An Examination of the Differences in the Funding of Minority-Owned Businesses (Small and Large) Compared to Non-Minority Businesses

An Examination of the Differences in the Funding of Minority-Owned Businesses

(Small and Large) Compared to Non-Minority Businesses

Small and medium enterprises (SMEs) are crucial for the economic development

of a region and a country (Rahman & Kabir, 2019). However, access to capital is a major

challenge for minority-owned companies (Robb, 2020). Research utilizing the Small

Business Credit Survey (SBCS) indicated that minority-owned companies regularly rely

on personal funds and often have a weak relationship with banks, as demonstrated by a

low credit application rate (Banks, 2021). In fact, even when minority-owned business

leaders have good credit, they may not be approved for a loan. The denial of capital is due

to a lack of adequate information among minority-owned small business owners. Also,

financial institutions impose requirements (e.g., past performance, credit score, etc.) for

accessing capital that automatically excludes many small firms. In 2017, the value-added

contribution of minority business enterprises (MBEs) to the gross domestic product

(GDP) was 2.3%, or approximately $500 billion, compared to 15.5% for nonminority-

owned businesses.

The findings from this study may enable minority-owned leaders to have an

informed understanding of the challenges they face so they can adopt appropriate

measures promoting their financial performance and, therefore, business growth. On the

other hand, more excellent knowledge of the funding disproportion among

minorityowned businesses could encourage financial institutions and government

agencies to ease business loan procedures, policies, and regulations that are detrimental to

this group of companies. The goal of this research study was to examine the degree to

which minorityowned business status and size of business explain the funding received

by businesses may limit minority-owned businesses’ ability to contribute to the

development of local economies and, therefore, the nationwide economy.

Historical Background

Minority-owned businesses are essential to the United States' economic growth.

Winston (2021) estimated that by 2044, the U.S. would have a majority-minority

population, and minority workers and MBEs would have a significant impact on the GDP.

In 2018, approximately 18.5%, or one million, U.S. employers were minority business

owners, and most were contributors to their communities’ job creation and wealth growth

(Vilasquez, 2020). Over the last 10 years, among the two million small businesses

created, 50% were minority-owned and contributed to as many as 4.7 million jobs created

in the United States of America, according to the US Committee on Small Business and

Entrepreneurs. A recent change due to the COVID-19 pandemic impacted small

businesses.

The COVID-19 pandemic has disproportionately impacted small businesses.

African Americans have faced economic hardships with 41% of active businesses,

followed by 32% of Latinx-owned compared to 17% of White-owned in the second

quarter of 2020 (Fairlie & Fossen, 2022; Fairlie, 2020; Velasquez, 2020). The CARES

Act, which included the Paycheck Protection Program (PPP) and Economical Injuries

Disaster Loan (EIDL) program, was not beneficial for many minority-owned businesses

(Fairlie & Fossen, 2022). The majority of MBEs are not affiliated with the Small Business

Administration (SBA). Even among affiliated businesses, many did not receive early

information about the program needed to apply. Institutional discrimination and social

inequalities create challenges that prevent minority-owned businesses from accessing

capital (Berdejo, 2021; Robb, 2020; Wainwright, 2020). Minority-owned businesses often

have weak relationships with financial institutions, have bad experiences with credit

applications, and rely on self-financing, unlike their non-minority-owned business

counterparts (SBCS, 2021).

Research has found that access to capital remains a factor disproportionately

affecting minority-owned businesses (Robb & Niwot, 2018), which prevents expansion

and innovation. Financing minority firms remains the top priority challenge in the US for

job creation and economic growth. Research has provided evidence of racial

discrimination against Black-owned businesses by banks and commercial lenders during

the COVID-19 pandemic disruption (Atkins et al., 2022). The concern was that

Blackowned businesses received approximately 50% lower loans through the PPP than

Whiteowned. A survey of businesses has shown that 41% of Black-owned businesses who

applied for loans through PPP did not receive funds, and an additional 21% were not

informed about the program (Atkins et al., 2022). The advocacy organizations Unidos

U.S. and Color of Change published that only 12% of Black and Latino small business

owners received the exact amount of loan applied through PPP, while 26% got a portion

of the funds requested (Santellano, 2021).

Organizational Context

In this quantitative non-experimental causal-comparative study, I used ex post

facto data to examine the differences in the disbursed/shipped approved funding amount

based on the minority-owned status and size of the business. The data set used within this

study was the Working Capital Transactions Authorization data set from 01/01/2006 to

09/01/2022, administrated by the Export-Import Bank of the United States (EXIM Bank,

2020). The data were drawn from businesses and lenders across the United States. The

data set enabled the identification of minority-owned small business enterprises regularly

established in the United States of America and engaged in exporting goods and services

abroad and well-established financial institutions that have agreements with EXIM Bank

and specialize in lending funds to small businesses. For the data set, I searched the

Walden University library, SBA, data.gov, and Census Bureau research engines. The data

set describes the capital transactions that small and minority-owned businesses have

received or been denied for exports and imports from EXIM Bank.

EXIM Bank is an official Export Credit Agency (ECA) founded under the renewal

statutory charter (Act of 1945, as amended; 12 U.S.C. §§635 et Seq.), which respects

international rules on ECA financing, and is a member of the Organization for Economic

Cooperation for Development (OECD) (Akhtar, 2019 & 2022). OECD was established in

1978 to provide credit to exporters while doing business abroad and facing competitors.

With ECA financing, the terms and conditions of financing are determined, and an

agreement for the repayment period is also made. In the early 1970s, EXIM Bank created

the Private Export Funding Corporation (PEFCO) as a privately owned entity designed to

buy loans from private lenders. The EXIM bank guarantees the loans and reduces risk-

taking associated with borrowing from commercial banks on the market (De Rugy, 2020).

In addition to EXIM Bank, other U.S. Government agencies also finance exports. The

U.S. Department of Agriculture specializes in agricultural goods and services exports.

SBA promotes small businesses for exports with a guaranteed program. Under the World

Trade Organization rules, arrangement-compliant export credit practices are not subject to

export subsidy prohibition. The bank’s goal is to fill market gaps when the private sector

is reluctant or unable to finance U.S. exporting companies and or when U.S. exports

compete against ECA-backed foreign export companies (Shekhar & Jena, 2021).

EXIM Bank is led by a five-member board of directors appointed by the President

of the United States of America and confirmed by the Senate (Democrat and Republican)

(Akhtar, 2019 & 2022). The president and vice-president of the EXIM bank are,

respectively, the board chairman and vice-chairman. A quorum of three out of five board

members is sufficient to conduct business, which includes the approval of financing over

10 million dollars with at least a term of 7 years for repayment. The board of directors

makes decisions on the bank’s requirements and policies. In addition, advisors and other

committee members assist the board of directors.

The primary mission of EXIM Bank is to support U.S. exports of goods and

services and to sustain jobs (Akhtar, 2019). To do so, the bank developed four key

programs:

1. Direct loans to foreign buyers of U.S. exports with an interest rate in

accordance with international trade rules and above the rate of the U.S.

Treasury.

2. Loan guarantees to lenders to protect U.S. exports against no-payment from

foreign buyers. The lenders fix the loan rate.

3. Insurance to protect U.S. exporters or financial institutions against any

exportrelated risk.

4. Working capital guarantees short-term loans to U.S. exporters (Akhtar, 2019,

2022; Young, 2019).

EXIM Bank is required to ensure that U.S. private exporters are properly financed

and that the repayment conditions are well-defined. The bank may enter into competition

to protect U.S. exports with terms, rates, and conditions when the international ECA

landscape changes. Each year, EXIM Bank extends more than 30% of its financing

authority to support small business exports, with a minimum of five percent to renewable

energy, energy efficiency, and energy storage technology exports (Akhtar, 2022).

Additionally, the bank’s objectives include environmentally beneficial exports and

exports to sub-Saharan Africa. EXIM bank set its default rate up to 2%. Thus, the bank

monitors its credit and transaction risks every quarter and reports its default rate. The

bank sets up the credit underwriting and due diligence of potential transactions to mitigate

risks to ensure repayment.

The charter of EXIM Bank requires that 75% of its funding be granted to small

businesses. The bank defines a small business as a company with no more than 1500

employees (Young, 2019). EXIM Bank protects small businesses against risks and losses

with loan dispenses, working capital, and guarantees (de Rugy & Leventhal, 2019).

Considering the organizational context, within this quantitative study, I examined the

differences in the disbursed/shipped approved funding amount based on the

minorityowned status and size of the business.

Problem Statement

Access to capital is vital for small enterprises for job creation, innovation, and

economic growth in the United States (Robb & Niwot, 2018). Recently, the U.S. Treasury

Department invested more than $4 billion in 332 institutions, where $3.9 billion was

assigned to community banks and $104 million to community development loan funds

(CDLFs; Brock, 2018). Between 2018 and 2019, the business lending rate increased by

seven percent, while the growth rate of small business loans ($1 million or less) was

stagnant (SBA Advocacy Office, 2020). The general problem was that some minority-

owned business entrepreneurs (who often have small businesses) could not gain a similar

success level in accessing lender funding as non-minorities, resulting in the high failure

rates of their business operations. The specific problem was that some business leaders

did not know the differences in the disbursed/shipped approved funding amount based on

the minority-owned status and size of the business.

Purpose Statement

The purpose of this quantitative non-experimental causal-comparative study

utilizing ex post facto data was to examine the differences in the disbursed/shipped

approved funding amount based on the minority-owned status and size of the business.

The targeted population was small enterprises legally established in the U.S. for over 5

years and small business loan banks. The independent variables were minority-owned

businesses (minority-owned businesses and non-minority-owned) and small businesses

(small and large businesses). The dependent variable was the disbursed/shipped amount.

The social change implication for this research was to investigate whether differential

loan funding exists (i.e., access to distributed/shipped approved loan amounts). Leader

resources were essential for businesses to improve their profitability. Also, access to

resources enhanced organizations’ job creation, innovations, and overall economic

growth.

Target Audience

The key stakeholders in this portfolio are small business leaders with a specific

focus on minority-owned business leaders. The research findings could give small

business leaders, specifically small minority-owned business owners, an opportunity to

understand their challenges and strategies to promote their financial performance.

Additionally, the proposed study’s findings have the potential to inform financial

institutions, loan banks, and government agencies (federal and local) to ease policies,

procedures, and loan processes toward the minority-owned business organizations, which

are the backbone of the local economy.

Research Question

Research Question (RQ): Is there a significant difference in the disbursed/shipped

approved funding amount based on the minority-owned status and size of the business?

Hypotheses

Based on the research questions, the hypotheses are:

Null Hypothesis (Ho1): There is no difference in the disbursed/shipped approved

funding amount based on the minority-owned status of the business.

Alternative Hypothesis (HA1): There is a difference in the disbursed/shipped

approved funding amount based on the minority-owned status of the business

Null Hypothesis (Ho2): There is no difference in the disbursed/shipped approved

funding amount based on the size of the business.

Alternative Hypothesis (HA2): There is a difference in the disbursed/shipped

approved funding amount based on the size of the business.

Null Hypothesis (Ho3): There is no difference in the disbursed/shipped approved

funding amount among minority-owned businesses and non-minority-owned businesses

based on the size of the business.

Alternative Hypothesis (HA3): There is a difference in the disbursed/shipped

approved funding amount among minority-owned businesses and non-minority-owned

businesses based on the size of the business.

Significance

The contribution to business practice and the potential positive implications for

social change are considerable for this study. Robb and Niwot (2018) argued that

Minority Business Development Agencies and SBA provided evidence of continuing

disparities between minority and non-minority-owned businesses for accessing capital. In

this study, I examined the differences in the funding of minority-owned businesses (small

and large) compared to non-minority companies, the disbursed/shipped approved funding

amount, and the relationship between minority-businesses status and the

disbursed/shipped approved loan amount when controlling for business size. This study’s

findings have the potential to positively contribute to business practices within

minorityowned companies of any size. They could inform leaders within small businesses

by better understanding funding allocations.

