
Below
Graduation
Number 10 1 2 1 2 16
% of Total 4.8% 0.5% 1.0% 0.5% 1.0% 7.7%
Graduation Number 10 11 6 9 10 46
% of Total 4.8% 5.3% 2.9% 4.3% 4.8% 22.1%
Technical Number 0 18 20 32 19 89
% of Total 0.0% 8.7% 9.6% 15.4% 9.1% 42.8%
Post
Graduation
Number 0 0 22 18 17 57
% of Total 0.0% 0.0% 10.6% 8.7% 8.2% 27.4%
Total Number 20 30 50 60 48 208
% of Total 9.6% 14.4% 24.0% 28.8% 23.1% 100.0%
(Source: Compiled by Researchers)
Table-14
Chi-Square Tests
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 97.800 12 0.000
Likelihood Ratio 92.985 12 0.000
Linear-by-Linear Association 34.478 1 0.000
No of Valid Cases 208
(Source: Compiled by Researchers)
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The perceived growth of business was measured on a 5-point scale, with the follow incategories:
Very Low: 1
Low: 2
Moderate: 3
High: 4
Very High: 5
This scale is similar to a Likert scale, which is commonly used in surveys to measure attitudes or perceptions. In this case, the scale
was used to assess the entrepreneurs' perceived growth of their business over the past year. The respondents were likely asked to
select one of the five option that best reflected their perception of their business growth. The use of this scale allowed the researchers
to quantify the perceived growth and analyse its relationship with other variables, such as educational level. The results of the cross-
tabulation analysis showed a significant association between educational level and perceived business growth, with entrepreneurs
having higher education levels (Technical and Postgraduate qualifications) reporting higher perceived business growth.
Interpretation: The Pearson Chi-Square p-value is 0.000, indicating statistical significance at the 5% level (p-value < 0.05). Cross-
tabulation analysis demonstrated a significant association between educational level and perceived business growth. Entrepreneurs
with higher education levels, such as Technical and Postgraduate qualifications, exhibit a higher perceived business growth.
Specifically, a substantial proportion of entrepreneurs with technical education (42.8%) reported moderate-to-high perceived
business growth. Similarly, 27.4% of entrepreneurs with a postgraduate education reported high perceived business growth.
Conversely, entrepreneurs with educational levels below graduation (7.7%) reported low perceived business growth. This analysis
suggests that educational level is a significant determinant of perceived business growth. These findings have implications for
policymakers and educators, emphasizing the need to promote entrepreneurship education and training programs. Overall, this
study underscores the critical role of education in fostering business growth and success.
Independent Sample t-Test: The Independent Samples t-Test is a statistical method employed to compare the means of two distinct
groups. This test is utilized to ascertain whether there is a statistically significant difference between the means of these two
independent groups. In this context, it is applied to evaluate the means of perceived business growth and training received by
entrepreneurs. The objective of the test is to determine whether a significant difference exists between the two groups. It is used to
test the null hypothesis (H0), which posits no difference between the groups, against the alternative hypothesis (H1), which suggests
a difference. The test assumes independence of the two groups and that the data follow a normal distribution. The independent-
samples t-test yields a t-value, p-value, and mean difference, which are instrumental in assessing the significance of the observed
difference. This analysis helps determine whether the training received by entrepreneurs significantly influences the perceived
growth of their businesses.
Hypothesis-3
H0: There is no difference between the average of the perceived growth of business and the training received by entrepreneurs.
H1: There is a difference between the average of the perceived growth of business and the training received by entrepreneurs.
Table-15
Group Statistics
N Mean
Std.
