





































78 

 

 

 
 

Franchising as a Path to Self-Employment for Women 
and Minorities in Retailing 

 
Juliana White 

Southeastern Louisiana University 
 

Aaron Matthew Gleiberman 
Louisiana State University 

 
Rebecca Rast 

Missouri State University 
 

Franchise-based retailing plays a vital role in fulfilling the public policy goal of supporting inclusion 
for women and minorities in the economic mainstream, through employment and self-employment 
opportunities. Using Census Bureau data, we compare franchising activity by two protected classes 
(women, minorities) with their comparison groups (men, non-minorities). Results indicate that 
franchising is used disproportionately by the protected classes as a path to self-employment. We also 
compare franchising activity among these groups across various sectors and find evidence that 
women and minorities use franchising to enter hard-to-access business sectors, of which they may 
have otherwise been excluded. Policy implications of these findings are discussed and directions for 
future research are offered. 
 
Keywords: franchise, women, minorities, labor discrimination, entrepreneurship, self-employment 
 

Introduction 
It has long been an important public policy goal in the United States to provide more 

opportunities for women and minorities to participate in the economic mainstream. Franchising is 
one potential avenue to aid in this goal. Franchising is undeniably a significant force in U.S. retailing 
(Ayorinde and Zubairu 2018; Combs and Ketchen, 2003), and is indeed one of the fastest-growing 
forms of retailing in the world, contributing $2.3tn annually to the global economy (Alon et al., 
2020; Michael, 2003). In the United States alone, franchising is responsible for approximately 9 
million jobs and contributed $541bn to the US gross domestic product (GDP) in 2016 (International 
Trade Administration, 2016). Due to its economic impact and public policy implications, the 
investigation of franchising activities is an important avenue of study. 

At its core, franchising aims to replicate successful retail business models by giving 
franchisees turnkey training and support. Consequently, it has been touted as a natural private sector 
means for providing self-employment opportunities to individuals who may not have acquired all of 
the skills and resources necessary to operate an independent business (Williams, 1999). In this 

http://journals.sfu.ca/abr ADVANCES IN BUSINESS RESEARCH 

2021, Volume 11, pages 78-101 



79 

 

business format, franchisees enjoy benefits from franchisors such as marketing support, training, 
and operations insight making the franchised business an attractive option for entrepreneurs with 
limited prior experience (Nijmeijer et al., 2014; Williams, 1999). Moreover, because franchisees gain 
access to established brands and publicly recognized service concepts, franchising may help 
overcome consumer reluctance to patronize women and minority-run businesses (Dyer and Ross, 
2000). This reluctance may be particularly true when the type of business is inconsistent with 
common industry stereotypes. For example, franchised female auto mechanics may face less 
resistance from consumers holding gender stereotypes than their independently operating 
counterparts. Thus, to the extent that franchising solves problems of access to skills and resources, 
or problems of consumer rejection, that are unique to women and minorities, those groups should 
be particularly attracted to franchising as a vehicle for starting their businesses. 

We empirically evaluate the extent to which women and minorities have been attracted to 
franchising relative to males and non-minorities through longitudinal data analysis of the 1997 and 
2012 Survey of Business Owners (SBO) (U.S. Census Bureau 2001, 2016). The data reveal that (1) 
women and minorities are indeed represented in franchising in disproportionately higher numbers 
than men and non-minorities, and (2) that this representation is sector-specific.  

 
Literature Review 

 The franchising business model can be traced back to the 1850s when the Singer Sewing 
company began marketing its products across the United States (Ayorinde & Zubairu 2018; Olotu & 
Awoseila 2011). Franchising calls for the exchange of business knowledge, tools, and resources from 
a franchisor who in turn requires a franchisee to make an equity investment in the franchisor’s 
business firm (Alon et al., 2017). Since its inception, franchising has attracted both franchisors who 
seek to grow their business ventures (Cumberland & Githens 2012), and franchisees who benefit 
from the training, skills, and distribution networks that franchising provides (Seo 2016; Alon et al., 
2017). Additionally, franchising allows greater access to certain industries through the use of 
established brands (Sanny et al., 2017).  
 In the 1990s, franchising experienced huge expansion both domestically and abroad through 
imitation of franchised business firms in the United States as well as the internationalization of such 
firms (Alon et al., 2020). Franchising has had far-reaching effects on international trade, specifically 
in service-based industries. This is evidenced by the $3.4tn in world service exports traced directly to 
developing economies (Franchisetimes top 200+, 2018). While the power of franchising can be seen 
globally, pronounced growth in franchising is also seen in the United States where the business 
model had its beginnings (Alon et al., 2020). 
 The topic of franchising saw a substantial increase in research interest from the years 2009 to 
2019, with a particular focus on international franchising showing tremendous growth in both 
articles published and citations (Alon et al., 2020). Due to the steadily increasing interest in 
franchising both domestically and internationally and the current research paradigm of exploring this 
phenomenon further, we believe franchising to be a highly relevant avenue of study. It is the goal of 
this research to add to the current body of literature on franchising and further increase our 
understanding of this business model, particularly in its potential to benefit women and minorities. 
 
Self-Employment Through Franchising 

Franchising is one of the most critical developments in retailing in the past century. By most 
estimates, it accounts for more than 40% of all retail dollars in the US economy (Combs and 
Ketchen, 2003). In particular, sectors, e.g., specialty food retailing, printing and copying, and tax 
preparations, it is the dominant form of retailing business organization (Combs and Ketchen, 2003). 
International growth is rapid and continuing, and franchised brands such as McDonald's, Pizza Hut, 



80 

 

and KFC are among the most recognizable brands throughout the world. Franchising has become 
so much a part of the marketing lexicon that it serves as the metaphor for the standardization of 
service offerings (Chiou and Droge, 2013; Kaufmann & Eroglu, 1999). Its unique incentive and 
organizational properties create hybrid relationships between franchisor and franchisee that provide 
opportunities for individuals, "to be in business for yourself, not by yourself" (Franchising World, 
1998). 

