Unveiling the Crucial Factors of Women Entrepreneurship in the 21st Century

Abstract

In the present era, women-owned firms are one of India’s fastest increasing entrepreneurial communities in the form of women entrepreneurs. The objective of the study is to identify the factors that influence women’s entrepreneurial orientation and firms’ performance. The research study discusses the influencing factors and their effect on firms’ performance and satisfaction in this regard. The proposed framework and hypotheses have been tested using data gathered from boutiques, beauty parlors, carpet manufacturers, and retail shops in Karnataka, India. Data analysis was done using univariate, bivariate, and multivariate techniques. In Structural Equation Modeling (SEM), paths were created for evaluating the cause-and-effect relationship between different factors viz., social, psychological, financial, and resource factors and entrepreneurial performance and satisfaction. Seven relationships were significant, while two relationships were insignificant in this structural equation. The key finding of the paper is that all factors have a significant impact on the firm’s performance. The implications of research results for researchers and practitioners are discussed, and suggestions have also been made.

1. Introduction

The concept of entrepreneurship could be defined during the 1700s as an effort related to business and industrial activities (Anggadwita et al. 2017; Fichter and Tiemann 2018; Leonidou et al. 2020). Economic historians and researchers have opined that even though inventors and entrepreneurs are two different domains, most inventors turned out to be entrepreneurs (Schumpeter 1947). Until the 1990s, the mainstream researchers and leading media houses perceived women’s entrepreneurial activities to be only small lifestyle ventures and sole proprietorships (Baker et al. 1997). Historically, during 1976, the first academic paper was published on female entrepreneurship (Schwartz 1976) and the first policy reported in 1979 entitled “The bottom line: unequal enterprise in America”. The first academic conference on women’s entrepreneurship was held in 1981 at Babson College, USA (Hisrich and O’Brien 1981), and the first academic book published on women’s entrepreneurship was in 1985 (Goffee and Scase 1991). A recent research finding quantifies that total women’s entrepreneurial activities on different continents compared to the adult working-age population from 18 to 64 are 10.2%, which is approximately three-quarters of that seen for males. The highest rate of entrepreneurial activities of women is found in Sub-Saharan Africa (21.8%), and the lowest rate is found in Europe, the Middle East, and Northern Africa regions (6%) (Hart et al. 2019). As per the recent global report, the average rate of women’s intention to start a business for the next three years is 17.6%, which is only 4% less than men. Fascinatingly, these entrepreneurial intentions are found more in low-income countries, followed by middle- and higher-income countries (Hart et al. 2019). The role of women in entrepreneurial activities can provide a significant contribution to economic and social development (Ozaralli and Rivenburgh 2016).

The women in India have been changed from goddess to devadasi, from pure to vulgar, from being supreme to being downtrodden (Wilson 2020; Jansi et al. 2019). The role of Indian women has undergone dramatic and drastic changes, and on several platforms, women in India have struggled and experienced identity issues in society. Every ‘yes’ for women had a corresponding ‘no’, and for every ‘no’ there is a ‘yes’. This atmosphere often creates uncertainty in society, and women struggled to define their role and importance to the world. The Indian economy has been gradually witnessing drastic change since the middle of 1991, after a reformation in economic policies related to liberalizing, globalizing and privatizing. This commercial extension has exposed international reality to the country, and women entrepreneurs in India have started gaining momentum. To establish empowerment and enhance quality of life, women’s entrepreneurship is one of the instruments of considerable importance. The gender gap in entrepreneurial activities has been defined as the difference between men and women engaged in this activity. The notable number of studies on the individual level of entrepreneurship is focused on male entrepreneurs, and very few studies focus on gender differences in entrepreneurship (Srivastava and Misra 2017).

