Investigating Factors Affecting Venture Growth Intention for Women

Entrepreneurs

by

Beth Johanna Gitlin

A dissertation

submitted to the School of Psychology

in the College of Psychology and Liberal Arts at

Florida Institute of Technology

in partial fulfillment of the requirements

for the degree of

Doctorate of Philosophy

in

Industrial/Organizational Psychology

Melbourne, Florida

July 2019

We the undersigned committee hereby approve the attached dissertation:

Investigating Factors Affecting Venture Growth Intention for Women

Entrepreneurs

By

Beth Johanna Gitlin

_____________________________

Lisa A. Steelman, Ph.D.

Professor and Dean

College of Psychology and Liberal Arts

Dissertation Adviser

_____________________________

Jessica L. Wildman, Ph.D.

Associate Professor

Industrial/Organizational Psychology

_____________________________

Gary N. Burns, Ph.D.

Professor

Industrial/Organizational Psychology

_____________________________

Enrique Perez, Ph.D.

Assistant Professor

Bisk College of Business

iii

Abstract

Title:

Investigating Factors Affecting Venture Growth Intention for Women

Entrepreneurs

Author:

Beth Johanna Gitlin

Principle Advisor:

Lisa Steelman, Ph.D.

During the past several years the number of women-owned firms increased

by 45% from 2007-2016, a rate five times faster than the national average. However,

their overall venture growth is far below the national average. The benefits of

studying the internal and external context in which this phenomenon has occurred

will help us to understand what types of interventions may contribute to enhancing

venture growth intention for women entrepreneurs. In light of the scant research

linking factors such as self-confidence, access to role models, perceived family

support and risk-taking to venture growth intention for women entrepreneurs, this

study examines a serial mediation model based partially on Ajzen’s Theory of

Planned Behavior (1991) and feminist theory. The proposed hypotheses were

investigated using data collected from 196 women entrepreneurs affiliated with a

national network of Women’s Business Centers partially funded by Small Business

Administration grants throughout the US. Hypotheses received mixed support. Risk

iv

propensity was positively related to venture growth intention. The relationship

between internal self-confidence and venture growth intention was mediated by risk

propensity. Neither access to role models nor perceived family support affected

venture growth intention through internal self-confidence and risk propensity.

Keywords: venture growth intention, women entrepreneurs, role models, self-

confidence, risk, family support.

v

Table of Contents

Abstract .................................................................................................................... iii

Table of Contents ....................................................................................................... v

List of Figures ........................................................................................................ viii

List of Tables............................................................................................................ ix

Acknowledgements .................................................................................................. xi

Introduction ................................................................................................................ 1

Literature Review ....................................................................................................... 5

Theory of Planned Behavior .................................................................................. 5

Feminist Theory ................................................................................................... 11

Gender and Entrepreneurship ............................................................................... 18

Model Development ............................................................................................. 21

Venture Growth Intention .................................................................................... 23

Risk Propensity .................................................................................................... 27

Internal Self-Confidence ...................................................................................... 30

Access to Role Models ......................................................................................... 35

Perceived Family Support .................................................................................... 39

Hypothesis Development ......................................................................................... 42

Method ..................................................................................................................... 47

Participants ........................................................................................................... 47

vi

Procedure.............................................................................................................. 49

Measures .............................................................................................................. 49

Results ...................................................................................................................... 54

Data Cleaning ....................................................................................................... 54

Descriptive Statistics ............................................................................................ 55

Preliminary Analysis ............................................................................................ 56

Hypothesis Testing ............................................................................................... 57

Exploratory Analyses ........................................................................................... 60

Discussion ................................................................................................................ 62

Limitations ........................................................................................................... 69

Theoretical Implications....................................................................................... 70

Practical Implications ........................................................................................... 75

Future Research .................................................................................................... 78

Conclusion ............................................................................................................... 79

References ................................................................................................................ 81

Appendix A: IRB Approval ................................................................................... 121

Appendix B: Venture Growth Intention Scale ....................................................... 122

Appendix C: Access to Role Models Scale ........................................................... 123

Appendix D: Perceived Family Support Scale....................................................... 125

vii

Appendix E: General Risk Propensity Scale .......................................................... 127

Appendix F: Internal Self-Confidence Scale ......................................................... 128

Appendix G: Demographics ................................................................................... 129

viii

List of Figures

Figure 1. Ajzen's Theory of Planned Behavior (Ajzen, 1991) ................................... 6

Figure 2. Entrepreneurial Event Model (Shapero & Sokol, 1982) ............................ 8

Figure 3.Theoretical Model ...................................................................................... 23

Figure 4.Family embeddedness perspective on new venture creation (Aldrich &

Cliff, 2003) ............................................................................................................... 40

Figure 5. First Stage Moderated Mediation with PFS as Moderator ....................... 61

Figure 6. Interaction effect of internal self-confidence and perceived family support

on risk-propensity .................................................................................................... 62

ix

List of Tables

Table 1. Demographics ............................................................................................ 48

Table 2. Summary of Intercorrelations, Means, and Standard Deviations for Study

Variables .................................................................................................................. 55

Table 3. Measures of Global Fit ............................................................................... 57

Table 4. Results of the Serial Mediational Testing for Hypotheses 3 and 4. ........... 58

Table 5. SEM Fit Statistics....................................................................................... 60

x

To my Mother and Father,

Pat and Hank Gitlin.

Thank you for your gift of

The love of learning.

I miss you greatly!

xi

Acknowledgements

My deepest gratitude and appreciation are shared with my advisor, Dr. Lisa

Steelman, for her encouragement, feedback and moral support when I needed it the

most. To the members of my committee, Dr. Jessie Wildman, Dr. Henry Perez and

Dr. Gary Burns, thank you for your thoughtful feedback and expertise shared along

this journey.

Thank you to the love of my life, my greatest cheerleader, and remarkably

patient husband, Scott Hoffman, who supported and encouraged me during the

eight years of this challenging and rewarding journey. Thank you for being my soft

place to fall.

Finally, I want to thank all of the amazing, wonderful women in my life

who have shown their collective support and encouragement through fantastic

conversations, long bicycle rides, amazing dragon boating experiences and

extensive mentoring and coaching sessions. You have impacted my life

significantly!

1

Introduction

Economic growth is a key concern for any country that wants to be able to

reduce its unemployment rate, create a better living and working environment for

its citizens, and demonstrate influence in the world arena. In the past, US economic

growth was largely derived from the top 500 largest America firms. However, a

major shift occurred from 1970 to 1996 in which the Fortune 500 employment

share dropped from 20 percent in 1970 to 8.5 percent in 1996 (Carlsson, 1992;

1999). The shift towards smaller firms can be attributed to intensification in global

competition and increase in market fragmentation. Also, rapid changes in

technological advances have made the world a “flatter” place and increased the

opportunities for individuals who have access to a computer and the internet to start

companies from anywhere in the global environment (Friedman, 2005).

Entrepreneurs are inarguably key drivers of economic growth regarding the

creation of new wealth and jobs. Additionally, many of them are the inventors and

innovators of new products, services and technologies that disrupt industries and

create new opportunities for other people and organizations. One-third or more of

the new jobs created globally are a result of entrepreneurial activity (GEM, 2005).

Economic growth through increased revenues and jobs is generally perceived as

good (Edelman et al., 2010) and considered to be a measure of entrepreneurial

success (Davidsson, 1989). Many researchers agree that entrepreneurial activity has

a significant impact on economic growth within most industrialized nations

2

(Capellaras et al., 2016; Sternberg & Wennekers, 2005). Furthermore, the founder’s

aspirations and expectations are important contributors to business growth (Baum

& Locke, 2004; Cassar, 2006; Davidsson, 1989; Delmar & Wiklund, 2008;

Wiklund & Shepherd, 2003). Entrepreneurs are instruments of social, political,

technological and economic change. They foster creativity and innovation and

contribute in a meaningful way to overall economic development (Brush et al.,

2004)

The creation and growth of women owned firms during the last twenty

years has contributed significantly to global economic development. For example,

it is estimated that there are now 11.3 million women-owned businesses in the

United States, employing nearly 9 million people and generating over $1.6 trillion

in revenues (AMEX, 2016). The number of women-owned firms increased by 45%

from 2007-2016 compared to a 9% increase among all businesses. The number of

women-owned firms during the past several years has grown more than five times

faster than the national average. For over 38% of the country’s businesses, women

are now the majority owners – up from 29% in 2007. Their firms employ 8% of the

private sector workforce – up from 6% in 2007. Employment growth in women

owned firms is up 18% since 2007 compared to a 1% decline among all US firms.

The increase in number of women starting businesses as well as employment

growth in women owned firms since 2007 is encouraging and relevant, but an

additional statistic tells a different story relating to the growth of women-owned

3

firms compared to the national average. Nationwide, just 9% of all firms are

considered to have “high economic impact” – in other words, they generate more

than $500,000 or more in revenues. Only 3% of women-owned firms generate the

equivalent or more (AMEX, 2016).

Growth is often seen as a successful outcome for small business as it not

only has a positive impact on the business itself, but it also has an impact on the

regional and national economies collectively (Costin, 2012). Little is known about

the small business growth phenomenon and theoretical development has been

limited (Wiklund et al., 2009). The research literature seems to be highly

fragmented.

Prior research on women’s entrepreneurship suggests that women choose to

deliberately not participate in venture growth (Goffee & Scase, 1983). Other

research reveals that women entrepreneurs may have conservative growth

expectations (Chaganti, 1986; Cliff, 1998) or lower growth expectations compared

to men (Rosa et al., 1996). Other studies indicate that female entrepreneurs have

different growth intentions than male entrepreneurs. Some researchers suggest

perhaps there is a lack of knowledge in understanding the growth aspirations of

women (Morris et al., 2006).

There is a lack of understanding and failure to conceptualize and build

explanatory growth theories regarding female entrepreneurship (Costin, 2012).

Carter and Shaw (2006) suggest that since 1971 (when research on women’s

4

entrepreneurship was first developed) there has been an increased awareness that

this field has been seriously underdeveloped – as opposed to being neglected. They

have indicated that growth in this field has occurred because of three parallel

developments. First, enhancement in data analysis and methodological

sophistication has occurred within the research field. Second, the research focus has

been increasingly on specialized areas and has become less broad and descriptive as

was the case in earlier studies. Third, earlier studies questioned if gender made a

difference, and now the focus is on how gender may influence the experience of

business ownership (Carter & Shaw, 2006).

Using the Theory of Planned Behavior (Ajzen, 1991) and Feminist Theory

as background, the purpose of this study is to examine how women entrepreneurs

make the decision to grow their businesses – in other words, what factors enhance

their desire to grow their businesses and what factors may inhibit their desire to

grow their business. The desire to grow the business is commonly referred to as

venture growth intention. It is assumed that before venture growth occurs, the

intent to grow one’s business must be established. The study of women’s

entrepreneurship and how venture growth intention is determined is extremely

important as it will inform ways in which female entrepreneurs make

entrepreneurial growth decisions considering internal and external factors and help

us to understand how to develop interventions that will enhance and create more

opportunities for choices in growth intention.

5

The primary focus of this study is to determine which internal and external

factors predict the likelihood of venture growth intentions by established women

entrepreneurs. A secondary focus is to determine what mechanisms impact the

relationship between these internal/external factors and venture growth intention.

Some suggest that growth is generally perceived as good (Edelman et al., 2010) and

that it is considered a measure of entrepreneurial success (Costin, 2012). As more

women entrepreneurs pursue growth, their contribution to economic growth and job

creation will steadily and significantly increase.

Literature Review

Theory of Planned Behavior

The purpose of this study is to examine external social norms and internal

individual attitudes that facilitate or inhibit venture growth intentions among

women entrepreneurs. More specifically, this study examines the mechanism of

action by which the factors under investigation may work to enhance venture

growth intentions among women business owners. This study will use two

theoretical frameworks to support the hypotheses – the Theory of Planned Behavior

and Feminist Theory.

The Theory of Planned Behavior (TPB), is a framework used to model

intentions and behaviors. It specifies the determinants or antecedents of intention to

perform a planned behavior as depicted in Figure 1 below (Ajzen, 1991).

6

Figure 1. Ajzen's Theory of Planned Behavior (Ajzen, 1991)

Intention captures the motivational factors that influence behavior and specifies

how hard an individual is willing to try and how much effort she is planning to

exert in order to execute a certain behavior (Lortie & Castogiovanni, 2015). At the

individual level, the strength of the intention is determined by attitudes toward the

behavior, subjective or social norms, and perceived control over the behavior.

Intention, along with perceived behavioral control, determines actual behavior.

Attitude is a subjective construct that refers to the degree to which a person has a

favorable or unfavorable appraisal of the identified behavior (Ajzen, 1991).

Subjective norm or social norm refers to the social pressure an individual may feel

to perform or not to perform the behavior. This social pressure is usually conveyed

by those closest or most important to that individual (Ajzen, 1991). Perceived

behavioral control is a subjective assessment of one’s ability to perform a certain

behavior with ease or difficulty; and, the assumption is made that it reflects past

7

experience as well as future obstacles or roadblocks (Ajzen, 1991). Generally

speaking, the more favorable the attitude and subjective norm with regard to the

behavior, and the greater the perceived behavioral control, the stronger the

individual’s intention will be to perform the behavior (Ajzen, 1991). Perceived

behavioral control plays a dual role in the TPB model. It helps to inform intentions

as well as interacting with them to jointly affect behavior (Maes et al., 2014).