Contribution to Business Practice

This research study's results, conclusions, and recommendations may benefit

financial institutions and small businesses. Small business refers to a privately owned

corporation, partnership, or sole proprietorship, having 500 employees or fewer

depending on the industry and generating an average annual income of 28.5 million U.S.

dollars (Robb, 2018; SBA, 2020; & U.S. Census, 2020). Small businesses are the basis of

economic growth in the U.S. Recently, the Department of Treasury approved more than $

4 billion for 332 small business lending institutions, of which $ 3.9 billion went to

community banks and $104 million to 51 CDLFs (Brock, 2018). While small businesses

have received funding from the federal government, minority-owned businesses

disproportionately received less funding than their non-minority counterparts (Robb &

Niwot, 2018)

Access to the distributed/shipped approved loan amount may be disproportionate

due to factors not considered by financial and small businesses. The study is vital for

business practice, given an investigation of whether funds are distributed equitably

between minority and non-minority-owned businesses may illuminate potential

disparities. Whether disparities are found or not, the study’s findings have the potential to

inform stakeholders within the government and business. Thus, the study’s findings have

the potential to reduce possible disparities and, as a result, improve the business

performance of minority-owned businesses.

Positive Social Change Implications

The positive social change implication of the proposed study was to investigate if

differential loan funding (i.e., access to disbursed/shipped approved loan amount) exists

so that leaders in business and financial sectors can be made aware of how funding

resources are distributed. Lender resources are essential for businesses to improve their

profitability. Also, additional funding resources have the potential to enhance job

creation, innovations, and overall economic growth. Small and medium enterprises

(SMEs) represent 95% of firms, participate in between 60% and 70% of global

employment, and contribute to the largest share of new jobs in the economies (Observer,

2000). Furthermore, SMEs contribute to the eradication of poverty and the improvement

in the living standards of vulnerable groups through the increase in income and

selfemployment (Naradda Gamage et al., 2020).

Theoretical Framework

The financial growth cycle (FGC) model for SMEs was introduced in 1988 by

Berger and Udell and later developed by Sanchez-Vital and Martin-Ugedo (2012) and

Huang et al. (2020). FGC offers an explanation for how small businesses progress

through the growth cycle stages with various financial characteristics. SMEs pass through

phases of financial growth and crisis. Borio et al. (2018) stressed that companies are

financed by angel finance, friends, family members, and others to encourage financial

growth. This growth was followed by a period of crisis due to the high credit interest rates

and the restrictions of financial institutions due to a lack of business information.

Hawkins and Kuang (2017) stated that it is vital to understand the drivers and dynamics

of lending behavior to understand the financial business cycle. The key tenants of the

FGC theoretical framework include SMEs, venture capital, financial institutions, angel

finance, public equity, lenders, and stakeholders.

The financial institutions, angel financers, and lenders perform transactions of the

disbursed/shipped approved loan amount based on the status and size of the business. The

FGC measures the cycle of financial growth for businesses in relation to the availability

of approved funding. This framework will be used as a lens within the proposed study to

provide a structure for understanding whether the growth of funding is equitably

disbursed based on minority status and the size of the business. Thus, the FGC theory

provides a framework for understanding the study’s focus on examining the differences

between minority-owned and non-minority-owned businesses (after controlling for

business minority status and size) in the funding received.

Operational Definitions

Angel finance is a term used to qualify personal or group funds invested in small

businesses with high risks and high returns on investment (Edelman et al., 2017).

Financial institutions are organizations that act as mobilizers and depositories of

savings and provide credit services and other financial services to the communities

(Bhole, 2004).

Public equity refers to large companies that raise capital publicly by issuing

shares, which enable investors to acquire the ownership interest in the company (Kumar

Rai & Shaikh, 2021; Meoli et al., 2018; Szkuta et al., 2021).

Small and medium enterprises (SMEs) represent 95% of firms, participate

between 60% and 70% of global employment, and contribute to the largest new jobs

share in the economies (Observer, 2000), are the most dynamic ventures in the global

economy and play a vital role in developing the human welfare of any country (Naradda

Gamage et al., 2020).

Venture capital is a mid-term equity investment or direct investment that promotes

the growth of SMEs to the stage of public equity with a clear exit strategy

(Nyagadza et al., 2019)

A Review of the Professional and Academic Literature

This literature review focuses on small businesses’ potential capital access status,

particularly the financial growth that challenges minority small business owners. The

literature review was conducted to examine research on topics surrounding the study’s

dependent variable, disbursed/shipped amount, and the independent variable,

minorityowned business status, when controlling for the size of the business. Within this

extant review of the literature, I critically analyzed and synthesized research describing

the theoretical framework, and prior studies focused on the funding of minority-owned

businesses’ status and size of business as they relate to funding received. The data

reviewed included peer-reviewed journal articles, books, and reports from governments'

and organizations’ websites. The vast majority of data reviewed were recently published

and no more than 5 years old.

The research literature I reviewed was retrieved from Walden Library, Business

and Management Academic databases with Business Source Complete, ABI/INFORM

Complete, Emerald Management, ProQuest Central, ScienceDirect, and Sage Premier.

Also, Data.gov, SBA, Census Bureau, Google, and Google Scholar engine search

contributed to my research. The literature review retrieved enabled me to identify

peerreviewed on the FGC model.

The Financial Growth Cycle (FGC) Model

Many researchers have established the business FGC models and theories. In this

business literature, I reviewed the business growth stages of development and the FGC in

the small business growth process. Penrose, in 1952 and 1959, originated the “Life Cycle

theory of the Firm” (LCTF) in the economics literature (Mac & Bhaird, 2010). The LCTF

is used to describe the growth phases of a firm from its creation to its maturity. The stage

of growth is set as follows: the traditional society, the precondition for take-off, the

takeoff, the drive to maturity, and the age of high mass consumption (Jacobs, 2022; Li &

Hung, 2013; Rostow, 1959).

The five growth stages, which are a sequential linear process, are inherent to any

country in the world. Traditional society has the characteristics of subsistence economics,

where all activities are at the rudimentary stage (Jacobs, 2022; Li & Hung, 2013; Rostow,

1959). Within this stage, the product from agriculture was sold for fiscality and not for

profit or gain (Hoffman, 2018). The population has no scientific perspective on the world

and technology. In the second stage, the precondition to take off, the production of

agriculture increases with trade activities which enable the creation of other business

services. The third is the stage of take-off, a period at the beginning of industrialization

characterized by economic growth and institutionalization of activities and workers. The

drive to maturity stage is the period where standardization of living increases with the use

of high technology, and it is characterized by the growth of the national economy and its

diversity. The last stage is high mass consumption; at this stage, the process of

industrialization is completed. The income of the workforce increases with the

establishment of labor unions. Even though these five stages of economic growth are

important, they are not necessary for today’s economic development of many countries

(Tsiang, 1964).

The number of stages of economic growth is not standard across all organizations.

Steinmetz (1969) proposed a growth model based on three stages, and Greiner, in 1972,

proposed a five-stage evolution-revolution model where each stage is separated by

revolution change (Mac and Bhaird, 2010). However, management succession is a crucial

factor contributing to changes in the organizational structure and small business progress.

Churchill and Lewis (1983) developed a five-stage model with eight prominent factors

for business succession (Manna, 2018). The five stages of business succession are

existence, survival, success, take-off, and resource maturity. These five stages are vital for

business management leaders, practitioners, and researchers to understand each step and

implement them according to business strategies and environment. The varied economic

growth models each provide an example of how companies move through the growth

stages.

In the sales-marketing cooperation strategy, researchers developed many stages of

growth for firm development. Manna (2018) established six stages for business growth as

follows:

x Bare land devoid of business is the area without any business. Some factors,

such as culture, tribal, and new business policy, naturally may influence the

business existence, or the business activities are relatively weak due to the

unfavorable environment.

x Establishment, at this stage, the businesses are set up with all opportunities to

succeed or disappear. The firm develops marketing and growth strategies to

conquer the market.

x Aggregation, the established business grows and creates extension branches. x

Competition and coaction, business leaders develop expansion strategies with the

local market as well as nationwide with specific products or services. In

competitive conditions, managers implement customer service as a key area of

innovation and invest in information technologies to achieve a high level of

customer satisfaction.

x Reaction is the stage at which the business leaders invest innovation and

information technologies to change the business market environment and

customer behavior.

x Stabilization, the stage where the firm becomes public. The period of the

standardization of living increases with the use of high technology and the

growth and diversity of the national economy (Jacobs, 2022; Li & Hung,

2013; Rostow, 1959).

However, this stage model does not apply in a biological analogy of organizations’

existence. Organizations are born, grow, and decline; and may also reawaken or disappear

(Mac & Bhaird, 2010).

The firm life cycle approach is a linear sequential process of firm growth, and it is

particularly applied in the literature on management and organizational studies. However,

the firm life cycle is not standardized. Atolia et al. (2018) explained that business cycles,

which are asymmetrical, are divided into two categories: steepness and deepness.

Steepness is marked by a sharp contraction followed by a long recovery period, and

deepness refers to the business cycle troughs which are often deeper than tall peaks.

Therefore, the business life cycle evolves at the same time with many economic activities

that are characterized by general recessions, contractions, and revivals (Tahir et al., 2020).

The cyclical period of businesses, such as duration, amplitude, and severity of economic

evolution, enables researchers to follow fluctuations in the economy and implement

strategies accordingly.

The business life cycle passes through at least three phases (startup, growth, and

crisis). The startup phase is the period of uncertainty characterized by Porter’s five forces

framework, introduced in 1979 to understand the market (Isabelle et al., 2020; Porter,

2021). The five forces framework are the threat of new entrants, the bargaining power of

buyers, the bargaining power of suppliers, the threat of substitute products or services,

and the rivalry existing among competitors. Challenges are high because the potential

partners, customers, and financial institutions do not have enough data and hesitate to

work with the company. The phase of growth is the period the company enters the

market, and, at this phase, the company may easily access capital. However, growth is

also considered as a period of stability. At that period, the company benefits and may

intend to invest in many sectors. The crisis phase is the period when the company faces

new challenges. The poor forecasting performance is due to the linear relationship

between the financial cycle and output fluctuations (Ng, 2011). The financial cycle boom

may end in crisis and weaken the company’s growth (Borio et al., 2018).

The life cycle theory of business is the foundation of economic progress that

allows businesses to mitigate risks through forecasting. Goodwin (1967) introduced the

growth cycle model based on Minorski’s (1962) classic predator-prey model for fish

population (Dessai et al., 2006). The growth cycle model was used to generate the growth

rate between capital and labor in the national revenue distribution (Sordi & Vercelli,

2014). The extension of the model in many directions has led to a framework that

combines growth and cycles that has been used by many researchers (Dessai et al., 2006).

The concept of growth is that investments have a determining effect on economic

dynamics and enfold two main directions (Sukharev & Voronchikhina, 2020). The

economic growth depends on the dynamic of the investments spending and investments

in the non-financial assets are crucial for future economic growth. Five channels of

financial development may influence economic growth (Levine, 2005; He et al., 2019).

Firstly, the improvement of investment formation and efficiency of capital distribution;

second, the level of enterprises management improved; third, the high-tech innovation

and the reduction of innovation risk create an excellent business environment for

enterprises; fourth, efficiently enhance investment savings; and lastly, promote trade in

goods and services.

The financial growth life cycle describes a business life cycle that passes through

three phases: the growth stage, maturity stage, and decline stage. The concept of a

financial cycle is the perceptions and attitudes of financial risk fluctuations observed over

time (Ng, 2011). It is self-reinforcing interactions between perceiving values and risk,

risk-taking, and financing constraints (Borio et al., 2018). Changes observed during

fluctuations are marked by swings in credit growth, asset prices, terms of access to

external funding, and other indicators of financial behavior (Borio et al., 2018; Ng, 2011).

The financial cycle is based on the forecast of public and private investors and the

behavior of the economy. A significant increase in financial investment, marked by an

economic boom or growth, can be ended with crises such as recessions (Borio et al.,

2018). Financial resources may affect non-financial aspects, mass spending, the behavior

of a whole economy, and even natural factors. Crises accompanied by recessions are the

characteristics of fallen asset prices, debts increase, and the reform of balance sheets,

which drag down growth. Overall, financial performance is measured through profit

behavior, earning behavior, dividend behavior, risk behavior, and cash flow behavior

(Dan Perbankan, 2021).