Innovative and proactive firms that rationally handle risk will be more effective in seizing possibilities. Innovative firms adapt to changing macro-economic factors and develop new capacities to achieve better productivity. All these features are created by the orientation of entrepreneurs, and entrepreneurs prefer to run a successful enterprise that gives them enough economic means to live a comfortable life (Agarwal and Lenka 2018). In reality, these expectations of aspiring entrepreneurs are not met due to lack of assistance/support and awareness. The failure rates of start-ups and new companies can be as high as 60% in the first five years of their venture. Women who attempt to start any venture are usually subjected to multiple environmental limitations, either in a managerial or entrepreneurial position. Starting and running a company includes significant entrepreneurial risk and effort, especially in view of the high rate of failure. The present research examines the factors that affect the levels of satisfaction among women entrepreneurs. Satisfaction can be seen as the main measure of the achievement of individual entrepreneurs. The utility derived from the entrepreneurs from their start-up business is a significant determinant of the survival of the business. The degree of entrepreneurial satisfaction and success is predominantly influenced by venture efficiency, but may also be affected by social factors, financial factors, psychological factors and resource factors. The existing study has focused mainly on explaining the factors influencing entrepreneurial satisfaction and performance of the firm. Much of the literature has proved sales, profit growth, market share and growth in ROI are the major influencing factors for measurement of the firm’s performance. This study attempts to analyze the relationship between a firm’s performance and the entrepreneur’s satisfaction (Samantroy and Tomar 2018).

2. Literature Review and Hypothesis Development

2.1. Social Factor

The entrepreneur mindset completely depends on societal ethics and beliefs. Lots of work has been in embedded in women, including family responsibility and societal responsibilities. The performance of women directly impacts the satisfaction of entrepreneurial and organization performance. In the context of social factors, the welfare of the family, family motivation and moral directions from the family are all considered as social factors. In addition, social and cultural factors such as behavior of employees, support of the family and government policies towards women’s entrepreneurship play a pivotal role in women’s entrepreneurship. However, there is evidence of a work-family interface related to the entrepreneurship of Indian women (Kimbu and Ngoasong 2016). Women’s entrepreneurship supports the economy, enhancing educational opportunities and other family concerns, and even influencing social status in society. Hence, the relationship within the domain may be hypothesized as follows:

H1. 

Social support has an influence on women entrepreneurs’ work satisfaction.

2.2. Financial Factors

Financial support for entrepreneurs through government authorized financial agencies and schemes are the main factors in this area. Women entrepreneurs contribute to the development of the economy through their commercial activities. The women entrepreneurs must know the loan scheme accessibility of the governments of central and state (Atmadja et al. 2018). The governments of central and state schemes and self-awareness programs need to empower the rural women entrepreneur, encouraging women entrepreneurs to take a career aim. In the real context, in government-sponsored programs supporting the urban middle class, around 45 percent are getting the benefit, whereas 40 percent of the people are still struggling to begin start-ups because of a lack of financial support (Perez et al. 2017). Therefore, the central and state governments have schemes that will have to be reached automatically. This will enhance the motivation among the women entrepreneurs, and it will lead to motivation. Hence, the relationship within the domain may be hypothesized as

H2. 

Financial factors influence women entrepreneurs’ work satisfaction.

2.3. Psychological Factors

Some of the unique attitudes, like an urge to learn for learning, not being afraid of business risks or failures, and high self-esteem are qualities in psychological factors. Women entrepreneurs have the indigenous knowledge and skills to manage the enterprise. However, at the same time, they face major problems like social barriers, lack of adequate education, and lack of awareness about legal formalities, which act as impediments for successful entrepreneurship (Digan et al. 2019). Now, the women entrepreneurs look for positive social reinforcement to develop abilities in women entrepreneurs. However, the ability of the entrepreneurs to innovate continually and their risk-taking ability are the crucial factors for the business in its maturity stage. “Proper training and education for women entrepreneurs through Entrepreneurship Development programs will enable them to adapt to innovative practices in business and which in turn will facilitate innovations in products, process, marketing, in designing organization structure and marketing” (Yadav and Unni 2016). In reality, it is not happening because of making an intention of using the loans for their business and making the entrepreneurship development programs strong, and it should reach all the areas, such as rural and urban. Hence, the relationship within the domain may be hypothesized as below:

H3. 

Psychological factors influence women entrepreneurs’ work satisfaction.

2.4. Resource Factors

Women entrepreneurs face challenges, such as lack of skilled labor, difficulties in retaining work, and low productivity of labor, impacting performance and satisfaction of firms. Additionally, lack of financial assistance slows down the purchase of raw materials and up-upgrading of infrastructure facilities to start a company. Product demand, infrastructure, warehousing facilities, power supply, and skilled labor force are considered to measure resource factors (Kungwansupaphan et al. 2016). Based on the above discussion, the authors have developed the following hypothesis.