The TPB has been an influential and well-utilized conceptual framework to

study human behavior (Ajzen, 2002; Armitage & Conner, 2001). Moreover, it has

been used frequently and in a multitude of ways in entrepreneurial research

literature as an explanatory model for entrepreneurial intentions, as well as

entrepreneurial activity (Kolvereid & Isaksen, 2006; Souitaris et al., 2007; Verheul

et al., 2012). For example, Kautonen et al. (2015) tested the TPB model to

determine how well it explained the emergence of business start-up behavior. They

found that all hypothesized relationships were significant and positive. Moreover,

subjective norms, attitude and perceived behavioral control explained 59% of the

variation in intention. The significance of this study showed that the theory (which

has been used in multiple entrepreneurial intention studies with implicit

assumptions formulated) can now be applied with demonstrated validity. An

additional study used the TPB model to focus on regional cultural clusters

predicting entrepreneurial intent in 12 countries (Engel et al., 2008). The

researchers wanted to understand the degree to which the antecedent variables

8

suggested in Ajzen’s model would predict entrepreneurial intent. They found that

the degrees varied by culture and only two countries (Finland and Russia) had all

three antecedent variables as statistically significant predictors of intention. The

sample used was university business students and they additionally surmised that

the variables in Ajzen’s model as operationalized in this particular study had the

statistically significant ability to explain up to 42 percent (Spain and USA) of the

variance in entrepreneurial intent. The Theory of Planned Behavior model has been

the dominant theoretical framework within the entrepreneurial intention literature

along with Shapero and Sokol’s (1982) entrepreneurial event model (Schlaegel &

Koenig, 2012).

The entrepreneurial event model, shown below in Figure 2, uses perceived

desirability, perceived feasibility and the propensity to act as antecedents that drive

intentions.

Figure 2. Entrepreneurial Event Model (Shapero & Sokol, 1982)

Perceived desirability is defined as the degree to which a person is drawn towards

becoming an entrepreneur and indicates individual preferences for entrepreneurial

behavior (Shapero & Sokol, 1982). An individual’s propensity to act is one’s

9

personal nature to act on one’s own decisions. There is a control element aligned

with this concept that leads to the desire to gain control by taking action. Shapero

suggested internal locus of control as an operationalization of this variable

(Krueger et al., 2000). Finally, perceived feasibility has been defined by Shapero

and Sokol (1982) as the degree to which one feels capable of starting a business.

Krueger (1993) was the first to test this model sampling 126 university business

students and found significant support for Shapero’s model in which

entrepreneurial intentions are largely derived from perceptions of feasibility,

perceptions of desirability, and a propensity to act which derives from control

beliefs. He also found that the impact of prior entrepreneurial exposure on

intentions is mediated indirectly through perceived desirability.

These two models overlap to a certain degree in which perceived

desirability and perceived feasibility (Shapero and Sokol’s model) appear to be

compatible with Ajzen’s (1991) attitudes and perceived behavioral control,

respectively (Krueger et al., 2000; van Gelderen et al., 2008). Both of these models

were found to have almost equal predictive power (Krueger et al., 2000).

In most entrepreneurial literature, the TPB has been used to explain

entrepreneurial intentions. A majority of the literature has focused on attitudes (e.g.

risk taking), social norms (e.g. perceived social pressure) and perceived behavioral

control (e.g. self-efficacy), that may predict if an individual has the intention to

start a business at some point in the near future. Many scholars capture this variable

10

as entrepreneurial intent and a few scales have been developed, although not yet

validated to measure entrepreneurial intent such as the Entrepreneurial Intention

Questionnaire (EIQ, Linan & Chen, 2009) and the intentions measurement

developed by Thompson (2009). A majority of the articles within entrepreneurial

literature have considered parts of the TPB or have used alternate configurations of

the model to explain their hypotheses and predictions (Lortie & Castogiovanni, 2015).

Furthermore, impressive support has been established for the various individual

relationships within the TPB model for predicting entrepreneurial intention. While a

considerable amount of research has been conducted using the TPB to explain and

predict intentions to begin new ventures, there exists a gap in the literature with regard

to researchers using this model to explain or predict venture growth intention. One of

the reasons this gap exists is that the majority of literature on venture intentions

research has used student samples to research entrepreneurial intention. The difficulty

in gaining insight to venture growth intention has occurred due to lack of access to the

appropriate entrepreneurial population to study – i.e. women who have been in

business for at least one or more years. It is the aim of this study to use the TPB as an

explanatory model to assist in predicting some of the behaviors, attitudes and

motivations that are distinctive in women entrepreneurs’ decision-making process with

regard to intention to grow their businesses, as opposed to starting a business. If we can

determine the action mechanisms that lead to venture growth intention for women

entrepreneurs, then training programs can be targeted specifically for women

entrepreneurs that address specific issues which may be preventing them from

11

growing their businesses.

Feminist Theory

Previous research has failed to theoretically account for gender in models

predicting entrepreneurial intentions of various types (including start-up intention

and growth intentions). Explanatory theories on entrepreneurship for and by

women are still lacking in academic research. The lack of research on women’s

entrepreneurship has been well documented (Baker et al., 1997; Brush et al., 2009;

de Bruin et al., 2006; Gatewood et al., 2003). Past research has explored the

motivation for women starting businesses (Brush et al., 2002; Buttner & Moore,

1997; Scott, 1986; Stevenson, 1986), decisions about business growth (Morris et

al., 2006; Orser & Hogarth-Scott, 2002; Shelton, 2006), work-family balance

(Adkins et al., 2013; Caputo & Dolinsky, 1998; DeMartino et al., 2006; Kirkwood

& Tootell, 2008) and the survival and sustainability of women-owned businesses

(Watson, 2003; Williams, 2004). Until recently, entrepreneurship has been

represented in the literature as an endeavor that provides gender neutral

meritocratic opportunities to individuals to realize their full potential for wealth

creation and innovation (Ahl & Marlow, 2012). Yet, these opportunities, arguably,

are not gender neutral. Additionally, entrepreneurship has been described in terms

of behaviors that are associated with masculine, agentic qualities (similar to the

literature on leadership) that include innovation, risk taking, and emphasis on

growth (Carland et al., 1984; Curran, 1991; Green and Cohen, 1995). The discourse

12

on entrepreneurship in the research literature point to features that have been

normalized as “masculine” and those that are outside of the norm are represented as

“other.” Those that don’t fit with the norm require some kind of remedy that can

only be accomplished through specific interventions (Ahl & Marlow, 2012).

Early research on female entrepreneurship has been based on observing

gender differences between men and women, and not based on feminist theories

(Mirchandani, 1999). Similarly, entrepreneurship is often defined in terms of

behaviors (innovation, risk taking, emphasis on growth) that are associated with

male entrepreneurs as opposed to female entrepreneurs (Carland et al., 1984;

Curran, 1991; Green & Cohen, 1995). Until the 1990’s, mainstream researchers

assumed that entrepreneurs were male and the measurement instruments developed

reflected this particular bias and assumption (Wilson & Tagg, 2010). Ahl explains,

“When pre-formulated questions, based on male-centered notions of

entrepreneurship are imposed on women entrepreneurs, there will be little chance to

capture anything different about women entrepreneurs, only “more” or “less” of

what is already imagined” (2004, p. 108). Many of these differences have been

explained in terms of how women entrepreneurs deviate from a so-called “male

norm.” (Bird & Brush, 2002; de Bruin et al., 2007). And, if there are performance

gaps identified, they can be rectified through specific policy intervention to address

female lack.

What is missing from the literature is a sense of embeddedness and context

13

specificity of entrepreneurship when it pertains to women entrepreneurs (Brush, de

Bruin & Welter, 2009; de Bruin et al., 2007). The “male norm” is taken for granted,

yet a more feminist perspective will add value to the research and expose the

“nonobvious” by creating a “female norm” for engaging in entrepreneurship

(Brush, de Bruin & Welter, 2009). The study of women’s entrepreneurship should

be explored and comprehended within a social context. If women are socialized

differently, perhaps they will perceive entrepreneurial opportunities with a different

perspective as well (DeTienne & Chandler, 2007). In order to address the unique

features of women’s entrepreneurship, existing theoretical concepts should be

expanded and current theoretical approaches should be broadened (de Bruin et al.,

2007). Feminist theory suggests that there might be a feminine set of processes and

behaviors that is underexplored when studying new venture creation and growth

intention (de Bruin et al., 2007).

The term gender is introduced by feminist scholars to differentiate between

biological sex and socially constructed sex (Ahl, 2006). Biological sex refers to

human bodies with male or female reproductive organs, whereas socially

constructed sex refers to masculinity and femininity within the structure of social

practices (Acker, 1992). However, the term gender, in recent times, has been used

by researchers interchangeably with biological sex, i.e. men and women. And, the

assumption is that women and men differ in meaningful aspects – otherwise, there

is no use for comparing. This study, however, will use the meaning of the word

14

gender in the socially constructed sense.

How does feminist theory fit in with the discussion on gender? Feminist

theory, in relation to Harding’s (1987) classifications, can be divided into three

groupings: 1) liberal feminist theory, 2) social feminist theory, psychoanalytical

feminist theory or radical feminist theory, and 3) social constructionist and post-

structuralist feminist theory. In liberal feminist theory, men and women are seen as

similar, i.e. they are regarded as equally able. Therefore, if subordination of women

to men is observed, the theoretical explanation for this must be due to structural

barriers (e.g. education, opportunity, social networks, mentors) or discrimination. A

male norm is assumed and women are advised within this setting to adapt to the

existing societal order (Calas & Smircich, 1996). Even though women and men are

thought of as equally capable, in early entrepreneurial research, comparing men and

women as entrepreneurs seems to have focused on some type of problem or

shortcoming of women. Thus, gender awareness has been framed in a comparative

manner (Eddleston & Powell, 2008; Godwin, Stevens & Brenner, 2006).

Furthermore, the underlying assumption has been that men and women are

fundamentally different, and female deficiency is usually how these differences are

expressed (Ahl & Marlow, 2012). Women were recognized as being less

entrepreneurial (Fagenson, 1993; Neider, 1987; Sexton & Bowman-Upton, 1990;

Zapalska, 1997), having less motivation for entrepreneurship and business growth

(Buttner & Moore, 1997; Fischer, Reuber & Dyke, 1993), having insufficient

15

education or experience (Boden & Nucci, 2000), having less qualified networking

skills (Aldrich, Reese & Dubini, 1989; Cromie & Birley, 1992; Katz & Williams,

1997; Smeltzer & Fann, 1989), being risk-averse (Masters & Meier, 1988), and

having less desire to start a business (Carter & Allen, 1997; Kourilsky & Walstad,

1998; Matthews & Moser, 1996; Scherer, Brodzinsky & Wiebe, 1990).

The second grouping of feminist theories - social feminist theory,

psychoanalytic feminist theory or radical feminist theory – suggests that men and

women are viewed as fundamentally different. Feminine traits are seen as unique

resources to be used to the benefit of the organization (Gilligan, 1982). This

particular view of feminism doesn’t question the male norm. Instead, a female

norm is juxtaposed adjacently and focuses on the unique competencies, needs,

experiences and values of women (Poggesi et al., 2016). Differences between men

and women are in early and ongoing socialization processes that shape an

individual’s identity, influencing her behavioral characteristics. This type of theory

still invites comparisons between men and women and can still produce a “male

norm” vs. “other” approach that is detrimental to the study of women’s

entrepreneurship. It suggests that there is still a difference in power relations and

that entrepreneurial activities performed by women are less than those performed

by men. Ahl (2004, p. 108) notes that, “when pre-formulated questions, based on

male-centered notions of entrepreneurship are imposed on women entrepreneurs,

there will be little chance to capture anything different about women entrepreneurs,

16

only “more” or “less” of what is already imagined.”

The third group of feminist theories, social constructionist and post

structuralist, envisions gender as independent of a person’s biological sex, and

instead focuses on what is masculine and what is feminine in a socially constructed

context. These theories refer to how femininity and masculinity are structured with

regard to their effect on social order. Gender is something that is accomplished or

done, rather than what “is” (Ahl, 2006). The constructionist approach uses gender

as a starting point and refrains from using gender as an explanation (Ahl, 2006).

Along with post-structuralism, it builds on the assumption that gender is socially

and culturally constructed (Henry et al., 2015). Whereas the first two groups of

theories suggest that assumptions regarding feminine weakness are embedded in

normative masculine beliefs (Ahl & Marlowe, 2012), a post structuralist approach

will help to expand the entrepreneurial discourse by focusing on women’s

narratives and sampling women only data sets in order to increase a deeper

understanding of the entrepreneurial experience without revealing gender bias.

Under this approach, for example, it is not as meaningful to focus on the

individual entrepreneur, but rather one should consider the individual juxtaposed

within the social context she is situated. Furthermore, variables such as family

embeddedness become more meaningful to consider when studying women’s

entrepreneurship as opposed to performing studies that compare women’s and

men’s entrepreneurial traits. Jennings and Brush’s (2013) review of the extant

17

literature on female entrepreneurship revealed that entrepreneurship is a gendered

phenomenon; entrepreneurial activity consists of a “family embeddedness” and

many entrepreneurs pursue goals beyond the traditional economic gain that is

touted in the majority of entrepreneurial studies. Using post-structural feminist

theories as a framework, the study of entrepreneurship would reflect the expansion

of what entrepreneurial behaviors, attitudes, motivations and intentions would

entail to more significantly reveal women’s experiences (Ahl & Marlow, 2012) in

the field without being subjugated to gender comparisons.

It is the goal of this paper to adopt the third set of feminist theories – social

constructionist and post-structuralist feminist theory – as an explanatory approach

to better understand how women make decisions regarding intention to grow their

businesses and how women implement entrepreneurial behaviors. Although

researchers have gained insight over the last 30 years as to how women become

entrepreneurs, perform as entrepreneurs, and exhibit entrepreneurial attitudes and

behaviors, the objective of a majority of research has been to find and elaborate on

differences between male and female entrepreneurs. Ahl (2006, p. 595) suggests

that prevailing research practices inadvertently contribute to the social construction

of women entrepreneurs by recreating "the idea of women as being secondary to

men and of women's businesses being of less significance."

Although in the last ten years there has been an observed increase in use of

feminist theory by researchers, the dominant framework is still a male-female

18

comparison model in much of the literature, with only a small number of studies

focused solely on women’s samples or within group comparisons of women (Henry

et al., 2015). The analytical frame of inquiry within entrepreneurship research to

date reflects a strong masculine bias. Adopting a post-structural or constructionist

approach would afford deeper understanding of entrepreneurship through women’s

experiences as well as provide clarity of how to develop interventions focused on

accelerated and increasingly successful outcomes for women entrepreneurs. The

proposed study addresses a gap in the entrepreneurial research literature in two

meaningful ways – by combining a feminist perspective and by sampling women

only in order to make significant inroads toward understanding a more complex

scenario of how women “do” entrepreneurship.

