Editorial Board

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