Because of its unique methods of training and operational and marketing support, 
franchising is viewed by many as an attractive alternative to the precariousness of independent self-
employment. Entrepreneurs are drawn to this business format due to the shared positioning with an 
established brand name and defined business strategy that franchising provides (Nijmeijer et al., 
2015). More importantly, it has been suggested that franchising also provides unique opportunities 
for women and minorities to become self-employed in the retail sector (McMillian and Baker, 2008; 
Williams, 1999). The training that a new franchisee gains in reputable systems is at least as significant 
as the training that a new employee might expect to receive within the same type of firm. In many 
instances, it far surpasses employee-type training designed to prepare the individual for the entry-
level tasks assigned. Franchisee training often includes real hands-on training in the basic managerial 
processes necessary to run one's own business (Nijmeijer et. al, 2014). When this training is 
accompanied by a business system that is time-tested and shown to have a significant likelihood of 
success, the prospective franchisee has access to a turnkey operation that makes self-employment 
available when it might not otherwise be possible. Franchisees also bring necessary financial capital 
and management capabilities that can significantly grow a franchisor’s growth potential, making 
franchising mutually beneficial for both parties (Gillis et al., 2020). 

Franchisee training in management techniques is particularly important for women. There is 
evidence that women entrepreneurs enter into self-employment with significantly less human capital 
than male entrepreneurs. Boden and Nucci (2000) found that women business owners were less 
likely to have prior managerial experience and less likely to have ten years of business experience 
than their male counterparts P0F

1
P. Women foreclosed from developing human capital through significant 

business experience may not have the necessary expertise to run their independent businesses. 
Franchising provides an alternative route to human capital formation. 

Entrepreneurship research has shown that franchisees and franchisors rely on extensive 
social support, necessitating a complex business framework and franchise network to obtain 
resources and achieve business success (Nijmeijer et al., 2014; Parker et al., 2018). Acquaintance, 
recognition, and trust are critical aspects of an entrepreneur's social capital in facilitating transactions 
with suppliers (Nahapiet & Ghoshal, 1998). In a franchise system, franchisors play the role of 
"brokers" (Aldrich, 1999) in connecting their franchisee-entrepreneurs to needed resource providers. 
Ongoing business support systems are common to franchise operations, providing access to 
industry knowledge, suppliers, and other necessary inputs making the franchisee less dependent on 
their networks (Combs et al., 2011; Peterson and Dant, 1991). For women and minorities who may 
lie outside traditional social and business networks, this brokerage removes another significant 
impediment to self-employment. 

Traditionally, women and minorities have faced difficulties obtaining financing for 
entrepreneurial ventures (Bardasi et al., 2011; Blanchard et al., 2008; Guzman and Kacperczyk, 2019, 
Yago et al., 2000). Stösic Panić (2017) found evidence of a pronounced gender gap in 
entrepreneurship financing strategies for male and female business owners in Serbia. Coleman 
(2000) found that although women had equal access to debt financing, they were more often asked 
to put up collateral and pay higher interest rates. Blanchflower, Levine, & Zimmerman (2003) and 

 
1 We did not find any studies that examined this same issue with respect to minorities. 



81 

 

Cavalluzo and Cavalluzo (1998) found that African Americans were much more likely to be denied a 
business loan application and that Hispanics were 22% more likely to withhold a loan application for 
fear of being denied credit. Further, Steil et al. (2018) showed that mortgage discrimination resulted 
in a disproportionate number of high-cost, high-risk mortgages for black and Latino borrowers. The 
body of evidence that women and minorities often face substantial hurdles when securing loans and 
financing gives further credence to the franchise business model.  

A franchisor's established system or brand is a legitimizing factor in the acquisition of 
financial inputs for women and minorities and may even lower the amount of needed capital. The 
credibility that an established franchise system provides (compared with an independent start-up) 
often makes the difference in getting the necessary financing to start a business (Shah, 1999). 
Competition for franchisee borrowers has increased to the point that specialized franchise lenders 
are willing to lend far more than the franchisees need (Larson, 1999). Moreover, although there is an 
additional capital requirement related to the franchise fee, the actual capital needs of a franchisee are 
likely to be lower than for an independent start-up. Many franchise systems either provide financing 
or arrange to finance prospective franchisees thus reducing the upfront cost of starting a franchise 
(Shane et al., 2006). 

Franchising may reduce internal, as well as external, impediments to self-employment for 
women and minorities. One reason for this relates to the perceived reduction in risk associated with 
becoming a franchisee. Franchising is typically thought to be a less risky route to business ownership 
than opening an independent business (Salar and Salar, 2014). There is evidence that women tend to 
be more risk-averse than men in investment decisions (Jianakoplos & Bernasek, 1998) and business 
ownership goals (Cliff, 1999) P1F

2
P. If franchising is perceived by women to be less risky, it will again be a 

relatively more attractive means for women to become self-employed than it will be for men. 
In addition to the willingness to accept the risk, one of the most critical characteristics 

associated with entrepreneurship is self-efficacy, i.e., the perception of one's readiness and ability to 
perform necessary tasks to achieve business success (Newman et al., 2019). Women score lower on 
entrepreneurial self-efficacy than men and are less confident in their ability to operate independently 
(Scherer et al., 1990). Wilson et al. (2015) also found that there were significant differences in 
perceptions of self-efficacy between minorities and non-minorities in the STEM disciplines. Because 
beliefs relating to self-efficacy are related to task choice (Zeldin and Pajares 2000) all else equal, we 
would expect women to be less willing than men to start their independent businesses. By creating a 
partnership between the franchisor and franchisee, and providing training and ongoing support, 
franchising allows women with doubts about their entrepreneurial self-efficacy to engage in a quasi-
entrepreneurial activity, i.e., owning a franchise.  

 
Sector-Specific Self-Employment Through Franchising 
 In addition to the greater access to training, financing, and other inputs, franchising may 
have a significant impact on resolving problems that minority entrepreneurs have on the demand 
side of their business. In a study of the clientele of ethnic businesses, Dyer and Ross (2000) found 
that not only did some whites resist patronizing ethnic establishments, but some ethnic consumers 
also did as well. One possible explanation is that industry segregation reflects continuing stereotypes 
that have their roots in strongly held prejudices. Under this scenario, consumers do not frequent 
particular types of women or minority-owned businesses because those business owners are 
perceived as inherently incapable of conducting that business to the satisfaction of the consumer, or 

 
2 We did not find any studies that directly examined the main effect of minority status on risk aversion. However, in the 

Jianakoplos and Bernasek (1998) study, race interacted with gender such that black women were particularly risk seeking. 