Gender and Entrepreneurship

The majority of entrepreneurial research literature has studied male

founders. Research studies that have been executed, for the most part, compare the

situation of women entrepreneurs to their male counterparts (Carrier, Julien &

Menvielle, 2008). They have found that women entrepreneurs tend to be less

growth oriented than men and have had different socialization experiences (Bussey

& Bandura, 1999). Women owned firms tend to be smaller (Cliff, 1998; Du Rietz

& Henrekson, 2000; Kalleberg & Leicht, 1991), tend to display lower propensity

towards growth (Menzies, Diochon & Gasse, 2004) and seem to grow less quickly

(Cooper et al., 1994; Fischer et al., 1993).

19

Ahl (2006) notes that within women’s entrepreneurial research literature

there are a number of shortcomings. These include, but are not limited to, a one-

sided empirical focus (Gatewood et al., 2003), a lack of theoretical grounding

(Brush, 1992), use of male-gendered measuring instruments (Moore, 1990;

Stevenson, 1990), and a lack of explicit feminist analysis (Mirchandani, 1999;

Ogbor, 2000; Reed, 1996). Ahl (2006) argues that research on women’s

entrepreneurship holds certain assumptions of business, family, society, gender, the

individual and the economy, all of which influence the research questions asked,

methods chosen and answers received. She points out a number of discursive

practices that support this claim. Some of these practices are apropos to this

particular study.

One practice in the literature suggests that the word entrepreneur and

entrepreneurship are male gendered. There are male-gendered measuring

instruments used (Moore, 1990; Stevenson, 1990), gendered attitudes toward

entrepreneurs developed (Nilsson, 1997) and male gendered theory used to support

entrepreneurial studies (Bird & Brush, 2002; Chell, Haworth & Brearley, 1991;

Mirchandani, 1999; Reed, 1996). The word entrepreneur is a masculine concept

and the researcher runs a risk of comparing women entrepreneurs to an already

built upon conception of a male-gendered archetype as entrepreneur.

Another discursive practice is to treat men and women as essentially

different. If entrepreneurship is viewed as an engine for economic growth, then

20

many researchers have studied the growth and performance of women-owned

businesses and have found them to be “less than.” They have been compared, in the

majority of articles, to male-owned businesses in which the women-owned

businesses are less profitable, appear to be smaller in general and have slower

growth (Fasci & Valdez, 1998; Hisrish & Brush 1984; Kalleber & Leicht, 1991;

Rosa & Hamilton, 1994). Many researchers subscribe to the notion that men and

women are different and there is an inherent risk when making a direct comparison

to a stereotype that already exists (Ahl, 2006). The direct result is an “othering” or

“less than” effect for women when compared in this manner.

A third practice is to assume that there is a division between work and

family where the woman still takes on most of the responsibility for the family. In

the general entrepreneurship literature, family appears to be non-existent as a

factor, but in the research about women’s entrepreneurship, family can be

positioned as a problem (Stoner et al., 1990) or it can, in contrast, be positioned as

a source of inspiration from which women learn unique skills such as networking,

democratic leadership, and relationship marketing (Brush, 1992; Buttner, 2001).

Nevertheless, family is still perceived as the woman’s responsibility and

entrepreneurial researchers suggest that a woman’s business is secondary, where

her primary responsibility is the family (Ahl, 2006). This reinforces the stereotype

of how women-owned businesses may be viewed and again creates an “othering”

effect if a research study is conducted with direct comparisons between men and

21

women-owned businesses rather than doing a within group comparison of only

women-owned businesses.

Jennings and Brush (2013) performed a comprehensive review of the extant

literature by comparing female entrepreneurship scholarship to the broader

entrepreneurship literature. They found (based on a review of 600+ articles

published between 1975-2012), that the collective body of knowledge on women’s

entrepreneurship has challenged mainstream theory by demonstrating that it is a

gendered occurrence, there is a type of family embeddedness that exists, for some

women it results out of necessity and for others it results from opportunity, and that

goals are often pursued beyond economic gain. Moreover, even though there has

been a recent proliferation of research studies performed on women’s

entrepreneurship, the proportion of research published in top-tier journals has

steadily declined since the late 1990s (Henry, Foss, & Ahl, 2016).

In order to expand the field of women’s entrepreneurship research (going beyond

male/female comparisons which help to create an “othering” or “less than” effect

for women entrepreneurs), this study will take an approach of sampling women

entrepreneurs only (using feminist theory as a base) and study venture growth

intention with its antecedents in order to gain a better understanding of how women

entrepreneurs may intend to grow their businesses.

Model Development

This study will use a serial mediation model that integrates the Theory of

22

Planned Behavior and Feminist Theory with venture growth intention. The purpose

of this study is to provide clarity on the mechanisms (including external and

internal factors) that may lead women business owners to intentionally decide to

grow their businesses. Using the Theory of Planned Behavior (TPB), social norms

are represented by access to role models and perceived family support, perceived

behavioral control (PBC) is represented by internal self-confidence and attitude is

represented by risk propensity. All three of these constructs should have a direct

effect on venture growth intention as exemplified in the Theory of Planned

Behavior. The full theoretical model is contained in Figure 3 below.

In proposing the hypotheses for the mediating mechanisms of access to role

models and perceived family support on venture growth intention, internal self-

confidence, a key proximal mechanism, will be defined and discussed. This

mechanism is not predicted to be the only intervening step in the causal pathway

between access to role models/perceived family support and venture growth

intention. Additionally, the model predicts that risk propensity will mediate the

relationship between self-confidence and venture growth intention. The following

sections will discuss the components of the theoretical model in detail.

23

Figure 3.Theoretical Model

Venture Growth Intention

Venture growth intention is a critical, yet understudied, aspect of venture

growth. It is important to examine the preconditions that facilitate or inhibit its

emergence. For the purpose of this study, growth intention is defined as “the

entrepreneur’s goals or aspirations for the growth trajectory she or he would like

the venture to follow” (Dutta & Thornhill, 2008). Growth intentions matter.

Numerous researchers suggest that the proportion of entrepreneurs with growth

intentions in the population is a more significant predictor of economic growth than

general start-up rates or self-employment rates (Stam et al., 2009; Stam et al.,

2011). Venture growth intention has been defined in various ways by several

researchers. They have studied similar measures of growth intention using names

such as growth intention, growth aspiration and growth motivation (Douglas, 2013;

Edelman et al., 2010; Kolvereid & Bullvag, 1996; Wiklund & Shepherd, 2003).

Venugopal (2016) suggests that aspirations represent long term hopes and goals;

motivations are the reasons why entrepreneurs pursue their goals; and intentions

Access to Role Models

Perceived Family Support

Self-Confidence

(Internal)

Risk Propensity

Venture Growth Intention

24

involve a purposeful component with specific stages to reach the goals. Dutta and

Thornhill (2008) describe growth intention as “The entrepreneur’s goals or

aspirations for the growth trajectory she or he would like the venture to follow” (p.

308). Another definition more suitable for the purposes of this study is “the

individual’s intention to start a new venture that will be substantially larger over

subsequent time periods.” (Douglas, 2013, p.9). Larger can have various meanings.

It could mean increased revenues, additional jobs created, expanded products and

services offered, increased profitability, expanded office and manufacturing space,

etc. It is purposely left vague so as to align with the desire and aim of the

entrepreneur.

Intentions are driven by critical attitudes and beliefs and are useful in

understanding behavior (Krueger, 2003). Within cognitive psychology, intention is

the intellectual state immediately preceding the implementation of a behavior.

Psychologists have often studied intentions as a useful method in understanding

and predicting behavior. An increased focus on the study of entrepreneurial

intentions has moved entrepreneurial research forward in a manner that places a

greater emphasis on predicting behaviors rather than explaining behavior.

Within entrepreneurial research, the role of entrepreneurial intention has

been widely studied with regards to launching a business (Bird, 1988; Bird &

Jelinek, 1988; Birley & Westhead, 1994; Crant, 1996). Intent is a cognitive state

prior to the decision to act and has been found to be the single best predictor of

25

subsequent behavior even if the predictive power is underwhelming (Krueger

2003). As Bird notes, “Intention, since it precedes venture formation, plays a

critical role in the initial conditions of the new venture” (Bird, 1992: 11). Planned

behavior is intentional and, therefore, Ajzen’s Theory of Planned Behavior has

become a dominant model of intentions within entrepreneurial literature for

studying both entrepreneurial intention and venture growth intention (Ajzen, 1991;

Kolvereid, 1996; Krueger, Reilly & Carsrud, 2000). Some critical advantages of

using intentions models include: 1) gives us clarity in how external factors such as

perceived family support and access to role models may influence intent and

behaviors; 2) offers predictive power rather than explaining what happened

retrospectively; 3) remains the single best predictor of subsequent action and 4) can

be used for various types of intentions (e.g. entrepreneurial intentions and venture

growth intentions). On the other hand, some disadvantages may include: 1) the

variability of intentions especially for complex or distal behaviors and 2) some

deliberation over the causal direction of intentions (Krueger, 2003).

Some of the individual drivers of initial growth intentions that have been

studied include risk taking (D’Amboise & Muldowney, 1988), self-efficacy (Boyd

& Vozikis, 1994; Krueger & Carsrud, 1993), proactivity (Crant, 1996; Kickul &

Gundry, 2002; Lau & Busenitz, 2001; Raijman, 2001), gender (Orser & Hogarth-

Scott, 2002), and education and family history (Crant, 1996; Stavrou, 1999).

Organizational factors that influence entrepreneurial intentions have included

26

resource availability (Lichtenstein & Brush, 2001; Petrakis, 1997), involvement of

external stakeholders (Flynn & Forman, 2001), and entrepreneurial team

orientation (Lumpkin and Dess, 1996; Lyon et al., 2000). Some researchers have

studied venture growth intentions of nascent entrepreneurs at the start-up phase

(e.g. Edelman et al., 2010; Dutta & Thornhill, 2008, 2014). One may expect that

intentions after launching a business may continue to exist after the start-up phase,

however, intentions related to how the business develops after formation are rarely

examined (Dutta & Thornhill, 2008). Other researchers have found that a positive

relationship exists between growth aspirations and subsequent venture growth

(Delmar & Wiklund, 2008; Stenholm, 2011). Moreover, venture growth is

important because of the economic benefits it provides to society which include job

creation, increased standard of living and technological innovations (Acs &

Mueller, 2008; Arminton & Acs, 2002; Carree & Thurik, 2003). It is therefore

important to study key internal and external factors that influence venture growth

intentions of entrepreneurs so that we may be able to develop interventions that can

help them to overcome obstacles or enhance their decision-making process that

may lead to accelerated venture growth. Those factors included in this study are

risk propensity, internal self-confidence, access to role models and perceived

family support.

27

Risk Propensity

One of the key issues that will predict venture growth intention is risk

propensity. The classic definition of risk is the probability of incurring a loss

(Knight, 1921). However, regarding decisions in business, risk is associated with

achieving or generating potential gain. Most researchers would agree that risk

relates to two dimensions including the likelihood of a particular incident occurring

(probability) and the results should the incident occur (Humbert & Brindley, 2015).

Researchers have suggested that decision making behavior could be divided into

three elements: risk perception, risk propensity and risk preparedness (Humbert &

Brindley, 2015). Risk perception is defined as a subjective explanation of expected

loss (Sitkin & Weingart, 1995). It is the individual’s view of the decision and the

resulting outcomes of the decision (Cunningham, 1967). The subjective nature of

this element is key as an individual or organization may view the same group of

circumstances with different filters, resulting in contrasting perceptions (Chung,

1998; Forlani & Mullins, 2000; March & Shapira, 1987; Ritchie & Brindley, 2001).

Risk propensity, on the other hand, is defined as an individual’s immediate

tendency to take or avoid risk (Pablo, 1997; Sitkin & Pablo, 1992; Sitkin and

Weingart, 1995). Moreover, how one approaches risk may be found on a scale from

risk seeker to risk avoider. Risk propensity can play a powerful function in varying

business decisions. In the extensive management literature, the executive’s risk

propensity is linked with the firms’ strategic risk-taking (Devers et al., 2008;

28

Martinez & Artz, 2006), corporate entrepreneurship (Ling et al., 2008) and

organizational performance (Saini & Martin, 2009). Risk propensity has also been

discovered to associate with entrepreneurial intentions (Zhao et al., 2010) and

entrepreneurial status (Zhang & Arvey, 2009). Nieß and Biemann (2014) suggest

that high levels of risk propensity positively predict the decision to become self-

employed, but then the relationship between risk propensity and self-employment

survival follows an inverted U-shaped curve suggesting that moderate levels of risk

propensity are necessary in order to maintain or continue with one’s business.

Many researchers have linked risk propensity to self-employment (Cramer, et al.,

2002; Van Praag & Cramer, 2001; Zacher et al., 2012). A majority of the literature

assumes that risk propensity is a causal predictor of the decision to enter into self-

employment.

Finally, risk preparedness could be regarded as measures taken to prepare

for and reduce the effects of risk. Risk preparedness seems to be affected by an

individual’s risk perception and propensity (Brindley, 2005). Risk preparedness

may depend on outcome ambiguity due to incomplete knowledge or on the

potential scale of losses or gains (Brindley, 2005).

The dominant theme in the entrepreneurial literature focuses on how

entrepreneurs may be predisposed towards risk or how they should manage risk.

(Busenitz, 1999). Researchers have identified that successful entrepreneurs are

moderate risk takers (Brockhaus, 1980; McClelland, 1961; Nieß & Biemann, 2014)

29

and that perceptions of risk change over time (Brindley & Wright, 2008). One

meta-analysis (Stewart & Roth, 2001) suggests that entrepreneurs have a higher

risk propensity than managers and that the propensity is especially evident among

growth-oriented firms. Other researchers counter this finding and take a more

conservative view that entrepreneurs, even those that are growth-oriented, are more

risk avoidant (Miner & Raju, 2004).

