Scaled Latina Enterprises in the United States of America
Department of Management, College of Business Administration, Central Michigan University, 200 Smith Hall, Mt. Pleasant, MI 48859, USA
Adm. Sci. 2024, 14(10), 245; https://doi.org/10.3390/admsci14100245
Submission received: 30 July 2024
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Revised: 27 September 2024
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Accepted: 30 September 2024
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Published: 3 October 2024
(This article belongs to the Special Issue Research on Female Entrepreneurship and Diversity)
Abstract
:Female Hispanic-owned businesses in the United States of America or Latina enterprises are emerging as an important conduit of national economic vitality. Using data from the 2023 Stanford Latino Entrepreneurship Initiative nationally representative survey of 1513 Latina-owned employer enterprises, this article is the first to offer a national portrait and determinants of scaled Latina enterprises. Scaled businesses include the largest Latina enterprises by annual sales revenue of USD 500,000 or more. These Latina enterprises are identified as scaled or scaling and represent 23.5% of all Latina employer enterprises. A comprehensive set of enterprise and entrepreneur characteristics provides the foundation to estimate the odds of scaled Latina enterprises utilizing binomial logistic regression. Results indicate that scaled Latina entrepreneurs are relatively younger, of Mexican origin, highly educated, and acculturated compared to their non-scaled Latina counterparts. Scaled Latina enterprises are more likely to grow endogenously by reinvesting profits instead of utilizing debt financing, are larger in size and scope, and are less likely to rely upon co-ethnic enclaves.
1. Introduction
Ms. Maria Rios’ ascent as an acclaimed immigrant Latina entrepreneur was unlikely. Maria Rios arrived in the US in 1980 at age 13 from a war-torn El Salvador. Maria, her two sisters, and her parents settled in Houston, Texas, with few resources and little English. With a family to support, Maria’s mother found work cleaning office buildings. Soon Maria was also helping her mother clean offices. Yet Maria persevered, transitioning to learn a new culture, language, and school system. Maria moved on to work for a waste management firm, where over a period of three years she learned the operation from the ground up (Flick 2015). During this time, Ms. Rios adroitly saw opportunity in others’ trash. Concurrently, Ms. Rios had earned her degree in business administration from the University of Houston and had begun her own waste management enterprise by the end of 1997 (Mantilla 2020).
Today, Nation Waste, Inc. is led by Maria Rios, the first female Latina-owned waste disposal company in the United States of America. Nation Waste is a multimillion-dollar enterprise with headquarters in Houston, Texas, and operations in the greater Houston and Austin areas. Yet, Ms. Rios is no ordinary entrepreneur; she landed on Fortune Magazine’s 2013 most powerful women in the US list (Sellers 2013). And Nation Waste, Inc. continues to flourish not only in waste disposal but also venturing into personal safety wearable monitoring systems (www.nationwaste.us (accessed on 13 July 2024)). Ms. Maria Rios and Nation Waste, Inc., represent a successful scaled Latina enterprise. Scaled Latina enterprises, those businesses with over USD 500,0001 in annual revenues (Orozco et al. 2020), are the primary focus of this article.
More generally, Hispanic2-owned businesses are a major contributor to the US economy. In all, there are 4.7 million Latino-owned businesses generating USD 800 billion in economic activity. Recent growth rates among Latino-owned businesses surpass the US national average and range between six and nine percent since 2018 (Gomez-Aguinaga et al. 2024). Employer businesses are those with at least USD 10,000 in annual revenues and employ at least one employee. There are 463,000 employer Latino-owned businesses, including 104,000 Latina-owned employer businesses in the US (Gomez-Aguinaga et al. 2024). Scaled Latina enterprises comprise 23.5% of Latina-owned enterprises.
As this research is exploratory and the first to consider scaled entrepreneurship among Latina business owners, two research questions provide a foundation for understanding scaled Latina entrepreneurship. (1) What is the profile (or scope) of Latina entrepreneurship in the United States of America; and (2) What are the determinants (both personal and firm-level characteristics) of Latina entrepreneurship? These research questions heed the call by Valdez (2011) to more fully focus on Latina business outcomes. Answers to these research questions comprise a fundamental contribution to Latina entrepreneurship in the US economy, allowing subsequent research and researchers to explore, compare, and build upon this empirical and baseline foundation of the scaled Latina enterprise.
The remainder of this article is organized and offered in the following order: a literature review encompassing related research; a description of the data, descriptive statistics, and methodology; a reporting and discussion of the multivariate statistical results; and a conclusion providing a summary and directions for future research.
2. Literature Review
In their comprehensive and national study of Hispanic-owned firms in the 2000s, Dávila and Mora (2013) find about one-third of Hispanic-owned firms are female-owned, with self-employment rates for Latinas of about eight percent. Significantly, Dávila and Mora (2013) note the self-employment rate for Latinas was above that of non-Hispanic women, though Latinas are generally underrepresented as business owners. This study also notes that Latina-owned businesses were generally smaller by annual revenues and had fewer employees than their male Hispanic and non-Hispanic counterparts. Additionally, Dávila and Mora (2013) find educational attainment and immigrant origin importantly impacted Latina business and earnings outcomes.
