Pacific B usiness R eview I nternational

A Refereed Monthly International Journal of Management Indexed With Web of Science(ESCI)
ISSN: 0974-438X
Impact factor (SJIF):8.396
RNI No.:RAJENG/2016/70346
Postal Reg. No.: RJ/UD/29-136/2017-2019
Editorial Board

Prof. Mahima Birla
(Editor in Chief)

Dr. Khushbu Agarwal
(Editor)

Dr. Asha Galundia
(Circulation Manager)

Editorial Team

A Refereed Monthly International Journal of Management

Socio-Economic and Motivational Factors affecting Women Entrepreneurs in Gautam Buddha Nagar, U.P.

Dr. Preeti Sharma

Amity Global Business School, Amity University Noida

 

Abstract

Purpose- In the light of Indian Women's tremendous potential to drive socio-economic development in the country, the current study focuses to study different socio-economic and motivational factors for women to become entrepreneurs.

Design/ Methodology/Approach- To explore these factors primary data collected through a self-constructed questionnaire (the responses from actual and potential entrepreneurs in Gautam Budhha Nagar district) was tested using actor analysis (Principal Components Analysis).

Findings- The findings explores five factors that are societal acceptance as a powerful economic tool, Urge for Self-sufficiency and family support, Capabilities and education, Benefit from opportunity in the market and Governmental support. The women entrepreneurs of different age, marital status, qualification and family status have different view on these motivation factors.

Practical/Research Implication- In current scenario the change of women from a housewife to an entrepreneur has become an unavoidable requirement. Thus the study was conducted to explore the socio- economic and motivational factors encouraging Indian women to change their current position.

Originality/Value–The study can provide valuable guidelines for policymakers to frame policies that can motivate women to contribute to economic development by demonstrating themselves as a production and development factor. The twin issues that are discussed relate to women's redevelopment and the economic growth of the nation.

Keywords: Socio economic Factors, KMO Test, Motivational factors, Women Entrepreneurs

Introduction

Down the ages the potentials of women were ignored and treated as secondary citizens in all societies. Women are seeking to remove such a mark by achieving a big achievement in the world's economic

 

 

 

 

development, offering a solution to the problems of unemployment and poverty (Balan & Samunnatha, 2013). Indian women have immense capacity to drive the country's socio- economic growth. The socio- economic empowerment of women not only confirms the advancement of their family, but also leads to the economic development of the country. For decades, Indian women's potential and entrepreneurial skills have been underutilized. They can not only become self-dependent, but also build livelihood opportunities for others, adding economic value to developing countries such as India. Recently, Indian women have begun to realize the value of their talent, ability, and education and have come forward to harness their self-development ability by entering into entrepreneurship ventures which in turn contributes to the country's growth. Initially they faced a large number of social, cultural and economic hurdles. Entrepreneurial growth in a society is a complex process that is heavily affected in a variety of positive and negative ways by various macro-external environmental factors such as political, economic, social, cultural, religious, and psychological factors that exist in society and affect businesses and their owners (Sharma P. , 2020).

Studies also show that women entrepreneurs are not experiencing the same opportunities as men to access start- up capital because of a variety of discriminatory patterns inherent in lending models (Derera, Chitakunye, & O'Neill, 2014).Now women are getting family support (i.e., emotional, instrumental, and financial support for the family) that is strongly correlated with being entrepreneurs and doing well (Neneh, 2017). Several research and scholars dealt with different motivational factors that drive women to become entrepreneurs. These numerous motivating factors inspire women to become entrepreneurs and women often face different obstacles to their entrepreneurial journey. Current paper has tried to explore various drivers that affect a normal woman entrepreneur in India.

The current study has been divided the study into six sections. First section deals with theoretical framework and supportive backing for current study. The second section discusses the review of related literature and potential scope for study on topic taken into consideration. The third portion is related to the variables of study, data and research

 

tools used to make analysis and interpretation. The fourth portion presents the results and discuss thereof. The fifth section shows the validity (limitation) of current study. The final segment presents the conclusion, suggestion and future direction of research on current study.