In addition to comparisons between entrepreneurs and managers, there have

been several studies comparing male and female entrepreneurs and their tolerance

for risk. One vein of research has reported that women entrepreneurs are more risk-

averse than men entrepreneurs (Sexton, 1989; Still & Timms, 2000). Other

researchers have failed to establish significant differences between men and women

entrepreneurs and managers related to risk propensity (Brindley, 2005; Hytti, 2005;

Masters & Meier, 1988; Slovic, 2000). Yordanova and Alexandrova-Boshnakova

(2011) found that men and women had similar risk perceptions, however women

entrepreneurs had lower risk propensities. Nelson (2015), in a review of the

empirical literature, suggests that there are more differences within men and within

women than across genders.

Some studies have focused on external factors that have contributed to risk

taking in an entrepreneurial setting. When risk is conflated with commitment and

role-congruent behavior, women can be seen as risk-averse (Maxfield et al., 2010).

Family and social context can play an important role when understanding risk

30

perception among women entrepreneurs. For example, role models can impact risk

perception (Dubinin, 1989). Additionally, an entrepreneurial parent is a major

influence (Lee, 1997) and can be a source of influence on risk perception. Access to

business start-up advice can impact risk perception as well (Chrisman et al., 1987).

To date the majority of entrepreneurial research that has linked risk to

intention has mainly focused on entrepreneurial intention. There has been little

research available making the connection between risk propensity and venture

growth intention. Ultimately this study is attempting to predict factors that lead to

venture growth intention and risk propensity is a key factor under examination.

Internal Self-Confidence

Until now, self-confidence has not been clearly defined in the

entrepreneurial research literature and, in many cases, it has been operationalized

and measured using a self-efficacy or entrepreneurial self-efficacy construct. There

have been numerous research studies using self-efficacy as a substitute for

confidence in entrepreneurial and business studies (Addis, 2008; Baldoni, 2009;

Clarke, 2011; Kanter, 2014; Kirkwood, 2009; Koellinger, Minniti & Schade, 2007;

Luthans, Luthans & Luthans, 2004; Luthans & Youssef, 2004).

Self-efficacy is a variable that has been widely studied in the

entrepreneurial research literature. Using Ajzen’s Theory of Planned Behavior

(1991), many scholars have substituted self-efficacy and entrepreneurial self-

efficacy as variables for perceived behavioral control in this theoretical model. Self-

31

efficacy has been described as the belief in one’s ability to perform a task or

behavior (Bandura, 1977) and is a core construct of Bandura’s Social Cognitive

Theory (1986). It is a task-specific concept that includes an evaluation of confident

beliefs an individual has about internal (personality) and external (environment)

limitations and opportunities (Drnovsek et al., 2010). Moreover, it is close to action

intentionality (Boyd & Vozikis, 1994). Perceived self-efficacy refers to “people’s

beliefs about their capabilities to exercise control over their own level of

functioning and over events that affect their lives (Bandura, 1991, p. 257). Many

studies have focused on the influence of perceived self-efficacy on entrepreneurial

intentions (Boyd and Vozikis, 1994; Chen et al., 1998; DeNoble et al., 1999; Liñán

& Chen, 2009; McGee, et al., 2009; Wilson et al., 2007; Zhao et al., 2005).

In addition to using self-efficacy as a variable for perceived behavioral

control in Ajzen’s Theory of Planned Behavior, some researchers have substituted

entrepreneurial self-efficacy as a more precise efficacy construct in order to more

appropriately understand its relationship to entrepreneurial startup intentions. While

some researchers have described entrepreneurial self-efficacy as the self-confidence

of entrepreneurs regarding specific tasks (Baron et al., 1999; Baum et al., 2001;

Boyd and Vozikis, 1994), others have defined it as confidence in one’s personal

ability to initiate a start-up venture (Chen et al., 1998; Segal et al., 2005). Specific

scales have even been developed to measure entrepreneurial self-efficacy (Forbes

2005; Kolvereid & Isaacson, 2006; Krueger et al., 2000; Zhao et al., 2005), but

32

have only been applied to undergraduate and MBA students and have yet to be

generalized to the entrepreneur and small business owner population. Many of

those studies have investigated the positive effect of entrepreneurial self-efficacy

on business start-up intentions (Byabashaija & Katono, 2011; Chen et al., 1998;

DeNoble, 1999; Jung et al., 2001; Nwankwo et al., 2012; Segal et al., 2005; Wilson

et al., 2007). Other studies (e.g. Kolvereid & Isaksen, 2006) did not find a

significant relationship between entrepreneurial self-efficacy and entrepreneurial

behavior.

Krueger et al. (2000) suggested self-efficacy to be a reasonable predictor of

venture start-up intentions. Others have found it to be a key determinant of venture

growth (Markman et al, 2002). Nevertheless, self-efficacy and entrepreneurial self-

efficacy are the factors that have been substituted for self-confidence in

entrepreneurial intention and venture growth intention studies related to

entrepreneurship (Chen et al., 1998; Krueger and Brazeal, 1994). To date, there has

been very little research showing the effects of self-efficacy on venture growth

intentions using established entrepreneurs as a sample population for measurement.

It is the purpose of this study to expand the research and go beyond the

limited scope of using self-efficacy and entrepreneurial self-efficacy as a substitute

for self-confidence and incorporate an integrated model of self-confidence

(addressing internal self-confidence) that includes self-efficacy (behavioral

component), and contains two additional elements of self-esteem (affective

33

component) and self-compassion (cognitive component) (Perkins, 2018). Self-

confidence according to Oxford’s dictionary is defined as “a feeling of trust in

one’s abilities, qualities, and judgment.” Perkins (2018) suggests that the process of

self-confidence can be explained by using the Integrative Model of Organizational

Trust (Mayer et al., 1995) in which individuals make the choice to trust themselves

and take risk in themselves. Self-confidence, similar to trust, is an attitude with

cognitive, behavioral and affective components. It is an overarching construct

influenced by three major factors: general self-efficacy, self-esteem, and self-

compassion. Each of these factors is important for understanding and achieving

internal self-confidence, which is a prerequisite for realizing the behavioral

manifestation of self-confidence, and includes taking action and taking risks with

oneself (Perkins, 2018).

Many studies in the research literature focus attention on the notion that

men tend to be more confident than women in numerous fields and various research

settings (Bengtsson et al., 2005). Until now, there has been little research focused

on whether gender differences in confidence levels exist in business start-up

abilities and business growth (Koellinger et al., 2008; Mueller, 2004). Additionally,

within this limited research, many of these studies have focused on students rather

than entrepreneurs (Koellinger et al., 2008). Wilson et al (2007) suggest that the

difference between men and women with regard to start-up propensity may be due

34

to a lack of self-confidence. This is also referred to as a possible explanation in

gender differences regarding entrepreneurial intention (Mueller, 2004).

One of the key factors to predict risk propensity is internal self-confidence.

According to the literature, self-confidence is related to risk preference and

uncertainty. Self-confidence is linked with varying levels of risk-taking behaviors

(Brindley, 2005; Maxfield et al., 2010; Yordanova & Alexandrova-Boshnakova,

2011). Brindley (2005) indicates women entrepreneurs’ confidence levels are

negatively linked to perceived levels of risk beyond the start-up phase. Humbert

and Brindley (2015) found that women have reported a rise in confidence levels

over time as businesses become more established. They additionally suggest that

raising women entrepreneurs’ level of confidence would increase their level of risk

taking. Others suggest that self-confidence is related to the ability to take risks for

entrepreneurs (Dinis et al., 2013). Siegrist, Gutscher and Earle (2005) found that

high levels of trust and confidence reduced risks.

Other researchers tap into self-efficacy and self-esteem, subcomponents of

self-confidence as described in this research, and how they correlate with risk.

Regarding self-esteem, individuals with lower amounts are more likely to self-

protect by minimizing the occurrence of risk, whereas people with higher self-

esteem have a greater tendency to self-enhance and, therefore, make riskier choices

(Brockner et al., 1993). Those high in perceived self-efficacy should take greater

risks according to Krueger and Dickson (1994). The influence of perceived self-

35

efficacy on risk taking was also found to be significant (Heath & Tversky, 1991).

Finally, Maxfield et al. (2010) found that self-efficacy strongly predicts risk taking

by women.

Addis (2008) suggests that confident people risk security and comfort to

achieve higher levels of growth and independence. Results show that decision

makers who are less risk averse and have more tolerance for ambiguity display

greater confidence in their choices (Ghosh & Ray, 1997). Perkins (2018) proposes

that one of the most frequently cited outcomes of self-confidence in the research

literature is risk-taking and taking action/initiative. Self-confidence, a construct

based on the integrative model of self-trust as mentioned above, means taking risks

in yourself as well (Perkins, 2018). Furthermore, the measure of how much one

self-trusts will impact one’s risk taking behaviors and initiative in pursuing one’s

goals.

In sum, by using this study’s operationalization of internal self-confidence,

we will achieve more depth in understanding how women entrepreneurs,

specifically, use it in relation to risk-taking behaviors.

Access to Role Models

One of the factors that influences internal self-confidence is access to role

models. According to social learning theory or social cognitive theory (Bandura,

1977, 1986), individuals are attracted to role models who can help them to further

develop themselves through learning new tasks and skills (Gibson, 2004). Role

36

models are explained by theories of role identification and social learning (Gibson,

2004). People learn by example (modeling) and are assumed to learn in a social

context by observing others, especially people they can identify with and who have

stellar reputations (Bosma et al., 2012). According to Morgenroth et al. (2015), role

models seem to motivate individuals to perform new behaviors and inspire them to

achieve ambitious goals. This is especially true for those involved in educational

and occupational settings that are part of stigmatized and underrepresented groups

– in this case, women entrepreneurs. The utility of role models has been studied in

many contexts including how they inform fundamental values for doctors (Paice,

Heard & Moss, 2002), how they deal with underrepresentation of women in science

(Stout, et al., 2011), and how they increase political activism in the younger

generation (Campbell & Wolbrecht, 2006). Role models can provide an

observational learning experience for the individual (Lent, Brown & Hackett, 1994;

Scherer, et al., 1989; Scott & Twomey, 1988), as well as directly influence the role

aspirant by participating in learning activities by giving advice or counsel (van

Auken et al., 2006). Many entrepreneurs claim that their decision to start a business

and continue with the development of their businesses has been influenced by

others, especially role models (Bosma et al., 2012).

Numerous studies have established role model effects on the entrepreneurial

intentions of students (Kruger, Reilly & Carsrud, 2000; Scherer, et al., 1989; Van

Auken et al., 2006). Additionally, Krumboltz et al. (1976) found that role models

37

may have a profound influence on career decisions. Some researchers have

observed that parental role models (parents who are or were entrepreneurs)

positively correlated with the decision to become an entrepreneur (Chlosta, et al.,

2010; Dunn & Holtz-Eakin, 2000; Fairlie & Robb, 2007; Hout & Rosen, 2000;

Parker, 2009). Others suggest that social networks also influence the decision to

become an entrepreneur assuming that they may provide role model examples as

well (Kim & Aldrich, 2005; Klyver, Hindle, & Schøtt, 2007). Additionally,

research studies indicate that high levels of regional entrepreneurialism may further

encourage new entrepreneurial initiatives because it is easier to find appropriate

examples. The presence of other entrepreneurs as role models may legitimize

entrepreneurial ambitions and exploits (Davidsson & Wiklund, 1997; Mueller,

2006).

Bosma et al. (2012) indicate that individuals are attracted to role models

who are perceived to be similar in characteristics, behavior or goals, and from

whom they are able to learn certain abilities or skills. Entrepreneurs tend to have

role models of the same gender, nationality, and industrial sector. The functions

that role models provide are interrelated. From a role identification theory

perspective, role models provide inspiration/motivation and increased self-efficacy.

From a social learning theory perspective, they additionally provide a means to

learn by example and by support (Bosma et al., 2012). All four of these functions

38

are thought to be interrelated when studying the effects of role models on

entrepreneurial behaviors.

Gaining access to role models appears to be critical for women

entrepreneurs determined to pursue venture growth (Bosma et al., 2012). As an

underrepresented group in the entrepreneurial world, women entrepreneurs often

state they need to see other women who have followed their dreams and achieved

success to believe that they, too, can achieve successful outcomes. Role models

have been found to be an antecedent to potential entrepreneurs’ thought processes

(Van Auken et al., 2006) and can affect career intentions as well (Krueger et al.,

2000). Positive role models can be critical in encouraging entrepreneurship

(Krueger at al., 2000; Scherer et al., 1989). Scherer, Adams, and Wiebe (1989) used

social learning theory to study the link between parental role models and the

development of a preference for an entrepreneurial career. They found that the

performance of the role model was not as important as the very existence of one.

Scott and Twomey (1988) found that parental role models and experience led to the

perception of oneself as an entrepreneur. Role models can help shape the outcome

expectations and self-efficacy of the individual leading to intentions of pursuing

said career (Lent et al., 1994; Nauta, Epperson & Kahn, 1999). Van Auken et al

(2006) also found the presence of role models may increase the desire to become an

entrepreneur and entrepreneurial self-efficacy, which in turn will influence

entrepreneurial intentions and activity (Krueger et al., 2000). Role model behavior

39

has also been found to impact perceived desirability and feasibility of the role for

the individual (Krueger, 2000; Krueger & Brazeal, 1994; Krueger, Reilly, &

Carsrud, 2000). Role models are important to the process in which beliefs,

attitudes, and intentions evolve through the cognitive processing of knowledge,

beliefs, and experiences (Lent et al., 1994).

Perceived Family Support

An additional factor that may have an influence on internal self-confidence

of entrepreneurial women is perceived family support. Theories of social support

(Sarason et al., 1990; Uchino, 2004) provide useful information by describing

frameworks associated with an individual’s social life (e.g. family ties and work

networks) and the functions that these frameworks serve. There are two primary

functions of social support – emotional support and instrumental support (Adams et

al., 1996; King, et al., 1995). Emotional support relates to positive encouragement,

understanding, attention, and positive regard. Instrumental support relates to

assistance in problem solving, etc.