H4. 

Resource factors influence women entrepreneurs’ work satisfaction.

2.5. Satisfaction Factors

Entrepreneurial satisfaction can be measured through individual performance. Individual entrepreneurs must decide whether they want to invest more time and money, cut back, or shut down (Jha et al. 2018). It can also affect whether entrepreneurs work with their clients and staff efficiently. Business satisfaction, client earnings satisfaction, family support, and staff satisfaction can measure satisfaction factors. Entrepreneurship has enabled women to develop their personality in terms of improved social skill and status, improved awareness of social problems, and awareness about the government facilities (Nsengimana et al. 2017). Women-based establishments are created in informal sectors after political reforms. Women entrepreneurs are more active, satisfied, and highly concentrated in traditional and household-based establishments. Some factors motivating women entrepreneurs are profit maximization, specific sector incentives, and the size of the company and its nature. Based on the above discussion, the following hypothesis has been developed.

H5. 

The satisfaction level of women entrepreneurs mediates the relationship between firms’ performance and environmental factors.

2.6. Firms’ Performance

There is evidence of women in leadership roles with return on equity, sales, assets, and investments of major corporations. The participation of women has increased in small-scale business, and it is observed that there has been a significant contribution by women entrepreneurs toward employment generation. Average annual growth in previous year’s revenue, previous year’s market share increase, previous year’s profit growth, and return on capital growth are considered metrics for calculating the success of the company (Setini et al. 2020). Any organization performance will depend on the following factors: identified leadership, social enterprise planning, community involvement, creative funding, human capital, legal support, and social enterprise marketing (Zhu et al. 2019). The women entrepreneur’s success depends on sales turnover and job creation. It also indicates risk running and expanding the business in small business entrepreneurs, and their expectations influence the organization performance. Based on the above discussion, the following hypothesis has been developed by the authors.

H6. 

Self-satisfied women entrepreneurs build successful businesses.

3. Methodology

Comprehensive literature reviews on women’s entrepreneurship consisting of various factors that impact performance and risk attitude to familiarize the status of the existing environment in the industry. To understand the satisfaction and entrepreneurial performance of women, a structured questionnaire was administered, and a state-wise survey was conducted using the survey method. The instrument has been designed applying various factors based on past studies and readability tests and administered using the cluster and snowball sampling method. The descriptive and exploratory research design was capitalized on to generate primary and secondary data. The hypothesis test was undertaken to understand the relationship between various variables using Pearson correlation.

The study aims to understand which factors play an important role in women’s entrepreneurship that influences entrepreneurial satisfaction and firm performance. The present study has made an attempt to explore the various factors, which fall under social, financial, psychological, resource, satisfaction, and firms’ performance (Palmer et al. 2019). The study was conducted from June 2020 to December 2020 in India, the data were collected from various states of India, and more than 400 women entrepreneurs participated. Their opinions were recorded through a structure questionnaire and tested using the developed hypotheses through Cronbach’s alpha test, exploratory factor analysis, confirmatory factor analysis, and goodness-of-fit to know the cohort between the questions through the alpha test. The Cronbach’s alpha values are very positive for all factors, proving good internal consistency (Refer to

Table 1. Kaiser–Mayer–Olkin and Cronbach’s alpha test.

Variable	KMO	Alpha
Social Factor	0.689	0.764
Psychological Factors	0.565	0.823
Financial Factors	0.789	0.755
Resource Factors	0.523	0.789
Satisfaction Factors	0.625	0.755
Firms Performance	0.623	0.889

Source: Data analysis.

).