Valdez (2011) notes the importance of intersectionality in shaping market capacity for Hispanic business owners; particularly salient and important is the connection between gender, class, ethnicity, and race. Valdez (2011) and Agius Vallejo and Canizales (2016) highlight the presence and impact of gender discrimination of Latina businesses from within and from beyond the Hispanic community, perhaps in part explaining the firm size and income gaps uncovered by Dávila and Mora. Valdez (2011) also remarks that Hispanic business success is often self-reflected as simply making profits.
Newman et al. (2023) and Zambrana et al. (2020) share a primary motivation for Latina entrepreneurship that is rooted in flexibility related to one’s family schedule and role (e.g., work–life balance) and community interests in their qualitative studies of Latina entrepreneurs. Other areas of importance were the use of mentors, family members, and networks (e.g., social capital) in overcoming institutional barriers and fear of formal debt. The tension between family and enterprise obligations is a persistent theme for Latinas (Newman et al. 2023). However, many Latina businesses may begin out of necessity (Agius Vallejo and Canizales 2016) and beyond the formal structures of the economy (Richardson and Pisani 2012).
In their qualitative study of middle-class and elite Latinas in Southern California engaged in and around entrepreneurship through a study of banking, coffee shops, and maker spaces, Santellano and Agius Vallejo (2024) share insights connecting opportunity-led entrepreneurship and community development. The authors argue that Latinas construct this through financial inclusion, social inclusion, and digital inclusion as pathways to overcome intersecting economic and patriarchal structural barriers and inequalities.
Scaled firms are those enterprises poised for growth. For some, this may include latent gazelles that are ready for business take-off (Mantilla 2020; Pisani et al. 2020). For others, it may include businesses of a foundational size (Orozco 2020). Picken (2017, p. 588) argues that “in the scaling phase, the entrepreneur must add significant resources and leverage processes and partnerships to grow the business within the framework of the validated business concept and a sustainable business model.” Scaling is no longer about firm survival (Fairlie et al. 2023), but rather about firm growth.
Within the context of Latina enterprises in this research, USD 500,000 in annual revenues is chosen as a departure point for scaling.3 This revenue breakpoint point is somewhat arbitrary but is selected based upon over two decades of research experience focused on Hispanic businesses. At this minimum annual revenue level and beyond, Latina enterprises are positioned for growth. Returning to our two research questions, this article seeks to shed light on the profile (or scope) of Latina entrepreneurship and the determinants of Latina entrepreneurship.
3. Data, Descriptive Statistics, and Methodology
3.1. Data
The data for this research are derived from the Stanford Latino Entrepreneurship Initiative (SLEI), housed in the Stanford Graduate School of Business, in coordination with the Latino Business Action Network (LBAN).4 The primary survey year data source is 2023, whereby SLEI conducted a nationally representative and numerically large cross-sectional survey of Latino-owned employer firms. Employer firms are businesses with one or more paid employees. The survey excluded own-account enterprises (owner-operated concerns with no paid employees) and businesses reporting less than USD 10,000 in annual revenues. Between July and September 2023, SLEI surveyed 5102 Latino-owned businesses.5 Of this number, 1513 were female-owned or Latina enterprises.
Survey respondents were screened to ensure majority Latina ownership. The 2023 survey was administered and completed online and took about 15 min to finish. The survey instrument covered business owner characteristics and demographics and enterprise characteristics and operations (e.g., funding, networks, current business issues, performance). The units of analysis in this research are the Latina entrepreneur and her enterprise. Respondents were chosen from proprietary business panels (Qualtrics) and SLEI outreach efforts (Gomez-Aguinaga et al. 2024). While survey respondents are generally representative of Latino-owned businesses nationally, the data are adjusted (weighted) by SLEI for sample differences using US Census data applying the 2023 Annual Business Survey as the base. The weighted estimates are used in the analyses that follow.
3.2. Descriptive Statistics
This section describes the descriptive statistics for Latina entrepreneurs and Latina enterprises.
3.2.1. The Latina Entrepreneur—Descriptive Statistics
Descriptive statistics for the Latina entrepreneur are reported in Table 1. The table provides information for scaled Latina entrepreneurs (column 2), non-scaled Latina entrepreneurs (column 3), and all Latina entrepreneurs (column 4). Demographic variables, chosen a priori, are based upon variable availability, the previous literature, and over two decades of research experience on the topic. These variables include age, birthplace (i.e., immigrant or non-immigrant), generation, Latino identity, sexual orientation, educational attainment, regional residence, civil status, and Latino-origin (e.g., Latin American roots). Other than civil status, the demographic variables studied are statistically different between scaled and non-scaled Latina entrepreneurs using univariate analyses (i.e., cross-tabulations, comparison of means). The descriptive statistics for scaled and non-scaled Latina entrepreneurs are compared next.