Some researchers have taken these theories of social support further and

applied them to the idea of “family-to-business” support (Baron, 2002; Jennings &

McDougald, 2007; Rogers, 2005). Aldrich and Cliff (2003) outlined a family

embeddedness perspective suggesting that the one social institution in which all

entrepreneurs are embedded is the family, and perhaps this is a primary social

institution that should be examined especially within the entrepreneurship research

40

field. The family embeddedness perspective framework is shown below in Figure

4:

Figure 4.Family embeddedness perspective on new venture creation (Aldrich &

Cliff, 2003)

The authors suggest that family system characteristics (e.g. transitions, resources,

norms, attitudes and values), on the left-hand side of the model, may influence the

process involved in new venture creation. For example, the goal towards achieving

balance between work and family can be one of the strongest motivations for

women to start and run their own businesses. Family resources, as well as norms,

attitudes and values can also play a pivotal role in influencing women growth-

oriented strategies.

The family embeddedness perspective encourages a family to be seen as a

major source of support to the entrepreneur, helping her to cope with the everyday

41

challenges of running a business (Whitaker & Garbarino, 1983). This perspective

maintains that the family plays a very important role in supporting and encouraging

an entrepreneur’s business (Aldrich & Cliff, 2003; Powell & Eddleston, 2013;

Rogoff & Heck, 2003). An entrepreneur will feel a sense of comfort and security

knowing that family members support her endeavors and intention to grow her

business.

Family to business support, a part of the family embeddedness framework,

is further subdivided into emotional support and instrumental support (Eddleston &

Powell, 2012). First, emotional support can come in the form of family members

encouraging the career choice of the entrepreneur and empathizing with frustration

regarding business problems (King et al., 1995). Second, instrumental support (at

work) may emerge by way of family members offering feedback regarding

business ideas, giving advice on how issues should be addressed, or providing

assistance with running the business (Eddleston et al., 2012). Another type of

instrumental support (at home) can come from family members assuming the larger

share of household responsibilities allowing the entrepreneur to focus more time on

growing her business. There are various ways in which family-to-business support

can be lacking as well. This may include a family member resenting the business

and suggesting that the entrepreneur is drawing attention away from the family.

Additionally, a family member may give one’s entrepreneurial career low priority

within the household. Finally, a family member may refrain from offering

42

feedback, advice or assistance with the business or the household.

The family is no longer analyzed as a liability for women and is considered

an important asset in women’s entrepreneurship and entrepreneurship research

(Powell & Eddleston, 2013). Yet, many women entrepreneurs voice concerns

regarding the perceived support of family members regarding their entrepreneurial

career and desire for success. According to Aldrich and Cliff (2003), the

mobilization of family forces is critical to the survival and growth of new ventures.

Entrepreneurs may feel more energized and motivated knowing that their family is

behind their efforts to grow their business. Family-to-business support may

increase their overall satisfaction with their career choice and help to strengthen

their commitment to continue pursuing entrepreneurial endeavors (Rogers, 2005).

Greater family-to-business support may likely encourage them to persist with their

business and meet their growth goals despite facing overwhelming obstacles

(Powell & Eddleston, 2017).

Hypothesis Development

Using the Theory of Planned Behavior (Ajzen, 1991), the purpose of this

study is to gain a more enlightened understanding of how women entrepreneurs

make decisions to grow their businesses. Additionally, it is the goal of this paper to

explore more deeply the factors that may either enhance or inhibit their desire to

expand their businesses. What makes the proposed theoretical model unique is that

the factors under examination notably stand out when comparing women’s

43

entrepreneurship to men’s entrepreneurship. More specifically, these factors, when

pertaining to women, have only been examined in the entrepreneurship literature in

a way that compares male business owners to female business owners and the

outcomes observed have contributed to a “less than” or “othering” effect of the

female business owner. It is an additional intention of this paper to examine these

factors through a feminist lens in order to determine the degree that access to role

models, perceived family support, through self-confidence and risk perception,

contribute to venture growth intention among women entrepreneurs. Once this has

been determined, then specific interventions can be suggested to facilitate venture

growth intention, and more importantly, venture growth for those women

entrepreneurs that choose to purposefully expand their businesses and may have

trouble overcoming roadblocks towards achieving their goals. Figure 3 depicts the

full model under investigation.

As stated above, risk propensity has been defined as an individual’s current

tendency to take or avoid risks (Pablo, 1997; Sitkin & Pablo,1992, Sitkin &

Weingart, 1995). I expect risk propensity to be positively related to venture growth

intention because in order to have intention to grow one’s business, there is a

certain amount of uncertainty that is involved in making the commitment or

decision for further business growth. Risk-taking has been a dominant theme in the

literature examined as a personality trait suggesting that successful entrepreneurs

are predisposed towards risky alternatives if they have certain levels of risk

44

propensity (Busenitz, 1999). Risk propensity is one of the factors that has been

identified as a potential influencer on an individual’s preparedness to take risks

(Brindley, 2005). It has also been identified to correlate with entrepreneurial

intentions (Zhao et al., 2010) and entrepreneurial status (Zhang & Arvey, 2009).

Therefore, I hypothesize:

H1: Risk propensity is positively related to venture growth intention.

As with any mediated relationships two types of connections must be

constructed. The mediator needs to be linked to the dependent variable (DV) and

the independent variable (IV’s) are to be connected to the mediator. I expect

internal self-confidence to be related to risk propensity because entrepreneurs with

higher levels of self-confidence are willing to risk the small failures that may occur

along the path towards growing their businesses to a higher level. Positive levels of

self-confidence should also translate into positive levels of risk propensity with

regard to venture growth intention as well since intention is the pre-determinant of

actual growth. In the research literature, a connection has been established between

self-confidence and risk-taking behaviors. Self-confidence has been found to

increase levels of risk-taking (Dinis et al., 2013). Women’s entrepreneurship

researchers suggest that a rise in confidence levels may increase levels of risk-

taking behaviors (Humbert & Brindley, 2015). In these cases, the measure used has

normally been identified as self-efficacy, but branded as self-confidence. This study

will use a more comprehensive measure of internal self-confidence that includes

45

measures of self-efficacy, self-esteem and self-compassion. Given that it has

already been established that risk propensity is related to venture growth intention

and the connection between internal self-confidence and risk propensity has also

been determined, the following hypothesis is proposed:

H2: The relationship between internal self-confidence and venture growth

intention is mediated by risk propensity.

Finally, I expect that access to role models will be related to internal self-

confidence. Role models can help shape the self-efficacy of an individual leading to

intentions of pursuing certain careers (Lent et al., 1994; Nauta, Epperson & Kahn,

1999). Merely the very presence of a role model (regardless of any kind of

behavior) can help increase entrepreneurial self-efficacy in an individual (Van

Auken et. al., 2006). Taking it one step further, when a woman entrepreneur is

exposed to a role model, she may think “wow, if she can do it, I can do it.” She

becomes less fearful of the ramifications and more comfortable with pursuing her

dreams and intentions when she sees others that look like her, have positions like

hers and demonstrate the possibility that venture growth can be accomplished

through the actions they have already taken. The role model may become more

involved in the entrepreneur’s business operations and the entrepreneur may also

learn business strategies, receive investment opportunities and/or advice on

business operations from the role models. Any one of these activities may support

her in gaining additional self-confidence and therefore igniting the intention to

46

grow her business further. Therefore, I hypothesize:

H3: The relationship between access to role models and venture growth

intention is serially mediated by internal self-confidence and risk propensity.

Regarding perceived family support, research literature suggests that

women’s entrepreneurial activity should be viewed from the perspective of family

embeddedness (Powell & Eddleston, 2013). Work-family balance is one of the

major reasons that women decide to start and run their own businesses. The family

plays a major role in supporting, encouraging and providing resources for an

entrepreneur’s business (Aldrich & Cliff, 2003; Powell & Eddleston, 2013; Rogoff

& Heck, 2003). An entrepreneur will feel a sense of comfort and security knowing

that family members support her endeavors and intention to grow her business.

Greater perceived family support may likely encourage entrepreneurs to be

motivated and committed to meet future growth goals. This sense of comfort and

security through perceived family support may lead to increased internal-self

confidence in an entrepreneur’s ability to grow despite facing overwhelming

obstacles. Similarly, since it has already been established that internal self-

confidence leads to risk propensity which in turn leads to venture growth intention,

I hypothesize that:

H4: The relationship between perceived family support and venture growth

intention is serially mediated by internal self-confidence and risk propensity.

47

Method

Participants

The sample for the present study is women business owners who are mostly

affiliated with Women’s Business Centers located throughout the United States.

The Women’s Business Centers are partially funded through a cooperative

agreement with the Small Business Administration (SBA) and there is a network of

approximately 110 centers nationally. The centers work with start-up and

established women-owned businesses to provide training, mentoring, financial and

networking resources to women interested in entrepreneurship. Additional

sampling came from women business owners who are affiliated with other

women’s business organizations that support the development of women-owned

businesses and women business owners with personal connections to the

researcher.

The final sample of 196 participants consisted of women business owners

(100%), White (94%), and on average 51 years old. Additional demographics show

that 69% were married, 14% divorced, 10% single, 5% domestic partnership, 2%

widowed and 1% separated. The women business owners were well educated, with

3% having a high school degree or equivalent, 10% having some college, 7%

having an Associate’s degree, 37% a Bachelor’s degree, 7% having some graduate

school, 28% a Master’s degree and 8% a Doctorate degree. Sixty-five percent were

the sole owners of their business and the average years of business ownership was

48

10. Eighteen states were represented in the survey with 49% of the participants

residing in Florida. Demographics are reported in Table 1.

Table 1. Demographics Factor Characteristic Value N

Race

Caucasian 81% 159

18

10

9

African American 9%

Hispanic 5%

Other 9%

Age

20-35 18% 34

53

103

36-49 28%

50+ 54%

Relationship

status

Married 69% 134

27

20

15

Divorced 14%

Single 10%

Other 8%

Education

High school 3% 6

33

73

14

54

16

Some college 17%

Bachelor’s 37%

Some post graduate 7%

Master’s 28%

Ph.D. 8%

Ownership

status

Sole Owner 65% 127

69 Multiple Partners 35%

Years in

Business

1-10 59% 115

57

23

11-25 29%

>25 12%

Business

Region

North 23% 45

121

6

15

8

South 62%

Midwest 3%

West 8%

Outside US 4%

Type of

Business

Consulting Services 22% 43

20

16

15

12

10

10

70

Marketing/Advertising/Comm/PR 10%

Retail Trade 8%

Healthcare 8%

Manufacturing 6%

Arts/Entertainment 5%

Professional (Law/Medical, etc.) 5%

Other 36%

Number of

Employees

<5 61% 116

48

23

4

5-19 25%

20-99 12%

100-249 2%

TY

Projected

Revenue

<$199,999 51% 96

57

36 $200,000-$999,999 30%

>$1,000,000 19%

49

Procedure

Data collection took place through an online cross-sectional survey

developed in Qualtrics that was sent to Women’s Business Centers throughout the

United States. They, in turn, distributed the survey to their clients who included

women business owners that have established businesses for more than a year.

Having the business established for at least a year indicates some stability in the

business and affords the entrepreneur some time to have established revenues. The

survey was also sent to women-owned businesses that may not have had Women’s

Business Center affiliation.

Measures

Demographics. Key entrepreneurial demographics measured include

gender, age, education, race/ethnicity, entrepreneurial parent, entrepreneurial

experience, number of years in business, revenue size, and number of people

employed.

Venture Growth Intention. This variable was measured based on

Zampetakis et al. (2016) research on business growth intentions. They based their

measurement on items developed by Davis and Shaver (2012) and Edelman et al.

(2010). Two questions were asked and the scale used was 1 = strongly disagree to 7

= strongly agree. The scale demonstrated high internal consistency using

Cronbach’s alpha (α= .83). The items include: 1) I want my business to be as large

as possible, and 2) I want a business I can manage myself or with a few key

50

employees (reverse-coded). An additional 4 items have been added to measure

growth intention. All items were then averaged to yield a growth intention score

(see Appendix A for all items).

Access to Role Models. Following the recommendations of Bosma et al.

(2012), access to role models was measured using six items in the pre start-up

subscale and six items in the post start-up subscale for a total of twelve items. Two

general items in each of the subscales asked the entrepreneur to rate whether they

had access to entrepreneurial role models and whether they would have

started/continued operations of the company without them. Additionally, the

entrepreneur was asked to rate an additional four items in the pre start-up subscale

and the post start-up subscale that represent the types of functions that the role

model may have provided (e.g. inspiration/motivation, self-efficacy, example, and

support). The scale used was 1) strongly disagree to 7) strongly agree (α = .93).

Sample items include: 1) I had/have access to role models in the post start-up

phase, 2) With this/these entrepreneur(s) in mind, I thought: “if s(he) can do this, I

can do this too.”, and 3) This(these) entrepreneur(s) has(have) really supported me

with the continued operation of my company.

Perceived Family Support. Eddleston and Powell’s (2012) measure of the

three dimensions of family-to-business support was employed. This was adapted

from King et al.’s (1995) measure of family support for workers and used for an

entrepreneurial population. Respondents indicated the extent to which they agree

51

on a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree) with four

items that represent emotional support (α = .82) and five items that represent

instrumental support for the business (α = .86) and four items that represent

instrumental support at home (α = .84). The scale demonstrated high internal

consistency in all three areas. Sample items include: 1) Members of my family are

interested in my business, 2) Family members often go above and beyond what is

normally expected in order to help my business succeed, and 3) If my business gets

very demanding, someone in my family will take on extra house-hold

responsibilities.

Internal Self-Confidence. Perkins’ (2018) Internal Self-Confidence Scale

was used to measure internal self-confidence; the three subdimensions are self-

efficacy, self-esteem, and self-compassion. The scale consists of 12 items and has a

highly reliable internal consistency Cronbach’s alpha of .92. The known measures

which the Internal Self-Confidence scale were validated against include Sherer et

al.’s (1982) General Self-Efficacy Scale (r = .743**), Rosenberg’s (1965) Self-

Esteem Scale (r = .814**), Raes et al.’s (2011) short-version of the Self-

Compassion Scale (r = .707**), and Paul and Garg’s (2014) short-form of the

Resilience Scale (r = .753**). The Internal Self-Confidence Scale asks participants

to indicate the extent to which they agree or disagree with each item on a 7-point

Likert scale. Sample items include 1) I believe in my ability to succeed, 2) While I

may not be perfect, I am good enough, and 3) I’m sure of myself and my beliefs.

