Fidow Abdikadir Noor, Effect of COVID-19 on Loan Repayment of Small Businesses in Kenya: A Case Study of Eastleigh Business Community (2020)

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Article by Abdikadir Noor Fidow of United States International University in Nairobi, in the European Journal of Business and Strategic Management, Vol.5, Issue 2 (2020), on how COVID-19 affected loan repayment by small businesses in the Eastleigh business community. The study randomly sampled 50 businesses, focusing on owners who used borrowed funds to start and run their businesses, and analyzed the data with descriptive statistics, regression and correlation. It found a statistically significant negative relationship between the pandemic outbreak and small businesses' ability to repay loans, with r(-.54) and a p value of 0.008. Citing the Central Bank of Kenya, the paper says small businesses make up 98% of all businesses in Kenya and create 30% of jobs annually.

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“Fidow Abdikadir Noor, Effect of COVID-19 on Loan Repayment of Small Businesses in Kenya: A Case Study of Eastleigh Business Community (2020).” Original at web.archive.org. Archived at Pandemic Darlings, https://pandemicdarlings.com/source-documents/fidow-abdikadir-noor-effect-of-covid-19-on-loan-repayment-of-small-bus-4edd4c5a22/, SHA-256 1aad503cb410629dc7f40eb2af69c625f10caad8404ef4da3f02cc3f8cc685bf.

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EFFECT OF COVID-19 ON LOAN REPAYMENT OF SMALL
BUSINESSES IN KENYA: A CASE STUDY OF EASTLEIGH
BUSINESS COMMUNITY

Fidow, Abdikadir Noor
European Journal of Business and Strategic Management
ISSN 2518-265X (Online)
Vol.5, Issue 2, No.1. pp 1 - 14, 2020
www.iprjb.org

EFFECT OF COVID-19 ON LOAN REPAYMENT OF SMALL
BUSINESSES IN KENYA: A CASE STUDY OF EASTLEIGH
BUSINESS COMMUNITY
1*
Fidow, Abdikadir Noor
United States International University (USIU)
afiidow@yahoo.co.uk, P.O. Box 16450-00610, Nairobi, Kenya
Abstract

Purpose: The aim of this research is to investigate empirically the effect of pandemic
outbreaks on loan repayment of small enterprises in Eastleigh business community, with
particular focus for those who used borrowed fund in starting and operating their businesses.
Design/methodology/approach: The target population of the study was the business
community of Eastliegh, and samples of 50 businesses were randomly selected from the
population. descriptive statistics were used to analyze the mean, mode, median, and the
variance of the collected data. Regression and correlation were used to analyze the strength and
the direction between the relationships of the different variable.
Findings: The research results indicated statistically significant negative relationship between
pandemic outbreak and loan repayment ability of small businesses in Easteigh, r(-.54), with p
value of 0.008.
Unique contribution to theory, practice, and policy: Pandemic outbreak affects business
performance and survival in different ways. Small business owners, regulators, lenders, and the
general public may benefit from this research by considering the impact of disruptions on small
businesses. The study is one of the first to respond to the effect pandemic outbreak on small
businesses after covid-19 pandemic eruption. Conducting this study was indispensable because
of the importance of small businesses for the economy of any country and the current situation
of covid-19 pandemic impact on them, specifically those who borrowed the fund they had
invested.
Key words: Pandemic Outbreak, Small Businesses, Loan Repayment.