The data collected were subjected to exploratory factor analysis to find out important factors influencing women entrepreneurs. The data were subjected to a varimax rotation method for good prediction of results. As for the first step in data cleaning, an image correlation matrix was worked out. The indicator variables with less than 0.50 along the diagonal axis were deleted first. Then, communalities were checked, and indicator variables with extracted communalities less than 0.5 were dropped from the analysis. In the last stage, the rotated matrix of the components was checked, and indicator variables with less than 0.5 values were dropped from the analysis. The indicator variables with cross-loadings were dropped from the analysis. The questions with eigenvalues of less than 1.0 were not included in the analysis. Data cleaning was carried out for missing values and outliers. Using factor analysis for psychological factors, the 12 questions (statements) were reduced to four under one factor. The financial factors were reduced to four measurement variables under one factor, explaining 64% of the total variance. The resource factors resulted in four measurement variables after dropping 17 variables, resulting in one factor with 72% of the total variance. The satisfaction variables were reduced to four measurement variables, resulting in one factor explaining 67% of the total variance. All elements have good load factors and general characteristics (Table 1). The firms’ performance factors were reduced to four, about 78% of the total variance associated with this design.

Reliability Analysis

To find out the internal consistency of the data, Cronbach’s alpha and split-half values are calculated. The split-half reliability of the data was enumerated by dividing respondents into two groups of equal sizes. The data collected from women entrepreneurs proved reliable, since the mean values of the two groups are more significant than average (group 1: 3.37, group 2: 3.46). Additionally, there is no significant difference in the mean values of the two groups (F0.941, p0.05). Cronbach’s alpha values of all the constructs are above 0.7 (Table 1).

4. Analysis and Findings

The dual usage of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) helped in the validation of the construct variables in the study. The explanation of each construct is given as follows.

The social factor consisted of four variables, with an average score of 4.1 (

Table 2. Summary of exploratory factor analysis.

Constructed Factors	Mean	SD	FL	Comm	EigenValue	V.E (%)
Social Factor	4.1				2.23	53.5
Social acceptance	4.0	0.937	0.547	0.578
Family moral support	3.6	0.746	0.758	0.557
Motivation from Family	3.8	0.812	0.808	0.656
Family welfare	3.9	0.913	0.817	0.668
Psychological Factors	4.0				2.38	62.257
Higher self-esteem	4.2	0.662	0.527	0.536
Confidence against failures and risk	4.1	0.984	0.782	0.612
No easy discouragement	4.1	0.853	0.834	0.696
Learning enthuse	4.2	0.597	0.505	0.522
Financial Factors	2.5				2.59	65
Governmental aid/support	3.6	1.214	0.736	0.526
Support from financial agencies	2.0	0.92	0.626	0.517
Motivation from business income	2.4	0.858	0.516	0.503
Self-awareness about Govt. schemes	2.3	1.188	0.725	0.546
Resource Factors	3.4				4.343	73.5
Raw material availability	3.3	0.873	0.573	0.513
Market demand for product	3.5	0.766	0.782	0.814
Availability of infrastructure	3.4	0.733	0.834	0.816
Availability of warehousing facilities	3.3	0.715	0.895	0.849
Satisfaction Factors	4.2				2.785	68.12
Satisfaction in business	4.3	0.68	0.774	0.614
Satisfaction in current business earning	4.1	0.745	0.78	0.637
Satisfaction in family support for business	4.2	0.57	0.667	0.544
Satisfied with workers	4.0	0.633	0.963	0.940
Firms Performance	3.2				5.99	79.4
Sales growth	3.6	0.936	0.783	0.631
Growth of market share	4.1	0.782	0.514	0.576
Profit growth	3.9	0.707	0.616	0.515
Growth in the return on capital	2.2	1.06	0.522	0.74

Source: data analysis; Note: SD–standard deviation; FL–factor loading; Comm–communality; VE–variances.

). About 78% of the total respondents believe that they work for the benefit of society (3.9), and 72% believe doing business has helped them to improve the wellbeing of the family (M3.6). About 76% of women believe that their family provides a source of motivation (3.8) and moral support (4) to start a business. An intensive study of this factor leads us to understand that family moral support is an important motivator for women to start and maintain a business. The psychological factor is considered to be the emotional reaction of the entrepreneur. Here, the average score is 4.0 (Table 2). The results showed that 84% of the respondents have high self-esteem (M 4.0), the level of confidence for doing business is found to be 84%, and, importantly, a remarkable number of women have expressed their emotional strength as they believe they are not easily discouraged (82%). In addition, 84% of the women entrepreneurs expressed their enthusiasm for learning while doing business (4.2). Analysis of this factor indicates that women entrepreneurs are not afraid of failures. The average value for the financial factor is 2.5, which is well below the average and emphasizes the reality of governmental and banking schemes for women’s entrepreneurial empowerment. The government schemes and aids are the major variables initiated by the union and various federal governments in India. About 62% of the respondents indicated that state institutions do not have enough financial resources (2.12) to provide for women entrepreneurs. In addition, 68% of respondents are very unlikely to feel motivated by financial support from the government (3.3). Women entrepreneurs are not aware of the various lending schemes offered by the government. A general analysis of this factor indicated that women entrepreneurs do not have access to government financial schemes.