52

(Perkins, 2018)

General Risk Propensity. Hung and Tangpong’s (2010) General Risk

Propensity (GRP) Scale was used to measure an individual’s general propensity

towards risk. General risk propensity is believed to be an individual’s overall

tendency to take or avoid risks. Participants were asked to respond on a 7-point

scale regarding the extent to which 5 items are accurate or inaccurate descriptions

of themselves. The scale has fair reliability, with a Cronbach’s alpha of 0.71 (Hung

& Tangpong, 2010). It has also been tested for measurement validity through

correlation analysis between the score of the five-item GRP scale and related scales

including openness (Goldberg, 2006), problem-specific ambiguity tolerance

(Ashford and Cummings, 1985), general ambiguity tolerance (McLain, 1993), and

financial risk propensity (Kapteyn & Teppa, 2002). Sample items include: 1) To

earn greater rewards, I am willing to take higher risks, and 2) I like to take chances,

although I may fail. (Hung & Tangpong, 2010).

Analyses

Analysis occurred in multiple stages. First, a set of preliminary analyses

was performed to evaluate the quality of the data for its intended use. Quality

checks were considered in the data cleaning and elimination of responses from the

dataset. The preliminary analyses included several tests to verify the

appropriateness of using the data for further evaluation. Details of this process are

provided in the next section.

53

Next, an additional set of analyses was conducted to test the proposed

hypotheses. Preacher and Hayes PROCESS macro was used to test the four

hypotheses initially. Then, Structural Equation Modeling (SEM) in R was used for

testing of alternative models to existing data in order to discover the role and

importance of mediating variables. This method allowed for a detailed analysis of

the hypothesized relationship within the context of the entire model. It is an

especially attractive method when testing mediating variables in that all of the

relevant paths are tested simultaneously and complications such as measurement

error and feedback are directly incorporated into the model (Baron & Kenny,

1986). Its advantages include the simultaneous evaluation of many internal and

external variables, the allowance of measurement error in both types of variables

and reduction of its biasing effects, the testing of both measurement and structural

models, the specification of latent variables with multiple observed indicators, and

the calculation of indices of fit of the model to the data (Bollen and Long, 1993;

Kenny, Kashy & Bolger, 1998; Mathieu & Taylor, 2006). Structural equation

modeling is generally conducted in two steps (Anderson & Gerbing, 1988;

McDonald & Ho, 2002). First, one checks the adequacy of the measurement

instruments using confirmatory factor analysis in order to test whether the

constructs exhibit sufficient reliability and validity. Then, the second stage

identifies the structural model(s) that best fit the data and tests the hypothesized

(direct/indirect) relationships between constructs.

54

SEM shows some advantages over regression analysis. SEM offers

flexibility in analyzing mediation models due to its ability to handle a mix of

measured and latent variables, thus being able to test large and complex models.

Furthermore, SEM assesses the concerns about the impact of the measurement

error on the estimation of relationships among variables (Hoyle, 2012; Hoyle &

Kenny, 1999) and it provides model fit information that estimates the consistency

of the model with the data. Some evidence suggests that straightforward SEM

models could be meaningfully tested even if sample size is quite small (Hoyle,

1999; Hoyle & Kenny, 1999; Marsh & Hau, 1999). Normally, N = 100–150 is

deemed to be the minimum sample size for conducting SEM (Anderson & Gerbing,

1988; Ding, Velicer, & Harlow, 1995; Tabachnick & Fidell, 2001; Tinsley &

Tinsley, 1987). Some researchers, depending on the number of parameters in the

model, may suggest an even larger sample size for SEM, N = 200 (Boomsma &

Hoogland, 2001; Hoogland & Boomsma 1998; Kline, 2005).

Results

Data Cleaning

First, the dataset was screened for cases of missing data. Entries were

deleted that were not 100% filled out excluding demographics. Entries were deleted

that failed three attention checks. This resulted in a final count of 196 total

participants.

55

Descriptive Statistics

An initial bivariate correlation analysis was conducted on the study

variables and results are reported in Table 2.

Table 2. Summary of Intercorrelations, Means, and Standard Deviations for Study

Variables

1 2 3 4 5 6 7 8 9 10 11 12

1. Access to Role Models -- (.93)

2. Pre Start-up .88** -- (.92)

3. Post Start-up .88** .58** -- (.92)

4. Perceived Family Support .12 .08 .10 -- (.89)

5. Emotional .06 .07 .02 .78** -- (.82)

6. Instrumental (Work) .09 .06 .09 .87** .58** -- (.90)

7. Instrumental (Home) .13 .08 .13 .70** .36** .37** -- (.81)

8. Internal Self-Confidence .13 .11 .12 .08 .06 .03 .10 -- (.87)

9. General Risk Propensity .06 .04 .09 -.06 -.13 -.01 -.03 .26** -- (.77)

10. Venture Growth Intention .07 .05 .06 .06 -.03 .15* -.02 .25** .29** -- (.71)

11. TY projected revenue .02 -.01 .04 .01 .03 -.06 .10 .09 .00 .20** --

12. No. employees this year -.06 -.12 -.02 .16* .19** .13 .06 .02 .10 .37** .28** --

Mean 55.69 28.80 23.74 58.91 20.09 20.22 18.60 72.66 25.98 31.64 5.14 1.76

SD 16.09 11.05 7.36 15.92 5.37 8.52 6.08 7.46 4.82 5.15 3.10 1.22

Notes. N=196; *p < 0.05; ** p < 0.01; TY = this year

Additionally, reliability for all scales used in this study are reported along

the diagonal in parentheses. Access to role models had a Cronbach’s alpha of .93.

Regarding the subscales of access to role models, the pre start-up subscale had a

Cronbach’s alpha of .92 for 6 items and the post start-up subscale had a Cronbach’s

alpha of .92 for 6 items. Venture growth intention had an initial Cronbach’s alpha

of .66 for 6 items, but when item 2 (I want a size I can manage myself or with a

56

few key employees) was removed, the reliability rose to .71. This item appeared to

be confusing and was worded in an opposite manner to the rest of the items in the

group and was, therefore, deleted. General risk propensity had a Cronbach’s alpha

of .77 for 5 items. Internal self-confidence had a Cronbach’s alpha of .87 for 12

items. Finally, perceived family support had a Cronbach’s alpha of .89 for 13 items.

Regarding the subscales of perceived family support, the emotional support

component included 4 items and had a Cronbach’s alpha of .82 the instrumental

support at work subdimension had a Cronbach’s alpha of .90 for 5 items, and the

instrumental support at home subdimension had a Cronbach’s alpha of .81 for 4

items.

Preliminary Analysis

Prior to testing the hypotheses, confirmatory factor analysis was performed

on the five variables in the model using R statistical package. In determining

adequate fit, several fit statistics were evaluated: the root mean square error of

approximation (RMSEA), the standardized root mean square residual (SRMR), the

comparative fit index (CFI) and the Tucker-Lewis Index (TLK). According to

Kenny (2014), the cutoffs for these statistics are widely argued, however generally

speaking, RMSEA and SRMR are preferred to be under .05; the poor fit cutoff is

.08. Regarding CFI and TLI, models with values above .95 are considered to fit

well, with values above .9 considered to be moderately fit. The fit statistics for this

model indicated poor fit (TLI = .69, CFI = .71, RMSEA = .09, SRMR = .08).

57

Modification indices were examined to identify possible sources of model

misspecification as well as paths that could be added to systematically improve the

fit of the model. CFA of the modified model (see Table 3) revealed that it still

provides a poor fit to the data (TLI = .83; CFI = .84; RMSEA = .06, SRMR = .08).

Table 3. Measures of Global Fit

x2 df p TLI CFI RMSEA SRMR

Acceptable fit

threshold <.05 >.90

(satisfactory)

>.90

(satisfactory) <.05 <.05

>.95 (good) >.95 (good)

Original model 2254 850 .000 .69 .71 .09 .08

Modified model (MI) 1727 879 .000 .83 .84 .06 .08

Notes. TLI: Tucker-Lewis index; CFI: comparative fit index; RMSEA: root mean

square error of approximation; SRMR: standardized root mean square residual

Hypothesis Testing

Hypothesis testing was conducted using the Preacher and Hayes PROCESS

macro for testing mediation and serial mediation. This program uses bootstrapping,

a process of iterative replacement, to generate confidence intervals around effects.

Significance is determined by the absence of zero in the confidence interval.

Hypothesis 1 predicted that risk propensity would be significantly related to

venture growth intention. A simple linear regression was used to assess this

relationship. The results of the regression show that risk propensity accounted for

9.3% of the variance in venture growth intention (r = .29, R2 = .093, F (1,186) =

18.00, p<.001); thus, Hypothesis 1 was supported.

Hypothesis 2, suggesting that risk propensity mediates the relationship

58

between internal self-confidence and venture growth intention, was supported. The

relationship between internal self-confidence and venture growth intention was

mediated by risk propensity. The path coefficient between internal self-confidence

and risk propensity was statistically significant, as was the path coefficient between

risk propensity and venture growth intention. The standardized indirect effect was

(.16)(.26) = .04. The significance of this indirect effect was tested using

bootstrapping procedures and the 95% confidence interval range indicated the

indirect effect was statistically significant because zero was not included (CI: .01,

.08).

Hypothesis 3, proposing that the relationship between access to role models

and venture growth intention is serially mediated by internal self-confidence and

risk propensity was not supported. The two-stage mediation path did contain zero

in its confidence interval (CI: -.03, .05). Hypothesis 4, which replaced access to

role models with perceived family support, was not supported (CI: -.02, .06). The

results of the tests of Hypotheses 3 and 4 are reported in Table 4.

Table 4. Results of the Serial Mediational Testing for Hypotheses 3 and 4. Hypothesis Independent

Variable

Mediator 1 Mediator 2 Path Coefficient SE 95% CI

a d b c’

3 Access to

Role

Models

Internal

self-

confidence

Risk

Propensity

.06 .16** .25** .01 .02 {-.03, .05}

4 Perceived

Family

Support

Internal

self-

confidence

Risk

Propensity

.04 .17** .26** .02 .02 {-.02, .06}

**p < .01, * p < .05

Path a represents the relationship between the IV and the first mediator. Path d represents the relationship

between the first mediator and the second. Path b represents the relationship between the second mediator and

the DV. Path c’ represents the direct effect between the IV and the DV.

59

The full SEM model was run in R and early indicators did not show a good

fit (TLI = .89, CFI = .88, RMSEA = .06, SRMR = .07). Several additional analyses

were run in an attempt to understand why access to role models and perceived

family support were factors that did not correlate well or predict well with the rest

of the model. First, a model was run using only the subdimension of the emotional

support subdimension of Perceived Family Support. It resulted in a poor fit as well

(TLI = .74, CFI = .76, RMSEA = .09, SRMR = .08). Next, the subdimension of

instrumental support at work was substituted for the emotional support

subdimension of Perceived Family Support. The model fit was also poor (TLI =

.76, CFI = .77, RMSEA = .09, SRMR = .07). However, an interesting finding

appeared in which the instrumental support at work subdimension correlated with

venture growth intention (r = .15*, p < .05); it had a direct effect on venture growth

intention, but not through internal self-confidence and general risk propensity.

Next, the instrumental support at home subdimension for Perceived Family Support

was substituted in the model and the results reported were also sub-standard (TLI =

.75, CFI = .76, RMSEA = .09, SRMR = .08). Two more models were evaluated

separating out the subdimensions of Access to Role Models. The pre start-up phase

subdimension was used in the next model and the fit statistics did not reach

acceptable levels (TLI = .79, CFI = .80, RMSEA = .08, SRMR = .08).The post

start-up phase subdimension was substituted in the previous model and the fit

statistics were also not adequate (TLI = .78, CFI = .80, RMSEA = .08, SRMR =

60

.08)

Table 5. SEM Fit Statistics

x2 df p TLI CFI RMSEA SRMR

Acceptable fit

threshold <.05 >.90

(satisfactory)

>.90

(satisfactory) <.05 <.05

>.95 (good) >.95 (good)

Original model 2615 1026 .000 .69 .71 .09 .08

PFS – Emotional 1666 657 .000 .74 .76 .09 .08

PFS – Instrumental

(Work) 1704 694 .000 .76 .76 .09 .07

PFS – Instrumental

(Home) 1676 657 .000 .75 .76 .09 .08

ARM – Pre start-up 1612 771 .000 .79 .80 .08 .08

ARM – Post start-up 1660 771 .000 .78 .80 .08 .08

Notes. TLI: Tucker-Lewis index; CFI: comparative fit index; RMSEA: root mean

square error of approximation; SRMR: standardized root mean square residual

Exploratory Analyses

In order to further understand the antecedents to venture growth intention,

several additional analyses were conducted.

I first conducted a first-stage moderated mediation analysis based on Figure

5 below in which perceived family support would have an interaction effect with

internal self-confidence. As mentioned above, the family embeddedness

perspective (Powell & Eddleston, 2013) suggests that women make decisions about

their businesses in conjunction with decisions about the effect of their decisions on

the family and also how the family dynamics influence their business. Greater

perceived family support, along with internal self-confidence, may encourage the

entrepreneur to take more risks and move forward with growing her business.

61

Figure 5. First Stage Moderated Mediation with PFS as Moderator

Internal self-confidence and perceived family support had a significant

interaction effect on risk propensity in predicting venture growth intention (b = .01,

p < .05). To better understand the pattern of this interaction, I plotted the

relationship between internal self-confidence and risk-propensity at low and high

levels of perceived family support (Figure 6), showing that the positive relationship

was stronger for individuals with high perceived family support. I further tested the

indirect effect of internal self-confidence on venture growth intention via risk

propensity at low and high levels of perceived family support, and estimated their

95% CI with 5000 bootstrapped samples. The indirect effect was stronger for

individuals with high levels of perceived family support (indirect effect = .08, 95%

[.02, .15]) and was not significant for individuals with low levels of perceived

family support (indirect effect = .01, 95% [-.02, .05].

