A Study on the Factors Influence Women Entrepreneurs in Tiruchirappalli District

International Journal of Advanced Scientific Research & Development (IJASRD)
ISSN: 2394 – 8906
www.ijasrd.org, Pp: 78 – 87
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R.V.S. College of Arts & Science, Karaikal
A Study on the Factors Influence Women Entrepreneurs in
Tiruchirappalli District
S. Hemavathy1
, Dr. Sheeba Julius2
ABSTRACT: The main objective of project is study factors influencing women
enterpreneurs in thichirapalli district, analyzing the socio economic cultural factors,
government policy factors, family status factors, personal characteristic factors, financial
factors, motivational factors, market and network factors. In this study researcher tried to
identify the factors influencing women entrepreneurs, so that areas of improvement can be
identified and necessary steps can be given for implementation. The research design adopted
in this study comes under descriptive design. A descriptive study is undertaken in order to
ascertain and be able to describe the characteristics of factors influencing women
entrepreneurs in Trichy district. The sampling method used for this study is simple random
sampling. In this study the researcher has adopted, independent sample t-test, multivariate
analysis, correlation, regression, factor analysis comes under the data analysis. The study
provides a comprehensive review of the 26 critical factors influencing the growth of women
entrepreneurs particularly in Trichy as the factors are derived from the global literature on
women entrepreneurship. These would aid in better positioning the significance of these
critical factors towards the success of the entrepreneurs in Trichy and in general.
KEYWORD: women enterpreneurs, entrepreneurship development, self-employment.
According to J.A. Schumpeter, “Women who innovates, imitates, or adopts a business
Activity is called women entrepreneur”. Thus women entrepreneur are those women who
initiate, organize and operate business enterprise and want to prove their mettle in innovative
and competitive jobs. She also want to oversee and control every aspects of her business for it
is overall success.
The Indian economy has been witnessing a drastic change since mid-1991, with new
policies of economic liberalization, globalization privatization initiated by the Indian
government. India has great entrepreneurial potential. At present, women involvement in
economic activities is marked by a low work participation rate, excessive concentration in the
unorganized sector and employment in less skilled jobs.
1.1 Women Entrepreneurs in India are broadly divided into the follow categories:
a) Affluent entrepreneurs
b) Pull factors entrepreneurs
c) Push
d) Self- employed entrepreneurs
e) Rural entrepreneurs
a) Affluent entrepreneurs: Affluent r entrepreneurs are women entrepreneurs who hail
from rich business families. They are the daughters, daughters-in laws, sisters, sisters-in laws
1
Ph.D., Research Scholar, Bharatiar University, Coimbatore, Tamil Nadu, South India – 641 046.
2
Assistant Professor & Research Supervisor, Department of Commerce, A.D.M. College for Women,
Nagapattinam, Tamil Nadu, South India – 611 001.

ISSN: 2394 – 8906
and wives of people in the society. Many of them are engaged in beauty parlour, interior
decoration, book publishing, film distribution and the like. The family supports the above type
of entrepreneur in carrying out their responsibilities.
b) Pull factors: Women in towns and cities take up entrepreneurship as a challenge to do
something new and to be economically independent. These are coming under the category of
pull factors they belong to educated women who generally lake up small and medium industries
where risk is low. Under this category, women usually start service centers schools, food
catering centers restaurants, grocery shops etc.
c) Push Factors: There are some women entrepreneurs who accepts entrepreneurial
activities to overcome financial difficulties. The family situation forces them either to develop
the existing family business or to start new ventures to improve the economic conditions of the
family. Such categories of entrepreneurs are termed as push factors.
d) Self Employed Entrepreneurs: Poor and very poor women in village and town rely
heavily on their own efforts for sustenance. They start tiny and small enterprises like brooms
making wax candle making providing tea and coffee to offices, ironing of cloths knitting work
tailoring firm etc., such women are called self –employed entrepreneurs.
e) Rural Entrepreneurs: Women in rural areas/villages start enterprise which needs
least organizing skill and less risk. Dairy products, pickles, fruit juices pappads and jagger
making are coming under this category of rural entrepreneur.
1.2 Categories of women entrepreneurs:
 Women in organized & unorganized sector
 Women in traditional & model industries
 Women in urban & rural areas
 Women in large scale and small scale industries
 Single women and joint venture
1.3 Supportive measures for women’s economic activities and entrepreneurship:
 Direct & indirect financial support
 Yojna schemes and programmes
 Technological training & awards
 Federations and associations
1.4 Direct & indirect financial support:
 Nationalized banks
 State fince corporation
 State industrial development corporation
 District industries centers
 Differential rates schemes
 Mahilaudyug needhi scheme
 Small industries development bank of India (SIDBI)
 State small industries development corporation (SSIDCs)