The availability of resources is one of the major factors determining the success of many endeavors. The average value for resource factor is 3.4, i.e., 68% of the respondents believed they are considering the availability of resources. It is noted that the availability of infrastructure is not poor (3.4), availability of raw material seems to be not highly satisfactory (3.3), market demand is moderately fine (3.5), and warehousing facility is also maintaining similar challenges (3.3). The level of satisfaction in activities enhances enthusiasm, and here the average satisfaction level of respondents is 4.2. The core variables for this factor are satisfaction in business (4.3), earning in business (4.1), level of satisfaction in family support for business (4.2), and satisfaction with staff members (4.0). These variables emphasize that overall satisfaction levels are acceptable and more than 80%. The performance of the firm determines the stability of business, and the respondents believe they are performing moderately. The vital variables of performance sales growth are (3.6), growth of market share (4.1) is considerably good, profit growth (3.9) and growth in the return on investment (2.2) are lesser than an acceptable level. These factors have efficiently analyzed this factor, indicating that women entrepreneurs are focused on success due to increased sales and market capitalization.

4.1. Confirmatory Factor Analysis

The CFA emerged after applying EFA. These variables were used as equivocal of corresponding hidden construct variables. The results showed that all factors were closely related to constructing variables (

Table 3. Results of confirmatory factor analysis.

Latent Construct	Variables	SRW	CR	R2
Social factors	SF2	0.720	8.105 ***	0.398
	SF4	0.657	7.651 ***	0.604
	SF5	0.712	Ref	0.501
	SF9	0.782	2.220 **	0.268
Psychological factors	PF3	0.522	2.427 **	0.169
	PF5	0.511	Ref	0.236
	PF6	0.922	3.100 **	0.877
	PF7	0.522	3.890 **	0.369
Financial factors	FF2	0.662	Ref	0.387
	FF7	0.563	4.503 ***	0.236
	FF9	0.552	3.889 ***	0.152
	FF15	0.733	4.542 ***	0.301
Resource factors	RF1	0.624	5.587 ***	0.195
	RF2	0.575	2.811 *	0.135
	RF3	0.752	Ref	0.578
	RF4	0.991	7.100 ***	0.981
Satisfaction factor	S1	0.643	Ref	0.488
	S2	0.722	4.874 ***	0.492
	S3	0.591	4.926 ***	0.167
	S4	0.523	1.929 *	0.136
Firms Performance	FP3	0.361	Ref	0.145
	FP11	0.322	3.127 **	0.197
	FP12	0.521	3.873 ***	0.172
	FP18	0.422	3.907 ***	0.158

Significance: * pB0.05, ** pB0.01, *** pB0.001. Source: Data analysis.

). Good model fit was established as GFI, and AGFI and CFI values in all constructions were higher than 0.9. Moreover, RMR values are less than 0.05. The RMSEA value was less than 0.08 (

Table 4. Summary of goodness-of-fit.

Constructs	χ2	DF	Chi Square/DF	CFI	RMR	GFI	AGFI	RMSEA	Bentler–Bonett Coefficient
Social	3.763	2	1.883	0.984	0.021	0.99	0.97	0.059	0.921
Psychological	1.025	2	0.514	1.000	0.010	1	0.99	0.0	0.956
Financial	3.126	2	1.565	0.991	0.027	0.97	0.93	0.021	0.921
Resource	29.627	9	3.294	0.987	0.042	0.97	0.93	0.090	0.987
Satisfaction	1.366	2	0.683	1.000	0.053	1	0.99	0	0.9836
Firms Performance	27.903	18	1.56	0.936	0.035	0.98	0.95	0.066	0.947

Source: Data analysis.