Review of Literature:

Orhan, M., & Scott, D. (2001) developed a factor model (using qualitative analysis to examine the circumstances of case study involving 25 French women entrepreneurs) that motivates women to start their own businesses. Mahajan, (2013) studies the current situation of women entrepreneurs in Indian context. Fatoki, (2014) examined the factors driving young female entrepreneurs to start business. The study focused on young female entrepreneurs (not older than 35 years), who started business in the last forty-two months. Mattingly, (2015) described variables that constitutes entrepreneurship are phenomena related to the emergence of new economic activity or interruptions, and improvements to existing economic activity rather than contexts.

Isiwu & Onwuka, (2017) examined different psychological factors that influence entrepreneurial objective among women entrepreneurs in Nigeria. Raghuvanshi, Agrawal, & Ghosh, ( 2017 ) categorized barriers to female entrepreneurship and studied their effect on female entrepreneurial success. Geetha & Rajani, (2017) have studied the motivational factors that motivate women entrepreneurs in Chittoor district. Vidyakala, (2018) identified the motivational factors prompting women towards entrepreneurship.

Sharma & Chakraborty, (2019) have studied all factors impacting women entrepreneurs positively and negatively. Shastriet. al, (2019) discussed the motives and primary challenges faced by women entrepreneurs in running small businesses in the Rajasthan city of Jaipur. Jafari-Sadeghi, (2020) analyzed the interplay of three forms of motivation on women and men's entrepreneurial activities in 24 European countries: opportunity-driven motivation, necessity-driven motivation and mixed motivation. Nguyen, Phuong, &Vo, (2020) studied the challenges, motivational factors, and success reason in context of developing economies taking the reference to Vietnam.Cho, et. al. (2020) studied the leadership aspect in

 

 

 

Asian women by investigating their challenges and opportunities in the selected Asian countries (China, India, Indonesia, Japan, Korea, Malaysia, Thailand and Vietnam). Agarwal, et. al. (2020) has done an in-depth study to explore the capabilities and proficiency of India women. They studied the trait (leadership qualities, risk taking and handling capacities, ability to identify the opportunities, and the abilities to visualize future challenges) of Indian women to be successful entrepreneurs.

The literature available has contributed on identifying various socio-economic and motivational factors that influence women in becoming entrepreneurs. The current paper is focused on recognizing and compiling various socio-economic and motivational variables and find out the impact of demographic conditions on these factors.

These factors were checked on women entrepreneurs in the district of Gautam Buddha to validate these factors in the context of women entrepreneurs. In short current study explores different socio-economic and motivational factors that influence women to become entrepreneurs and the effect of demographic conditions on these motivational factors. The next section describes the variables selected as factors and statistical methods applied to draw conclusions from study.

 

Research Methodology

Variables and Data Description

Current research takes 21 socio-economic and motivational factors defined from established thematic studies. Such variables i nclude every socio- economic and encouragement factor that inspires women to become entrepreneurs. The coding, description and reference (from which factors have been developed) have been reported in table A, attached to annexure.

Primary data has been used to conduct exploratory factor analysis. A self-constructed (based on factors identified from previous researches)five points (Strongly Agree, Agree, Neutral, Disagree and Strongly Disagree) questionnaire was administered to more than 200 female entrepreneurs having less than 10 years of experience in Gautam Buddha District) to obtain data for the study. The women entrepreneurs taken as samples include boutiques holders, beauticians, coaching centers, tiffin delivery services, medical clinics, cosmetic and gift shops and general stores. Out of 200 questionnaires only 188 could be collected. Due to incomplete responses and not proper responses only 160 responses were used for final study. Table 1 shows the respondent profile.