Scaled Latina entrepreneurs are on average somewhat younger than their non-scaled Latina entrepreneur counterparts, though both groups are middle-aged. Immigrant entrepreneurs comprise just more than one-third of all Latina entrepreneurs and 40% of non-scaled Latina entrepreneurs. Only about one-fifth of scaled Latina entrepreneurs are immigrants. This proportion mirrors generations6, as the newest arriving Latina entrepreneurs are more represented in the non-scaled Latina entrepreneur category. Latino identity is a self-reported variable derived from the question, “How much is being Latino an important part of how you see yourself, from 0 being not at all important to 10 being extremely important?” Answers between 0–3 were recoded as weak, 4–6 as medium, and 7–10 as strong Latino identity. Most respondents report a strong Hispanic identity, a little higher for non-scaled Latina entrepreneurs, whereas a weak level of Hispanic identity is more associated with scaled Latina entrepreneurs. There was no statistical difference in sexual orientation between scaled and non-scaled Latina entrepreneurs, with more than eight in ten reporting a heterosexual orientation.
A large proportion of Latina entrepreneurs possess a high school education or less. This is the case for 36% of scaled Latina entrepreneurs and 45% of non-scaled Latina entrepreneurs. On the upper end of educational attainment, just more than one-quarter of both groups have earned college degrees or higher. For education at the associate’s degree level, scaled Latina entrepreneurs are twice as numerous as non-scaled Latina entrepreneurs (20% versus 8%). Regional residence differences find more scaled Latina entrepreneurs in the Northeast, with non-scaled Latina entrepreneurs more numerous in the South. There are no statistical differences within civil status, with the clear majority being married. Of the four Latino-origin groups—Mexican, Puerto Rican, Cuban, and other—scaled Latina entrepreneurs with Mexican roots are the largest percentage group.
3.2.2. The Latina Enterprise—Descriptive Statistics
Descriptive statistics for the Latina enterprise are reported in Table 2. The table provides information for scaled Latina enterprises (column 2), non-scaled Latina enterprises (column 3), and all Latina enterprises (column 4). Firm-level variables, chosen a priori, are based upon variable availability, the previous literature, and over two decades of research experience on the topic. The variables include age of the business, primary sales area of the business (e.g., local or outside the local area [comprising state, national, and international sales areas]), the number of employees, the proportion of employees as Latino, recent requests for business financing, business debt, firm profitability, and industry sector. Other than business debt, the firm-level variables studied are statistically different between scaled and non-scaled Latina entrepreneurs using univariate analyses (i.e., cross-tabulations, comparison of means). The descriptive statistics for scaled and non-scaled Latina enterprises are compared next.
Scaled Latina enterprises are nearly six years older on average than non-scaled Latina enterprises. While both groups of enterprises are more heavily locally focused, this is less so for scaled Latina enterprises, where over 30% derive most of their sales outside the local area. Consistent with revenue size, scaled Latina enterprises have more paid employees than their non-scaled counterparts. Most non-scaled Latina enterprises employ fewer than 10 workers, whereas 44% of scaled Latina businesses have ten or more employees. While both sets of Latina enterprises hire a majority of co-ethnic employees, scaled Latina enterprises have a larger mix of non-Hispanic employees than non-scaled Latina enterprises. Most Latina enterprises have not applied for financing over the preceding 12 months, though just more than one-fifth of scaled Latina enterprises and one-third of non-scaled Latina enterprises have undertaken pathways for financing over the past year. A higher percentage of scaled Latina enterprises report profits and few losses in contrast to non-scaled Latina enterprises, with more than one-quarter of each group reporting break-even business profits. Lastly, by industry classification, non-scaled Latina enterprises are present in higher proportions in accommodations and food services, health care, and other services. On the other hand, scaled Latina enterprises are found in higher proportions in manufacturing, trade (retail and wholesale), professional services, finance, real estate, and insurance.
In summary, a composite profile overview suggests scaled Latina entrepreneurs may be described as married, middle-aged, more acculturated (through generations lived in the US), more educated, found throughout the US but proportionately higher in the Northeast and less so in the South, and with Mexican ancestral roots. Additionally, nearly one in four Latina entrepreneurs (23.5%) have a scaled enterprise. This answers in part the first research question considering the profile and scope of scaled Latina entrepreneurship in the US. An aggregate profile overview of scaled Latina enterprises suggests business maturity of over 10 years, with a heavy local presence, with a good number of co-ethnic employees, without outside debt or current pathways for finance, making money, and primarily engaged in trade, professional services, and construction. This addresses the first research question, considering the profile and scope of scaled Latina entrepreneurship in the US.
3.3. Methodology
The second research question explores the determinants of scaled Latina entrepreneurship. This is undertaken in two parts: one focused on the characteristics of the entrepreneur and the other on the characteristics of the enterprise. Non-scaled Latina enterprises and entrepreneurs are the comparator groups. Addressing this question requires a multivariate statistical approach that distinguishes between dichotomous group outcomes (scaled versus non-scaled). Binomial logistic regression handles dichotomous sets well, is a robust multivariate statistical tool with few assumption requirements (Pampel 2000), and is useful in predicting the odds or likelihood of group membership. Principally, binomial logistic regression provides an enhanced and empirical pathway to understand what characteristics best predict scaled entrepreneurship among Latina businesses and business owners. Two logistic regressions are estimated; the first concerns the Latina entrepreneur, and the second considers the Latina enterprise.
For the analysis of the entrepreneur, a scaled Latina entrepreneur is coded as 1 and a non-scaled Latina entrepreneur is coded as 0. In this case, the scaled Latina entrepreneur is the dependent variable. A set of independent or predictor variables that may predict scaled entrepreneurship are drawn from Latina entrepreneur demographics found in Table 1. Independent variables allow the use of specific entrepreneur characteristics—age, birthplace, generation, Latino identity, sexual orientation, educational attainment, regional residence, civil status, and Latino-origin—to help predict (or estimate) a scaled entrepreneurship outcome.