82 

 

because of discrimination (Carter et al., 2015). Stereotypes may also exist on the part of the 
prospective business owners themselves. In other words, evidence of industry segregation may 
reflect choices on the part of women and minorities that are due at least in part to questions that 
they have about their abilities. Williams (1999) argued that franchising solves some of those issues 
because the brand masks the ownership of the outlet. Consumers holding such stereotypes would 
not associate their patronage of the business with the local owner but instead with the corporate 
franchisor. Franchisors typically prevent the identification of franchised units with the individual 
franchisee, ensuring that all outlets are seen as part of the overall system (Chiou and Droge 2013). 
This “masking” also provides benefits to obtaining capital. Anna et al. (2000) found that women 
operating in non-traditional (i.e., male-dominated) sectors reported considerable frustration in 
obtaining loans or credit than those in traditionally female sectors.  
 
Hypotheses 

Franchising provides specific benefits and opportunities which are not present strictly with 
self-employment. Past research suggests that franchising can provide an enhanced experience, 
growth prospects, training, and support which may be crucial elements for business success (Seo 
2016; Alon et al., 2017). 

Women and minorities have been shown to particularly benefit from the in-depth training 
and support provided by franchising (McMillian and Baker 2008; Nijmeijer et al., 2014). Since 
women and minorities tend to score lower in entrepreneurial self-efficacy versus their male, non-
minority counterparts (Scherer et al., 1990; Wilson et al. 2015), they also may be less likely to take on 
the tremendous risks associated with independent business ownership (Zeldin and Pajares 2000). 
Because franchising solves some of the problems associated with self-employment that are either 
unique to women and minorities or more prevalent among those groups, we would expect: 

 
Hypothesis 1: The representation of women and minorities in franchising will be disproportionately higher 
than their representation in self-employment overall 
 
The knowledge that women and minorities disproportionately face difficulties securing 

financing for business loans (Stösic Panić 2017; Steil et al. 2018) offers further evidence that 
franchising may be a particularly powerful means of business access for these groups. This inability 
to obtain loans or credit may be due to lenders themselves holding stereotypes or to their belief that 
consumers do. Furthermore, Carter et al. (2015) uncovered the unique challenges that women and 
minorities may endure with regard to industry segregation and discrimination, with such effects 
being particularly pronounced in male-dominated business sectors (Anna et al. 2000). Thus, just as 
franchising is proposed to solve general issues unique to prospective women and minority business 
owners, it should solve sector-specific issues as well. We would expect: 

 
Hypothesis 2: Women and minorities will be disproportionately over-represented as franchisees in sectors 
where they are disproportionately under-represented as business owners overall 

 
Data Analysis and Results 

 To examine the stated hypotheses, we utilized the Survey of Business Owners (SBO)P2F

3
P 

developed by the U.S. Department of Commerce and published in 1997 and 2012 (U.S. Census 
Bureau 2001, 2016).  

 
3 Extensive details regarding the sampling procedures, response rates, and error estimates are contained in the 

introduction to the SBO report (U.S. Census Bureau 2001, 2016). 



83 

 

A Look at the 1997 Franchise Data 
We first compare the overall incidence of franchising in the protected classes (e.g., all 

minorities together, minority women, and minority men) relative to the comparison groups (e.g., all 
white men and women together, white women, and white men) (Table 1). Recall that Hypothesis 1 
suggested that the protected classes would be represented in franchising to a greater extent than 
their comparison groups who may arguably enjoy better access to independent business 
opportunities.  
 
Table 1 –  Comparison of Overall Incidence of Franchising Across Groups (1997) 
 

Groups Compared 

Total Incidence 

(Independents & 

Franchisees) 

Franchisee 

Count 

Franchisees as 

Proportion of 

Total Incidence 

z valueP3F

4 p value 

UAll Women vs. All Men 
All Women 
All Men 

 
 

5,888,883 
11,364,260 

 
 

188,444 
311,897 

 
 

3.20% 
2.74% 

 
 

53.45 

 
 

0.000 

UAll Minority vs. All White 
All Minority 
All White 

 
 

1,999,046 
15,254,097 

 
 

68,314 
432,028 

 
 

3.42% 
2.83% 

 
 

46.36 

 
 

0.000 

UWhite Women vs. White 
Men 
White Women 
White Men 

 
 

5,139,641 
10,114,456 

 
 

158,937 
273,091 

 
 

3.09% 
2.70% 

 
 

43.66 

 
 

0.000 

UMinority Women vs. 
Minority Men 
Minority Women 
Minority Men 

 
 
 

749,242 
1,249,804 

 
 
 

29,507 
38,807 

 
 
 

3.94% 
3.11% 

 
 
 

31.39 

 
 
 

0.000 

UMinority Men vs. White 
Men 
Minority Men 
White Men 

 
 

1,249,804 
10,114,456 

 
 

38,807 
273,091 

 
 

3.11% 
2.70% 

 
 

26.15 

 
 

0.000 

UMinority Women vs. White 
Women 
Minority Women 
White Women 

 
 

749,242 
5,139,641 

 
 

29,507 
158,937 

 
 

3.94% 
3.09% 

 
 

38.87 

 
 

0.000 

 
In each of the above pairs, the name of the protected class is listed first, followed by the 

name of the comparison group. As the results in Table 1 show, all six comparisons were statistically 
significant at p ≤ .001. The protected classes consistently demonstrated higher participation in 
franchising than their comparison groups. Specifically, we find women participating in franchising in 
higher proportions than their male counterparts in all three female versus male comparisons (i.e., all 

 
4 Z-tests were used here since the sample size is large (Ru et al. 2017; Zakaria et al. 2016; Afthanorhan et al. 2015; Liang 
and Pan 2011). While the population standard deviation is unknown, the law of large numbers and central limit theorem 
justify the use of Z-tests because the large sample sizes tend to be more accurate estimations of the population, and the 
sample standard deviation can be used as a good estimate of the population standard deviation (Stephan 2014; Ozgur 
and Strasser 2004). 
 