Deviation
Std. Error
Mean
Got Training from MSME or Other Institution Yes 55 1.8909 0.97511 0.13148
Perceived Growth of Business Over the Past Year No 153 3.9608 0.81823 0.06615
(Source: Compiled by Researchers)
Table-16
Independent Samples Test
t-test for Equality of Means
t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval
of the Difference
Lower Upper
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(Source: Compiled by Researchers)
Interpretation: The table above indicates that the p-value is 0.000, which is significant at the 5% level of significance (p-value <
0.05). The results of the independent-samples t-test revealed a statistically significant difference between the means of perceived
business growth for entrepreneurs who received training (YES) and those who did not (NO). Specifically, the mean perceived
business growth for entrepreneurs who received training is 1.8909, which is significantly lower than the mean perceived growth for
those who did not receive training (3.9608). The difference between the two means is -2.06988, suggesting that entrepreneurs who
received training perceive lower business growth. The 95% Confidence Interval of the difference (-2.33710, -1.80265) does not
encompass zero, further indicating a significant difference. These findings imply that receiving training from the MSME or other
institutions significantly impacts entrepreneurs' perceived business growth. However, the direction of this relationship is contrary
to expectations, as entrepreneurs who received training reported lower perceived growth. Consequently, the null hypothesis (H0)
is rejected, demonstrating a significant difference in the average perceived business growth between entrepreneurs who received
training and those who did not.
IV. Findings of the Study:
i. The data indicates that most respondents, 57.5%, are from Kolkata Main, showing a strong central presence. North Kolkata has
15.9% of respondents, while South Kolkata comprises 26.6%. This distribution indicates a somewhat uneven spread throughout the
city. The significant presence of Kolkata Main may stem from its central location and its accessibility. Respondents are bold and
vocal about their business opinions. (Table 1)
ii. The data reveals that 66.8% of those surveyed are married, 20.2% are unmarried, and 13% are divorced. This suggests that
married women are more engaged in achieving economic independence than are others. (Table 2)
iii. The data shows that 63.5% of respondents fall within the 36-45 age range, 14.8% are aged 46-55, and 10.6% are between 26-
35 years old. Compared to other age groups, women aged 36-45 appear to be the most active in starting and maintaining businesses.
(Table 3)
iv. The data indicates that 42.8% of respondents are in technical fields, 27.4% are postgraduates, 22.1% are graduates, and 7.7%
have education below graduation level. Many women entrepreneurs in Kolkata possess technical education to enhance their business
skills and generate profits. (Table 4)
v. The data show that most respondents can effectively balance their business and family lives, reflecting strong time management
and prioritization abilities. The survey found that married business owners (75%) are more likely than single owners (40%) to report
difficulties in managing work and family responsibilities. This suggests that an entrepreneur's ability to handle family and business
commitments may be influenced by marital status.
vi Future studies can investigate why there is a notable difference in how entrepreneurs view their business growth based on whether
they receive training or not. Data indicates that a significant number of respondents (28.8%) see substantial growth in their
businesses, reflecting a positive perspective and potential for growth. 59.1% of those surveyed are moderately successful, while
40.9% are highly successful. (Table 7)
vii. Data reveals that the business experience of women entrepreneurs is categorized into two groups: 50.0% have less than 5 years
of experience, and 50.0% have more than 5 years. This shows an equal distribution of experiences among them.
viii. The data show that 53.4% of respondents employ 5-10 employees, 37.0% employ 1-5, 6.7% employ 10-20, and 2.9% employ
more than 20 employees. This finding indicates that women's entrepreneurship contributes to job creation. (Table 10)
ix. Unmarried and divorced entrepreneurs may need less assistance in managing family and business duties, while married
entrepreneurs may need more support and resources to balance these responsibilities. Policymakers and organizations can create
programs to assist entrepreneurs based on their marital status.
x. Entrepreneurs with higher education (technical and postgraduate) are more likely to perceive greater business growth.
Policymakers and educational institutions should develop programs that enhance entrepreneurial skills and knowledge, especially
for those with lower educational levels. Entrepreneurs with a lower education (below graduation and graduation) may need extra
support and resources to boost their business growth.
xi. Entrepreneurs receiving training from the MSME or other institutions may not always experience higher growth in their
businesses.
Perceived
Growth
of
Business
Over the
Past Year
Equal variances
assumed
-15.271 206 0.000 -2.06988 0.13554 -2.33710 -1.80265
Equal variances
not assumed
-14.063 82.909 0.000 -2.06988 0.14719 -2.36263 -1.77712
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Challenges Faced by Married Women
Married women, comprising 66.8% of the respondents, are more likely to face difficulties in balancing work and family
responsibilities, with 75% reporting challenges compared to 40% of single owners. This can be attributed to societal expectations
and traditional roles where women are expected to be primary caregivers and homemakers, leading to a "double shift" phenomenon.