For the analysis of the enterprise, a scaled Latina enterprise is coded as 1 and a non-scaled Latina enterprise is coded as 0. In this analysis, the scaled Latina enterprise is the dependent variable. A set of independent or predictor variables that may predict scaled enterprises are drawn from Latina enterprise characteristics found in Table 2. Independent variables allow the use of specific business properties—business age, primary sales area, number of employees, proportion of co-ethnic (Latino) employees, financing request, firm debt, profitability, and industry—to help predict (or estimate) a scaled enterprise outcome.
These independent variables were chosen a priori and are based upon more than two decades of extensive experience researching Latino entrepreneurship and the associated literature and variable availability in the SLEI data set. Two binomial logistic regression estimations are undertaken to explore the determinants of scaled Latina entrepreneurship for 2023; results follow next.
4. Results and Discussion
This section reports and discusses the results of each logistic regression. The first logistic regression reports the odds of being a scaled Latina entrepreneur (scaled entrepreneur = 1). Categorical variables with k ≥ 2 categories require one category to be the reference category. When only two categories are present, such as immigrant, one category is identified as the reference category and is coded equal to one (e.g., immigrant = 1), otherwise coded as 0. When more than two categories are present, this is reported as “reference”, as identified in Table 3 and Table 4. The significant variables are reported one by one, ceretis paribus, for the Latina entrepreneur and then the Latina enterprise, followed by a discussion for each below.
4.1. The Latina Entrepreneur—Binomial Logistic Regression Results and Discussion
The variables that significantly decrease the odds of being a scaled Latina entrepreneur are stated first. As Latinas age, the odds of their being a scaled business owner decrease at the rate of 1.3% per additional year of age.7 First- and second-generation Latinas are 70.5% and 39.7%, respectively, less likely to be scaled entrepreneurs in reference to third-generation Latinas. In reference to the highest level of education, graduate education, four other educational attainment levels decrease the odds of scaled Latina entrepreneurship. Latinas with a high school education, education attained at a technical, trade, or vocational school, some college, but no degree, and those with an associate’s degree are 69.6%, 70.6%, 47.9%, and 45.5%, respectively, less likely to be scaled Latina entrepreneurs as compared to Latinas with graduate educations. In reference to Latina entrepreneurs residing in the West, Latinas residing in the Midwest are 40.2% less likely to have a scaled enterprise. In reference to Latinas with Mexican ancestral roots, Latinas with Puerto Rican, Cuban, and other Latino ancestral roots are 43.9%, 50.1%, and 44.6%, respectively, less likely to be scaled Latina entrepreneurs.
Two variables enhance the odds of scaled Latina entrepreneurship: Latino identity and residence. Latina entrepreneurs reporting a weak identity with being Latino are more likely to have a scaled enterprise. In reference to Latinas reporting a strong Latino identity, Latinas with a weak Latina identity are 2.7 times more likely to have a scaled enterprise. In reference to Latinas residing in the West, Latinas residing in the Northeast are 61.2% more likely to have a scaled enterprise. The binomial logistic regression diagnostics are all acceptable and appear at the bottom of Table 3. The model is significant with a Nagelkerke R2 of 0.193. The model predicts reasonably well at 76.5% (or 1.2 times better than chance) and predicts non-scaled Latina entrepreneurs exceptionally well (94.8%).
The logistic regression results provide a tapestry of scaled Latina demographic characteristics and are discussed further. Scaled businesses are more likely the province of younger third-generation Latinas.8 Acculturation through lived family generations and Latino identity strongly influence scaled Latina entrepreneurial outcomes. Latina entrepreneurs from third-generation or longer-present families in the US may provide tacit knowledge valuable to business scaling. Additionally, acculturation through a process of assimilation may result in a weaker Latino identity for Latina entrepreneurs. This weaker Latino identity may facilitate greater participation, encounter fewer institutional barriers, and perhaps provide a pathway for informal acceptance into the mainstream economy. Advanced education is a harbinger to scaled Latina entrepreneurship. Simply, graduate-level education is an enabler of scaled Latina entrepreneurship. Advanced education is strongly connected to more scaled Latina entrepreneurs in the Northeast and Latinas of Mexican origin.9 Both groups have proportionally more advanced degrees. On the other hand, scaled Latina entrepreneurs in the Midwest have lower levels of educational attainment.10
4.2. The Latina Enterprise—Binomial Logistic Regression Results and Discussion
The variables that significantly enhance the odds of being a scaled Latina enterprise are reported first. Each additional year a business is in existence increases the odds of being a scaled enterprise by 6.8%. Enterprises with a primary sales reach beyond their local area are 59.3% more likely to be scaled than Latina businesses primarily selling locally. Businesses with ten or more employees are 8.5 times more likely to be scaled than Latina businesses employing fewer than ten employees. As the percentage of Latino employees declines, the odds of being a scaled enterprise increase. In reference to businesses with 60–100% of employees as Latino, enterprises with 0–40% and 40–60% Latino employees are 105.8% and 44.6%, respectively, more likely to be scaled in comparison. With construction as the reference segment for industry, firms in manufacturing, finance, insurance and real estate, and transportation and warehousing are 4.5 times, 2.6 times, and 2.4 times more likely, respectively, to be a scaled enterprise.