84 

 

women versus all men, white women versus white men, and minority women versus minority men). 
We also find minority groups consistently participating in franchising in higher proportions than 
their white counterparts in each of the three minority versus white comparisons (i.e., all minority 
versus all-white disregarding gender, minority males versus white males, and minority females versus 
white females). These findings support the first hypothesis and are consistent with the idea that 
franchising does solve problems associated with business ownership that are unique to these 
protected groups.  

Hypothesis 2 suggests that the participation of protected groups in franchising will differ 
systematically from their participation in business ownership overall. We argued that franchising 
should increase the attraction of, or access to, particular sectors. We operationalize the relative 
penetration of franchising in a sector by computing the odds ratio of the protected class and its 
different groups. For example, we divide the percentage of women business owners in a sector who 
are franchisees by the percentage of men business owners in that sector who are franchisees. Sector-
by-sector odds ratios are computed for the same six comparisons (e.g., all women versus all men)  
and the results are presented in Table 2. 



85 

 

Table 2 – Relative Penetration by Sectors (1997) 
 

 

UTotal 
Penetration as 
Franchisees 

UTotal 
Penetration 

(Independents 
& Franchisees) 

UTotal 
Penetration 
Percentage 

UTotal 
Penetration 

as 
Franchisees 

UTotal 
Penetration 

(Independents 
& Franchisees) 

UTotal 
Penetration 
Percentage 

UOdds Ratio 

URelative 
Woman/ 
Minority 
Sector 

Penetration 

 Women Men   

All Sectors 188,444 5,888,883 3.20% 311,897 11,364,260 2.74% 1.17 NA 
Agriculture 3,592 119,731 3.00% 1,003 463,522 0.22% 13.86 2.03% 

Construction 1,470 183,695 0.80% 9,508 1,645,925 0.58% 1.38 3.12% 

Manufacturing 2,895 152,346 1.90% 3,836 365,368 1.05% 1.81 2.59% 

Transportation 4,674 141,623 3.30% 24,680 557,280 4.43% 0.75 2.40% 

Wholesale Trade 4,945 154,542 3.20% 12,820 383,797 3.34% 0.96 2.62% 

Retail Trade 67,787 1,093,342 6.20% 115,588 1,384,703 8.35% 0.74 18.57% 

Finance, Insurance, Real Estate 45,813 602,802 7.60% 78,413 1,338227 5.66% 1.30 10.24% 

Services 44,218 3,158,444 1.40% 64,758 4,625,572 1.40% 1.00 53.63% 

Not Classified 9,600 282,358 3.40% 8,044 599,866 1.34% 2.54 4.79% 

 Mantel-Haenszel Chi Square Statistic = 20.45, p <.001; Correlation (col 7 & 8)R R= -0.239, p = .54 

 Minorities White   

All Sectors 68,314 1,999,046 3.42% 432,028 15,254,097 2.83% 1.21 NA 
Agriculture 1,002 58,454 1.71% 3,665 524,799 0.70% 2.45 2.92% 

Construction 2,385 169,152 1.41% 8,593 1,660,468 0.52% 2.72 8.46% 

Manufacturing 1,057 47,906 2.21% 5,674 469,808 1.21% 1.83 2.40% 

Transportation 7,016 121,254 5.79% 22,338 577,649 3.87% 1.50 6.07% 

Wholesale Trade 1,333 45,320 2.94% 16,432 493,019 3.33% 0.88 2.27% 

Retail Trade 23,247 327,169 7.11% 160,126 2,150,875 7.44% 0.95 16.37% 

Finance, Insurance, Real Estate 10,949 154,917 7.07% 113,277 1,766,112 6.34% 1.11 7.75% 

Services 17,294 954,052 1.81% 91,683 6,829,964 1.34% 1.35 47.73 

Not Classified 4,814 120,820 2.98% 12,831 761,404 1.69% 2.36 6.04% 

 Mantel-Haenszel Chi Square Statistic = 30.36, p <.001; Correlation (col 7 & 8) = -0.250, p = .52 

 White Women White Men   

All Sectors 158,937 5,139,641 3.09% 273,091 10,114,456 2.70% 1.15 NA 
Agriculture 3,664 111,882 3.27 0 412,917 0.00% 0.00 2.18% 

Construction 1,112 164,412 0.68%  7,480 1,496,056 0.50% 1.35 3.20% 



86 

 

Manufacturing 2,672 136,323 1.96% 3,001 333,485 0.90% 2.18 2.65% 

Transportation 3,543 119,249 2.97% 18,794 458,400 4.10% 0.72 2.32% 

Wholesale Trade 4,793 140,298 3.42% 11,640 352,721 3.30% 1.04 2.73 

Retail Trade 58,303 952,933 6.12% 101,825 1,197,943 8.50% 0.72 18.54% 

Finance, Insurance, Real Estate 41,322 545,518 7.57% 71,954 1,240,594 5.80% 1.31 10.61% 

Services 38,353 2,727,670 1.41% 53,330 4,102,294 1.30% 1.08 53.07% 

Not Classified 7,630 241,358 3.16% 5,200 520,046 1.00% 3.16 4.70% 

 Mantel-Haenszel Chi Square Statistic = 24.22, p <.001; Correlation (col 7 & 8) = -0.201, p = .60 

 Minority Women Minority Men   

All Sectors 29,507 749,242 3.94% 38,807 1,249,804 3.11% 1.27 NA 
Agriculture 0 7,849 0.00% 1,002 50,605 1.96% 0.00 1.05% 