 

Table 1 : Respondent's Profile

 

Descriptive Factor

Division of Factor

Frequency

% of total samples

Age

18-25

36

22.5%

 

25-40

81

50.62%

 

40 and above

43

26.86%

Marital Status

Single

26

16.25%

 

Married

109

68.13%

 

Divorced

13

8.12%

 

Widow

12

7.5%

Highest Qualification

Functionally Literate

15

9.37%

 

Upto Senior Secondary

20

12.5%

 

Graduate

40

25%

 

Post Graduate or above

85

53.13%

Number of Children

None

39

24.38%

 

1

45

28.12%

 

2

66

41.25%

 

3

10

6.25

Work experience before starting your own venture

No experience

43

26.88%

 

=2

17

10.63%

 

2 to 5 years

32

20%

 

More than 5 years

68

42.5%

Current Family status

Lower Middle class

39

24.36%

 

Middle class

81

50.62%

 

Upper Middle class

40

25%

Source: (Responses of Questionnaire)

 

 

 

Statistical Tools Used:

SPSS software was used to perform Principal-components method of factor analysis of the data collected through the

 

questionnaires. Factor analysis has been used to form close construct that motivate women entrepreneurs in current environment. The complete statistical tools application has been divided into steps which are as under:

 

 

Table 2: Variables and coding

 

Demographic factor

Division of Factor

Nominal value

Age

18-25

1

 

25-40

2

 

40 and above

3

Marital Status

Single

1

 

Married

2

 

Divorced

3

 

Widow

4

Highest Qualification

Functionally Literate

1

 

Upto Senior Secondary

2

 

Graduate

3

 

Post Graduate or above

4

Current Family status

Lower Middle class

1

 

Middle class

2

 

Upper Middle class

3

 

Source: Author

Statistical Method:

To measure the sample adequacy for all the variables Kaiser-Meyer-Olkin measure has been applied and to measure the sample adequacy of each variable separately anti-image correlation has been calculated. Kaiser (1975) suggested that KMO> 0.6 is satisfactory (middling), while KMO value more than 0.6 is considered good. KMO statistic varies between 0 and 1. To calculate measure of variance communality (h2) table has been created. Communality is a squared variance-accounted-for statistic replicating how much variance in measured variables is explained by the hidden constructs (e.g., the factors). Cronbach Alpha has been used to measure internal consistency and reliability.

Analysis of factors

After exploring socio-economic and motivational variables, the mean response in those variables was used to test the most impacting factor. To test the impact of

 

demographic conditions on different motivational factors ANOVA has been used. The taken demographic factors to analyze the impact on motivational factors are age, marital status, qualification and family status. These factors were categories and given nominal values as under:

The next section discusses the empirical results drawn from application of mentioned statistical techniques. Section four describes the results and their interpretation.

Empirical Results

KMO test was conducted to check whether the data is suitable for factor analysis(Results are reported in table 3). The value of Kaiser-Meyer-Olkin measure is 0.659 which is more than 0.6 and the results value of Bartlett's test of sphericity is significant (p<0.001, p=0.000). The measured value indicates the adequacy of responses. The Anti image correlation and communality (values attached to appendix in table B and C) was also found satisfactory which indicates sample adequacy of all the variables individually.

 

 

 

Table 3: KMO and Bartlett's Test

 

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.659

 

Bartlett's Test of Sphericity

Approx. Chi-Square

3281.187

Df

210

Sig.

.000

 

Source: Author's Calculation

Table 4 shows the factors explored, factor loading total variance explained and Cronbach alpha values of the factors explored. The table displays the total variance explained by five factors that motivates women entrepreneurs' current working scenario. Total variance

 

explained by these factors is 69.31%.The values of alpha coefficient > 0.7 (acceptable) or between 0.7 or 0.6 (middling value) are acceptable. In our table all the factors have value more than 0.6. So this confirms the internal consistency and reliability of the scale.

 

Table 4: Factors Explored

 

Factor Name

Variables/statements

Factor loading

Reliability

 

 

Societal acceptance as a powerful economic tool (Variance explained- 17.89%)

Women are treated as a powerful tool for economic development

0.642

 

 

 

 

 

 

 

0.764

Women are considered to possess more creative, patient and multi-tasking abilities

0.68

women are rendered increased financial decision making power

0.73

They are no more considered to have lack of decision making power

0.642

Less effected form Prevailing gender discrimination now

0.622

 

Urge for Self-sufficiency and family support (Variance explained- 15.90%)

They get more economic stability and freedom compared to housewives

0.74

 

 

 

