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 References Afthanorhan, A., Ahmad, N., & Sabri, A. (2015). A parametric approach using z-test for comparing 2 means to multi-group analysis in partial least square structural equation modeling (PLS-SEM). British Journal of Applied Science & Technology, 6(2), 194-201. Aldrich, H. (1999). Organizations evolving. Thousand Oaks, CA: Sage Publications. Aldrich, H. & Fiol, M. (1994). Fools rush in? The institutional context of industry creation. Academy of Management Review, 19(4), 645-670. Alon, I., Apriliyanti, I.D., & Parodi, M.C.H. (2020). A Systematic Review of International Franchising. Multinational Business Review, 29(1), 43-69. Alon, I., Madanoglu, M., & Shoham, A. (2017). Strategic agility explanations for managing franchising expansion during economic cycles. Competitiveness Review: An International Business Journal, 27(2), 113-131. Anna, A., Chandler, G., Jansen, E., & Mero, N. (2000). Women business owners in traditional and non-traditional industries. Journal of Business Venturing, 15(3), 279-303. Ayorinde, A.A., & Zubairu, U.M. (2018). A Systematic Review of Franchising as an Alternative Business Model. Covenant Journal of Entrepreneurship, 2(2), 54-71. Bardasi, E., Sabarwal, S., Terrell, K. (2011). How do female entrepreneurs perform? Evidence from three developing regions. Small Business Economics, 37, 417-441. Blanchard, L., Zhao, B., Yinger, J. (2008). Do lenders discriminate against minority and woman entrepreneurs? Journal of Urban Economics, 63, 467-497. Blanchflower, D, Levine, P. & Zimmerman, D. (2003). Discrimination in the small business credit market. The Review of Economics and Statistics, 85(4), 930-943. Boden, R. & Nucci, A. (2000). On the survival prospects of men's and women's new business ventures. Journal of Business Venturing, 15(4), 347-363. Cardella, G.M, Hernandez-Sanchez, B.R., Sanchez-Garcia, J.C. (2020). Women entrepreneurship: a systematic review to outline the boundaries of scientific literature. Frontiers in Psychology, 11(Article 1557), 1-18. 97 Carter, S., Mwaura, S., Ram., M., Trehan, K., Jones, T. (2015). Barriers to ethnic minority and women’s enterprise: existing evidence, policy tensions, and unsettled questions. International Small Business Journal, 33(1), 49-69. Chiou, J. & Droge, C. (2015). The effects of standardization and trust on franchisee’s performance and satisfaction: a study on franchise systems in the growth stage. Journal of Small Business Management, 53(1), 129-144. Cliff, J. (1999). Does one size fit all? Exploring the relationship between attitudes toward growth, gender, and business size. Journal of Business Venturing, 13, 523-542. Coleman, S. (2000). Access to capital and terms of credit: A comparison of men and women- owned small businesses. Journal of Small Business Management, 38(3), 37-52. Combs, J.G. & Ketchen, D.J., Jr. (2003). Why do firms use franchising as an entrepreneurial strategy? A meta-analysis. Journal of Management, 29(3), 443-465. Combs, J.G., Ketchen, D.J., Jr., Shook, C.L., Short, J.C. (2011). Antecedents and consequences of franchising: past accomplishments and future challenges. Journal of Management, 37(1), 99-126. Cumberland, D., & Githens, R. (2012). Tacit knowledge barriers in franchising: practical solutions. Journal of Workplace Learning, 24(1), 48-58. Cumberland, D.M., Litalien, B.C. (2019). Social franchising: a systematic review. Journal of Marketing Channels, 25(3), 137-156. Dyer, L. & Ross, C. (2000). Ethnic enterprises and their clientele. Journal of Small Business Management, 38(2), 48-65. Emerson, R. W. (1998). Franchise selection and retention: Discrimination claims and affirmative action programs. Arizona Law Review, 40(Summer), 511-613. Fleiss, J. L. (1981). Statistical methods for rates and proportions. Second edition, New York: John Wiley and Sons. Franchisetimes top 200þ (2018), available at: www.franchisetimes.com/Resources/Top-200/ Franchising World (1998). International franchise association advertisement (pp.50). July-Aug. 98 Gillis, W.E., Combs, J.G., & Yin, X. (2020). Franchise management capabilities and franchisor performance under alternative franchise ownership strategies. Journal of Business Venturing, 35(1), 120-138. Guzman, J., Kacperczyk, A. (2019). Gender gap in entrepreneurship. Research Policy, (48), 1666-1680. International Franchise Association (1996). Code of principles and standards of conduct. September 19, 1996 Ed. International Trade Administration (2016), “Franchising”, available at: https://2016.export.gov/industry/franchising/index.asp Jianakoplos, N. A. & Bernasek, A. (1998). Are women more risk averse. Economic inquiry, 36 (Oct), 620-630. Kaufmann, P. J. & Eroglu, S. (1999). Standardization and adaptation in business format franchising. Journal of Business Venturing, 14(1), 69-85. Larson, M. J. (1999). They're both in the ring now: Securitization and portfolio lenders put the gloves on to get deals. Franchise Times, Apr, 10-11, 15, 17. Liang, J. J., & Pan, W. S. (2011). Testing the mean for business data: should one use the z-test, t- test, F-test, the chi-square test, or the p-value method? Journal of College Teaching and Learning, 3(7), 79-88. Mantel, N., & Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. Journal of National Cancer Institute, 22, 719-748. Marvel, M.R., Davis, J.L., Sproul, C.R. (2016). Human capital and entrepreneurship research: a critical review and future directions. Entrepreneurship Theory and Practice, 40(3), 599-626. McMillian, C.W., & Baker, K.J. (2008). Discrimination claims and diversity initiatives: what’s a franchisor to do? Franchise Law Journal, 28(2), 1-14. Michael, S.C. (2003). Determinants of the rate of franchising among nations. Management International Review. 