Through Goodwin’s growth cycle model, the financial growth model (FGC) for

SMEs was introduced in 1998 by Berger and Udell. The FGC is proper for every firm and

may be applied depending on internal factors (e.g., decision-making, policies,

organization, operations, etc.) and external factors (e.g., government business policies,

lenders, market orientation, etc.). A firm needs additional financing due to business

growth, financial performance, innovations, and to be competitive in the global market.

SMEs, including minority-owned small businesses, often only have access to funding

from family and friends, private equity, or debt markets where the interest rate is often

high. The information asymmetry problem (Butt et al., 2013; Sanchez-Vidal &

MartinUgedo, 2012) and the agency costs problem (Sanchez-Vidal & Martin-Ugedo,

2012) interact because the lender companies control the interest cost. As long as the

company grows, the leadership has the capacity to mitigate or alleviate information

asymmetry problems. The more the company grows (age and size), the manager controls

the financial cycle, becomes less risky, and gets confidence from external investors and

financial institutions. Sanchez-Vidal and Martin-Ugedo (2012) formulated five

hypotheses for testing the FGC essentially based on age and size. The study’s two

independent variables (age and size) are selected because they influence the information

asymmetry problem. Age and size may significantly contribute to the FGC.

A company, in the process of attaining a level of sustainability, develops growth

strategies for risks and overcomes uncertainties. Some researchers argued that resource

constraints, challenges, capabilities, structures, and strategies enable the company to grow

and reach sustainability (Huang et al., 2020). FGC is a cycle with consecutive positive

and negative changes in the business process (Paweta, 2018). It is considered a financial

cycle (Borio et al., 2018) encompassing the interactions between the value perceived and

risk, risk-taking, and financial constraints. An increase in the credit value implies an

increase in asset value, the price of assets. The financial constraints and risks prevent

small businesses from accessing loans and may provoke an economic crisis. The period

of random fluctuation, during which a company gathers financial information and

resources, develops networking through marketing, workshops, and exhibitions and is

followed by an expansion phase. Three stakeholder groups (business owners, workers,

and investors) are important to reduce the information asymmetry problem in the business

growth cycle (Atolia et al., 2018). The business owner (manager) elaborates the project

plan, mobilizes funds, and hires resources; the worker provides service for wages; and the

investor provides capital, equity, and liquidity assets against interest.

The capital debt and equity are vital for a company’s financial growth, especially

when intending to become a public company. As the company progresses, the capital

structure contributes to the benefits realization (Butt et al., 2013; Modigliani & Miller,

1958, 1963; Pandey, 2004; Shahar et al., 2015). The capital structure is a combination of

short-term and long-term financing with a mix of debt and equity capital that is

indispensable for a company to achieve its financial goals (Butt et al., 2013). Pecking

order theory and signaling theory are essential to understanding the relationship between

financing decisions and investments. Signaling theory and pecking order theory (Butt et

al., 2013; Huang et al., 2020; Pandey, 2004; Shahar et al., 2015) are vital in the capital

structure and FGC. According to the Pecking order theory (Myers & Majluf, 1984), a

company may finance a project with only its internal resources like reserves and benefits

(Ahmadimousaabad et al., 2013), and use less debt with high growth (Pandey, 2004).

Instead, the Signaling theory promotes the growth of a company during the recession risk

by contracting external debt (Butt et al., 2013). Huang et al. (2020) argued that at the

same time, pecking order and signaling theories are concerned with the relationship

between a firm’s cash flow and debt structure to growth; they individually contribute to

the company's growth at all levels of the company’s financial life cycle. Micro, small, and

medium enterprises, which are the pillars of economic growth, need support from

financial institutions and their stakeholders.

Micro, Small, and Medium Enterprises (MSMEs)

The development of the economy of any country often depends on micro, small,

and medium enterprises (MSMEs). MSMEs are the backbone of the world economy, and

their performance impacts social development and economic growth (Bashir et al., 2021;

Martins et al., 2022; Novikasari et al., 2021; Velasquez,2020). SMEs represent 95% of

firms, participate in between 60% to 70% of global employment, and contribute to the

largest new jobs share in the overall economy (Ridwan et al.,2020). More than 90% of

SMEs represent the total enterprises in a country, contribute up to 80% of employment in

the industry workforce, and about 40% to the national GDP (Albassami et al., 2019;

Bashir et al., 2021). SMEs are also the most dynamic ventures in the global economy and

play a vital role in developing the human welfare of any country (Naradda Gamage et al.,

2020). SMEs are critical for sustainable economic growth, and their integration in the

region considerably contributes to economic development. MSMEs/SMEs have been

regulated into many sectors of activity, such as industry, service, agriculture, restaurant,

and transport (Novikasari et al., 2021; SBA, 2020).

Small business refers to a privately owned corporation, partnership, or sole

proprietorship with 500 s or fewer employees, depending on the industry. Small

businesses generate an average annual income of 28.5 million U.S. dollars (Robb, 2018;

SBA, 2020; U.S. Census, 2020). The definition of SMEs varies by country and region.

This definition is based on each country's economic, cultural, and social habits, often on

the value of assets or the number of employees (Martins et al., 2022). The European

Commission (EC) considers SMEs as those companies with 250 employees or fewer and

that make no more than 50 million Euros and/or present an annual total balance sheet of

less than 43 million Euros (Bashir et al., 2021; Martins et al., 2022). The statistical data of

the Organization for Economic Cooperation and Development (OECD) explained that

99% of all businesses correspond to SMEs (Niewohner et al., 2019), contribute about

60% of employment, and make between 50 and 60% of GDP (Martins et al., 2022). The

contribution of SMEs is to alleviate poverty and sustain economic growth. SMEs are

involved in community development, specifically in rural economies. The importance of

small businesses in community development is to eradicate poverty, inequality, and

unemployment, support the local population to fulfill their basic needs, and help

marginalized groups (e.g., disabled, female heads of household, uneducated persons;

Naradda Gamge et al., 2020).

SMEs, which play an important role in the job creation, poverty and

unemployment reduction, and economic growth, have a very high failure rate. The failure

rate of SMEs is high in the short period from their inception because many of them face

challenges, including little or no investment, lack of knowledge of the market, lack of

formal planning and demand forecasting, lack of managerial and technical skills, and

limited access to economic resources (Caballero-Morales, 2021). The vulnerability of

SMEs is due to internal and external risks (Asgary et al., 2020; Caballero-Morales, 2021)

and is often beyond their capacity to control, influence, and manage. However, internal

risks can be controlled through risk management and treatment measures that managers

and business owners implement. This approach is not often set up in developing

countries. SMEs are vulnerable to external risks because these risks are beyond their

capacity to manage, control, or influence (Asgary et al., 2020).

The vulnerability of SMEs in developing and emerging countries is more

pronounced. Weak institutional support makes SMEs less prepared to manage the risks.

Also, they often do not have the expertise to manage risks and anticipate the risks

outbreak. Thus, to mitigate risks in emerging countries as well as developed countries, the

World Economic Forum (WEF) has created, assessed, and monitored 30 global risks

since 2005 (Asgary et al., 2020). According to the WEF, a global risk is an uncertain

event or condition that, if it occurs, may negatively impact SMEs for at least ten years.

SMEs represent more than 90% of all companies worldwide and are the backbone of the

world economy in formal and informal business sectors (Thorgren & Williams, 2020). In

Japan, over 99.8% of all companies are SMEs, which employ more than 70% of the

workforce and generate at least 50% of the GDP (Asgary et al., 2020). Ninety-eight

percent of all economic entities in Mexico are SMEs, and they contribute more than 50%

of the country’s GDP (Caballero-Morales, 2021).

In the global market, SMEs remain vital for global supply chain and international

transactions, contributing to global economic growth and alleviating poverty. The aim of

the International Labor Organization (ILO) is that SMEs contribute to creating productive

employment and decent work for all (ILO, 2022). SMEs are the key factor to a nation's

economic development and social well-being. Two in three jobs created in the world

come from SMEs, according to ILO. In developing countries, SMEs with less than 100

employees and from the private sector generate at least 50% of job creation, whereas in

developed economies, they contribute up to 55% to the GDP. Policymakers may focus

more on SMEs to enhance economic growth. The performance of SMEs is vital for

economic and social development, specifically in rural economies (Bashir et al., 2021).

Two factors are important for SMEs. The first factor is that SMEs stand to improve

antipoverty programs efficiently; second, SMEs' development is an ingredient for

innovation and sustainable growth. These factors are vital for SMEs’ performance and

sustainability and contribute to global economic growth.

Small businesses are the basis of economic growth in the U.S. Recently, the

Department of Treasury approved more than $4 billion for 332 small business lending

institutions, of which $ 3.9 billion went to community banks and $104 million to 51

CDLFs (Brock, 2018). According to the ILO, at least 62% of employment (Ridwan,

2020; Tambunan, 2018, 2019) created by SMEs are informal and often have difficult

working conditions (e.g., lack of social security, lower wages, poor occupational safety

and health conditions, and weaker industrial relations). Also, SMEs are flexible and have

the capacity to move from one product to another in an environment where the market

demand changes quickly; expansion is easy during economic growth (Tambunan, 2018,

2019). SMEs are social entrepreneurs working for community interests and processing

minimum profit distribution among their members (Ridwan et al., 2020). However, at the

same time, they can be used for any contract during an economic crisis, and their degree

of failure is very high.

One of the biggest challenges SMEs encounter in launching their operations is

accessing capital. Access to capital is a challenge, and the lack of adequate policies

beneficial for both lenders and borrowers prevents small startup businesses from

innovating, growing, and creating jobs (Robb & Niwot, 2018). Many researchers have

shared the factors specific to different countries that impede the growth and sustainability

of SMEs. In Bangladesh, scientists found that among SMEs, 50.53% have no access to

formal sources of finance, 13.68% have restricted access, and 35.79% have no restrictions

(Islam & Miajee, 2018). Although 59.6% of SMEs applied for working capital financing,

only half of them got loans from their banks. SMEs often have initial finance to startup,

but not sufficient for operations. Due to the lack of information from SMEs, traditional

banks' financial requirements can be extremely costly (Dong et al., 2019). The weak

growth of SMEs is due to the financial constraints, capital constraints, poor technologies,

and tight regulations faced by these businesses (Nkwabi & Mboya, 2019).

Many studies proved that the absence of the use of technologies and financial

resources prevents small businesses from innovating and, therefore, contributing to the

country’s economic growth. Information on SMEs’ financial health is opaque, so they do

not expose their financial statements to the public. Investing in innovation and technology

requires external finance from banks and financial institutions, the main source of

funding (Kijkasiwat & Phuensane, 2020). The fact that external investors do not have

enough data on SMEs, their level of credit trustworthiness is very low, and they have

difficulties accessing financial capital. Lenders hesitate to extend credit loans to small

businesses because they consider small business loaning an alluring and gainful endeavor

(Islam & Miajee, 2018). SMEs are viewed to be high-hazard borrowers due to their low

level of capitalization, deficient resources, and failure to conform to the lender’s security

requirements. Islam and Miajee (2018) identified seven reasons that make formal banks

to loan small businesses less probable:

x Lending small businesses is seen to be extremely hazardous. They are very

vulnerable, the rate of failure is very high, and the financial statements and

operation information are opaque, preventing lenders from being hesitant

(Kijkasiwat & Phuensane, 2020).

x Small business owners experience fear of gaining access to financial capital due

to the conditions of loaning and the high cost of processing before getting the

loan.

x Banks prefer loaning to large companies to protect their investment, and

shareholders often control these companies. The fact that large companies

have a long history with banks, they have an investment agreement that

facilitates the process of transactions. Also, shareholders influence banks’

policies and may restrict SMEs’ access to capital.

x The loan managerial expenses are very high, as is the interest rate, orienting

small businesses to other sources of financing.

x The absence of SMEs’ history (e.g., financial statements, records

bookkeeping) automatically excludes them from accessing financing. x

Borrowers do not have any means to guarantee the loan requested, even

though banks may be willing to support the project.

x Many small businesses are informal or do not register with legal institutions for

the benefit inherent to SMEs.

Overall, SMEs struggle due to many factors, with financing and access to credit being

among the most challenging, as reported by industry experts and researchers (Rao et al.,

2018). Policymakers, banks, financial institutions, and small business organizations must

come together to define rules and regulations that are beneficial for all and boost the

economy of nations.