This finding is consistent with existing literature, which suggests that women often bear the brunt of domestic responsibilities,
making it challenging to balance work and family life.
Role of Technical Education
Technical education plays a significant role in aiding business growth, with 42.8% of respondents having a technical background.
This can be linked to the fact that technical education provides women entrepreneurs with the necessary skills and knowledge to
enhance their business operations and generate profits. Studies have shown that technical education can equip entrepreneurs with
the skills to innovate and adapt to changing business environments.
Impact of Training on Business Growth
The study finds that entrepreneurs receiving training from institutions like MSME may not always experience higher growth in
their businesses. One plausible explanation is that training programs may not always be tailored to the specific needs of women
entrepreneurs, or the training may not be effectively implemented. Additionally, the perceived growth may be influenced by various
factors, including the entrepreneur's prior experience, business model, and market conditions.
Job Creation and Entrepreneurship
The study highlights the contribution of women entrepreneurship to job creation, with 53.4% of respondents employing 5-10
employees and 37.0% employing 1-5 employees. This finding underscores the importance of supporting women entrepreneurs in
their business ventures.
Recommendations
Based on the study's findings, policymakers and organizations can create programs to assist entrepreneurs based on their marital
status, providing more support and resources to married entrepreneurs to balance their work and family responsibilities.
Additionally, educational institutions can develop programs that enhance entrepreneurial skills and knowledge, especially for those
with lower educational levels.
Future Research Directions
Future studies can investigate the reasons behind the notable difference in how entrepreneurs view their business growth based on
whether they receive training or not. Understanding the factors influencing perceived growth can help tailor training programs to
better support women entrepreneur
V. Conclusion:
Women entrepreneurs in Kolkata, particularly those aged 36–45, demonstrate notable advancements in establishing and managing
their own enterprises. This demographic of female entrepreneurs is predominantly married and possesses a technical education,
which is crucial for their entrepreneurial endeavours. The findings of the study indicate that factors such as marital status,
educational attainment, and training from organizations such as MSME significantly influence entrepreneurs' perceptions of
business growth and success potential. Furthermore, this research underscores the critical necessity for these entrepreneurs to
balance familial responsibilities with the demands of business management. In particular, married female entrepreneurs encounter
various challenges in this balancing act, where the pressures of domestic and business obligations can create distinct obstacles. The
study also reveals the substantial potential of women-led businesses in job creation, with 53.4% of survey participants reporting
employment of between 5 and 10 individuals in their enterprises. These insights and findings are of considerable importance to
various stakeholders, including policymakers, entrepreneurs, and organizations that provide training and support for prospective
business owners. There is a clear imperative for targeted initiatives and programmes aimed at promoting women's entrepreneurship
and fostering business growth in Kolkata. By doing so, it is possible not only to support these women in their endeavours but also
to enhance the overall economic environment of the region through sustained job creation and business development.
Suggestions:
i. Besides being mothers, wives, and daughters-in-law, female entrepreneurs also have other duties to manage. To meet their
responsibilities, women entrepreneurs must choose the type of business they wish to operate.
ii. Women should possess strong time-management abilities. Using technology, they can effectively balance their personal and
work lives.
iii. The effectiveness and limitations of government programs and policies should be evaluated regularly.
iv. Understanding lending options, financial incentives, and subsidies is crucial for female entrepreneurs.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue IX, September 2025
www.ijltemas.in Page 38
v. Financial institutions must improve their awareness of the various programs and credit financing options available.
vi. Therefore, the loan process must be fair. Increasing the loan amount has made it easier for women-owned businesses to secure
loans, which has been helpful. Consequently, many women want to start and run their own businesses.
vii. The government should offer training programs to assist female entrepreneurs in areas such as sales and innovative production.
Women entrepreneurs are required to complete this training.
viii. Analysing all the various issues leads to the conclusion that, as people's tastes and preferences evolve and technology must
also adapt, women entrepreneurs need to be more informed about and have access to technology.
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