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1.5 Scope of the study:
The outcome of this paper can be used by researchers, government, non-governmental
organizations, civil society, and local community to formulate effective policy that motivate
women to become entrepreneurs. This will have a positive effect on women participation on
the economic development of India.
1.6 Objectives of the study:
1. To find out the demographic information of the women entrepreneurs.
2. To identify the information regarding the business done by the women entrepreneur.
3. To measure the factors influencing women entrepreneur with respect to socio economic
& cultural factors, government policy & rules factors family status factors, personal
characteristics factors, financial and fund support factors motivational factors, market&
network factors.
1.7 Hypotheses framed:
 There is significant difference in the mean score of influencing factors among the
women entrepreneurs.
 There is significant difference between the influencing factor sore across the
independent variables.
1.8 Review of Literature:
Franck, Anja K (2012) examine the factors which motivate women’s informal micro-
entrepreneurship in Malaysia. Design/methodology/approach - The qualitative analysis
employed in this paper is based upon empirical findings from field work conducted in the state
of Penang on the north-western coast of Peninsular Malaysia. In total, 39 hawkers (petty
traders) were interviewed using an interview guide which contained open-ended questions
regarding work-life history, labor market choices and conditions of work. The paper presents
two selected case stories, as well as the general findings across the whole sample. Findings -
In contrast to the view that women’s informal micro-entrepreneurship is motivated only by
"involuntary exclusion from the labor market" or "poverty", this paper has found that women’s
micro-entrepreneurship can be motivated by a wide range of factors including: to earn an
income; interest in doing business; increased flexibility and autonomy; possibility to combine
with family obligations; and re-negotiating spatial practices. Conclusive with previous studies
it also argues that necessity and choice may be "co-present" in the motives to enter into
entrepreneurship. Research limitations/implications - The limited sample of this study has
implications for the generalizability of results. Further studies into the women’s micro-
entrepreneurial activities in Malaysia are therefore encouraged. Social implications - women’s
micro-entrepreneurship is increasingly being promoted as a way to create growth and
development (particularly through micro-credit schemes). Increasing knowledge around
motivational factors, performance and conditions of work for women informal micro-
entrepreneurs is therefore important when trying to establish appropriate policies.
Originality/value - There are very few studies in the Malaysian context which focus upon
women’s informal micro-entrepreneurship in general and hawking in particular. This study

ISSN: 2394 – 8906
therefore presents new knowledge around women’s informal micro-entrepreneurship in
Malaysia.
Gundry, Lisa K, Ben-Yoseph, Miriam; Posig, Margaret (2002) The study of
phenomenon related to women’s entrepreneurship has been augmented by the tremendous
growth in the formation and development of women-owned businesses during the past 2
decades. Following the last comprehensive review of research on women-owned firms that was
conducted in the mid-1990s, this paper examines major areas of inquiry related to
entrepreneurial capabilities, motivations and the acquisition of resources to launch and grow
the business. The most contemporary research is synthesized to provide implications for
entrepreneurship education, and recommendations to guide further scholarship and practice in
this area are presented.
Research Methodology
2.1 Research design:
The research design used in this is descriptive Research.
2.2 Nature of data:
The primary and secondary data sources are used for the collection of information for
the study.
2.2.1 Primary data: The primary data include data collected from the women
entrepreneurs in trichy.
2.2.2 Secondary data: Secondary data was collected from internet and used for
preparing industry profile. Review of literature from secondary sources such as websites and
online database PROQUEST.
2.3 Universe:
Universe of the study comprises of all the women entrepreneurs, in Trichy district. The
list of total women entrepreneurs in Trichy district was collected from TIDISSIA which
contained 400 women entrepreneurs.
2.4 Sample size:
The sample size was 220 women entrepreneurs in Trichy. The sample size was
calculated using the formula
N = (Z*S) 2
, where; Z=1.96, S = 0.378, e = 0.05
e
2.5 Sampling method:
The sampling method used for this study is Simple Random Sampling. Because the
researcher used lottery method to select the 220 entrepreneurs from the universe.
2.6 Data analysis:
Independent sample t-test, MANOVA for factors influencing women entrepreneurship
and its dimensions.