The economic development of a country depends on its SMEs. SMEs play a vital

role in developed and developing countries and are the most dynamic in the present

global economy, contributing to human well-being (Naradda Gamge et al., 2020;

Albassami, 2019). Even though large companies influence SMEs, their collaboration is

significant in enhancing the global economy. Small businesses are the foundation for

large companies in many countries. They construct a local technological base, have the

capacity to use local resources such as raw materials, generate savings, encourage the

participation of vulnerable groups, and support local economies (Naradda Gamge et al.,

2020; Albassami, 2019). However, financial accessibility constraints negatively impact

SMEs’ performance. The financial constraints are a handicap to innovation and

technologies (Kijkasiwat & Phuensane, 2020). Large companies can use internal and

external finance from banks for innovation and technology and prevent risks. In contrast,

internal finance is the only source of investment for many SMEs. Due to financial

hardship, SMEs see their cash flow decline and are outperformed by larger companies.

U.S. SBA instituted many programs that contribute to enhancing small business activities

and the communities’ well-being. Recently SBA developed many programs to support

small businesses, including loan guaranty programs, small business development centers,

women development centers, Service Corps of retired executive, microloan Technical,

and others to enhance small business access to capital, and increase small business

opportunities in federal contracting, access to direct loans for businesses, and other

financial opportunities (Fairlie, 2021; CRS, 2021). Congressional interest in these

programs has increased for two reasons (SBA, 2021). The first is that small businesses

are the pillar of the U.S. economic growth and job creation. Second, since 2020, the

interest again increased to support small businesses negatively affected by the

coronavirus pandemic and, in turn, the nationwide economy. To respond to the crisis,

Congress passed on March 27th, 2020, the Coronavirus Aid, relief, and Economic

Security (CARES) Act, including $349 billion and later increased by $669 billion to fund

the PPP (CRS, 2021; Fairlie & Fossen, 2021; Humphries et al., 2020). This fund,

designed to support small business endeavors and provide economic relief, should be

reimbursed partially or forgiven once established conditions are met. The EIDL programs

(about 3.6 EIDL loans for $200 billion and about 5.8 million EIDL advances for $20

billion) were designed to support small businesses that were forced to close or lose their

activities due to the coronavirus (CRS, 2021; Fairlie & Fossen, 2021; Humphries et al.,

2020).

The event of high technologies and digitalization enable SMEs to enter the global

market and do business with any company. Globalization and rapid technological

improvements promoted international trade, which eased the SMEs to export products

and services (Safari & Saleh, 2019). The expansion of SMEs in the global market

significantly impacts job creation, innovation, and economic growth. Globalization and

technological improvements created opportunities and threats for SMEs in developed and

developing countries. SMEs have opportunities because they can enter the global market

and develop partnerships with any company. SMEs are completely integrated into their

community, and partnering with other businesses gives them a competitive advantage in

their products and services.

Entering the global market is a challenge for SMEs. Multinational corporations

(MNCs) and transnational corporations (TNCs) have occupied the global market,

impeding SMEs and threatening them with potential closures. The financial accessibility

constraints negatively impact SMEs’ performance. The financial constraints handicap

innovation and advancements in technologies (Kijkasiwat & Phuensane, 2020). Large

companies can use internal and external finance from banks for innovation and

technology advancement as well as to prevent risks. In contrast, for many SMEs, internal

finance is the only source of investment. Facing financial hardship, SMEs see their cash

flow decline and continue to be outperformed by larger companies.

With the rapid technological improvement, U.S. small business exporters have

easy access to the global market but face adversities. Recent changes to the global

economy (market and trade liberalization initiatives) and rapid improvement technologies

have contributed to SMEs’ growth through exporting products and services (Safari &

Saleh, 2019). To support SMEs that are specialized in exporting or importing products or

services and avoid the influence of foreign MNCs/TNCs, the SBA has created export

financing programs to ensure lenders with up to a 90% guarantee of export loans (SBA,

nd). In the same perspective, EXIM-Bank was created to support U.S. exporters of goods

and services and promote job creation and economic growth.

The fact that U.S. SMEs may have a cash flow shortage to fulfill an export order

and seek a capital working loan to finance, for instance, its purchase of materials or

supplies for the export order, the product of the good, or the collection of payment from

the foreign buyers, EXIM Bank put in place the working capital guarantee program which

guarantees up to 90% of the principal and interest on a loan made to participating lenders

for export-related inventory and accounts receivables (Akhtar, 2019; EXIM Bank, 2020).

Also, EXIM Bank has created the supply chain finance guarantee program to guarantee

up to 90% to approved lenders and exporters and increase liquidity for the fulfillment of

export orders. Each year, EXIM Bank extends more than 30% of its financing authority to

support small business exports, with a minimum of 5% to renewable energy, energy

efficiency, and energy storage technology exports (Akhtar,

2019; EXIM Bank, 2020). Despite SMEs' challenges to global market entry and rivalry,

the U.S. EXIM Bank strives to boost economic growth with small businesses' protection

abroad and promote job creation.

Going globally is a partnership and networking process based on each company's

specialization. Supply chain financial (SCF) is a key factor for small businesses to easily

operate in the global market and promote economic growth (Ali & Gongbing, 2018). The

SCF was introduced to reduce the working capital, cut transaction costs, and decrease

debt ratios through financial mechanisms (e.g., factoring, trade financing, and inventory

financing; Ali et al., 2018; Jia et al., 2020; Zhu et al., 2019). The SCF builds trust

between the buyer, supplier, and financial institutions. The fact that information is

asymmetric is a huge challenge for SMEs seeking to finance their business growth.

Financial institutions use SCF as a tool to fulfill financing requirements and accomplish

their growth in a timely manner (Ali et al., 2018). Supply chain finance is a critical tool

for SMEs’ growth because it contributes to the reduction of net operative capital,

increases profit, and strategic benefit (Zhu et al., 2019). In addition, SCF can mitigate

risks between supply and demand in the financial flow and create value-added for the

supply chain with capital constraints by integrating the financial institutions, SMEs, and

constraints capital firms’ members of the supply chain.

Supply chain finance promotes financial transactions based on confidence. The

importance of SCF for SMEs is that it contributes to minimizing debt costs, creating new

opportunities to obtain loans, and decreasing working capital, especially for weak supply

chain players (Ali et al., 2018). Information on the SCF, including transaction costs,

debts, management liabilities, and information on the market, politics, and technology

environment, contribute to reducing investment risks and capital costs of projects

financed within supply chains, enhance financial decisions, and optimize financing (Jia et

al., 2020) which are vital for SMEs financial performance and therefore the U.S.

economy. The SCF brings supply chain partners together to build trust commitment,

develop mutual benefit, and therefore benefit SMEs’ performance, which positively

impacts economic growth in the global market. SCF is an opportunity for policymakers,

experts, and business practitioners to lean on the researchers’ findings and implement

appropriate strategies that may contribute to SMEs’ financial performance, which,

therefore, positively affects the well-being of the community.

The growth of small businesses necessarily passes through the small business

owners' and managers' competencies and skills building. The government should promote

vocational training to empower small business owners or those willing to build businesses

in financial management and promote the best practices to access finance (Tambunan,

2018, 2019). Companies should comply with legal requirements specific to bookkeeping,

reporting gross income, and paying taxes to the government (Novikasari et al., 2021).

Knowledge, skills, and abilities are the three main areas that business owners, managers,

and personnel must possess to boost businesses and have access to any resources

(Sedyastuti et al., 2021). Thus, minority-owned small business enterprises involved in

local economic development to reduce poverty and inequality and protect vulnerable

persons are more concerned with getting skills, knowledge, competencies, etc., to

promote their companies.

Minority-Owned Small Business Enterprises (MBEs)

Minority small businesses, despite their statute second zone companies, contribute

to their community’s well-being and economic growth. Minority-owned small business

enterprises are the pillar of job creation and create jobs at a similar rate to newly created

non-minority businesses (Montout, 2019; Fairlie et al., 2010). Minority-owned small

businesses also play a vital role in community development and improve the population's

well-being in areas where poverty and unemployment are historically high (Berdejo,

2021). MBEs are composed of African Americans, Hispanics, women-owned small

businesses, veterans, and other ethnic groups. Over the last 10 years, among the two

million small businesses created, 50% were minority-owned and contributed to as many

as 4.7 million jobs created in the United States of America, according to the U.S.

Committee on Small Business and Entrepreneurs. Minorities are less represented in the

entrepreneurial marketplace. Even though they represent 38% of the U.S. population,

only 19% own small businesses (Berdejo, 2021). In the inner cities, this gap is more

pronounced, where 67% of the population are minorities, and 23% are minority-owned

businesses, according to census data (Berdejo, 2021).

The contribution of MBEs is significant to U.S. economic growth due to their

integration into community development and population welfare. Winston (2021)

estimated that by 2044, the United States would have a majority-minority population, and

minority workers and MBEs would have a significant impact on the GDP. According to

the data in 2017, MBEs with employees were 1.015 million and generated $1.401 trillion

in revenue with 8.923 million people employed (Winston, 2021). In 2018, approximately

18.5%, or one million U.S. employers, were minority business owners and most were

contributors to their communities’ job creation and wealth growth (Vilasquez, 2020). The

contribution of MBEs to GDP is 2.3% value-added or $500 million against 15.5% for

non-minority. By 2044, the minority population will constitute the majority of the

workforce. At that trend, the contribution of MBEs to GDP will be 5.5% value-added,

which is insufficient to catch up with the non-minority (Winston, 2021). To avoid

harming the United States’ human capital development and economic growth, researchers

recommended that policymakers, experts, business practitioners, and other stakeholders

consider the implications of the shifting marketplace.

Accessing capital and attracting opportunities remain a challenge for

minorityowned businesses due to the persistent disparities. A report from the Federal

Reserve in 2017 supported that the source of external credit to small businesses always

comes from banks. Carlisle (2019) argued that some small businesses lack expertise or

cannot support the costs related to the financing program; thus, lenders designed

intermediaries to assist low-income minority communities in accessing capital. The recent

works and federal officials underlined factors like the small size of business, low income,

weak credit histories, lack of loan information, or lack of clear title of agricultural land

prevent or dissuade minority farmers and ranchers, and women from accessing loans

(Clements, 2021). The disparities between minority-owned and non-minority-owned

firms regarding loan approval rates, credit lines, cash advances, etc., remain current.

Mayorga (2019) argued that the new securing funding rule that the administration

introduced made it hard for small businesses to access the capital for growth.

Any restrictive policy prevents minority-owned businesses from accessing credit

and contributes to their underperforming, preventing community members from taking

advantage of it and thus limiting local economic growth. Capital is vital for new and

existing businesses that need startup costs and growth financing. The research of Hwang

et al. (2019) found three vital sources of capital that small business owners may use for

startup and/or launch activities. The research studies showed that 64.4% of funds come

from personal/family savings, 16.5% are business loans from banks or financial

institutions, and 9.1% use personal credit cards.

The disparity between minority-owned businesses and non-minority-owned

businesses is current despite efforts made by governments and other organizations. The

difference in accessing financing across racial and ethnic groups has been noted by

researchers (Hwang et al., 2019). Barriers to accessing financing prevent many positive

trends and outcomes for minority entrepreneurs. Barriers often stop people in the process

of running their businesses. Barriers are one of the factors that slow business activities

and may contribute to failure. In the United States, many minority-owned small

businesses experience additional challenges from different barriers. At least 83% of

entrepreneurs do not access bank loans or venture capital at the time of startup, 65% rely

on personal and family savings for startup capital, and 10% carry balances on their

personal credit cards (Hwang et al., 2019). Some research shows that minority business

owners use their personal and family savings for startup capital (Robb & Niwot, 2018).

The data from the U.S. Census Bureau show that half of all Hispanic and half of all

African American households have less than $7,683 and $6,314, respectively, compared to

$110,500 for non-minority households. In 2021, the Federal Reserve System (FRS) data by race

and ethnicity indicated that 43% of Black adults and 40% of Hispanic adults had a family income

less than $25000, which is at least twice the rate among White and Asian adults (FRS, 2022). In

contrast, the family income of Whites and Asians was disproportionately over $100,000. The levels

of income of African American and Hispanic individuals and households are a challenge for saving

and often prevent minorities from investing directly in the business, using collateral to obtain a

business loan, and/or acquiring other businesses (Robb & Niwot, 2018). The fact that minorities

have the lowest income and do not have enough savings presents a challenge to running a business.