Requests for financing and firm debt both decrease the odds of a Latina enterprise being scaled. Latina businesses requesting financing are 39.0% less likely to be scaled enterprises, in contrast to Latina businesses not requesting financing in the previous 12 months. Latina businesses carrying debt are 34.8% less likely to be scaled compared to those Latina enterprises without debt. Businesses incurring losses are 83.3% less likely to be scaled than profitable Latina businesses. In reference to construction, Latina businesses in accommodation, food services, and health care are 67.2% and 68.4%, respectively, less likely to be scaled. The binomial logistic regression diagnostics are all acceptable and appear at the bottom of Table 4. The model is significant with a Nagelkerke R2 of 0.403. The model predicts reasonably well at 82.7% (or 1.3 times better than chance) and predicts non-scaled Latina enterprises exceptionally well (94.1%).
A portrait of scaled Latina enterprises emerges from the logistic regression results and is discussed further. Scaled Latina enterprises try to avoid debt and are reluctant to seek outside financing. This may be part and parcel a result of startup funding obstacles and a self-reliant and conservative approach to debt financing. Care with debt and financing enables profitable Latina businesses to grow endogenously, using profits to slowly reinvest into the firm so time in business allows for measured scaling. With scaling comes expected increases in size and scope. Scaled Latina businesses simply have more employees to assist with and take on growth. More revealing is the finding that proportionately fewer Latino workers lead to a greater likelihood of scaling. This shows scaled Latina businesses moving toward the mainstream and away from enclave environments. This is a finding that is in concert with Pisani (2022) in his typology of Latino businesses and customers, where a plurality of Latino-owned businesses serve non-Latino customers with a non-Latino product.
The scope of business operations beyond the local environment is also expected as scaled businesses grow and expand regionally and beyond. Scaled firms are more likely to have a larger geographic presence in search of building sales and developing business opportunities. Much harder to discern is industry. As construction is heavily influenced by Latino co-ethnic business owners, construction was the reference category. Perhaps segments in manufacturing, trade, transportation/warehousing, and finance, insurance, and real estate require more inputs than construction, or that construction enterprises headed by Latinas are just smaller in comparison. As it stands, the relationship among industry segments is less understood, certainly an area in need of further research.
5. Conclusions
In many ways, Maria Rios, the Houston-based Latina entrepreneur and owner of Nation Waste, Inc. we met in the introduction, exemplifies the findings of scaled Latina entrepreneurship. Ms. Rios entered the workforce as a teenager, helping her mother clean offices. Building upon this experience, she saw an opportunity to open her own garbage disposal business as a young woman as she was earning her college degree in business. Ms. Rios gradually increased the size of her business, reinvesting and expanding as she went along. As a lifelong learner, Ms. Rios augmented her business skills with additional training in the Stanford Latino Entrepreneurship Initiative’s education program, which in many ways mirrors an executive MBA targeted to Latino business owners (Orozco 2020). Soon her business expanded beyond Houston to include Austin and included sales and employees beyond co-ethnics. Atypically, Ms. Rios is a first-generation immigrant from El Salvador but arrived in the US as a middle school student, and she sought business financing, as new garbage trucks cost about USD 300,000. Ms. Rios also credits adroit business planning in her success (a variable not included in the SLEI survey but important for further research).
Ms. Rios and many other Latina entrepreneurs and their businesses are key drivers of economic growth and business formation in the US (Gomez-Aguinaga et al. 2024). Without them and their co-ethnic male counterparts, new business startups and US economic growth would be at a standstill (Orozco et al. 2020). This exploratory study is the first to focus on scaled Latina entrepreneurship with nationally representative data from 2023 that answered two research questions of scope and determinants. In doing so, a profile of scaled Latina entrepreneurs and their enterprises comes into the spotlight. Findings show that nearly one-quarter of Latina employer enterprises are scaled or scaling with annual sales of USD 500,000 or more. These opportunity-led business ventures seek out new growth markets with tacit information gained from generations of lived US experience coupled with high levels of educational attainment and acculturation. While younger Latinas are more likely to have scaled businesses, they are also more likely to have older businesses, indicating a much earlier startup history. Also evident in scaled Latina entrepreneurship are business size proxied by ten or more employees, a wider business geographic scope beyond the local environment, and cultural roots traced back to Mexico rather than other Latino origin areas.
From a managerial standpoint, scaled Latina entrepreneurship may benefit from strong co-ethnic networks to enhance interdependent business relations, business and trade association membership, and robust mentorship from successful mentors such as Ms. Rios. Public policy may provide fuller pathways to education, especially graduate education, and access to government contracting and public funding, and reduce institutional and societal barriers, from banking discrimination to at-large structural and cultural biases (Richardson and Pisani 2017).
The foremost limitation of this study is the cross-sectional nature of the data. At this point in time, the SLEI data do not allow for longitudinal assessment of scaled Latina entrepreneurship. Further refinement of industry classification and questions concerning business planning should be undertaken in future SLEI surveys. While not significant, the inclusion of sexual orientation is a first in a national study of Latina entrepreneurship. Perhaps more qualitative studies may shed more light on this variable. Triangulation of results using qualitative analyses and case studies would also add to the robustness of the empirical results presented in this article.