0.731

Potential of women is no more suppressed

0.646

Moral support from family and friends

0.831

Financial freedom

0.676

 

Capabilities and education (Variance explained- 13.794%)

Education

0.614

 

 

0.663

Need for excellence

0.781

Pursue hobby as an earning activity

0.649

better social status of self

0.499

 

Benefit from opportunity in the market (Variance explained- 11.816%)

Increasing Demand for a product and services in the market

0.626

 

 

 

 

 

0.623

Processing skills for the products and service development

0.573

Ready markets available

0.474

Future prospects in Market

0.422

Need for money for the family’s survival

0.575

 

Governmental support (Variance explained- 9.91%)

Availability of various government schemes for women empowerment

0.491

 

 

0.693

Easy and cheap loans to women entrepreneurs

0.706

Rebate in taxes

0.601

Source: Author's Calculation

 

 

 

 

So we can see that five new factors have successfully been constructed using factor analysis and assigned as the factors motivating women entrepreneurs in current scenario. These factors have been named as societal acceptance as a powerful economic tool, Urge for Self-sufficiency and family support, Capabilities and education, Benefit from opportunity in the market and Governmental support.

Table 5 presents the mean of responses given by women entrepreneurs on motivation factors for starting their own ventures. From the table we can conclude that the biggest motivation factor for them is societal acceptance as a

 

powerful economic tool which has highest mean and comparatively lesser variance of responses. The second motivation factor is support from government to start and run their venture effectively, the factor has the least variance of responses. The third factor is opportunities in the market. The next motivational factor is urge for Self- sufficiency and family support with the highest variance of responses. And the least motivating factor among all five factors is Capabilities and education, again having high variance of responses.

 

Table 5: Descriptive Statistics

 

Socio-Economic and Motivational factor

Minimum

Maximum

Mean

Std. Deviation

Variance

Societal acceptance as a powerful economic tool

2.40

5.00

4.5128

.41354

.171

Urge for Self-sufficiency and family support

3.00

5.00

4.3336

.45535

.207

Capabilities and education

3.00

5.00

4.2889

.44924

.202

Benefit from opportunity in the market

3.40

5.00

4.3953

.34981

.122

Governmental support

3.67

5.00

4.5019

.33981

.115

 

Source: Author

Analysis of Relationship between demographic factors and motivational factors

From the results  of table  6 we can  conclude that  the

 

opinions of women in different age group, marital status, qualification and different family status are significantly different in all the five factors.

 

 

Table 6: Robust Tests of Equality of Means (Welch Test)

 

Factor

Variable

Statistica

df1

df2

Sig.

 

Factor 1

Age

6.611

2

405.350

.001

Marital status

21.670

3

144.919

.000

Qualification

7.714

3

193.480

.000

Family status

20.490

2

406.244

.000

 

Factor 2

Age

35.879

2

375.768

.000

Marital status

8.286

3

129.193

.000

Qualification

9.204

3

187.397

.000

Family status

14.007

2

388.730

.000

 

Factor 3

Age

4.563

2

344.428

.011

Marital status

6.305

3

129.343

.001

Qualification

8.856

3

171.238

.000

Family status

3.577

2

342.709

.029

 

 

 

Factor

Variable

Statistica

df1

df2

Sig.

 

Factor 4

Age

1.900

2

336.010

.151

Marital status

2.871

3

125.034

.039

Qualification

12.353

3

175.359

.000

Family status

24.730

2

345.865

.000

 

Factor 5

Age

42.426

2

388.522

.000

Marital status

14.700

3

139.432

.000

Qualification

5.617

3

179.464

.001

Family status

12.017

2

350.176

.000

 

Source: Author

From the results of Tukey post hoc test (reported in table 6.1 to 6.4) we can conclude the relationship in age, marital status, qualification and family status.