) (Kenny et al. 2015). The measures of the same concept and instrumental questions are correlated in converged validity measures. The higher correlation indicates scales measuring the intended concept or variable measurement validity (Raykov et al. 2018). “A scale with a Bentler–Bonett coefficient of 0.90 or more indicates solid convergent validity” (Bentler 2006). The Bentler–Bonett coefficient for all the scale measurements was higher than 0.9 (Table 4), indicating strong convergent validity (Bentler and Bonett 1980).

The discriminant validity is provided when measures of constructs must not be highly related to each other. The importance of evaluating discriminant validity is to make a successful assessment so that no item should load more highly on another construct than on the construct to which it is supposed to belong. The studies of Cronbach and Meehl (1955), Vaske et al. (2017), and de Vet et al. (2017) have emphasized the importance of evaluating the validity of the discriminant constructs used. A successful assessment of the reliability shows that there must not be a strong correlation with each other test, which is designed to measure theoretically different concepts. This assessment is administered in two ways. The diagonal elements of the correlation matrix (

Table 5. Discriminant validity and correlation analysis.

Constructs	Social	Psychological	Financial	Resource	Satisfaction	Firms Performance	p Value
Social	0.625						0.153
Psychological	0.041	0.693					0.598
Financial	0.030	0.059	0.553				0.208
Resource	0.008	0.045	0.048	0.626			0.001
Satisfaction	0.108	0.077	0.108	0.132	0.548		0.507
Firms Performance	0.285	0.4	0.007	0.075	0.135	0.763	0.065

Source: Data analysis.

) signify the square root of average variance. The result emphasized that each diagonal element is more significant than all the entries in corresponding rows and columns, of which the diagonal element is a part. Hence, discriminant validity is attained, as outcomes of the analysis meet this condition. Additionally, for good discriminant validity, the elements should not load higher in another design (Loudon et al. 2017). The data satisfy both criteria for validity. Hence, it is proven that discriminant validity is adequate.

The following table (

Table 6. Structural business modeling and composite reliability.

Dependent Variable	Independent Variable	SRW	CR (Sig.)	R2
Firms’ performance	Social variable	0.177	3.821 ***	0.3
	Psychological variable	0.268	5.656 ***
	Finance variable	0.032	2.586 *
	Resource variable	0.069	2.254 *
Entrepreneurial satisfaction	Social variable	0.079	1.985	0.1
	Psychological variable	0.059	0.952.
	Finance variable	0.109	1.99 *.
	Resource variable	0.144	2.532 **.

Source: Data analysis; Significance: * sig < 0.05; ** sig < 0.01; *** sig < 0.001.

) refers the structural business modeling and composite reliability.

4.2. Structural Equation Modeling (SEM)

Structural equation modeling (SEM) is a statistical technique that demonstrates relationships between many variables. In the present study, the authors have studied factors affecting women’s satisfaction and business performance of the firms owned by women. The results are discussed, as mentioned below. AMOS’s path model was created to assess causal relationships between various factors affecting women’s entrepreneurship, as shown in Figure 1. Social, psychological, financial, and resource availability factors have been analyzed using generalized scales (Hayes et al. 2017). Table 2 and Table 3 present standardized assessment values and indicators of reliability of compliance. All indices indicate the reliability of the entire model: GFI, CFI, NFI, and AGFI significantly exceed 0.9, and RMSEA is close to 0.05. Of the nine pathways analyzed, seven are significant relationships, while two are non-significant (Table 5).