Although minorities are able to launch the business due to the barriers they face, the degree of

survival is very low.

Financial institutions and their shareholders contribute to the minority-owned

business’s success as well as their failure. Financial constraints are one of the factors

playing an important role in racial inequality (Kim et al., 2021). The problem of liquidity

negatively affects current consumption and reduces investment, mobility, and wealth

accumulation in the repetitive economic cycle. Universal employer data from the Census

Bureau shows that the racial financing gap is most pronounced at the startup and narrows

as the firm ages (Kim et al., 2021). Black-owned businesses are less likely to obtain bank

loans, more likely to refrain from applying because of expected denial, and more likely to

report that lack of finance reduces their profitability. Black and Hispanics are twice as

likely to start a business with less than $10,000 compared with White and Asian business

owners (Robb & Niwot, 2018). When minority business owners request a loan from a

bank, contrary to their White counterparts, Hispanic-owned businesses may not be

granted the full amount, while Black-owned businesses may see the requested amount cut

in half or the total amount rejected. Most of the time, Black-owned businesses refuse to

request business finance loans because they do not want to link their business profitability

to the bank rejection (Kim et al., 2021). Racial bias persists when it comes to financing

new businesses, influencing lenders' consideration toward minority-owned businesses'

success. Lenders charge minority business owners a high-interest rate on bank loans

compared to similar white business owners (Fairlie & Niwot, 2018; Hwang et al., 2019).

Although minority-owned businesses are marginalized, the population of this

ethnic group remains vital to the U.S. economic growth. With the growing minority

population in the U.S. (Robb & Niwot, 2018), Boston’s 200-year-old Eastern Bank

initiated an ambitious goal to fill the wealth gap and enhance economic inclusion

(Carlisle, 2019). In 2017, the bank, in partnership with Eastern Bank Charitable

Foundation, launched the Business Equity Initiative with a three-year commitment of $10

million to substantially reduce wealth inequality by bringing together minority-owned

businesses, supplier partnerships, and community development experts to address the

problem of income inequality in Massachusetts and southern New Hampshire. Federal,

state, and local governments have made direct investments, grants, and guarantees

through SBA loans, Small Business Innovation Grants, Small Business Transfer

Technology Program, regional venture capital funds, and other initiatives designed to

support SMEs (Hwang et al., 2019). In the same perspective, large-cap companies have

initiated programs to support Black-owned businesses with the intention to reduce the

racial wealth gap (Velasquez, 2020). The amount of funds that financial services pledged

was $1.15 billion which included $350 million in procurement spending on Black-owned

businesses. While the federal government is the largest procurer in the U.S., State

governments, municipalities, and public educational institutions contribute up to $1.5

trillion for procurements. In addition to these programs that the government reinforced,

the PPP was initiated for the resilience of small businesses due to the COVID-19

pandemic. The Coronavirus Aid, relief, and Economic Security (CARES) Act, included

$349 billion and later increased by $669 billion to fund the PPP (CRS, 2021; Fairlie &

Fossen, 2021; Humphries et al., 2020).

Many research studies underlined that in addition to financial discrimination,

minority-owned businesses are confronted by diverse types of discrimination, such as

loan application denial, discouraging borrowers, demanding a price premium, and

supplying lower quantities of credit. Discrimination is recurrent in the small business loan

lending marketplace (Fairlie et al., 2010; Montout, 2019). The racial differences in

financial hardships are due to racial differences in credit risk (Robb, 2020). Companies

specialized in determining credit scores are prohibited from using race, gender, and other

forms of discrimination as criteria for lending money (Montout, 2020; Robb & Robinson,

2018). Minority-owned businesses may face challenges to market access for the goods

and services they produce due to consumer discrimination by customers, other

companies, or redlining (Fairlie & Robb, 2010). The term redlining” was the way the

federal government and lenders would select or delimit a neighborhood with a red line

where they would not invest based on demographics alone (Burke et al., 2023). Redlining

is a discriminatory practice that prohibits a community based on racial and ethnicity

access to elementary services such as mortgage, insurance, loans, and other financial

services (Burke et al., 2023; Egede et al., 2023; Swape et al., 2022). About 38% of White-

owned businesses had not experienced financial hardship for 12 months, compared with

17% of Black-owned and 29% of Asian-owned and Hispanic-owned businesses. Over

decades, national and regional studies proved that limited capital, human and social

capital, and racial discrimination are the main sources of disparity in minority business

performance (Fairlie & Robb, 2010). Inequal access to financial capital remains the most

important factor that prevents minority-owned businesses from growing.

Minorities and women's businesses, which contribute to the families’ job creation

and promote the community’s development, always face discrimination challenges. Many

studies and reports support that minorities and women have been historically and

consistently disadvantaged by the effects of discrimination in business enterprises

(Wainwright, 2020). Although disparities between non-minority male-owned businesses

and minority-owned and women-owned businesses have been severe, the Disadvantaged

Business Enterprise Program has significantly reduced the gap. The Office of Minority

and Women Inclusion, established under the Dodd-Frank Wall Street Reform and

Consumer Protection Act section 342, which oversees Federal Deposit Insurance

Corporation’s (FDIC) Minority and the Women Outreach Program, strives to promote

minority- and women-owned businesses through the FDIC’s procurements for goods and

services (FDIC, 2022). The FDIC is an independent government corporation that

provides deposit insurance and performs bank supervision. The FDIC intends to maintain

stability and confidence within the bank system and protect against loss nationwide.

Nowadays, high-tech enterprises nourish the business world and promote economic

growth. However, compared to their counterparts, the representation of African

American-owned enterprises and innovation in the high-tech sector are quasi-inexistent

(London & Sheikh, 2020). Most of the White-owned Businesses or 68.5% created

businesses specialized in high-tech and innovation. African American-owned businesses

are underrepresented with 7.4% compared to the 14% overall private-sector African

Americans employment rate. According to London and Sheikh (2020), African Americans

only represent 2% of executives and 11% of technicians in the high-tech sector, which

highlights the lack of diversity in high-tech. High-tech innovation is a powerful tool in

today’s economic development. Winston (2021) estimated that by 2044, the United States

would have a majority-minority population, and minority workers and MBEs would have

a significant impact on the GDP. The exclusion of African Americanowned businesses has

a negative impact on this community, and therefore, the overall economic growth will be

negatively impacted.

In addition, MBEs challenge discrimination in the U.S. business development,

whatever their contribution to the U.S. economic growth. The performance of MBEs

depends on the measures that the shareholders of commercial banks undertake regarding

their orientations (Franquesa & Vera, 2021). The grant of credit to minority-owned small

business enterprises depends on the ethnicity/race of the owners, size, and the age of the

business. Nguyen and Pacheco (2021) supported that confidentiality in loan credit

agreements is vital for affiliated-bank mutual funds while investing in the firms that

borrow with the affiliated banks. The confidentiality strictness is a factor that impairs the

financial covenants, which may affect minority-owned businesses. The request for

proposal or request for quote procedures and policies are restrictive, preventing

minorityowned small businesses from being competitive because of limited access to the

funding source to satisfy the financial requirement (Offei et al., 2019).

Recent business development and economic growth changes challenge SMEs to

implement new proactive strategies to access finance. Environmental, social, and

governance are the measures SMEs need to introduce in the strategic planning for getting

finance and short and long-term sustainability (Păun (Zamfiroiu) et al., 2021). In addition,

Velasquez (2020) argued that minority small business owners, especially blackowned

businesses, the local employers contributing to their community's job creation, face

institutional discrimination and social inequalities, losing approximately a billion dollars

of revenue every year. The three persistent challenges, such as inadequate access to

capital, lack of mentorship, and non-proportionate business opportunities, prevent

minority business owners from prospering.

In the wake of COVID-19, minority-owned small businesses have experimented

with new ways to work with their employees safely, offer better income, and propose new

community services. Among 1,000 small businesses nationwide, more than 40% of

minority-owned-small businesses created new services to support their communities,

compared to 27% of businesses overall (Dua et al., 2020). During COVID-19, business

knowledge information is shared among small business owners and ethnic groups that

support their communities (Crick et al., 2021). The COVID-19 pandemic drastically

changed people's lifestyles (e.g., live, learn, work, and socialize) and small businesses

where socioeconomic and ethno-racial inequality were crucial (Ong et al., 2020). The

disruption of businesses which led to the closure of stores, factories, and businesses of all

sectors due to the COVID-19 pandemic, has disproportionately hit small businesses.

Among the businesses that COVID-19 negatively impacted, African Americans owned

41%, and 32% were Latinx compared to 17% whites owned (Atkins et al., 2022; Berdejo,

2021; Fairlie & Fossen, 2022; Fairlie, 2020; Ong et al., 2020; Velasquez, 2020).

The COVID-19 pandemic provoked a sudden disruption in economic behavior,

specifically with SMEs. The first quarter of 2020 started with the massive closing of

stores and other businesses, which negatively affected the U.S. economy and the

worldwide economy (Fairlie, 2020; Fairlie & Fozen, 2021). The mandatory closing due to

the COVID-19 outbreak plummeted the number of U.S. business owners from 15.0

million in February 2020 to 11.7 million in April 2020. The COVID-19 pandemic has

created unfavorable economic, social, and financial conditions similar to the crisis of

2000 (Kottika et al., 2020). In the first quarter of 2020, the U.S. GDP was reduced by

4.8% while the GDP of the Eurozone was reduced by 3.8%. In addition to the structural

challenge that minority-owned businesses face (Dua et al., 2020), COVID-19 negatively

impacted 41% African American-owned U.S. small businesses and 32% Latinx compared

to 17% White-owned (Atkins et al., 2022; Berdejo, 2021; Fairlie & Fossen, 2022; Fairlie,

2020; Ong et al., 2020; Velasquez, 2020). The COVID-19 pandemic outbreak challenges

small business leaders and researchers to develop appropriate strategies to prevent similar

events.

The coronavirus pandemic outbreak caused U.S. federal and state governments to

make drastic decisions to protect the population and businesses. The federal government

established the CARES Act, which offered support to businesses, including the PPP and

the EIDL program (Fairlie & Fossen, 2022) to support SMEs that were victims of the

COVID-19 pandemic. Priority was given to underserved markets and minority-owned

businesses. However, minority-owned small businesses face structural challenges due to

their economic fragility (Dua et al., 2020). While the federal government offered $349

billion through the PPP to address the COVID-19 crisis, many minority-owned small

businesses did not receive support because most were not members of the SBA (Hangen

& Swack, 2020). Forty-one percent of Black-owned small businesses did not benefit from

the PPP funds, and 21% did not get feedback from lenders (Atkins et al., 2022). It has

been noted that the first round of the PPP was not beneficial to Black-owned businesses

(e.g., the loan amounts that Black-owned businesses received were approximately 50%

lower compared to similar White-owned businesses). Overall, the smallest businesses

were unaware of the PPP and less likely to apply. In addition, those who applied later for

a loan saw the process take longer and somewhat did not get approved (Humphries et al.,

2020).

Summary and Transition

In this section, I presented the proposed study's background, problem, purpose,

and significance. The problem was that some business leaders did not know the

differences in the disbursed/shipped approved funding amount based on the

minorityowned status and size of the business. The research question that guides this

study is: Is there a difference in the disbursed/shipped approved funding amount based on

the minority-owned status and size of the business? I highlighted the target population,

the contribution to business practice, and the positive social change implications. Next, I

identified the FGC as the study’s theoretical framework and provided the key tenants of

the FGC. To assist readers’ comprehension of the study’s research and findings, I

provided operationalized definitions to elucidate the minority-owned businesses. Finally,

this section concludes with a summary of prior literature and highlights current gaps in

the research that this study intends to fill.