Age and motivational factors

The women in age group of 18-25 have same opinion as women in 25-40 while women in age group 40 and above have significantly different opinion on societal acceptance. First two age groups take societal acceptance as motivational factor while third group does not confirm it. In context of urge for self-sufficiency and family support age group 18-25 and 40 and above have similar opinion while

 

second age group is significantly different from other two age groups. First and third age groups consider urge for self-sufficiency and family support as motivational factor while second age group does not confirm it. On the factor capability and education age group of 18-25 have same opinion as women in 25-40 while women in age group 40 and above have significantly different opinion. First two age groups take this factor as motivational factor. All three age groups have same opinion about benefit from opportunities in the market (no significant difference of opinion). All the three age groups have significantly different opinion on government support.

 

Table 6.1: Age categories and the motivational factors

 

Factors

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

 

 

Age category

 

Mean Differenc e (I-J)

 

 

Sig.

 

Mean Differenc e (I-J)

 

 

Sig.

 

Mean Differen ce (I-J)

 

 

Sig.

 

Mean Differen ce (I-J)

 

 

Sig.

 

Mean Differenc e (I-J)

 

 

Sig.

1

2

.00912

.97

.30694*

.000

.01211

.958

.03613

.536

.17934*

.000

3

-.10620

.05

.09926

.098

.13607*

.016

.07729

.110

.27289*

.000

2

1

-.00912

.97

-.30694*

.000

-.01211

.958

-.03613

.536

-.17934*

.000

3

-.11532*

.01

-.20769*

.000

.12396*

.007

.04117

.400

.09355*

.005

3

1

.10620

.05

-.09926

.098

-

.13607*

.016

-.07729

.110

-.27289*

.000

2

.11532*

.01

.20769*

.000

-

.12396*

.007

-.04117

.400

-.09355*

.005

Source: Author

 

 

 

Marital status and motivational factors

On the factor of societal acceptance single women entrepreneurs have significantly different opinion from all. While married and divorced women entrepreneurs have no significant different opinion. The opinion of widow and divorced is also not significantly different. On self- sufficiency and family support single women entrepreneurs have different opinion than married while there is no

 

significant difference in the opinion of single, married and divorced women entrepreneurs. On capability and education single, married and divorced women entrepreneurs have similar opinion while widow women entrepreneurs have significantly different opinion. All four categories have similar opinion on benefit from market opportunities. On governmental support single women entrepreneurs have significantly different opinion than others.

 

 

Table 6.2: Marital status and the motivational factors

 

Factors

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

 

 

 

Marital status

 

Mean Difference (I-J)

 

 

 

Sig.

 

Mean Differen ce (I-J)

 

 

 

Sig.

 

Mean Differen ce (I-J)

 

 

 

Sig.

 

Mean Differen ce (I-J)

 

 

 

Sig.

 

Mean Differen ce (I-J)

 

 

 

Sig.

Single

Married

-.11818*

.03

.17878*

.00

.13381*

.02

.06036

.34

.16890*

.00

Divorced

-.25422*

.00

.13461

.28

.19523*

.05

.17722*

.01

.20483*

.00

Widow

-.33486*

.00

-.02332

.99

-.03597

.96

.07747

.53

.21897*

.00

Married

Single

.11818*

.03

-.17878*

.00

-.13381*

.02

-.06036

.34

-.16890*

.00

Divorced

-.13604

.11

-.04417

.91

.06142

.79

.11686

.11

.03593

.89

Widow

-.21668*

.00

-.20210*

.00

-.16978*

.04

.01711

.99

.05007

.72

Divorced

Single

.25422*

.00

-.13461

.28

-.19523*

.05

-.17722*

.01

-.20483*

.00

Married

.13604

.11

.04417

.91

-.06142

.79

-.11686

.11

-.03593

.89

Widow

-.08064

.74

-.15793

.27

-.23119*

.04

-.09975

.45

.01414

.99

Widow

Single

.33486*

.00

.02332

.99

.03597

.96

-.07747

.53

-.21897*

.00

Married

.21668*

.00

.20210*

.00

.16978*

.04

-.01711

.99

-.05007

.72

Divorced

.08064

.74

.15793

.27

.23119*

.04

.09975

.45

-.01414

.99

 

 

Source: Author

Qualification and motivational factors

On societal acceptance females entrepreneurs having functional literacy and upto senior secondary have similar opinion which is significantly different opinion from other literacy categories (Graduate and postgraduate women entrepreneurs have similar opinion). On self-sufficiency and family support the graduate women entrepreneurs have significant different opinion than others (others have

 

similar opinion). On capability and education all women entrepreneurs have similar opinion. On benefit from market opportunities all women entrepreneurs have significantly different opinion. On governmental support the opinion of functionally literate and literate upto senior secondary is similar while their opinion is significantly different from graduate and post graduate (they have similar opinion).