Construction 357 19,283 1.85% 2,028 149,869 1.35% 1.37 2.57% 

Manufacturing 222 16,023 1.39% 834 31,883 2.62% 0.53 2.14% 

Transportation 1,130 22,374 5.05% 5,886 98,880 5.95% 0.85 2.99% 

Wholesale Trade 153 14,244 1.07% 1,180 31,076 3.80% 0.28 1.90% 

Retail Trade 9,484 140,409 6.75% 13,763 186,760 7.37% 0.92 18.74% 

Finance, Insurance, Real Estate 4,491 57,284 7.84% 6,458 97,633 6.62% 1.19 7.65% 

Services 5,865 430,774 1.36% 11,428 523,278 2.18% 0.62 57.49% 

Not Classified 1,970 41,000 4.80% 2,844 79,820 3.56% 1.35 5.47% 

 Mantel-Haenszel Chi Square Statistic = 1.41, p > .05, NS; Correlation (col 7 & 8)R R= -0.026, p = .95 

 Minority Men White Men   

All Sectors 38,807 1,249,804 3.11% 273,091 10,114,456 2.70% 1.15 NA 
Agriculture 1,002 50,605 1.98% 0 412,917 0.00% 0.00 4.05% 

Construction 2,028 149,869 1.35% 7,480 1,496,056 0.50% 2.71 11.99% 

Manufacturing 834 31,883 2.62% 3,001 333,485 0.90% 2.91 2.55% 

Transportation 5,886 98,880 5.95% 18,794 458,400 4.10% 1.45 7.91% 

Wholesale Trade 1,180 31,076 3.80% 11,640 352,721 3.30% 1.15 2.49% 

Retail Trade 13,763 186,760 7.37% 101,825 1,197,943 8.50% 0.87 14.94% 

Finance, Insurance, Real Estate 6,458 97,633 6.62% 71,954 1,240,594 5.80% 1.14 7.81% 

Services 11,428 523,278 2.18% 53,330 4,102,294 1.30% 1.68 41.87% 

Not Classified 2,844 79,820 3.56% 5,200 520,046 1.00% 3.56 6.39% 

 Mantel-Haenszel Chi Square Statistic = 13.91, p <.001; Correlation (col 7 & 8)R R= -0.216, p = .58 

 Minority Women White Women   

All Sectors 29,507 749,242 3.94% 158,937 5,139,641 3.09% 1.27 NA 
Agriculture 0 7,849 0.00% 3,664 111,882 3.27% 0.00 1.05% 

Construction 357 19,283 1.85% 1,112 164,412 0.68% 2.74 2.57% 



87 

 

Manufacturing 222 16,023 1.39% 2,672 136,323 1.96% 0.71 2.14% 

Transportation 1,130 22,374 5.05% 3,543 119,249 2.97% 1.70 2.99% 

Wholesale Trade 153 14,244 1.07% 4,793 140,298 3.42% 0.31 1.90% 

Retail Trade 9,484 140,409 6.75% 58,303 952,933 6.12% 1.10 18.74% 

Finance, Insurance, Real Estate 4,491 57,284 7.84% 41,322 545,518 7.57% 1.03 7.65% 

Services 5,865 430,774 1.36% 38,353 2,727,670 1.41% 0.97 57.49% 

Not Classified 1,970 41,000 4.80% 7,630 241,358 3.16% 1.52 5.47% 

 Mantel-Haenszel Chi Square Statistic = 10.91, p <.001; Correlation (col 7 & 8)R R= -0.045, p = .91 
 
We analyze the odds ratios using the Mantel-Haenszel test for sector differences (Mantel and Haenszel 1959; Fleiss 1981). A significant test statistic confirms 
systematic differences in the relative level of penetration by protected class franchisees across sectors. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



88 

 

As reported in Table 2, sector differences were found in all comparisons except one (i.e., 
minority women versus minority men: Mantel-Haenszel Chi Square Statistic = 1.41, p > .05). 
Individual penetration differences are summarized in Table 3. Positive (negative) odds ratios indicate 
that the proportion of sector business owners that are franchisees is greater (smaller) for the 
protected class than for the comparison group. A faint pattern can be detected with Construction, 
Manufacturing, Finance, Insurance, and Real Estate, Services, and Not Classified sectors showing generally 
positive odds ratios. This indicates that women and minorities participate in franchised business 
models (rather than self-ownership models) disproportionately in these particular sectors, lending 
support to Hypothesis 2.  
 
Table 3 – Summary of Penetration Differences (1997) 
 

 

Sectors 

All 

Women 

vs. All 

Men 

All 

Minorities 

vs. All 

White 

White 

Women 

vs. White 

Men 

Minority 

Women vs. 

Minority 

Men 

Minority 

Men vs. 

White Men 

Minority 

Women 

vs. White 

Women 
 Agriculture + + - - - - 

Construction + + + + + + 

Manufacturing + + + - + - 

Transportation - + - - + + 

Wholesale Trade - - + - + - 

Retail Trade - - - - - + 

Finance, Insurance, and Real Estate + + + + + + 

Services NA + + - + - 

Not Classified + + + + + + 

 
A plus (+) indicates that the more disadvantaged group shows a higher degree of penetration in the focal sector 
compared to the more advantaged group. The more disadvantaged group is shown above in bold for each comparison 
attempted. A minus (-) shows the opposite effect. The plus signs correspond to Odds Ratios greater than one in Table 2; 
conversely, the minus signs correspond to Odds Ratios less than one. When the Odds Ratio in Table 3 is exactly equal to 
one, the NA notation is used to show no differences in penetration rates. 

 
The most reliable evidence of the expected relationship between franchising penetration and 

general levels of sector access or attractiveness would be a negative correlation between the access 
measure and the odds ratio measure across sectors. Clearly, with only nine sectors, the likelihood of 
finding a significant correlation is minimal. Nevertheless, as reported in Table 2, correlations are 
consistently negative for all comparisons, and non-trivial for four of six comparisons (i.e., except for 
minority women and minority men, and minority women and white women comparisons). An 
example will help clarify. We see that women experience real or perceived difficulties in entering the 
construction industry (i.e., a relatively low sector access of 3.12%; Table 2, last column), but that 
relative to men they appear to have found an alternative route to self-employment through 
franchising (positive odds ratio of 1.38). 
 
A Look at the 2012 Franchise Data 
 As with the first dataset, we utilized the 2012 SBO data ((U.S. Census Bureau 2016) to 
evaluate the overall incidence of franchising in the protected classes (e.g., women, minorities, 
minority women) relative to the comparison groups (e.g., men, non-minorities, nonminority 
women). In Hypothesis 1, it was suggested that the protected classes would be represented in 



89 

 

franchising to a greater extent than groups with arguably greater access to independent business 
opportunities.  
 