Funding
This research received no external funding.
Institutional Review Board Statement
The data used in this research is secondary data. The SLEI data that is released does not possess identifying characteristics of the entrepreneur or enterprise. This is much like public data received from the US Census Bureau. No institutional review board statement is needed.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data may be requested from SLEI at https://www.gsb.stanford.edu/faculty-research/labs-initiatives/slei (accessed on 13 July 2024).
Conflicts of Interest
The author declares no conflicts of interest.
| 1 | All monetary figures in this article refer to US dollars. |
| 2 | The terms Latino and Hispanic are used interchangeably in this article. By convention, Latina refers specifically to Hispanic females, whereas Latino may refer to all Hispanics or only to Hispanic males. Latino refers to all Hispanics in this article unless noted otherwise. |
| 3 | For all Hispanic firms (male and female), SLEI utilizes a benchmark of USD 1 million in annual revenues (Orozco et al. 2018). As Latina firms are on the whole much smaller than their male counterparts, the USD 500,000 annual revenue benchmark is the foundational framework for scaling in this study. |
| 4 | See Gomez-Aguinaga et al. (2024) for a fuller description of the Stanford Latino Entrepreneurship Initiative (SLEI) and the Latino Action Business Network (LBAN). Associated websites are found at https://www.gsb.stanford.edu/faculty-research/labs-initiatives/slei (SLEI) and at https://www.lban.us/ (LBAN), accessed on 13 July 2024, respectively. |
| 5 | Data and sample detail are derived from Gomez-Aguinaga et al. (2024). |
| 6 | Gomez-Aguinaga et al. (2024, p. 55) define generations in the following manner: “Categorization of individuals based on their nativity backgrounds and that of their ancestors. For this study, we analyze three immigrant generations: (1) first-generation or immigrants, who were born outside of the 50 U.S. states; (2) second-generation or children of immigrants, who were born in the United States to foreign-born parent(s); and (3) third and subsequent generations, who both their parents and themselves were born in the United States” (bold type appears in the original). |
| 7 | This is calculated as |1 − Exp(β)|. For example, the calculation for age is |1 − 0.987| or 0.013 or 1.3%. As Exp(β) is less than 1, this is interpreted as a decrease. |
| 8 | A comparison of means test reveals that third-generation scaled Latina entrepreneurs are significantly younger than their first- and second-generation counterparts (ANOVA: F = 2.557, df = 2, p = 0.079). |
| 9 | A crosstabulation of Latino origin and education confirms this assessment (Pearson Chi-Square = 48.390, df = 18, p = 0.001). |
| 10 | A crosstabulation of regional residence and education supports this assessment (Pearson Chi-Square = 52.209, df = 18, p = 0.001). |
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Table 1.
Descriptive statistics for Latina entrepreneurs (2023).
| Variable | Scaled Entrepreneurs | Non-Scaled Entrepreneurs | All Entrepreneurs |
|---|---|---|---|
| Mean Age (std. dev.) | 39.2 (9.3) | 40.8 (9.1) | 40.4 (9.3) |
| Immigrant—Yes [Born Outside of US and Puerto Rico] (%) | 21.7 | 40.2 | 35.8 |
| Generation (%) | |||
| 1st Generation | 27.3 | 56.6 | 49.7 |
| 2nd Generation | 33.8 | 24.1 | 26.4 |
| 3rd Generation | 38.4 | 19.3 | 23.9 |
| Latino Identity (%) | |||
| Weak | 9.9 | 2.1 | 3.9 |
| Medium | 14.1 | 13.7 | 13.8 |
| Strong | 76.0 | 84.2 | 82.3 |
| Sexual Orientation (%) | |||
| Straight (heterosexual) | 83.1 | 88.3 | 87.1 |
| Other (non-heterosexual) | 16.9 | 11.7 | 12.9 |
| Education (%) | |||
| Less than High School Degree | 19.5 | 12.5 | 14.1 |
| High School Degree or Equivalent | 16.9 | 32.7 | 29.0 |
| Technical, Trade, or Vocational School | 4.8 | 10.6 | 9.2 |
| Some College, No Degree | 12.4 | 10.7 | 11.1 |
| Associate’s Degree | 19.8 | 7.9 | 10.7 |
| Bachelor’s Degree | 21.5 | 14.2 | 15.9 |
| Master’s, Doctorate, or Professional Degree | 5.1 | 11.4 | 9.9 |
| Regional Residence (%) | |||
| Midwest | 10.1 | 9.9 | 10.0 |
| Northeast | 15.8 | 10.9 | 12.0 |
| South | 38.6 | 47.2 | 45.2 |
| West | 35.5 | 32.0 | 32.8 |
| Civil Status | |||
| Single | 19.2 | 18.0 | 18.3 |
| Married/Living Together | 66.4 | 68.7 | 68.2 |
| Divorced/Widowed | 14.4 | 13.3 | 13.6 |
| Latino Origin Roots (%) | |||
| Mexican | 60.0 | 41.1 | 45.5 |
| Puerto Rican | 17.7 | 23.2 | 21.9 |
| Cuban | 7.6 | 15.1 | 13.3 |
| Other Latino | 14.6 | 20.6 | 19.2 |
| N (%) | 355 (23.5%) | 1158 (76.5%) | 1513 (100.0%) |
Italics = the two groups are statistically different (utilizing cross-tabulations or comparison of means tests @ p ≤ 0.10). For variables with percentages, some rounding errors may be present. Source: Author’s calculations from the SLEI 2023 survey.