A study of the influences of all factors on the firms’ performance results showed that all factors account for 30% of deviations. R2 .300 is mediated by entrepreneurial satisfaction. The psychological factor is the most significant predictor (SRW 0.255, Sig. B 0.001), followed by social factors (SRW 0.188, Sig. B 0.001), resource factors (SRW 0.058, Sig. B 0.05), and financial factors (SRW 0.012, Sig. B 0.05) when explaining the activities of the firm (Table 6). In addition, a study of the factor effect on satisfaction has shown that resource factors (SRW 0.134, Sig. B 0.001) and financial factors (SRW 0.103, Sig. B 0.05) explain the difference in entrepreneur satisfaction. It can be observed that social factors, to a large extent, explain the firms’ performance, but do not affect satisfaction. Hence, the influence of social support on firms’ performance is partially accepted. The inference of this hypothesis is that women entrepreneurs with higher social support tend to achieve better firm performance. The first hypothesis is partially accepted. Financial factors significantly and positively influence satisfaction and firms’ performance. The satisfaction of women entrepreneurs with financial factors leads to better firm performance. Women entrepreneurs have difficulty in procuring loans, and this hypothesis is accepted, as many women entrepreneurs find it difficult to get loan approvals. Psychological characteristics influence the firms’ performance and partially influence the satisfaction of women entrepreneurs, and psychological characteristics measure willingness to take the business risk. Women entrepreneurs are willing to take business risks. The women entrepreneurs have agreed that they do face problems with resource factors. It was noted that self-satisfied women entrepreneurs build successful businesses.

5. Discussion

Indian women entrepreneurs are very keen to do business. Women have been taking an interest in income generation through entrepreneurship. This research examines factors that influence women’s satisfaction with doing business and entrepreneurship performance. Research shows that women who have been satisfied with their work achieved a high level of consistent performance. This is consistent with the findings of Covin and Slevin, 1989 (Covin et al. 2020; Gupta et al. 2018; Lee et al. 2019). The severity of various factors (positive and negative), such as social, psychological, financial, and resources, is critical to the satisfaction and effectiveness of women entrepreneurs. The results of the study indicate that society will accept the family support that will lead to motivation (Juma and Sequeira 2017). The motivated entrepreneur engages with a lot of work, that work empowers with money, and this will support the family welfare. Therefore, women entrepreneurs are encouraged by society.

Another factor of women entrepreneurs highlights the relationship between psychological factors and female entrepreneurs’ satisfaction, where they play an important role in satisfying businesswomen, as the desire for strength and belonging is expressed in psychological features (Isiwu and Onwuka 2017). If entrepreneurs can only learn new approaches, new ideas can be implemented, because they seldom fear failure. Psychologically, as seen in this study, they have the confidence to face failure and remain at work. The results of the study show the importance of financial factors in terms of the level of satisfaction of businesswomen. Government financial aid and the support of families affect the success of businesses (Mascarenhas et al. 2017). However, if they are satisfied, they will remain relevant, as satisfaction is more expressed in the financial benefits of businesses that can only occur if they have access to them through financial institutions or their families. The women entrepreneurs have some difficulties in various forms like collecting raw material, gathering information about the market and the value, lack of infrastructure, and getting the right warehousing facilities.

For the women entrepreneurs in selected organizations, most of the women entrepreneurs have good success rates through a handful of business earnings (Welsh and Kaciak 2018), because they get enough support from the family members and the staff of the company. By keeping all observations of women entrepreneurs, gaining the market sales growth, share, profit, and return of the capital, they felt that the firms had performed well.

6. Conclusions

The present study provides some contribution to the existing literature on women entrepreneurs, especially in India. In India, successful women entrepreneurs are influenced significantly by social factors. A psychological factor, such as the ability to face failures, is predominant among women entrepreneurs in India. Entrepreneurial satisfaction is dependent upon firm performance. The authors have made a quantitative study by having various factors that influence women entrepreneurs. The study found that social, psychological, financial, and resource factors will impact women entrepreneur satisfaction and firm performance (Rosca et al. 2020). The authors have some of the suggestions that will be helpful for the government and other statutory bodies to resolve issues facing the woman entrepreneur. Banks need to promote and encourage women entrepreneurs by offering cost-effective financial assistance. Governments should channelize their resource allocation to rural women entrepreneurs to utilize resources for productive purposes. Indian rural areas should be built with proper infrastructural facilities and market connectivity. The empowerment of women entrepreneurs’ knowledge in the domain through various programs through training with financial support is needed (Lenka and Agarwal 2017).

7. Future Research Directions

The study can be extended by taking more sample size in different areas of India. The study can be extended by having the same industry (i.e., SMEs) or any other industry. Moreover, a comparative study can be possible. The study can be extended by having more variables, which are not taken in the study.