Table 4 – Comparison of Overall Incidence of Franchising Across Gender Groups (2012) 
 

Groups Compared 

Total 
Incidence 

(Independents 
& Franchisees) 

 
Franchisee 

Count 

Franchisees 
as Proportion 

of Total 
Incidence 

 
z 

value P4F

5 

 
p 

value 

UAll Women vs. All Men 
All Women 
All Men 

 
 

15,849,766 
26,082,284 

 
 

1,667,802 
3,386,341 

 
 

10.52% 
12.98% 

 
 

-237.26 

 
 

0.000 
 

UAll Minority vs. All White 
All Minority 
All White 

 
 

6,616,666 
35,315,384 

 
 

840,764 
4,213,379 

 
 

12.71% 
11.93% 

 
 

56.55 

 
 

0.000 

UWhite Women vs. White Men 
White Women 
White Men 

 
 

12,929,461 
22,385,923 

 
 

1,329,219 
2,884,160 

 
 

10.28% 
12.88% 

 
 

-229.65 

 
 

0.000 
 

UMinority Women vs. Minority Men 
Minority Women 
Minority Men 

 
 

2,920,305 
3,696,361 

 
 

338,583 
502,181 

 
 

11.59% 
13.59% 

 
 

-76.70 

 
 

0.000 
 

UMinority Men vs. White Men 
Minority Men 
White Men 

 
 

3,696,361 
22,385,923 

 
 

502,181 
2,884,160 

 
 

13.59% 
12.88% 

 
 

37.63 

 
 

0.000 

UMinority Women vs. White Women 
Minority Women 
White Women 

 
2,920,305 
12,929,461 

 

 
338,583 

1,329,219 
 

 
11.59% 
10.28% 

 
65.90 

 
0.000 

 

 
The results in Table 4 show that all six comparisons were statistically significant at p ≤ .001. 

The protected classes demonstrated higher participation in franchising than the comparison group 
only across three instances rather than all six, as was seen in the 1997 data. Specifically, we find 
women participating in franchising in higher proportions than their male counterparts in just one of 
the comparison groups (i.e., minority women versus white women). Additionally, we find minorities 
participating in franchising in higher proportions than their white counterparts in two comparison 
groups (i.e., all minority versus all-white disregarding gender, minority males versus white males). In 
the comparison groups of all women versus all men, white women versus white men, and minority 
women versus minority men, we did not uncover a higher degree of franchising activity as a 
proportion of the total incidence of businesses for the 2012 data. These recent findings still lend 
support to the first hypothesis and are consistent with the idea that franchising does solve problems 

 
5 Z-tests were used here since the sample size is large (Ru et al. 2017; Zakaria et al. 2016; Afthanorhan et al. 2015; Liang 
and Pan 2011). While the population standard deviation is unknown, the law of large numbers and central limit theorem 
justify the use of Z-tests because the large sample sizes tend to be more accurate estimations of the population, and the 
sample standard deviation can be used as a good estimate of the population standard deviation (Stephan 2014; Ozgur 
and Strasser 2004). 



90 

 

associated with business ownership that are unique to the protected groups. Changes in certain 
comparison groups from 1997 to 2012 may be due to a host of factors relating to higher 
independent business ownership among protected classes outside of franchising and a higher degree 
of franchising activity among men and non-minorities in general. 

Recall that Hypothesis 2 suggests that the participation of protected groups in franchising 
will differ systematically from their participation in business ownership overall. We assess this for 
the 2012 CBO study data by computing the odds ratio of the protected class and its contrasting 
group. Results for the six comparison groups are displayed in Table 5.  

As reported in Table 5, sector differences were found in all comparisons. Individual 
penetration differences are summarized in Table 6. Positive (negative) odds ratios indicate that the 
proportion of sector business owners that are franchisees is greater (smaller) for the protected class 
than for the comparison group. A faint pattern can be detected with Agriculture, Construction, Retail 
Trade, and Services sectors showing generally positive odds ratios. Again, much like the pattern seen 
with the 1997 data, we find evidence that women and minorities participate in franchised business 
models (rather than self-ownership models) to a higher degree in these particular sectors, lending 
support to Hypothesis 2. 

 
 
 
 
 
 
 
 
 
 
 
 



91 

 

Table 5 – Relative Penetration by Sectors (2012) 
 

 

UTotal 
Penetration 

as 
Franchisees 

UTotal 
Penetration 

(Independents 
& Franchisees) 

UTotal 
Penetration 
Percentage 

UTotal 
Penetration 

as 
Franchisees 

UTotal 
Penetration 

(Independents 
& Franchisees) 

UTotal 
Penetration 
Percentage 

UOdds Ratio 

URelative 
Woman/ 
Minority 
Sector 

Penetration 

 Women Men   

All Sectors 1,667,802 15,849,766 10.52% 3,386,341 26,082,284 12.98% 0.81 NA 
Agriculture 23,917 141,063 16.95% 70,861 464,760 15.25% 1.11 0.89% 

Construction 44,715 606,285 7.38% 196,020 3,396,949 5.77% 1.28 3.83% 

Manufacturing 46,797 319,616 14.64% 157,413 728,664 21.60% 0.68 2.02% 

Transportation 41,803 491,237 8.51% 176,710 1,604,556 11.01% 0.77 3.10% 

Wholesale Trade 49,212 325,058 15.14% 156,649 841,808 18.61% 0.81 2.05% 

Retail Trade 402,144 1,906,018 21.10% 455,223 2,083,562 21.85% 0.97 12.03% 

Finance, Insurance, Real Estate 309,822 2,325,634 13.32% 833,998 4,989,561 16.71% 0.80 14.67% 

Services 749,299 9,733,111 7.70% 1,339,103 11,969,986 11.19% 0.69 61.41% 

Not Classified 93 1,744 5.33% 364 2,438 14.93% 0.36 0.01% 

 Mantel-Haenszel Chi Square Statistic = 56315.78, p <.001 Correlation (col 7 & 8)R R= -.139, p=.721 