ISSN: 2394 – 8906
Result
The independent sample t-test of factors influencing women entrepreneurship and its
dimensions (see table 1) shows that the significant value for independent sample t-test of
government policy factor score is 0.027 which is less than 0.05, personal characteristic factor
score is 0.001 and factors influencing women entrepreneur score is 0.012.Therefore we reject
the null hypothesis. Ho. Hence, women entrepreneurs with business license have higher score
of government policy factor, personal characteristic factor, and influencing factor when
compared to women without license.
The multivariate analysis of variance for influencing factors as dependent variable and
other dimensions as independent variables (see table 2) indicates that significance value for
Wilks’ Lambda value is 0.000 for the marital status of the respondent and 0.002 for
qualification of the respondent, and 0.000 for the other income of the respondent and 0.030 for
spouse qualification of the respondent which is less than 0.05. i.e., MANOVA is significant for
the independent variables, status, qualification, other income, and spouse qualification.
.
Findings
Demographic information: A summary of the participants’ background is reported. It
is clear from that most of the respondent those who have participated in the survey are between
the age group of 36 to 45. However, most of the respondents are completed their professional
training and their monthly income below 10,000.
Rational information: Most of the respondents are living in nuclear family and their
spouse are completed their school. Majority of the respondents business was owned personally
and established their business by themselves, aim to make a profit, and running their company
at micro level. Most of the respondents are having their employees between 2 to 5, mostly
operating in manufacturing sector. Majority of the respondents targeted only local market, and
do not having the license.
Factors influencing women entrepreneurs: Factors influencing women entrepreneur
varies highly according to the changes in socioeconomic cultural factor, government policy
factor, financial factor, personal characteristic factor, motivational factor, market network
factor. And family factor has low positive significant correlation with socio-economic cultural
factor, government policy factor, financial factor, family status factor, motivational factor,
market network factor.
Factors influencing women entrepreneur is affected by changes in personal
characteristic factor, family status factor, government policy factor, motivational factor,
financial factor, market network factor. The study reveals that the construct factors influencing
women entrepreneurship varies for Indian situation and it contains 19 items belonging to 8
factors instead of 26 items belonging to 7 factors in an International situation.
Socio-economic cultural factors: Socio-economic cultural factor score influence on
women entrepreneurs is low. The Socio-economic cultural factor for of divorced respondents
was the highest and married respondents were the lowest. The Socio-economic cultural factor
score for respondents with UG qualification was the highest and school qualification was the
lowest. The Socio-economic cultural factor score for women entrepreneur operating in service
sector was the highest and trade sector was the lowest.

ISSN: 2394 – 8906
Government policy and rule factors: Women entrepreneurs with Business license
have higher w=score of government policy factors, when compared to women without Business
license. Influence on women entrepreneurs the government policy factor score is low. The
government policy factor score for respondents with PG qualification was the highest and
school qualification was the lowest. The government policy factor score for women
entrepreneur operating in manufacturing sector was the highest and service sector was the
lowest.
Family status factors: Women entrepreneurs with Business license have higher score
of family status factors, when compared to women without Business license. The mean score
for family status factor score is low. Family factor has low positive significant correlation with
Socio-economic cultural factor, government policy factor, financial factor, family status factor,
motivational factor, market network factor. The family status factor of single respondents was
the highest and marred respondents were the lowest. The family status factor is for ownership
of owned personally was the highest and owned with partners was the lowest. The family status
factor score for women entrepreneur operating in service sector was the highest and trade sector
was the lowest.
Personal characteristics factors: Women entrepreneurs with Business license have
higher score of personal characteristic factor, when compared to women without Business
license. The mean score for personal characteristic factor score is low. The personal
characteristic factor score for respondents with PG qualification was the highest and school
qualification was the lowest. The personal characteristic factor score for women entrepreneur
operating in service sector was the highest and trade sector was the lowest.
Financial resources factors: Women entrepreneurs with Business license have higher
score of financial resources factor, when compared to women without Business license. The
mean sore for financial resources factor sore is very high. The financial factor is for other
sources of income, others respondents were the highest and business respondents were the
lowest. The financial factor score for women entrepreneur operating in service sector was the
highest and trade sector was the lowest.
Motivational factors: Women entrepreneurs with Business license have higher score
of motivational factor, when compared to women without Business license. The mean score
for motivational factor score is moderate. The motivational factor of single respondents was
the highest and divorced respondents were the lowest. The motivational factor is for score for
respondents with UG qualification was the highest and professional qualification was the
lowest. The sector of business, for women entrepreneur operating in service sector was the
highest and other sector was the lowest.
Market and informational network factors: Women entrepreneurs with Business
license have higher score of market and network factor, when compared to women without
Business license. The mean score for market and network factor score in moderate. The market
and informational network factor for score for respondents with PG qualification was the
highest and school qualification was the lowest. The market and informal network factor for
other sources of income, other respondents was the highest and business respondents was the
lowest. The market and informal network factor is for spouse qualification, others respondents
was the highest and professional respondents was the lowest.