 

 

 

Table 6.3: Qualification and the motivational factors

 

Factors

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

 

 

Qualification

 

Mean Difference (I-J)

 

 

Sig.

 

Mean Difference

(I-J)

 

 

Sig.

 

Mean Difference (I-J)

 

 

Sig.

 

Mean Differenc e (I-J)

 

 

Sig.

 

Mean Differenc e (I-J)

 

 

Sig.

1

2

-.17712

.06

-.10061

.56

-.13047

.31

-.19689*

.004

-.19358*

.01

3

-.25862*

.00

-.22557*

.01

-.32902*

.00

-.17586*

.00

-.04406

.82

4

-.14982*

.05

-.02674

.96

-.23080*

.00

-.29146*

.00

-.10978

.09

2

1

.17712

.06

.10061

.56

.13047

.31

.19689*

.00

.19358*

.00

3

-.08150

.45

-.12496

.16

-.19856*

.00

.02103

.97

.14952*

.00

4

.02730

.95

.07387

.53

-.10033

.24

-.09457

.10

.08380

.17

3

1

.25862*

.00

.22557*

.01

.32902*

.00

.17586*

.00

.04406

.82

2

.08150

.45

.12496

.16

.19856*

.01

-.02103

.97

-.14952*

.00

4

.10880*

.02

.19884*

.00

.09822

.07

-.11560*

.00

-.06572

.15

4

1

.14982*

.05

.02674

.98

.23080*

.00

.29146*

.00

.10978

.09

2

-.02730

.95

-.07387

.53

.10033

.24

.09457

.10

-.08380

.17

3

-.10880*

.02

-.19884*

.00

-.09822

.07

.11560*

.00

.06572

.15

 

 

Family status and motivational factors

On societal acceptance and self-sufficiency and family support, female entrepreneurs from middle class have significantly different opinion than other two categories. On capability and education the women entrepreneurs from lower middle class have significantly different opinion than

 

other two categories. On benefit from market opportunities all three categories have significantly different opinion. On government support lower middle and middle class have similar opinion while the opinion of upper middle class is significantly different.

 

 

Table 6.4: family status and the motivational factors

 

Factors

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

 

 

Family status

 

 

Mean Difference

(I-J)

 

 

 

Sig.

 

 

Mean Difference (I-J)

 

 

 

Sig.

 

 

Mean Difference

(I-J)

 

 

 

Sig.

 

 

Mean Difference

(I-J)

 

 

 

Sig.

 

 

Mean Difference (I-J)

 

 

 

Sig.

1

2

.20672*

.000

.19369*

.000

.03712

.664

-.14384*

.000

-.05688

.179

3

.01915

.898

.02668

.845

-.06631

.356

-.27054*

.000

-.17692*

.000

2

1

-.20672*

.000

-.19369*

.000

-.03712

.664

.14384*

.000

.05688

.179

3

-.18757*

.000

-.16701*

.000

-.10342*

.030

-.12670*

.000

-.12004*

.000

3

1

-.01915

.898

-.02668

.845

.06631

.356

.27054*

.000

.17692*

.000

2

.18757*

.000

.16701*

.000

.10342*

.030

.12670*

.000

.12004*

.000

 

 

 

Source: Author

 

 

 

Threats to validity:

Present research is limited to results drawn from responses obtained from only one district female entrepreneurs. The tests and interpretation are both sampling based and sample size based. The results of the analysis may differ depending on the sample size, areas, and socio-economic and entrepreneurial motivation factors.