Perceived Family

Support

Self-Confidence

(Internal)

Risk Propensity Venture Growth

Intention

62

Figure 6. Interaction effect of internal self-confidence and perceived family support

on risk-propensity

Notes. ISC: Internal Self-Confidence. PFS: Perceived Family Support

Second, a first stage moderated mediation was conducted substituting

Access to Role Models for Perceived Family Support and an interaction effect was

not found in this instance. Finally, a second stage moderated mediation was

conducted using perceived family support as the moderator, and this time, an

interaction effect with risk propensity was not found. Access to role models was

substituted for perceived family support in this second stage moderated mediation

and it also did not have an interaction effect with risk propensity.

Discussion

The purpose of this study was to examine how women entrepreneurs make

the decision to grow their businesses – in other words, what factors predict the

likelihood of venture growth intentions by established women entrepreneurs. The

25.3

25.4

25.5

25.6

25.7

25.8

25.9

26

26.1

26.2

Low ISC High ISC

Ris

k P

rop

ensi

ty

Low PFS

High PFS

63

present effort sought to add to the current lack of research literature regarding

venture growth intentions for women entrepreneurs as well as provide clarity on

some of the factors that affect venture growth intentions directly and indirectly.

Overall, this goal was accomplished to a certain extent. Therefore, the results of the

regression analyses are examined below.

Hypothesis 1 proposed that risk propensity was positively related to venture

growth intention and it was supported. As risk propensity (the individual’s

immediate tendency to take or avoid risk (Pablo, 1997; Sitkin & Pablo, 1992; Sitkin

& Weingart, 1995) increases, venture growth intention increases. Most of the

research to date linking risk to intention has mainly focused on entrepreneurial

intention – in other words, intention to start a business. The above finding is

important due to the lack of research available making the connection between risk

propensity and venture growth intention in the entrepreneurship literature. The

current finding also extends the previous research by providing a national sample

of women entrepreneurs, where previous studies focused mostly on student

populations.

In accordance with prior research suggesting that some of the most

frequently cited outcomes of self-confidence are variables associated with risk

(Perkins, 2018), Hypothesis 2 was also supported. It proposed that risk propensity

mediates the relationship between internal self-confidence and venture growth

intention. As a woman entrepreneur’s internal self-confidence continues to

64

increase, the relationship with venture growth intention also increases through

greater risk propensity. As noted previously, risk propensity has been found to

associate with entrepreneurial intentions (Zhao et al., 2010) and entrepreneurial

status (Zhang & Arvey, 2009). Moreover, high levels of risk propensity had been

found to positively predict self-employment intention. (Nieß & Biemann, 2014) The

link between risk propensity and self-employment has been established in the

research literature (Cramer, et al., 2002; Van Praag & Cramer, 2001; Zacher et al.,

2012). This connection takes the entrepreneurial research a step further by

demonstrating a positive relationship between risk propensity and venture growth

intention for women entrepreneurs.

Previously, self-confidence had been linked with varying levels of risk-

taking behaviors (Brindley, 2005; Maxfield et al., 2010; Yordanova &

Alexandrova-Boshnakova, 2011). Additionally, Maxfield et al. (2010) found that

self-efficacy strongly associated with risk-taking by women. Confident people have

been found to risk security and comfort to achieve higher levels of growth.

(Addis,2008).

According to Perkins (2018), self-confidence has been ill-defined in various

ways within the research literature in which many studies have used measures of

self-efficacy or self-esteem to substitute for the measure of self-confidence.

Previous research had not included a more robust measure of self-confidence. This

study used a more comprehensive measure of internal self-confidence (including

65

subdimensions of self-efficacy, self-esteem and self-care) that when analyzed with

risk propensity, it suggested a significantly positive relationship.

This finding is also significant in that it reinforces the Theory of Planned

Behavior (Azjen, 1991) and the venture growth intention model presented above.

The Theory of Planned Behavior suggests that the strength of the intention is

determined by attitudes toward the behavior, subjective or social norms, and

perceived control over the behavior. Perceived behavioral control is a subjective

evaluation of one’s capacity to execute a particular behavior with ease or difficulty;

and, the assumption is made that it reflects past experience as well as future

roadblocks (Ajzen, 1991). Previous research suggests that there are positive

relationships between risk taking behaviors and entrepreneurial intent (D’Amboise

& Muldowney, 1988), as well as self-efficacy and entrepreneurial intent (Boyd &

Vozikis, 1994; Krueger & Carsrud, 1993). Yet these variables have not been

studied previously in relationship with venture growth intention in this manner.

This study is unique in that a mediational relationship was found in which internal

self-confidence is positively related to venture growth intention through general

risk propensity.

Hypothesis 3, proposing that the relationship between access to role models

and venture growth intention is serially mediated by internal self-confidence and

risk propensity, was not supported. According to previous research, role models

had been found to shape self-efficacy and outcome expectations leading to

66

intentions of pursuing an entrepreneurial career (Lent et al., 1994; Nauta, Epperson

& Kahn, 1999). Van Auken et al (2006) also found that the presence of role models

may increase entrepreneurial self-efficacy. Additionally, role models have been

identified as a critical component to the process in which beliefs, attitudes and

intentions evolve (Lent et al., 1994). Therefore, it was surprising to have found no

significant relationship between access to role models and self-confidence or any

other variable in the above model. One issue may be that access to role models may

not have been precisely defined or measured. For instance, access to role models

was perhaps too vaguely defined and respondents could have been thinking about

physically accessible role models they interacted with or they could have been

thinking about role models idolized from afar. Further, we don’t know how they

interacted specifically with the role models in this study.

An additional exploratory analysis was conducted using the confidence

subdimensions (self-efficacy, self-esteem and self-care). to understand if there were

any significant relationship between access to role models and one of the above

subdimensions. A bivariate correlation was performed and the result indicated that

there was a significant positive relationship between access to role models and the

self-care subdimension (r = .153, p < .01). Taking it a step further, a serial

mediation analysis was conducted testing whether the relationship between access

to role models and venture growth intention was serially mediated by the self-care

subdimension of internal self-confidence and risk propensity. The two-stage

67

mediation path did not contain zero in its confidence interval (CI:.00, .01). A

significant indirect effect was found to have occurred. Without understanding how

the entrepreneur interacted with the role models (e.g. perhaps it was on a more

personal level vs a professional level), it may be difficult to reach a conclusion as

to the impact of access to role models on venture growth intention.

Hypothesis 4, which suggested that the relationship between perceived

family support and venture growth intention was serially mediated by internal self-

confidence and risk propensity, was also not supported. As noted previously, the

goal towards achieving balance and integration between work and family may be

one of the strongest motivators for women to start and grow their businesses. A

family embeddedness perspective (Powell & Eddleston, 2013) suggests that the

entrepreneur views the family as a major source of encouragement providing

instrumental and emotional support on a daily basis (Eddleston & Powell, 2012).

Without this type of support, other researchers suggest that women entrepreneurs

may not be as motivated to sustain and grow their businesses and the enlistment of

family cooperation is critical to business growth and survival. (Aldrich & Cliff,

2003). Many women entrepreneurs express concern as to whether they will receive

support of family members regarding their desires and goals for achieving success

and growth in their entrepreneurial endeavors. With this in mind, further

exploration of how perceived family support may have a significant relationship

with venture growth intention, internal self-confidence, and risk propensity was

68

important to pursue.

Therefore, one potential explanation for the above non-finding is that upon

further explanatory analysis, it was found that perceived family support had a

moderating effect on the relationship between internal self-confidence and risk

propensity. So, rather than perceived family support predicting internal self-

confidence, there occurred a first-stage moderated mediation effect in which

internal self-confidence and perceived family support had a significant interaction

effect on risk propensity in predicting venture growth intention. At low levels of

perceived family support, there was not a significant interaction effect. However,

high levels of perceived family support had a significant interaction with internal

self-confidence to predict risk propensity and venture growth intention for women

entrepreneurs. Although a serial mediation effect did not occur, the above

exploratory analysis suggests that perceived family support has a key impact on

women entrepreneurs’ decision-making processes with regard to venture growth

intention. If she does not perceive a high level of family support, she may feel the

need to take less risk with regard to her business (as family in many cases comes

first) and therefore not take additional opportunities to grow her business. This

finding demonstrates that family embeddedness (the idea that decisions about her

business are made with a high regard for their effect on her family) is a key

consideration with regard to venture growth intention. This research extends the

previous entrepreneurship literature by using a diverse geographical sample of

69

women owned businesses as well as suggesting that perceived family support plays

a key role in the interaction effect with internal self-confidence to help predict risk

propensity and eventually venture growth intention.

Limitations

The data set utilized for this study provided many clear advantages in that it

was a diverse sampling of women-owned businesses in various industries located

throughout the United States. Although there wasn’t an extremely high level of age

diversity in the sampled population with the average age of the women being 50

years old, it makes sense since the average age for a woman to start a business is 40

and the women surveyed were selected business owners who have been in business

for at least a year or more. The sample size of 196 may have been a contributing

limitation, even though many researchers suggest that 200 is an acceptable

sampling for SEM analysis (Wolf et al., 2013). Regarding any limitations with

scales used, venture growth intention was the only scale constructed that had not

been validated previously and additional items were added for the purpose of this

research.

Another significant limitation to the results was demonstrated by the failure

of the SEM model to demonstrate adequate fit. The failure may be related to the

lack of fit in the measurement model and also it may be attributable to model

misspecification. Perhaps there was inclusion of irrelevant variables, exclusion of

relevant variables, or inadequately determined relationships between variables.

70

A third limitation may be the single cross-sectional survey which may have

posed some threats to the validity of the serially mediated hypotheses. In addition,

there may be some concern with regard to common method bias due to the use of a

cross-sectional survey (Podsakoff et al., 2012). Some suggest that it is difficult to

test mediation effects without performing experimental manipulation and having

longitudinal studies performed (Stone-Romero & Rosopa, 2008). However, Spector

(2019) suggests that cross-sectional designs are important when you get into a new

domain where little is known – as in this case with venture growth intention and

women’s entrepreneurship. Another reason to conduct a cross-sectional design is

when one is performing exploratory research where situations exist and the patterns

of the relationships are unknown.

Finally, the first step of this research was to focus on women-only

established businesses as opposed to the often used comparison models between

men and women utilized by previous researchers that create the “othering effect” in

which results for women business owners end up being “less than” what the

standard is considered to be – which turns out to be a male standard. Regarding the

entrepreneurship research to date, very little has been done focusing solely on

women entrepreneurs to enable us to understand how women entrepreneurs “do”

business.

Theoretical Implications

Prior to this study, the research on women’s entrepreneurship has failed to

71

provide solid evidence as to how women “do” entrepreneurship. As noted

previously by Ahl (2006), there are a number of shortcomings in women’s

entrepreneurial research literature in which she labels “discursive practices.” These

include a lack of theoretical grounding (Brush, 1992), use of male-gendered

measuring instruments (Moore, 1990; Stevenson, 1990), a one-sided empirical

focus (Gatewood et al., 2003) and a lack of explicit feminist analysis (Mirchandani,

1999; Ogbor, 2000; Reed, 1996). This paper contributes to entrepreneurial research

theory by integrating Ajzen’s Theory of Planned Behavior with Feminist Theory to

address a few of the discursive practices that Ahl (2006) introduces.

First, this paper has addressed the issue in which researchers have focused

mainly on male-owned businesses and male entrepreneurs and the women have

been added to the studies as afterthoughts for comparative purposes. This has

created a “less than” or “othering effect” when direct comparisons have been made

and generalizations developed regarding between group dynamics. Very few

studies have been performed in entrepreneurial research literature that focus on

within group results of women entrepreneurs in which we can learn and understand

more in-depth how women “do” business. This paper has contributed to the

research by sampling a diverse population of women owned businesses only and

studying within group effects.

Second, another discursive practice that has been suggested by Ahl (2006)

is the overuse of male gendered measurement instruments. This paper has been able

72

to introduce at least one measurement scale that is gender neutral leaning, and, it is

a more comprehensive measure of self-confidence than used in previous

entrepreneurial research literature. In fact, numerous research studies in

entrepreneurship and business studies have substituted self-efficacy for confidence

(Addis, 2008; Baldoni, 2009; Clarke, 2011; Kanter, 2014; Kirkwood, 2009;

Koellinger, Minniti & Schade, 2007; Luthans, Luthans & Luthans, 2004; Luthans

& Youssef, 2004). This is the first entrepreneurial study that has used a more

comprehensive measure of internal self-confidence. The Internal Self-Confidence

Scale based on the Integrated Model of Self-Confidence (Perkins, 2018) was

recently developed and validated using sample sizes including a relatively large

percentage of women (60% range) in the developmental stages of the scale. This

may indicate a forward lean toward gender neutrality in the use of this particular

comprehensive scale

Third, this project expands the understanding of the various relationships

between self-confidence, risk propensity and venture growth intention. By using a

more fully developed scale of internal self-confidence based on the Integrated

Model of Self-Confidence (Perkins, 2018), this study provides further evidence

that, for women entrepreneurs, internal self-confidence is a key antecedent to

venture growth intention. Previous research had connected self-confidence and self-

efficacy to entrepreneurial intention (Boyd and Vozikis, 1994; Chen et al., 1998;

DeNoble et al., 1999; Liñán & Chen, 2009; McGee, et al., 2009; Wilson et al.,

73

2007; Zhao et al., 2005). Venture growth intention has been linked to risk taking

(D’Amboise & Muldowney, 1988) and self-efficacy (Boyd & Vozikis, 1994;

Krueger & Carsrud, 1993). Additionally, in the entrepreneurial literature,

connections had been made between self-efficacy and risk taking as well (Heat &

Tversky, 1991; Krueger & Dickson, 1994; Maxfield et al., 2010). Finally, the

Integrated Model of Self-Confidence (Perkins, 2018) is based on self-trust theory,

and Meyer et al. (1995) suggest that if you learn to trust yourself, you are more

likely to take risks in yourself. This study contributes to the entrepreneurship

literature by connecting the above-mentioned variables in a way that suggests a

significant relationship between internal self-confidence and venture growth

intention via risk propensity for women entrepreneurs. This is the first time that this

relationship has been identified and studied. It’s an important relationship to

identify in that it can inform the development of interventions that can address the

entrepreneur’s decision-making processes and motivations toward venture growth

intention.