Section 2: Project Design and Process

Within this study, I examined the differences in the disbursed/shipped approved

funding amount based on the minority-owned status and size of the business. I utilized ex

post facto data collected from the Working Capital Transactions Authorization dataset

from 01/01/2006 to 09/01/2021, administrated by the Export-Import Bank of the United

States (EXIM Bank, 2020). Section 2 of this study includes a discussion of the study

method and design along with a description of how I collected and analyzed that data

within this study.

Method and Design

The purpose of this quantitative non-experimental causal-comparative study

utilizing ex post facto data was to examine the differences in the disbursed/shipped

approved funding amount based on the minority-owned status and size of the business.

Research Question (RQ): Is there a significant difference in the disbursed/shipped

approved funding amount based on the minority-owned status and size of the business?

Based on the research questions, the hypotheses are:

Null Hypothesis (Ho1): There is no difference in the disbursed/shipped approved

funding amount based on the minority-owned status of the business.

Alternative Hypothesis (HA1): There is a difference in the disbursed/shipped

approved funding amount based on the minority-owned status of the business

Null Hypothesis (Ho2): There is no difference in the disbursed/shipped approved

funding amount based on the size of the business.

Alternative Hypothesis (HA2): There is a difference in the disbursed/shipped

approved funding amount based on the size of the business.

Null Hypothesis (Ho3): There is no difference in the disbursed/shipped approved

funding amount among minority-owned businesses and non-minority-owned businesses

based on the size of the business.

Alternative Hypothesis (HA3): There is a difference in the disbursed/shipped

approved funding amount among minority-owned businesses and non-minority-owned

businesses based on the size of the business.

Research Method

In a quantitative study, a researcher uses quantitative methods to quantify and

analyze variables to get probate results (Apuke, 2017). A quantitative researcher

investigates the pertinent data to find the relationship between variables and provide

further recommendations. My research topic was an examination of the differences in the

funding of minority-owned businesses (small and large) compared to non-minority

businesses. The quantitative methodology was suitable for this study.

Research Design

The non-experimental design should be used since the groups examined are

neither randomly assigned nor should the independent variables be actively manipulated

within the proposed study. I analyzed secondary data to explain the interaction effect

between the independent and dependent variables. Using ex post facto data enabled me as

the researcher to identify the independent and dependent variables clearly and to what

extent these independent variables explain the dependent variable. My study focused on

ex post facto data with two existing independent variables (minority-owned businesses

and non-minority-owned) and a dependent variable (disbursed/shipped approved funding

amount). This study enabled me to examine the interaction effect of these two

independent variables on the dependent variable (Bougie & Sekaran, 2019).

Assumptions

Assumptions are notions or beliefs the researcher believes accurately guide the

study (Tocaven Gonsalez & Kastereen, 2021). The researcher conducts the study with the

operating assumptions. This study assumes that small businesses seek to acquire loans

from lenders (e.g., financial institutions). Another assumption is that the constructs that

fall under the secondary data (e.g., the Working Capital Transactions Authorization

dataset from 01/01/2006 to 09/01/2021) used for the study are valid and reliable sources.

Limitations

Limitations for any study are the potential weaknesses that the researcher cannot

control but are inherent to the research design, statistical model, and funding constraints

(Theofanidis & Fountouki, 2018). I used the data from the existing dataset; thus, the

variables available for examination are restricted to what is initially collected. Within the

authorizations dataset on the Import-Export Bank of the United States, the minority flag

was predetermined, preventing us from operationalizing minorities within the proposed

study.

Delimitations

Delimitations are the boundaries or limit the researcher sets within the study's

objectives (Theofanidis & Fountouki, 2018). With this study, I examined the differences

in the funding of minority-owned businesses (small and large) compared to non-minority

companies. My study was focused on small companies based in the United States from

2017 to 2022.

Data Collection

The Export-Import Bank of the United States approved the Working Capital

Transactions Authorization dataset from 01/01/2006 to 09/01/92022 (EXIM Bank, 2020).

The data were drawn from businesses and lenders across the United States. I used

Walden Library, ProQuest, ScienceDirect, Emerald, Sage, and Singer for my research.

Google Scholar and Google Search engine to find the Working Capital Transactions

Authorization data set from 01/01/2006 to 09/01/92021 (EXIM Bank, 2020). The data set

described the capital transactions that small and minority-owned businesses received for

exports and imports. The independent variables were minority-owned business status and

size of business. The dependent variable was the disbursed/shipped approved funding

amount. The scale of the measurement for the independent variable (minority-owned

business status) was nominal (minority = 1 and non-minority = 0), and the measurement

for the independent variable (business size) was nominal (small = 1 and not small = 0).

The measurement scale for the dependent variable was the ratio (disbursed/shipped

approved funding amount).

Data Analysis

Within this non-experimental causal-comparative study, I conducted a two-way

ANOVA. This enabled me to identify the main effect differences for each independent

variable on the dependent variable and the interaction of the independent variables within

the two-way ANOVA. Within this study, I examined the difference in the

disbursed/shipped approved funding amount based on the minority-owned status of the

business and the difference in the disbursed/shipped approved funding amount based on

the size of the business. Lastly, I examined the difference in the disbursed/shipped

approved funding amount among minority-owned and non-minority-owned businesses

based on the size of the business.

Ethics

Ethical research is the fundamental ethical principle that researchers must follow in

the process of dealing with participants (e.g., physical, institutional, and others). When

conducting research with human subjects, the U.S. government and institutions set up

regulations and ethical guidelines focusing on the participant’s rights and welfare

(Fernandez Lynch, 2020). In the context of this research, Walden University mandated

institutional review board (IRB) guidelines that I complied with to meet the university’s

ethical standards. Four steps were imperative to be completed: the researcher must

complete Form A, enabling IRB to provide tailored guidelines, submit the required

documents that meet the university’s ethical standards for approval, gain approval for the

proposal in accordance with the required documents, and finally I as the researcher

received a confirmation via email. I complied with the university’s ethical standards

before conducting my research.

This proposed research study used a quantitative research methodology using ex

post facto data the Working Capital Transactions Authorization dataset from 01/01/2006

to 09/01/2022. I explained my research work to all participants, including how I planned

to collect the data and protect the documentation, ensuring their privacy. The data will be

destroyed after 5 years in accordance with the university’s policy. I signed an agreement

with participants to ensure the research was conducted within the code of conduct.

According to Sim and Waterfield (2019), the consent has four components: disclosure, the

researcher gets adequate information needed; comprehensive, all participants properly

understand the information that the researcher collected; competence, the participants

have the capacity to accept or refuse the agreement; and voluntarily, any participant is not

under pressure to give his consent. The application of ethical principles was crucial to

protect and preserve participants’ dignity, rights, and personal identification information

during the designing, conducting, and reporting of research (Matandika et al., 2022).

The term “ethics” is a set of normative rules that define the behavior and actions

of a group living in an organization based on the norms and conducts (Pappa & Filos,

2019; Pappa et al., 2022). A code of ethics is a set of rules, principles, and practices that

all actors voluntarily adhere to for the performance of an organization. The code of ethics

requires continually implementing the best practices through training and communication

of an organization's ethics guidelines and policies (Pappa et al., 2022). The relationship

between methods and ethics is noticeable in the quantitative method because researchers

often claim that the quantitative methods are value-neutral or objective (Zyphur &

Pierids, 2019). An ethical climate is imperative for improving organizational performance

(Sabiu et al., 2019). The ethical climate defines policies, practices, and procedures on

ethical matters, which influences the participants’ attitudes and behavior toward the

performance of an organization (Ahmad et al., 2018). The decision-making and conduct

of people are based on the trust between the researcher and participants and what is

considered as wrong or right.

Transition and Summary

In Section 2, in addition to the purpose statement and the research

question/hypothesis I presented briefly, I explained the importance of the study’s research

method and design. After enumerating the assumptions, limitations, and delimitations, I

described how I collected and analyzed data and ended with a discussion of ethical

research. In Section 3, I work on deliverables. The contents of deliverables consists of an

executive summary, a presentation of quantitative data analysis, which includes graphs

and figures, results and conclusions of the analysis, recommendations for action,

communication plan, social change impact, and skills and competencies,

Section 3 The Deliverable

In this section, I provide an executive summary of the quantitative data analysis

results, including conclusions, recommendations for actions, a communication plan, and a

description of the impact of social change. I organized this section as follows: (a)

executive summary, (b) presentation of quantitative data analysis, (c) descriptive and

inferential results and conclusions of the analysis, (d) recommendations for action, (e)

communication plan, (f) social impact, and (g) skills and competencies.

Executive Summary

The purpose of this quantitative non-experimental causal-comparative study

utilizing ex post facto data is to examine the differences in the disbursed/shipped

approved funding amount based on the minority-owned business status and size of the

business. The data set used within this study is the Working Capital Transactions

Authorized data set, administered by the Export-Import Bank of the United States (EXIM

Bank, 2020) and drawn from businesses and lenders across the United States. The target

population examined within this study was small enterprises legally established in the

United States for more than 5 years and small business loan banks. A two-way ANOVA

analysis was used to determine if there was a statistically significant difference between

the disbursed/shipped approved funding amount for the two independent variables: size

of the business and minority-owned business status.

Purpose of the Project

Utilizing a quantitative methodology, I examined the differences in the funding of

minority-owned businesses (small and large) compared to non-minority businesses. A

non-experimental causal-comparative design was used since the groups examined were

neither randomly assigned nor were the independent variables actively manipulated

within the study. My study focused on ex post facto data with two independent variables:

minority-owned business status and size of business, and a dependent variable:

disbursed/shipped approved funding amount. My study was to examine the interaction

effect of the two non-numeric independent variables on the single numeric dependent

variable (Bougie & Sekaran, 2019).

The social change implications associated with this research are the potential

contribution of highlighting the iniquities in the disbursed/shipped approved funding

amount between minority and non-minority businesses, thereby reducing the inequalities

between minority and small businesses. Within this study, I present the study’s findings,

including the descriptive results, the tests for assumptions, and the results addressing the

research question. This section also includes a discussion of the applications for

professional practice and social change implications. Finally, this section ends with

recommendations for action and further research, a reflection based on this study, and a

conclusion of the study.

Overview of Findings

Within this study, I examined whether there was a significant difference in the

disbursed/shipped approved funding amount based on the minority-owned status and size

of the business. I used Statistical Package for Social Science (SPSS) statistical software to

conduct a two-way ANOVA for data analysis. I ued SPSS to examine the descriptive and

inferential results and provided my analysis and conclusions. The results of the findings

indicated that there was a statistically significant interaction between minorityowned

status and the size of the business on the disbursed/shipped approved funding amount F

(1, 48014) = 36.49, p < .001, Partial η2= .001. Thus, the null hypothesis (Ho3), that There

is no difference in the disbursed/sipped approved funding amount among minority-owned

and non-minority-owned businesses based on the business size, was rejected. Given that a

significant interaction was found, I analyzed the simple main effects of minority-owned

status and the size of the business. There was a statistically significant difference in

disbursed/shipped approved funding amount between small and non-small businesses

based on minority business status, F (1, 48014) = 95.932, p < .001,

Partial η2 = .001.

Recommendations

Within this quantitative ex-post facto study, I analyzed the difference in the

disbursed/shipped approved funding amount based on the minority-owned status and size

of the business. The independent variables were minority-owned business status and

small business size with two categorical value levels, respectively. The dependent

variable was the ranked disbursed/shipped approved amount. The findings of this study

might contribute to positive social change by highlighting iniquities between minority and

non-minority businesses, thereby reducing the inequalities between minority and small

businesses in the disbursed/shipped approved loan amount. Also, the results of the

findings could challenge lenders and decision-makers to create greater equity in funding

minority businesses. Results might enhance business strategies and financial performance

and improve nationwide economic growth.