43(3), 267-290. Nahapiet, J. & Ghoshal, S. (1998). Social capital, intellectual capital and the organizational advantage. Academy of Management Review, 23(2), 242-266. 99 Newman, A., Obschonka, M., Schwarz, S., Cohen, M., Nielsen, I. (2019). Entrepreneurial self- efficacy: a systematic review of the literature. Journal of Vocational Behavior, 110(B), 403- 419. Nijmeijer, K. J., Fabbricotti, I.N., & Huijsman, R. (2014). Making franchising work: a framework based on a systematic review. International Journal of Management Reviews, 16, 62-83. Nijmeijer, K.J., Fabbricotti, I.N., & Huijsman, R. (2015). Creating advantages with franchising in healthcare: an explorative mixed methods study on the role of the relationship between the franchisor and units. PLOS One, (Feb), 1-21. Olotu, O. A., & Awoseila, F. (2011). Reinventing business growth through franchising in developing economies: A study of the Nigerian fast food sector. International Journal of Marketing Studies, 3(1), 162-170. Ozgur, C., & Strasser, S. E. (2004). A study of the statistical inference criteria: Can we agree on when to use Z Versus t?. Decision Sciences Journal of Innovative Education, 2(2), 177-192. Parker, S.L., Cutts, S., Nathan, G., Zacher, H. (2018). Understanding franchisee performance: the role of personal and contextual resources. Journal of Business and Psychology, 33TUhttps://doi.org/10.1007/s10869-018-9558-5U33T. Peterson, A., & Dant, R. P. (1991). Perceived advantages of the franchise option from the franchisee perspective: Empirical insights from a service sector. Journal of Small Business Management, 28(3), July, 46-61. Ru, B., Wang, X., & Yao, L. (2017). Evaluation of the informatician perspective: determining types of research papers preferred by clinicians. BMC medical informatics and decision making, 17(2), 5-14. Salar, M., Salar, O. (2014). Determining pros and cons of franchising by using swot analysis. Procedia – Social and Behavioral Sciences, 122, 515-519. Sanny, L., Abdurachman, E., Simatupang, B., & Heriyati, P. (2017). Franchising Performance from Franchisee Perspective: Case in Education Franchising in Indonesia. Global Business Review, 18(3), 605-616. https://doi.org/10.1007/s10869-018-9558-5 https://doi.org/10.1007/s10869-018-9558-5 100 Scherer, R. F., Brodzinski, J. D., & Weibe, F. A. (1990). Entrepreneur career selection and gender: A socialization approach. Journal of Small Business Management, (Apr), 37-44. Seo, K. (2016). The effect of franchising on debt maturity in the US restaurant industry. Tourism Economics, 22(6), 1404-1422. Shah, M. (1999). What's next for Buz Knyal. Franchise Times, April, 8-9. Shane, S., Venkatesh, S., Aravindakshan, A. (2006). The effects of new franchisor partnering strategies on franchise system size. Management Science, 52(5), 773-787. Steil, J.P., Albright, L., Rugh, J.S., Massey, D.S. (2018). The social structure of mortgage discrimination. Housing Studies, 33(5), 759-776. Stephan, C. N. (2014). The application of the central limit theorem and the law of large numbers to facial soft tissue depths: T‐Table robustness and trends since 2008. Journal of forensic sciences, 59(2), 454-462. Stösic Panić, D. (2017) Performance and financing strategies of female and male entrepreneurs in the republic of Serbia. International Journal of Gender and Entrepreneurship, 9(2), 136- 156. U.S. Census Bureau (2001). 1997 economic census: Company statistic series. U.S. Commerce Department, US Printing Office: Washington, D.C., September. U.S. Census Bureau (2016). 2012 survey of business owners. U.S. Commerce Department. Williams, D. L (1999). Why do entrepreneurs become franchisees? An empirical analysis of organizational choice. Journal of Business Venturing, 14(1), 103-124. Wilson, D.M., Bates, R., Scott, E., Painter, S.M., Shaffer, J. (2015). Differences in self-efficacy among women and minorities in STEM. Journal of Women and Minorities in Science and Engineering, 21(1), 27-25. Yago, G., Ford, R. L. & Gordon, J. (2000). Economic prosperity, women and access to credit. Milliken Institute and National Women's Business Council Report, Oct. 4, 2000. Zakaria, S. A., Saad, S. A., & Azziz, N. H. A. (2016). Performance of undergraduate engineering students in mathematics according to gender. In AIP Conference Proceedings. 1750(1), p. 040002). AIP Publishing LLC. 101 Zeldin, A.L, Pajares, F. (2000). Against the odds: self-efficacy beliefs of women in mathematical, scientific, and technological careers. American Educational Research Association, 37(1), 215-146.