Fourth, Ahl (2006) indicates that in the general entrepreneurship literature,

family appears to be a non-existent factor, yet, in women’s entrepreneurial research

family has been positioned as a problem (Stoner et al., 1990); and, it has also been

positioned as a source of inspiration and support (Brush, 1992; Buttner, 2001).

Regardless, this appears to be an area that may not only need to be studied in

relation to women’s entrepreneurship, but should be a factor included in the studies

74

on entrepreneurship in general. Family embeddedness, the notion that work and

family are not a separate issue and should be perceived as an integrated

phenomenon, is an extremely important factor to consider with regard to

understanding the decision-making process and intentions for venture growth. As

outlined previously, theories of social support (Sarason et al., 1990; Uchino, 2004)

describe frameworks in which an individual operates within social settings (e.g.

business networks and family ties). These theories have been extended by some

researchers that have applied them to “family-to business” support (Baron, 2002;

Jennings & McDougald, 2007; Rogers, 2005). Aldrich and Cliff (2003) suggested

that one social institution in which all entrepreneurs are embedded is the family

(i.e. a family embeddedness perspective) and that perhaps this is one of the most

important external factors to study as a primary social institution that should be

examined within the entrepreneurship research field. This paper contributes to

theoretical understanding of this phenomenon by including perceived family

support and how it interacts in the proposed model of women’s entrepreneurship.

Through additional exploratory analysis, this study found that the indirect effect of

internal self-confidence on venture growth intention via risk propensity was

stronger for individuals with high levels of perceived family support and not

significant for individuals with low levels of perceived family support. This is

important because it demonstrates the influence of external factors (the social

institution of family) that interact with and influence internal factors (internal self-

75

confidence) that may create motivation and intention for business growth. It also

informs how support organizations should proceed with interventions that will

increase the likelihood of venture growth intention.

Practical Implications

For women business owners, this research suggests that the continued

development of risk propensity and self-confidence along with the ability to

negotiate more support at home and work from family members may be a

successful formula in leading to venture growth intention and ultimately venture

growth. Entrepreneurial development organizations may benefit from this research

by designing business mentoring and coaching programs specifically for women

entrepreneurs addressing these factors that lead to the initiation and development of

venture growth intention. The concept that women entrepreneurs view business

growth through the lens of family embeddedness and its effects on their decision-

making processes should alert those organizations that support entrepreneurial

growth for women and address their specific needs with regard to venture growth.

Current business mentoring programs in many of these organizations focus

on the nuts and bolts of how to conduct business. For example, Women’s Business

Centers and Small Business Development Centers nationally (supported by SBA

funding) most often provide training and workshops on legal, accounting,

marketing and operational issues with a focus on start-up businesses and beyond. A

lesser percentage of support organizations provide mentoring and coaching

76

programs that target some of the factors that are addressed in this study such as

self-confidence, risk propensity and family support. For the most part, these

organizations address the needs of the business and rarely provide focus on the

developmental needs of the entrepreneur as leader or how the entrepreneur

negotiates relationships with their specific support systems. It is assumed that the

entrepreneur comes fully equipped with the confidence, the propensity to take risks

and the appropriate amount of support to start and grow a business on their own or

with a business partner. In fact, in many circumstances, they are evaluated to see if

they already have what many in the entrepreneurship field call “entrepreneurial

mindset” and if they already have what it takes, then the training focus is more on

the tasks and operations of running a business as opposed to focusing on areas of

how to prepare oneself for growing a business.

For example, if high levels of family support are a critical component in the

venture growth intention model, then perhaps mentoring and coaching programs

should include sessions with family member involvement so that they can more

easily support the needs of the entrepreneur and the steps they must take in order to

achieve business growth. Or, perhaps there are mentoring and training sessions that

should be developed for families and other social support networks connected with

the entrepreneur that set expectations and provide understanding that it’s not just

the entrepreneur that goes through the rigorous process of growing a business, but

the whole family is involved. An interesting comparison could be made to the

77

training and other interventions that are provided for families of expatriates when

they go on a foreign assignment for large corporations. In these instances, pre-

departure, during the assignment and post-assignment training is provided to help

the families acclimate to the unusual circumstances of living in a foreign country

and assimilating back into their original culture (Hechanova et al., 2003). Although

it may be difficult to make a direct comparison to the expatriate experience,

developing interventions that address family acclimatization to the unusual

circumstances of starting and growing a business should be addressed in helping to

achieve successful outcomes for the entrepreneur and her business.

If self-confidence has a significant positive relationship with venture growth

intention, then perhaps these organizations should also provide experiential

learning, coaching and development that supports the growth of self-confidence in

their developmental programs. Many organizations expect that the entrepreneur has

a high level of self-confidence perhaps because they already started their business,

but what seems to be apparent is that a developmental process is needed to increase

self-confidence along the way as the entrepreneur chooses a path for accelerated

business growth. Leadership development programs and coaching programs should

be administered alongside of “how to” workshops in order to assist the

entrepreneur on her path toward venture growth intention and venture growth.

78

Future Research

This study was a starting point using a cross-sectional survey sample of

women entrepreneurs to delve into the factors that may be critical for them in the

process of deciding to grow their businesses. An exploratory independent samples

t-test was performed comparing women entrepreneurs in this study to a general

population of women surveyed in Mturk. Final results indicated that the women

entrepreneurs (M = 72.66, SD = 7.46) reported significantly higher levels of self-

confidence than a general population of women (M = 63.33, SD = 13.18, t (395) =

8.65, p < .01, N=201). Women entrepreneurs (M = 25.98, SD = 4.82) reported

significantly higher levels of risk propensity than a general population of women,

as well (M = 21.02, SD = 6.49, t(395) = 8.62, p < .01, N=201). One consideration

for the future is to conduct longitudinal research to determine if confidence drives

business success and growth or if business success and growth drive increased

confidence. Future research should focus on more qualitative efforts to understand

the contextually unique factors for women entrepreneurs, as well as what gender-

neutral measures need to be developed that are more appropriate to measure women

entrepreneurs’ attitudes, behaviors and intentions. It would also be informative to

investigate other external factors that could possibly affect venture growth intention

such as gaining access to capital or the ability to access and utilize appropriate

business networks and relationships (specifically understanding the density, size

and strength of ties within the networks). This would help to provide more clarity

79

and understanding if there are additional significant external factors that need to be

addressed and interventions developed to enhance the motivation and success of

venture growth intention as well as venture growth.

Another potential avenue of research would be to examine types of

interventions such as various types of mentoring programs (including peer-to-peer

and group mentoring), one-on-one coaching programs and the like to see how they

interact with and moderate some of the relationships in the proposed model above.

This would help to address and model those that have significant effect on venture

growth intention and provide much needed research in developing more successful

programs that address the specific needs of women entrepreneurs who seek venture

growth.

Finally, the effect of role models on venture growth intention (based on

previous research) seems to be a critical area to study. A more precise and targeted

understanding of how women entrepreneurs interact with or use role models in

conjunction with advancing toward venture growth intention may be useful to

study. This paper focused only on whether they had access or not, but a more useful

study as suggested above may help to fine tune the interventions needed to assist

women entrepreneurs in the decision-making process toward venture growth.

Conclusion

Women entrepreneurs’ contribution to economic growth and job creation

has steadily and significantly increased over the last 20 years. Yet, researchers and

80

the business community alike have focused little effort on the actual factors that

lead to their intentions and subsequent decisions to grow their businesses. It is

important to understand this phenomenon because, although women are starting

businesses at a faster rate than the industry average, they are growing their

businesses at a slower rate than the national average. The primary focus of this

study was to shine a light on this issue so that economic development

organizations, entrepreneurial support organizations and other entities that support

entrepreneurship can implement interventions that will address these factors that

help to promote venture growth intention and, therefore, venture growth.

This study sought to bolster the body of knowledge surrounding women’s

entrepreneurship which is currently lacking in using women entrepreneur only

samples for within group comparisons as well as more gender-neutral measures to

delve into understanding how women “do” entrepreneurship. It also was able to use

a more comprehensive measure of internal self-confidence based on the Integrated

Model of Self-Confidence (Perkins, 2018). Finally, the results of this study offer

some evidence that internal self-confidence leads to venture growth intention via

risk propensity and the conditions that impact its efficacy – i.e. higher rates of

perceived family support. Outcomes conveyed in this study provide additional

support for investing additional resources into this area of research as women

continue to excel in the business world creating jobs and significant economic

development opportunities for themselves, their families and their communities.

81

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Appendix A: IRB Approval

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Appendix B: Venture Growth Intention Scale

Please rate the extent to which you agree or disagree with the following statements

about your business. (1 = strongly disagree to 7 = strongly agree)

1. I want my business to be as large as possible.

2. I want a size I can manage myself or with a few key employees. (R)

3. I want my business profitability to grow over time.

4. I want to create jobs for others.

5. It is one of my goals to grow my business over time.

6. I want to add products or services to my business over time.

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Appendix C: Access to Role Models Scale

Please rate your agreement or disagreement with each statement. (1 = strongly

disagree; 7 = strongly agree).

Pre-Startup

1. I had access to role models in the pre-start-up phase.

2. Without this/these role models I would probably have not started my

company.

3. I admired this/these role model(s) before I started my company.

(inspiration/motivation)

4. With this/these role model(s) in mind, I thought, "if (s)he can do this, I can

do this too." (self-efficacy)

5. This/these role model(s) has/have been a positive example for me at the

start-up phase of my company. (example)

6. This/these role model(s) has/have really supported me with starting up my

company. (support)

Post-Startup

7. I had/have access to role models in the post start-up phase.

8. Without this/these role model(s), I would probably not have continued

operating my company.

9. I admired this/these role model(s) in the phase of further development of

my company. (inspiration/motivation)

124

10. With this/these role model(s) in mind, I thought, "if (s)he can do this, I can

do this too." (self-efficacy)

11. This/these role model(s) has/have been a positive example for me in the

further development of my company. (example)

12. This/these role model(s) has/have really supported me with the continued

operation of my company. (support)

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Appendix D: Perceived Family Support Scale

Please indicate your level of agreement with each of the statements below (1 =

strongly disagree, 7 = strongly agree).

Emotional support (alpha = .82)

1. When I talk with them about my business, family members don’t really

listen (reverse coded).

2. When I have a problem at work, members of my family express concern.

3. Members of my family are interested in my business.

4. When I’m frustrated by my business, someone in my family tries to

understand.

Instrumental support for the business (alpha = .86)

1. I can count on my family members to fill in for me and/or my employees in

times of need.

2. Family members often contribute to my business without expecting to be

paid.

3. My family gives me useful feedback about my ideas concerning my

business.

4. Family members often go above and beyond what is normally expected in

order to help my business succeed.

5. Members of my family often help me with my business.

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Instrumental support at home (alpha = .84)

1. Members of my family help me with routine household tasks.

2. My family members do their fair share of household chores.

3. My family leaves too much for the daily details of running the house to me

(reverse coded).

4. If my business gets very demanding, someone in my family will take on

extra house-hold responsibilities.

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Appendix E: General Risk Propensity Scale

Please indicate your level of agreement with each of the statements below (1 =

strongly disagree, 7 = strongly agree).

1. I like to take chances, although I may fail.

2. Although a new thing has a high promise of reward, I do not want to be the

first one who tries it. I would rather wait until it has been tested and proven

before I try it. (Reverse)

3. I like to try new things, knowing well that some of them will disappoint me.

4. To earn greater rewards, I am willing to take higher risks.

5. I seek new experiences even though their outcomes may be risky.

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Appendix F: Internal Self-Confidence Scale

Please indicate your level of agreement with each of the statements below (1 =

strongly disagree, 7 = strongly agree).

Self-Efficacy

1. I am capable of achieving my goals.

2. I believe in my ability to succeed.

3. I have what it takes to get things done.

4. I often have doubts in my ability to meet my goals. (R)

Self Esteem

5. I am a person of value and worth.

6. I am happy with who I am as a person.

7. I am sure of myself and my beliefs.

8. I feel good about myself and who I am.

Self-Care

9. When I make a mistake, I can easily forgive myself.

10. While I may not be perfect, I am good enough.

11. I can learn from failures and try again.

12. I have the ability to cope with feelings of self-doubt.

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Appendix G: Demographics

1. What is your gender?

Male

Female

Other

2. How old are you?

under 25

25-34

35-44

45-54

55-64

65 or over

3.What is your race or ethnic background? (check all that apply):

White/Caucasian, Anglo, European American; not Hispanic

Black/African American

Hispanic or Latino, including Mexican American, Central American

Asian or Asian American, including Chinese, Japanese

Pacific Islander or Native Hawaiian

American Indian

Alaskan Native

Middle Eastern, including Northern African, Arabic, West Asian, and others

Other: Please Describe___________________

4. What is your nationality?

United States

Other: Please describe____________________

5. What is your marital status?:

Single

Married

Separated

Divorced

Widowed

Domestic Partnership (single, living together)

6. What is your highest education level?

High School graduate or equivalent

Some College

Associate’s degree

130

Bachelor’s degree

Some Graduate school

Master's Degree

Doctorate (including a Juris Doctorate – law degree)

7. How long have you owned your business?

less than 1 year

1-3 years

4-6 years

7-10 years

11-15 years

16-24 years

25 + years

8. Did you start the business or acquire the business?

9. Are you the sole owner of the business? Y/N

10. If not the sole owner, how many owners are there (including yourself)?

11. Do you have majority ownership? Y/N

12. What was last year’s total revenue?

<$49.999

$50,000-99,999

$100,00-$249,999

$250,000-$499,999

$500,000-$999,999

$1,000,000-$4,999,999

$5,000,000-$10,000,000

$>10,000,000

13. What is this year’s projected total revenue?

<$49.999

$50,000-99,999

$100,00-$249,999

$250,000-$499,999

$500,000-$999,999

$1,000,000-$4,999,999

$5,000,000-$10,000,000

$>10,000,000

131

14. How many people do you currently employ (include yourself)?

<5

5-9

10-19

20-49

50-99

100-249

250-499

500-1000

>1000

15. Do you have a parent that owns(ed) a business? Y/N

16. How did you hear about this survey?

Your place of work/organization: Please describe_________________

LinkedIn

Personal connection

Professional society affiliation

Women’s Business Center: Please describe_____________________

Other: Please describe__________________