Presentation of the Findings

In this section, I share the research study’s findings aligned with the research

question. I briefly discuss the techniques of data collection and data analysis. Then, I

present descriptive and inferential statistical results, discuss the tests of the assumptions,

and conclude with a concise summary. Descriptive statistics depict the sample using

central tendency (mean, median, and mode), range and standard deviation, and graphics

(Guetterman, 2019; Sullivan-Bolyai & Bova, 2014). Descriptive statistics are used to

describe in a few words the basic features of the data in a study, such as the mean and

standard deviation (SD) (Mishra et al., 2019), and provide a first view of the data

(MacFarland, 2011). Inferential statistics enable a researcher to analyze the data collected,

test hypotheses, answer research questions (Sullivan-Bolyai & Bova, 2014), and draw

conclusions from a sample to a population (Guetterman, 2019; Mishra et al., 2019). The

two-way ANOVA is the appropriate method used to examine whether the independent

variables have an interaction effect on the dependent variable. The SPSS is the software

that I used to conduct a two-way ANOVA to examine the difference in the fractional

ranked data of disbursed/shipped loan amount based on the minority-owned status of the

business and the difference in the fractional ranked data of disbursed/shipped loan

amount based on the size of the business. The two-way conducted utilizing SPSS enabled

me to test the data in accordance with the research question and hypotheses. The test of

between-subjects showed that there was a statistically significant interaction between

minority-owned status and the size of business on disbursed/shipped approved funding

amount, F (1, 48014) = 36.49, p < .001, Partial η2 = .001. The null hypothesis was

rejected because the interaction effect between variables was statistically significant

(p < .05).

Data Collection

The data set used in this research study, the Export-Import Bank of the United

States, Approved Working Capital Transactions Authorization dataset from 01/01/2006 to

12/31/2022, includes minority-owned small businesses in the United States of America

(EXIM Bank, 2020). I used Google Scholar and Google Search to find the Approved

Working Capital Transactions Authorization dataset drawn from businesses and lenders

across the United States. The Approved Working Capital Transactions Authorization

dataset described the capital transactions that small and minority-owned businesses

received for exports and imports. The independent variables used within this study were

minority-owned business status and size of business. The dependent variable was the

disbursed/shipped loan amount. The scale of the measurement for the independent

variable minority-owned business status is nominal (minority = 1 and non-minority = 0),

and the measurement for the independent variable the business size is nominal (small = 1

and not small = 0). The measurement scale for the dependent variable, the

disbursed/shipped approved funding amount, is a ratio. The dependent variable was

operationalized as a percentage of fractional ranked disbursed/shipped loan amount data.

The percentage of fractional ranked data of disbursed/shipped loan amount was created

using a transformation of the disbursed/shipped approved funding amount variable to

address the outliers within the data. I used Transform, the Rank Case, and Rank Types

(Fractional Rank as Percentage) within the analyses I conducted in SPSS to create the

percentage of fractional ranked data of disbursed/shipped loan amount for analysis.

Data Analysis

Within this non-experimental causal-comparative study, I conducted descriptive

statistics to depict the sample and inferential statistics, specifically a two-way ANOVA, to

examine the interaction between minority-owned status and the size of the business on

the disbursed/shipped approved funding amount. Descriptive statistics depicting the

sample's central tendency (i.e., mean and median), range, and standard deviation are

presented. The study’s analysis also included tests of the assumptions associated with the

two-way ANOVA. The application of the two-way ANOVA is necessary for the

interaction effects and to test the significance of the interaction term. A two-way ANOVA,

also known as a two-way factor, was used to determine whether there is a simultaneous

effect of at least two nominal independent variables (Assaad et al., 2015). A two-way

ANOVA was used to understand whether there was any interaction between the

independent and dependent variables (Mishra et al., 2019). The two-way ANOVA enabled

me to identify the effect differences for each independent variable on the dependent

variable and the interaction effect of the independent variables on the dependent variable.

Within this study, I examined the difference in the fractional ranked data of

disbursed/shipped loan amount based on the minority-owned status of the business and

the difference in the fractional ranked data of disbursed/shipped loan amount based on the

size of the business. Lastly, I examined the difference in the fractional ranked data of

disbursed/shipped loan amounts among minority-owned and non-minority-owned

businesses based on the size of the business.

Descriptive Statistics

I retrieved the data set from the U.S. EXIM Bank website. The data set described

the capital transactions that small and minority-owned businesses received for exports

and imports. I identified two independent variables: small business size, which was

categorized into two groups (small = 1 and non-small = 0), and minority-owned business,

which was split into two categories (minority = 1 and non-minority = 0). The

measurement scale for the dependent variable disbursed/shipped approved funding

amount is ratio. The dependent variable was a percentage of fractional ranked

disbursed/shipped loan amount data. I used Transform, Rank Case, and Rank Types

(Fractional Rank as Percentage) to calculate the percentage of fractionally ranked

disbursed/shipped approved funding amounts utilizing SPSS statistical software.

The data included 48,018 businesses within the Approved Working Capital

Transactions Authorization data set. The mean funding amount for small businesses was

$2,346,909 with a standard deviation (SD) = $27,100,000, while the mean for non-small

businesses was $4,304,617 with an SD = $33,300,000. Given the presence of outliers and

the large standard deviations, I transformed the dependent variable (disbursed/shipped

approved funding amount) to the percentage of fractional ranked data of

disbursed/shipped loan amount. I then calculated the descriptive statistics for the

percentage of fractional ranked data of disbursed/shipped approved funding amounts. The

mean percentage of fractional ranked data of disbursed/shipped loan amount for

nonminority-owned small businesses was M = 49.53 (SD = 27.59), while the mean for

minority-owned small businesses was M = 44.97 (SD = 27.49). The mean percentage of

fractional ranked data of disbursed/shipped approved funding amount for non-small

businesses was M = 56.45 (SD = 32.69). The mean percentage of fractional ranked data

of disbursed/shipped loan amount for minority-owned businesses was M = 63.00 (SD =

28.71) compared to non-minority was M = 56.21 (SD= 32.80). Minority-owned small

businesses had the smallest percentage (27.49) of fractional ranked data of

disbursed/shipped approved funding amount. No missing data were noticed. Table 1

depicts the descriptive statistics for the independent and dependent variables included in

the study.

Table 1

Means and Standard Deviations for Fractional Rank Percent of Disbursed Shipped

Amount

Small

Non-minority

49.5318

27.58647

34815

Minority

44.9744

27.48759

5994

Total

48.8624

27.61879

40809

Total

Non-minority

50.6451

28.62926

41776

Small business flag

Minority owned flag

Mean

Std. deviation

Non-small

Non-minority

56.2131

32.79896

6961

Minority

62.9964

28.71475

248

Total

56.4465

32.68856

7209

Minority

45.6904

27.75914

6242

Total

50.0010

28.56601

48018

Note: Dependent variable: Fractional Rank Percent of Disbursed Shipped Amount

Test of Assumptions

Assumptions testing is crucial for data analysis in any statistical model. When

tests of the assumptions are met for the test statistics (e.g., F, t), it indicates that the

results, including p-values and descriptive and inferential statistics (e.g., effect size,

confidence intervals, correlation coefficients), are accurate (Hu & Plonsky, 2021). The

analysis of variance F test is commonly used to test the null hypothesis to determine the

effect of the independent variable on the dependent variable (Sheng, 2008). Thus,

assumptions need to be met so that the F test may produce a valid statistical result. The

testable assumptions for the two-way ANOVA are no significant outliers, the dependent

variable (residuals) should be approximately normally distributed, and the homogeneity

of variance (i.e., the variance of your dependent variable [residuals] should be equal)

(Laerd Statistics, 2024). I conducted a two-way ANOVA to test the main and interaction

effects of the two independent variables (categorical) on the continuous dependent

variable (Bougie & Sekaran, 2019; Green & Salkind, 2019).

Outliers

An examination of the assumption of no significant outliers was generated from

an exploration of the descriptive statistics. The independent variables included in this

study were both dichotomous. The first independent variable, minority-owned business

status, is nominal (minority = 1 and non-minority = 0), and the second independent

variable, small business size, is also nominal (small = 1 and non-small = 0). Utilizing

SPSS Statistics software, I split the data files to explore the descriptive statistics and

evaluate outliers within the dependent variable, the percentage of fractional ranked data

of disbursed/shipped loan amount. The two-way ANOVA is concerned with the

investigation of the simultaneous effects of two nominal variables, which might take

different categorical values known as levels (Assaad et al., 2015). The manipulated test of

boxplots proved that there were no outliers as assessed by inspection of the boxplots. The

examination of the boxplots (see Figure 1) displaying the interaction between

independent variables small business size and minority-owned small business status on

the dependent variable ranked data of disbursed/shipped loan amount showed the normal

distribution of disbursed/shipped approved amount. Thus, the results proved no outliers,

as assessed by inspection of a boxplot.

Figure 1

Outliers of Small Businesses and Minority-Owned Small Businesses

Normality

The assumption of normality is a test of the residuals rather than the raw data.

Therefore, an investigation of the residuals, Res_1, is required to determine if each cell of

the design is normally distributed (Laerd Statistics, 2024). The two-way ANOVA assumes

that the data/residuals of each cell are normally distributed. Thus, I conducted the

Kolmogorov-Smirnov normality test as a test of normality. The Kolmogorov-Smirnov

normality test was run to test each group's combination of the two independent variables

(Minority-Owned small business status and small business size). The p-value of the

Kolmogorov-Smirnov normality test was less than 0.001 (p < .001). The assumption of

normality has been violated, indicating that the Residual (Res_1) and dependent variable

(percentage of fractional ranked data of disbursed/shipped loan amount) have not been

normally distributed for each group combination of the two independent variables. Thus,

248

<.001

34815

.000

the data were not normally distributed as assessed by the Kolmogorov-Smirnov normality

test (p < .001). Table 2 depicts the assumption of normality for the variables within the

study.

Table 2

Assumption of Normality Test

Small Kolmogorov-Smirnova business flag Minority owned flag Statistic df

Sig.

Non-small Non-minority Residual for PDisburs .190 6961 .000

Minority Residual for PDisburs .134

Small Non-minority Residual for PDisburs .166

Minority Residual for PDisburs .201 5994 .000

Note: “a”; Lilliefors significance correction

The data set used in this study is large, and ANOVAs can be fairly robust to

deviations from normality, although no specific research has been conducted into a

twoway ANOVA. Given that two-way ANOVA could be robust to the violation of

normality, it may allow the researcher to make inferences without needing the assumption

of normality (Laerd Statistics, 2024). Also, at this time, SPSS statistics does not offer a

robust test for the two-way ANOVA.

The histogram enabled me to understand the way the data were distributed and

provided a visual inspection of the assumption of normality. The histogram examined the

displayed curve of the dependent variable ranked disbursed/shipped approved amount

(see Figure 2). The assumption of normality on the dependent variable ranked

disbursed/shipped approved amount was statistically significant. Thus, I failed to reject

the null hypothesis. A visual inspection of the histogram displaying the fractional ranked

percentage of the disbursed/shipped approved amount indicated that the assumption of

normality was violated (see Figure 2).

Figure 2

Histogram of Fractional Rank Percent of Distributed Shipped Amount

Another method of assessing the normality of the residuals of the dependent

variable, the percentage of fractional ranked data of disbursed/shipped loan amount, was

through examining a Q-Q plot. The normal Q-Q plots were used to assess the assumption

of normality graphically. Based on an inspection of the residuals presented in the Q-Q

plots in Figure 3, the groups considered are all skewed in a similar manner; thus, the

violation of normality is not considered a serious violation of this assumption (Laerd

Statistics, 2024). It should be noted that if the distributions are all skewed in a similar

manner, this is not as troublesome when compared to the situation where you have groups

that have differently shaped distributions (e.g., each combination of groups has different

skews) (Laerd Statistics, 2024).

Figure 3

Normal Q-Q Plots of Residual for Percentage of Disbursed Shipped Amount

Expected

Normal

Expected

Normal

Q-Q

Plot

Residual

for

PDisburs

Small

Business

Size=

Non-Small,Minority

Owned

Status=

Minority

-50 -25 0

25 50

Observed

Value

Normal

Q-Q

Plot

Residual

for

PDisburs

Small

Business

Size=

Small,Minority

Owned

Status=

Non-Minority

-50

-25

25 50

Observed

Value

Homogeneity

The assumption of homogeneity of variance was tested with Levene’s test of

equality of variance. The importance of testing for the assumption of homogeneity was to

raise questions concerning the degree of precision (Forbes & Ingebo, 1975). The test of

homogeneity of variance was vital to verify the assumption of the homogeneity of

variance (i.e., variance of your dependent variable [residuals] should be equal) before

running the two-way ANOVA (Manshur & Husni, 2020). The null hypothesis for the

assumption of equal variance of the dependent variable (the ranked disbursed/shipped

approved amount) was equal across groups of the independent variables (i.e.,

minorityowned business status and small business size). The assumption of homogeneity

of variances was violated, as assessed by Levene’s test for equality of variances, p < .001.