 Minorities White   

All Sectors 840,764 6,616,666 12.71% 4,213,379 35,315,384 11.93% 1.07 NA 
Agriculture 6,440 33,438 19.26% 88,338 572,385 15.43% 1.25 0.21% 

Construction 18,000 408,834 4.40% 222,735 3,594,400 6.20% 0.71 2.58% 

Manufacturing 14,305 105,525 13.56% 189,905 942,755 20.14% 0.67 0.67% 

Transportation 51,751 436,121 11.87% 166,762 1,659,672 10.05% 1.18 2.75% 

Wholesale Trade 19,862 180,702 10.99% 185,999 986,164 18.86% 0.58 1.14% 

Retail Trade 158,754 644,680 24.63% 698,613 3,344,900 20.89% 1.18 4.07% 

Finance, Insurance, Real Estate 109,801 757,044 14.50% 1,034,019 6,558,151 15.77% 0.92 4.78% 

Services 461,816 4,049,801 11.40% 1,626,586 17,653,296 9.21% 1.24 25.55% 

Not Classified 35 521 6.72% 422 3,661 11.53% 0.58 0.00% 

 
Mantel-Haenszel Chi Square Statistic = 3165.90, p<.001  Correlation (col 7 & 8)R R= .460, p=.213 

 

 White Women White Men   

All Sectors 1,329,219 12,929,461 10.28% 2,884,160 22,385,923 12.88% 0.80 NA 
Agriculture 22,052 133,168 16.56% 66,286 439,217 15.09% 1.10 0.84% 



92 

 

Construction 39,874 537,894 7.41% 182,861 3,056,506 5.98% 1.24 3.39% 

Manufacturing 42,176 279,420 15.09% 147,729 663,335 22.27% 0.68 1.76% 

Transportation 35,058 402,884 8.70% 131,704 1,256,788 10.48% 0.83 2.54% 

Wholesale Trade 41,844 265,112 15.78% 144,155 721,052 19.99% 0.79 1.67% 

Retail Trade 332,618 1,606,836 20.70% 365,995 1,738,064 21.06% 0.98 10.14% 

Finance, Insurance, Real Estate 269,096 2,016,485 13.34% 764,923 4,541,666 16.84% 0.79 12.72% 

Services 546,431 7,686,157 7.11% 1,080,155 9,967,139 10.84% 0.66 48.49% 

Not Classified 70 1,505 4.65% 352 2,156 16.33% 0.28 0.01% 

 Mantel-Haenszel Chi Square Statistic = 52861.03, p<.001 Correlation (col 7 & 8)R R= -.147, p=.707 

 Minority Women Minority Men   

All Sectors 338,583 2,920,305 11.59% 502,181 3,696,361 13.59% 0.85 NA 
Agriculture 1,865 7,895 23.62% 4,575 25,543 17.91% 1.32 0.05% 

Construction 4,841 68,391 7.08% 13,159 340,443 3.87% 1.83 0.43% 

Manufacturing 4,621 40,196 11.50% 9,684 65,329 14.82% 0.78 0.25% 

Transportation 6,745 88,353 7.63% 45,006 347,768 12.94% 0.59 0.56% 

Wholesale Trade 7,368 59,946 12.29% 12,494 120,756 10.35% 1.19 0.38% 

Retail Trade 69,526 299,182 23.24% 89,228 345,498 25.83% 0.90 1.89% 

Finance, Insurance, Real Estate 40,726 309,149 13.17% 69,075 447,895 15.42% 0.85 1.95% 

Services 202,868 2,046,954 9.91% 258,948 2,002,847 12.93% 0.77 12.91% 

Not Classified 23 239 9.62% 12 282 4.26% 2.26 0.00% 

 Mantel-Haenszel Chi Square Statistic = 5838.35, p<.001  Correlation (col 7 & 8)R R= -.367, p=.331 

 Minority Men White Men   

All Sectors 502,181 3,696,361 13.59% 2,884,160 22,385,923 12.88% 1.05 NA 
Agriculture 4,575 25,543 17.91% 66,286 439,217 15.09% 1.19 0.16% 

Construction 13,159 340,443 3.87% 182,861 3,056,506 5.98% 0.65 2.15% 

Manufacturing 9,684 65,329 14.82% 147,729 663,335 22.27% 0.67 0.41% 

Transportation 45,006 347,768 12.94% 131,704 1,256,788 10.48% 1.23 2.19% 

Wholesale Trade 12,494 120,756 10.35% 144,155 721,052 19.99% 0.52 0.76% 

Retail Trade 89,228 345,498 25.83% 365,995 1,738,064 21.06% 1.23 2.18% 

Finance, Insurance, Real Estate 69,075 447,895 15.42% 764,923 4,541,666 16.84% 0.92 2.83% 

Services 258,948 2,002,847 12.93% 1,080,155 9,967,139 10.84% 1.19 12.64% 

Not Classified 12 282 4.26% 352 2,156 16.33% 0.26 0.00% 

 Mantel-Haenszel Chi Square Statistic = 1383.83, p<.001  Correlation (col 7 & 8)R R= .415, p=.267 

 Minority Women White Women   

All Sectors 338,583 2,920,305 11.59% 1,329,219 12,929,461 10.28% 1.13 NA 
Agriculture 1,865 7,895 23.62% 22,052 133,168 16.56% 1.43 0.05% 



93 

 

Construction 4,841 68,391 7.08% 39,874 537,894 7.41% 0.95 0.43% 

Manufacturing 4,621 40,196 11.50% 42,176 279,420 15.09% 0.76 0.25% 

Transportation 6,745 88,353 7.63% 35,058 402,884 8.70% 0.88 0.56% 

Wholesale Trade 7,368 59,946 12.29% 41,844 265,112 15.78% 0.78 0.38% 

Retail Trade 69,526 299,182 23.24% 332,618 1,606,836 20.70% 1.12 1.89% 

Finance, Insurance, Real Estate 40,726 309,149 13.17% 269,096 2,016,485 13.34% 0.99 1.95% 

Services 202,868 2,046,954 9.91% 546,431 7,686,157 7.11% 1.39 12.91% 

Not Classified 23 239 9.62% 70 1,505 4.65% 2.07 0.00% 

 Mantel-Haenszel Chi Square Statistic = 4365.48, p<.001  Correlation (col 7 & 8)R R= .172, p=.659 
 
We analyze the odds ratios using the Mantel-Haenszel test for sector differences (Mantel and Haenszel 1959; Fleiss 1981). A significant test statistic confirms 
systematic differences in the relative level of penetration by protected class franchisees across sectors. 