Conclusion and suggestions:

The current study shows that over the years the status of female entrepreneurs has changed positively but we can observe that they have started to gain prominence in family and society. The all-round progression in the country requires the effective leadership and initiations from the educated and dynamic women entrepreneurs. Now there is a necessity of various schemes and programs for women entrepreneurs to motivate them. The internal as well as external motivating factors help women to move their direction towards economic development of self and the country. Women who develop high self-efficacy are more likely to be entrepreneurs, and strategies for building high female self-efficacy are needed to turn more women into entrepreneurs to improve national / grassroots growth.

To truly promote and improve entrepreneurial approaches, there is an increasing need to foster creative ways of thinking, different skills and new forms of behavior . Women entrepreneurs should be given sufficient awareness and understanding of entrepreneur selection approaches that can assist in the investment decision making process because it helps entrepreneurship agents to assess individuals and their opportunities more effectively .

The findings of the study present five socio-economic and motivational factors that are societal acceptance as a powerful economic tool, support from government, opportunities in the market, urge for Self-sufficiency and family support, and Capabilities and education as per the the average of responses collected.

This study only considers single district female entrepreneurs. There is a potential scope of study for other

 

regions which comprise many cities. The results of this study can be validated in other Indian cities and states with a large-scale randomly selected target population (as every state and district have different employment opportunities, wages and distribution of income). It is also interesting to compare entrepreneurs between men and women using established comprehensive framework.

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Annexure:

Table A: (Details of Socio-Economic and Motivation factors)

 

Variable Coding

Socio-Economic and Motivational variables

References

X1

Increasing Demand for a product and services in the market

(Krishnamoorthy & Balasubramani, 2014)

X2

Processing skills for the products and service development

(Suganthi, 2009)

X3

Availability of various government schemes for women empowerment

(Krishnamoorthy & Balasubramani, 2014)

X4

Women are treated as a powerful tool for economic development

(Rathna, Badrinath, & Anushan, 2016)

X5

Women are considered to possess more creative, patient and multi-tasking abilities

(Ismail, Shamsudin, & Chowdhury, 2012)

X6

women are rendered increased financial decision making power

(Balan & Samunnatha, 2013)

X7

Ready markets available

(Krishnamoorthy & Balasubramani, 2014)

X8

Future prospects in Market

(Ismail, Shamsudin, & Chowdhury, 2012)

X9

Education

(Suganthi, 2009)

X10

Easy and cheap loans to women entrepreneurs

(Krishnamoorthy & Balasubramani, 2014)

X11

They are no more considered to have lack of decision making power

(Suganthi, 2009)

X12

Need for money for the family’s survival

(Ismail, Shamsudin, & Chowdhury, 2012)

X13

Rebate in taxes

(Krishnamoorthy & Balasubramani, 2014)

X14

They get more economic stability and freedom compared to housewives

(Neneh, 2017)

X15

Potential of women is no more suppressed

(Moses, Amalu, & others, 2010)

X16

Moral support from family and friends

(Neneh, 2017)

X17

Financial freedom

(Rathna, Badrinath, & Anushan, 2016)

X18

Less effected form Prevailing gender discrimination now

(Moses, Amalu, & others, 2010)

X19

Need for excellence

(Ismail, Shamsudin, & Chowdhury, 2012)

X20

Pursue hobby as an earning activity

(Rathna, Badrinath, & Anushan, 2016)

X21

better social status of self

(Rathna, Badrinath, & Anushan, 2016)

 

 

Table B:Anti-image Correlation

 

Variable

Correlation value

Variable

Correlation value

X1

.544a

X12

.552a

X2

.581a

X13

.629a

X3

.635a

X14

.577a

X4

.561a

X15

.755a

X5

.513a

X16

.669a

X6

.534a

X17

.719a

X7

.531a

X18

.717a

X8

.557a

X19

.592a

X9

.579a

X20

.664a

X10

.583a

X21

.644a

X11

.578a

 

 

 

Table C: Communalities

 

Variable

Extraction

Variable

Extraction

X1

.469

X12

.468

X2

.438

X13

.424

X3

.413

X14

.597

X4

.583

X15

.498

X5

.451

X16

.718

X6

.566

X17

.508

X7

.423

X18

.474

X8

.494

X19

.634

X9

.410

X20

.473

X10

.603

X21

.505

X11

.477