ISSN: 2394 – 8906
Suggestions
 An Awareness programme should be conducted on a mass scale with the intention of
creation awareness among women about the various areas to conduct business.
 Organize training programmes to develop professional competencies in managerial,
leadership, marketing financial, production process, profit planning, maintaining books
of accounts and other skill. This will encourage women to undertake business.
 Vocational training to be extended to women community that enables them to
understand the production process and production management.
 Women in business should be offered soft loans & subsides for encouraging them into
industrial activities. The financial institutions should provide more working capital
assistance both for small scale venture and large scale ventures.
 Making provision of micro credit system and enterprise credit system to the women
entrepreneurs.
 Educational institutes should tie up with various government and Non-government
agencies to assist in entrepreneurship development mainly to plan business project.
 Women should try to upgrade themselves in the changing times by adapting the latest
technology benefits. Women must be educated and trained constantly to acquire the
skill and knowledge in all the functional areas of business management. This can
facilitate women to excel in decision making process and develop a good business
network.
 Increase the ability of women to participate in the labor force by ensuring the
availability of affordable child care and equal treatment in the work place. More
generally, improving the position of women in society and promoting entrepreneurship
generally will have benefits in terms of women’s entrepreneurship.
Conclusion and Future Work
The study provides a comprehensive review of the 26 critical factors influencing the
growth of women entrepreneurs particularly in Trichy. As the factors are derived from the
global literature on women entrepreneurship, it is hoped that the recommendations made in this
study provide useful guidelines to women entrepreneurs, government, associations, and BGOs
and other relevant stakeholders. It is also hoped that additional research will be undertaken to
build upon this work. Empirical evidence and /or case studies on successful women
entrepreneurs based on the factors proposed are possible research areas. These would aid in
better positioning the significance of these critical factors towards the success of women
entrepreneurs in Trichy and in general.
Reference
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ISSN: 2394 – 8906
Table 1:
Independent sample t-test of factors influencing women entrepreneurship and its
dimensions
t-test for Equality of Means
t df
Sig.
(2-tailed)
Mean
Difference
Soceconculfac
Equal variances assumed 1.085 218 .279 .09297
Equal variances not assumed 1.387 94.995 .169 .09297
Govtpolfac
Familystatusfac
Perscharachfac
Finanfac
Equal variances assumed -1.018 218 .310 -.07634
Equal variances not assumed -1.246 87.001 .216 -.07634
Motivfac
MarketNetworkfac
Influenfac

ISSN: 2394 – 8906
Table 2:
Multivariate analysis of variance for influencing factors as dependent variable and other
dimensions as independent variables:
Effect Value F
Hypothesis
df
Error
df
Sig.
Intercept
Pillai's Trace .858 164.478a
7.000 190.000 .000
Wilks' Lambda .142 164.478a
7.000 190.000 .000
Hotelling's Trace 6.060 164.478a
7.000 190.000 .000
Roy's Largest Root 6.060 164.478a
7.000 190.000 .000
Age
Pillai's Trace .154 1.100 28.000 772.000 .330
Wilks' Lambda .854 1.096 28.000 686.477 .336
Hotelling's Trace .162 1.091 28.000 754.000 .342
Roy's Largest Root .073 2.020b
7.000 193.000 .054
Status
Pillai's Trace .308 2.296 28.000 772.000 .000
Wilks' Lambda .720 2.342 28.000 686.477 .000
7.000 193.000 .000
Qualification
Pillai's Trace .166 2.470 14.000 382.000 .002
14.000 380.000 .002
7.000 191.000 .000
Course
Pillai's Trace .018 .491a
7.000 190.000 .840
Wilks' Lambda .982 .491a
7.000 190.000 .840
Hotelling's Trace .018 .491a
7.000 190.000 .840
Roy's Largest Root .018 .491a
7.000 190.000 .840
Income
Pillai's Trace .121 .861 28.000 772.000 .674
Wilks' Lambda .882 .865 28.000 686.477 .668
Hotelling's Trace .129 .869 28.000 754.000 .662
7.000 193.000 .021
Otherincome
Pillai's Trace .243 3.777 14.000 382.000 .000
14.000 380.000 .000
7.000 191.000 .000
Family
Pillai's Trace .104 1.504 14.000 382.000 .106
14.000 380.000 .107
7.000 191.000 .045
Spouse
Pillai's Trace .216 1.575 28.000 772.000 .030
Wilks' Lambda .798 1.580 28.000 686.477 .030
7.000 193.000 .003

A Study on the Factors Influence Women Entrepreneurs in Tiruchirappalli District

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