Table 2.
Descriptive statistics for Latina enterprises (2023).
| Variable | Scaled Enterprises | Non-Scaled Enterprises | All Enterprises |
|---|---|---|---|
| Mean Age of Business in Years (std. dev.) | 13.7 (11.2) | 8.0 (8.5) | 9.3 (9.5) |
| Primary Sales Area (%) | |||
| Local | 69.6 | 78.1 | 76.1 |
| State/National/International | 30.4 | 21.9 | 23.9 |
| Current Number of Employees (%) | |||
| One to Nine | 56.6 | 88.4 | 80.8 |
| Ten or More | 43.5 | 11.6 | 19.2 |
| Percent of Employees Latino (%) | |||
| 0–40 | 22.5 | 19.3 | 20.1 |
| 40–60 | 19.2 | 13.4 | 14.7 |
| 60–100 | 58.3 | 67.3 | 65.2 |
| In the Past 12 Months, Has the Business Requested or Applied for Financing? (%) | |||
| Yes | 22.3 | 38.3 | 34.6 |
| No | 77.7 | 61.7 | 65.4 |
| Business Debt (%) | |||
| Yes | 25.2 | 29.0 | 28.2 |
| No | 74.8 | 71.0 | 71.8 |
| Profitability (%) | |||
| Yes | 70.4 | 64.2 | 65.6 |
| No | 1.1 | 9.5 | 7.5 |
| Breakeven | 28.5 | 26.3 | 26.8 |
| Industry (%) | |||
| Construction | 10.4 | 11.2 | 11.0 |
| Accommodation and Food Services | 4.8 | 15.4 | 12.9 |
| Manufacturing | 5.4 | 1.9 | 2.7 |
| Trade | 31.0 | 10.3 | 15.1 |
| Professional Services | 20.6 | 16.5 | 17.4 |
| Finance, Insurance, Real Estate | 7.9 | 3.7 | 4.7 |
| Health Care | 4.2 | 16.4 | 13.5 |
| Transportation/Warehousing | 5.9 | 6.3 | 6.2 |
| Entertainment | 2.0 | 2.0 | 2.0 |
| Other Services | 7.9 | 16.3 | 14.3 |
| N (%) | 355 (23.5%) | 1158 (76.5%) | 1513 (100.0%) |
Italics = the two groups are statistically different (utilizing cross-tabulations or comparison of means tests @ p ≤ 0.10). For variables with percentages, some rounding errors may be present. Source: Author’s calculations from the SLEI 2023 survey.
Table 3.
Binomial logistic regression for scaled Latina entrepreneurs (=1).
| Variable | β | S.E. | Wald | Exp(β) ^ |
|---|---|---|---|---|
| Constant | 0.658 | 0.523 | 1.582 | 1.932 |
| Mean Age (in years) | −0.013 | 0.008 | 2.804 | 0.987 * |
| Immigrant (yes = 1 [reference]) | 0.013 | 0.336 | 0.001 | 1.013 |
| Generation | 18.087 ‡ | |||
| 1st Generation | −1.220 | 0.319 | 14.663 | 0.295 ‡ |
| 2nd Generation | −0.506 | 0.175 | 8.366 | 0.603 ‡ |
| 3rd Generation | Reference | Reference | Reference | Reference |
| Latino Identity | 20.470 ‡ | |||
| Weak | 1.312 | 0.308 | 18.102 | 3.714 ‡ |
| Medium | −0.194 | 0.195 | 0.989 | 0.824 |
| Strong | Reference | Reference | Reference | Reference |
| Sexual Orientation (straight = 1 [reference] | 0.283 | 0.189 | 2.258 | 1.328 |
| Education | 48.565 ‡ | |||
| Less than High School Degree | −1.825 | 1.372 | 1.769 | 0.161 |
| High School Degree or Equivalent | −1.190 | 0.309 | 14.808 | 0.304 ‡ |
| Technical, Trade, or Vocational School | −1.225 | 0.349 | 12.326 | 0.294 ‡ |
| Some College, No Degree | −0.652 | 0.259 | 6.349 | 0.521 † |
| Associate’s Degree | −0.607 | 0.278 | 4.765 | 0.545 † |
| Bachelor’s Degree | 0.119 | 0.244 | 0.240 | 1.127 |
| Master’s, Doctorate, or Professional Degree | Reference | Reference | Reference | Reference |
| Regional Residence | 12.730 ‡ | |||
| Midwest | −0.514 | 0.242 | 4.523 | 0.598 † |
| Northeast | 0.478 | 0.226 | 4.471 | 1.612 † |
| South | −0.108 | 0.162 | 0.441 | 0.898 |
| West | Reference | Reference | Reference | Reference |
| Civil Status | 0.732 | |||
| Married/Living Together | 0.027 | 0.176 | 0.024 | 1.028 |
| Divorced/Widowed | 0.191 | 0.243 | 0.617 | 1.210 |
| Single | Reference | Reference | Reference | Reference |
| Latino Origin Roots | 16.581 ‡ | |||
| Puerto Rican | −0.579 | 0.220 | 6.925 | 0.561 ‡ |
| Cuban | −0.694 | 0.254 | 7.483 | 0.499 ‡ |
| Other Latino | −0.591 | 0.195 | 9.141 | 0.554 ‡ |
| Mexican | Reference | Reference | Reference | Reference |
| Diagnostics | ||||
| −2 Log Likelihood | 1428.115 ‡ | |||
| Cox and Snell R2|Nagelkerke R2 | 0.129|0.193 | |||
| Hit Ratio (% Correct): Yes (scaled entrepreneur)|No (not a scaled entrepreneur)|Overall | 17.7|94.8|76.5 | |||
| N | 1492 | |||
Notes: PPC—proportional chance criterion; (PPC) = a2 + (1 − a)2. A good model predicts 1.25 times the PPC. Latina scaled entrepreneurs: (0.237)2 + (1 − 0.237)2 = 0.638; 1.25 times = 0.798; the model predicts 0.765, slightly less than 1.25 times chance. ^ Represents significance at the * p ≤ 0.10; † p ≤ 0.05; and ‡ p ≤ 0.01 levels. Source: Author’s calculation from 2023 SLEI survey.