94 

 

Table 6 – Summary of Penetration Differences (2012) 
 

 

Sectors 

All Women 

vs. All Men 

All 

Minorities 

vs. All 

White 

White 

Women 

vs. 

White 

Men 

Minority 

Women 

vs. 

Minority 

Men 

Minority 

Men 

vs.White 

Men 

Minority 

Women vs. 

White 

Women 

 Agriculture + + + + + + 

Construction + - + + - - 

Manufacturing - - - - - - 

Transportation - + - - + - 

Wholesale Trade - - - + - - 

Retail Trade - + - - + + 

Finance, Insurance, and Real Estate - - - - - - 

Services - + - - + + 

Not Classified - - - + - + 

 
A plus (+) indicates that the more disadvantaged group shows a higher degree of penetration in the focal sector 
compared to the more advantaged group. The more disadvantaged group is shown above in bold for each comparison 
attempted. A minus (-) shows the opposite effect. The plus signs correspond to Odds Ratios greater than one in Table 5; 
conversely, the minus signs correspond to Odds Ratios less than one. When the Odds Ratio in Table 5 is exactly equal to 
one, the NA notation is used to show no differences in penetration rates. 

 
Conclusion 

The results of this study indicate that women and minorities disproportionately use 
franchising as a route to self-employment in the retail sector across two periods of data collection. 
We do not know for sure whether these individuals would have become self-employed if the 
franchising option were not available to them. However, given the comparison with men and non-
minorities, it does appear that franchising may have something unique to offer to groups who face 
systematic impediments to independent business ownership. The Census Bureau data from both 
1997 and 2012 suggest that the overall level of participation of women and minorities in franchising 
is found to be higher than participation in independently-owned businesses. Though this is an 
important insight for policymakers, the inroads made by women and minorities in these franchise 
business ventures remain relatively small when compared to the population statistics. It is important 
to remember that although the unique characteristics of the franchise relationship may help 
overcome some of the self-employment hurdles faced by women and minorities, its impact is 
entirely dependent on the willingness of franchisors to grant licenses to women and minorities 
franchisees. Such inclusion makes good business sense and should be encouraged by policy makers 
and governmental agencies such as the Office of Entrepreneurial Development (OED).  

Nevertheless, discrimination claims have been rising in the franchising arena just as they 
have in business generally (Carter et al., 2015). The claims of discrimination strike at the very essence 
of our collective sense of morality and fair play and the emergent societal consensus for inclusion 
(Emerson, 1998; McMillian and Baker, 2008). In an industry where rapid growth and market 
preemption are critical, the inability to recruit qualified franchisees because of a reputation for 
discriminatory practices can be crippling for franchise systems. 

Affirmative action campaigns launched by groups like NAACP, PUSH (People United to 
Serve Humanity), and SCLC (Southern Christian Leadership Conference) have targeted specific 
franchise systems, and most large franchise systems have now adopted programs aimed at 
encouraging greater franchisee diversity (McMillian and Baker, 2008). For instance, GM, Ford, and 



95 

 

Chrysler each offer assistance to minorities through their dealer development programs offering 
loans, loan guarantees, and equity participation initiatives. All three have documented substantial 
gains towards their diversity goals. Several large oil companies have similar development programs. 
Diversity programs can also be found in many well-known business format franchise systems, 
including McDonald's, Burger King, KFC, Hardee’s, Shoney’s, Day’s Inn, and Denny’s (see 
Emerson 1998 for details on the automobile, oil, and fast-food industry initiatives). This trend is also 
reflected in the International Franchise Association’s (IFA) Emerging Markets Program and its 
revised Code of Principles and Standard of Conduct (International Franchise Association, 1996) 
supporting private initiatives for affirmative action programs. Thus, the structural characteristics of 
the franchise relationship, combined with internally and externally motivated diversity programs, 
helps to open doors to self-employment for women and minorities within the retail sector.  
 
Limitations and Future Research 

Continuing to expand research in the area of women and minority-owned businesses and 
franchises would be a valuable endeavor to provide more insights into the rationale behind 
attraction and avoidance to various types of business ownerships. Research into the impediments 
faced by women entrepreneurs, such as the four primary barriers of (1) socio-political legitimacy 
barriers, (2) structural barriers; (3) social capital barriers, and (4) human capital barriers, would 
provide more background and insight into these issues. Socio-political legitimacy, the process by 
which key stakeholders (e.g., consumers) accept a venture given existing norms and laws, would 
benefit from further study to determine if consumers are indeed more likely to patronize women 
and minority franchisees in non-stereotypical businesses than independent business owners (Aldrich 
& Fiol, 1994; Cardella et al., 2020). Structural barriers, such as overt discrimination and systematic 
barriers that result in differential access to business opportunities (Carter et al., 2015), would benefit 
from a nuanced study on the circumstances under which women and minorities have equal access to 
sources such as financing as male business owners do. Social capital, such as networks or 
relationships and norms warrants further study to better understand the social connections and 
benefits that stem from franchise opportunities (Cumberland and Litalien, 2019; Nijmeijer et al., 
2014). Finally, looking at how human capital benefits from the education and work experience 
afforded from entrepreneurial success deserves further attention (Marvel et al., 2016).  

Though this research focuses on women and minorities as broad categorizations, the authors 
recognize that these groups are not entirely monolithic entities. Future research might explore 
additional psychographic and demographic factors which further define different sub-segments of 
these groups (i.e., ethnicity, age, marital status, etc.) and in doing so may uncover valuable insights. 
While our evidence has shown that women and minorities gravitate towards the franchising format 
of retailing in disproportionately higher numbers and that there are sector-based differentials to this 
pattern, new research will significantly benefit from a more causal investigation of this complex 
topic.  

 

  



96 

 

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