Thus, I rejected the null hypothesis. Table 3 depicts the results of Levene’s Test of equality

of error variance.

Table 3

Levene’s Test of Equality of Error Variance

Levene

statistic

df1

df2

Sig.

Fractional rank percent of

disbursed/shipped

amount

Based on mean

Based on median

and with adjusted df

304.771

298.579

48014

47637.54

<.001

Based on trimmed

mean

304.325

48014

<.001

Inferential Results

A two–way ANOVA was conducted at p = .05 and 95% confidence interval to

evaluate whether there was a statistically significant difference in the ranked

disbursed/shipped approved amount based on the minority-owned status and size of the

small business. The independent variables were minority-owned business status and small

business size with two categorical value levels respectively. The dependent variable was

the ranked disbursed/shipped approved amount. The research question was: Is there a

significant difference in the disbursed/shipped approved funding amount based on the

minority-owned status and size of the business? The study’s hypotheses were:

Null Hypothesis (Ho1): There is no difference in the disbursed/shipped approved

funding amount based on the minority-owned status of the business.

Alternative Hypothesis (HA1): There is a difference in the disbursed/shipped

approved funding amount based on the minority-owned status of the business

Null Hypothesis (Ho2): There is no difference in the disbursed/shipped approved

funding amount based on the size of the business.

Alternative Hypothesis (HA2): There is a difference in the disbursed/shipped

approved funding amount based on the size of the business.

Null Hypothesis (Ho3): There is no difference in the disbursed/shipped approved

funding amount among minority-owned businesses and non-minority-owned businesses

based on the size of the business.

Alternative Hypothesis (HA3): There is a difference in the disbursed/shipped

approved funding amount among minority-owned businesses and non-minority-owned

businesses based on the size of the business.

The results of the two-way ANOVA conducted to examine the effects of minority-

owned business status and size of business on the distributed/shipped approved funding

amount allowed for an examination of the study’s three null hypotheses. The main effect

of minority-owned small business status on the distributed/shipped approved funding

amount was not statistically significant with F(1, 48014) = 1.41, p = .236; thus, I failed to

reject the null hypothesis (Ho1. The main effect of small business size was statistically

significant with F(1, 48014) = 173.14, p < .001; thus, the null hypothesis (Ho2) was

rejected. These tests were based on the linearity-independent pairwise comparisons

among the estimated marginal means. The results of the interaction between minority-

owned business status and size of the business on the distributed/shipped approved

funding amount were statistically significant with F (1, 48014) = 36.49, p <

.001, partial η2 = .001. Thus, I concluded that the null hypothesis (Ho3) was rejected.

Table 4 and profile plots (see Figure 4) show that the assessment of the interaction

between independent variables on the dependent was statistically significant.

Table 4

Tests of Between–Subjects Effects: Dependent Variable Fractional Rank Percent of

Disbursed/Shipped Amount

Source

Type III Sum of

Squares

Mean Square

Sig.

Partial

Eta

Squared

Corrected Model

469623.112a

156541.037

194.151

<.001

.012

Intercept

10448295.455

12958.5

.000

.213

SmallBusinessFlag

139599.412

173.139

<.001

.004

MinorityOwnedFlag

1133.375

1.406

.236

.000

SmallBusinessFlag *

MinorityOwnedFlag

29421.083

36.490

<.001

.001

Error

38713059.011 48014

806.287

Total

159232682.17 48018

Corrected Total

39182682.124 48017

a. R Squared = .012 (Adjusted R Squared = .012)

Figure 4

Profile Plots

Analysis Summary

A two-way ANOVA was conducted to examine the effects of minority-owned

business status and small business size on the disbursed/shipped approved funding

amount. The assumptions of the two-way ANOVA were tested by residual analysis. The

assumption of no outliers was assessed by inspection of boxplots; the normality

assumption was assessed using Kolmogorov-Smirnov’s normality test for each cell of the

design and the homogeneity of variance assumption was assessed by Levene’s test. There

were no outliers; however, residuals were not normally distributed (p < .05) and there was

a violation of the homogeneity of the variances (p = .001). While the two-way ANOVA is

robust to the violation of normality of the residuals, the unequal variances may impact the

accuracy of the study’s findings; thus, the findings should be interpreted with caution.

There was a statistically significant interaction between minority-owned business

status and small business size on the disbursed/shipped approved funding amount, F (1,

48014) = 36.49, p < .001, partial η2 =.001. An analysis of the simple main effects for

small business size was performed with statistical significance receiving a Bonferroni

adjustment p < .001. There was a statistically significant difference in the mean of

disbursed/shipped approved funding amount between minority small businesses and

nonsmall businesses for minority–owned businesses, F (1, 48014) = 95.93, p < .001,

partial η2 = .002, and for non-minority-owned businesses F (1, 48014) = 321.17, p <

.001, partial η2 = .007. There also was a statistically significant difference in mean

disbursed/shipped approved funding amount scores between minority-owned businesses

and non-minority-owned businesses for small businesses, F (1, 48014) = 131.729, p <

.001, partial η2 = .003 and for non-small, F (1, 48014) = 13.666, p < .001, partial η2 =

.000.

All pairwise comparisons were conducted to examine each simple main effect

with reported 95% confidence intervals (CI) and p-values Bonferroni-adjusted within

each simple main effect. The mean “disbursed/shipped approved funding amount” for

minority and non-minority small businesses were 44.97 ± 27.49 and 49.53 ± 27.59,

respectively. Non-minority small businesses had a statistically significantly higher mean

“disbursed/shipped approved funding amount” than minority small businesses, 4.56 (95%

CI, 3.78 to 5.34), p <.001. Minority non-small businesses had a statistically significantly

higher mean disbursed/shipped approved funding amount than non-minority non-small

businesses 6.78 (95% CI, 3.19 to 10.38), p <.001.

The mean disbursed/shipped approved funding amount for minority and

nonminority non-small businesses were 63.00 ± 28.71 and 56.21 ± 32.80, respectively.

Nonsmall non-minority businesses had a statistically significantly higher mean

disbursed/shipped approved funding amount than small non-minority Businesses 6.68

(95% CI, 5.95 to 7.41), p <.001. Non-small minority businesses had a statistically

significantly higher mean disbursed/shipped approved funding amount than small

minority businesses, 18.02 (95% CI, 14.42 to 21.63), p <.001.

Recommendation for Action

This research study's results, conclusions, and recommendations might be

beneficial to financial institutions and small businesses. Small business refers to a

privately owned corporation, partnership, and sole proprietorship, having 500 employees

or fewer depending on the industry, and generating an average annual income of 28.5

million U.S. dollars (Robb, 2018; SBA, 2020). Small businesses are the basis of

economic growth in the United States. Recently, the Department of Treasury approved

more than $4 billion for 332 small business lending institutions in which $3.9 billion

went to community banks and $104 million to 51 CDLFs (Brock, 2018). While small

businesses have received funding from the federal government, minority-owned

businesses disproportionately received less funding than their non-minority counterparts

(Robb & Niwot, 2018)

Access to the distributed/shipped approved loan amount might be disproportionate

due to factors not considered by financial and small businesses. The proposed study was

vital for business practice, given that an investigation of whether funds were distributed

equitably between minority and non-minority-owned businesses might illuminate

potential disparities. The study’s findings have the potential to inform stakeholders within

the government and business. Examining the proportionality of the disbursed/shipped

approved funding amount provides evidence that can inform future decisions regarding

the distribution of funding. Thus, the study’s findings had the potential to reduce possible

disparities and, as a result, improve the business performance of minority-owned

businesses and the nationwide economy.

Recommendations for Further Research

This study was a quantitative ex post facto study and could not be conducted

without some limitations. Limitations for any study are the potential weaknesses that the

researcher cannot control but are inherent to the research design, statistical model, and

funding constraints (Theofanidis & Fountouki, 2018). In the secondary data analysis,

researchers are limited to the available data or cannot conduct follow-up surveys with

participants (Johnston, 2014; Kumara, 2022). In my research, I faced limitations

associated with secondary analysis specific to unbalanced data. The original dependent

variable, disbursed/shipped approved funding amount, failed the assumption of normality

for the two-way ANOVA. Although I used the transform procedure within SPSS to create

the percentage of fractional ranked data of disbursed/shipped approved funding amount

and Residual (Res-1), the assumption of normality was still violated.

In addition to limitations associated with the data, I faced other limitations during

the data analysis and examination of the findings. In the process of the dataset

manipulation, it was necessary for me to categorize the data into dichotomized variables

(i.e., small businesses versus non-small businesses and minority-owned businesses versus

non-minority-owned businesses). To deepen the analysis of the study topic future research

could categorize these data further. The primary researchers conducted the initial data

collection; thus, as the secondary researcher, I did not have full knowledge of the primary

data collection process (Johnston, 2014). Additional research should be conducted to

document further any disproportionality in the disbursed/shipped approved funding

amount. That may address businesses and other institutions concerned and boost

economic growth in general.

Communication Plan

Once the results of this study’s findings are published in ProQuest, the first step is

to share my research results with my peers, community, and Walden University social

media, which I am part of. Next, I will publish the study’s findings on Facebook,

LinkedIn, and other relevant social media. As an expert and consultant, I will organize

webinars to share results with small business owners, banks, and other stakeholders and

provide advice on the importance of the study’s results as assets for them to improve their

turnover and growth and, therefore, impact their communities. I will participate in

conferences, seminars, and workshops concerned with small business development.

Implications for Social Change

The results of the study’s findings underlined that the minority-owned small

businesses only represented 6,242 among the 48,014 businesses within the dataset

examined, with a mean of M = 45.69 (SD = 27.76) that had access to the

disbursed/shipped approved funding amount. Minority-owned small businesses play a

vital role in community development and improve the population's well-being in areas

where poverty and unemployment are historically high (Berdejo, 2021). It is estimated

that by 2044, the U.S. will have a majority-minority population, and minority workers

and MBEs will significantly impact the GDP (Winston, 2021). This study’s findings may

be used to challenge leaders in business and financial sectors to be aware of how funding

resources are distributed. Lender resources are essential for businesses to improve their

profitability. Also, additional funding resources have the potential to enhance job

creation, innovation, and overall economic growth. SMEs represent 95% of firms,

between 60% and 70% of global employment, and contribute to the largest new jobs

share in the economies (Observer, 2000). Positive social change implications for this

study enhanced the promotion of minority-owned small businesses. Furthermore, SMEs

contributed to the eradication of poverty and the improvement in the living standards of

vulnerable groups through the increase in income and self-employment (Narada Gamage

et al., 2020).

Skills and Competencies

Prior to starting this research study, I was facing many challenges, as a startup

business owner. With my work experience with many organizations and institutions, my

first challenge was to build my business database and professional networking. My first

idea was to approach small business agencies, especially the Veteran Business Outreach

Center, for assistance, seminars, and workshops. Next, I went to get financing from banks

and financial institutions for my business building and operations. Most of them refused

due to the lack of business history. Those who agreed to finance my business proposed a

credit line with high-interest rates. The last challenge was that I am Black and an

immigrant in the United States. I had to work hard to finance my business. Furthermore, I

observed that in my community, many small businesses had minority or immigrant

owners.

Small businesses, specifically minority-owned small businesses, although they are

the foundation of economic growth in the United States, often experience the highest rate

of failure. Growth is a challenge for SMEs due to the lack of financing and credit, as

reported by industry experts and researchers (Rao et al., 2019). The COVID-19 pandemic

disproportionately impacted small business owners: 41% among Back/African American

owners and, 34% for Latinx owners compared to 17% for White owners (Belitski et al.,

2022; Fairlie & Fossen, 2022). Despite governmental efforts (local or nationwide) to

promote small businesses, the discrimination against minority-owned small businesses

remains current. Minority-owned small business enterprises, which are often involved in

their local economic development to reduce poverty, and inequality and protect

vulnerable persons, are in need of support to strengthen their skills, knowledge, and

competencies to promote their companies and communities.

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