Table 4.
Binomial logistic regression for scaled Latina enterprises (=1).
| Variable | β | S.E. | Wald | Exp(β) ^ |
|---|---|---|---|---|
| Constant | −2.794 | 0.293 | 91.143 | 0.061 ‡ |
| Mean Age of Business (in years) | 0.066 | 0.009 | 60.172 | 1.068 ‡ |
| Primary Sales Area (Local = 1 [reference]) | 0.465 | 0.180 | 6.653 | 1.593 ‡ |
| Current Number of Employees (1 to 9 =1 [reference]) | 2.249 | 0.186 | 145.678 | 9.476 ‡ |
| Percent of Employees Latino | 11.914 ‡ | |||
| 0–40 | 0.722 | 0.215 | 11.322 | 2.058 ‡ |
| 40–60 | 0.369 | 0.218 | 2.851 | 1.446 * |
| 60–100 | Reference | Reference | Reference | Reference |
| In the Past 12 Months, Has the Business Requested or Applied for Financing? (no = 1 [reference]) | −0.495 | 0.197 | 6.326 | 0.610 † |
| Business Debt (no = 1 [reference]) | −0.428 | 0.195 | 4.819 | 0.652 † |
| Profitability | 10.551 ‡ | |||
| No | −1.792 | 0.579 | 9.570 | 0.167 ‡ |
| Breakeven | −0.230 | 0.187 | 1.516 | 0.794 |
| Yes | Reference | Reference | Reference | Reference |
| Industry | 94.995 ‡ | |||
| Accommodation and Food Services | −0.849 | 0.362 | 5.502 | 0.428 † |
| Manufacturing | 1.698 | 0.429 | 15.661 | 5.461 ‡ |
| Trade | 1.052 | 0.292 | 12.947 | 2.862 ‡ |
| Professional Services | 0.346 | 0.288 | 1.446 | 1.414 |
| Finance, Insurance, Real Estate | 1.285 | 0.359 | 12.773 | 3.613 ‡ |
| Health Care | −1.153 | 0.391 | 8.694 | 0.316 ‡ |
| Transportation/Warehousing | 1.234 | 0.384 | 10.344 | 3.436 ‡ |
| Entertainment | 0.633 | 0.558 | 1.286 | 1.883 |
| Other Services | −0.523 | 0.321 | 2.658 | 0.593 |
| Construction | Reference | Reference | Reference | Reference |
| Diagnostics | ||||
| −2 Log Likelihood | 1053.803 ‡ | |||
| Cox and Snell R2|Nagelkerke R2 | 0.262|0.403 | |||
| Hit Ratio (% Correct): Yes (scaled enterprise)|No (not a scaled enterprise)|Overall | 42.0|94.1|82.7 | |||
| N | 1410 | |||
Notes: PPC—proportional chance criterion; (PPC) = a2 + (1 − a)2. A good model predicts 1.25 times the PPC. Serial entrepreneurs: (0.219)2 + (1 − 0.219)2 = 0.658; 1.25 times = 0.822; the model predicts 0.827, slightly more than 1.25 times chance. ^ Represents significance at the * p ≤ 0.10; † p ≤ 0.05; and ‡ p≤ 0.01 levels. Source: Author’s calculation from 2023 SLEI survey.
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Pisani, M.J. Scaled Latina Enterprises in the United States of America. Adm. Sci. 2024, 14, 245. https://doi.org/10.3390/admsci14100245
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Pisani MJ. Scaled Latina Enterprises in the United States of America. Administrative Sciences. 2024; 14(10):245. https://doi.org/10.3390/admsci14100245
Chicago/Turabian StylePisani, Michael J. 2024. "Scaled Latina Enterprises in the United States of America" Administrative Sciences 14, no. 10: 245. https://doi.org/10.3390/admsci14100245
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