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Vol.5, Issue 2, No.1. pp 1 - 14, 2020
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1. 0 INTRODUCTION
Pandemic is a kind of epidemic that spreads across a wider geographical area than epidemic
and affects significant number of the population (Qiu, Rutherford, Mao, & Chu, 2017). Since
the beginning of this century, there have been a number of pandemic outbreaks like Spanish
flue of 1918, flue pandemic of 1957, H1N1 2009, and COVID-19 of 2019/2020 (Sohrabi, et al.,
2020). Since the 16th century, pandemics have occurred regularly every 30 to 40 years. The
Spanish flue killed more than 50 million worldwide, because there were no cure for influenza
and other complications like pneumonia, while antibiotics were not invented. The fact that
there was no centrally enforced lockdowns to curb the spread of the infections complicated the
matter.
Covid-19 is severe acute respiratory syndrome that has the capability to transmit between the
animals and humans (Gorbalenya, 2020). The government has taken actions to enforce closure
of bars, restaurants, down-to-dusk curfew, and ‘social distancing’ in order to contain or slow
the spread of the coronavirus pandemic. Most, if not all, small businesses don’t have the
resources to survive this kind of curfew and quarantine without the government assistance.
According to recent survey by Central Bank of Kenya (2018), small businesses (firms that
employ between one to 200 employees) constitute 98% of all business population in Kenya,
create 30% of jobs annually, and contribute 80% of the income for low and middle class
citizens in Kenya (Maengwe, & Otuya, 2016). As the government contemplates broader and
stronger measures to comprehend and contain the spread of the COVID-19 pandemic, the
economists and financiers are warning that the ever-important sector of small businesses will
collapse in large numbers. Yet, the government so far has neither issued any significant help
for the businesses to survive under unending quarantine and curfew, nor passed any laws
suspending or lessening the burden of maturing debt obligations. In few months, the
Coronavirus epidemic has changed the ways almost all businesses operate in unprecedented
approach. The outbreak has delivered an indiscriminate blow to all businesses from large
Airlines to small shops, and has been forced a change of how they work amid a series of
closures ordered by the government to contain the tide of the virus.
The economic stagnation and the casualty of three million-plus small businesses in the country
will not only obliterate those jobs created by the bars, shops, restaurants, and service providers,
but also will destroy the down stream jobs that depend on them. Many small businesses in
Eastliegh (the largest market in sub Saharan Africa) started reporting that the process of mass
layoffs, and closing businesses is ongoing. When I sampled ten restaurants in Eastliegh, they
told me that they are operating half capacity and sent 50% of their employees on unpaid leave.
The SME performance index 2019, further indicated that only half of small businesses survive
longer than three years, and one of the key challenges is liquidity. Business start-ups have
truncated revenue due to lack of market share, loyal customers, and known brand. But the
overhead cost like rent and payroll are fixed, which leave very little liquid cash to owners.
Although many ward and county representatives suggest more businesses will begin to close
very soon under the weight of the government dogmas, the experts are reluctant to predict the
precise number that the curfew and quarantine may cause their closure. Currently, the long
distance transport is 80% down in revenue; bars, restaurants, and hospitality industry, 85%,
while manufacturers are down to 50% due to different business disruptions (Kagwaini,et. al,

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2020). Based on this trend, 40% of small businesses will close within the next 25 days of
curfew and quarantine, and 70% of them will close permanently within two months.
Currently, some business owners have already begun closing, while others are reaching out
their personal pockets and burning their savings in order to survive. If the government doesn’t
take major steps to rescue small businesses, the economy should expect a wave of permanent
closures and loss of jobs, thus causing insecurity and economic downturn. Visualize a bar or
restaurant with overhead of rent, matured debt, salaries and wages, to pay, yet the government
reduced its operation time by half without any support. The business will live day by day for
some time before closing down completely.
According to Wheat, and Farrell (2017) research, 50% of small businesses have enough cash
on hand to survive only 27 days, and if there is no cash flow income within that period, the
business will close shop. The bars, restaurants, and hospitality industry are particularly
vulnerable because they have to maintain high overhead costs like rent, fixtures, debt, taxes,
service contracts, payrolls, and many more that add up to a budget, which is very tough to
accumulate during difficulty periods. When the government indefinitely shuts down a business,
which has liquid cash to survive only 27 days, there is little chance that it will reopen again.
Large and multinational companies have resources and reserves to cover those expenses during
crises because they can take advantage from economies of scale to outperform smaller
competitors, and earn resources to survive in a recession periods, due to the fact that they have
access to superior lending options both from local and outside of the country. This will enable
them access to easier and cheaper cash to pay bills during quarantine and curfew times.
This paper examines small businesses in Eastleigh and empirically tests hypothesis that
business disruptions like cash flow shortages, supply flow interruptions, high cost of supplies,
missing sales targets, and short operating periods have no significant effect on loan payments
of small businesses in Eastleigh. Because of small businesses concentration in Eastleigh, the
study will generate a result that can be generalized to Nairobi, Kenya, and to the whole world.
Apart from being a home for many small businesses, Eastleigh is segregated from other party
of the city due to COVID-19, which created a situation where thousands of small business
cannot get enough customers, stock supply, and cash flow to enable them pay their outstanding
loans.
The rest of the paper will proceed as follows: section two will present theoretical framework by
reviewing previous research. Section 3 will present methodology and sampling, section four
will deal with results of the study, and section five will discuss the finding of the research,
concluding, and recommendations.
Statement of the Problem
There is no doubt that most countries in the world depend on their small businesses in driving
their economies forward (Love, & Roper, 2015). According to recent survey by Central Bank
of Kenya (2018), small businesses constitute 91% of all business population in Kenya, create
30% of jobs annually, and contribute 80% of the income for low and middle class citizens in
Kenya (Maengwe, & Otuya, 2016). A survey conducted by Kenya Bureau of Statistics (2017)
divulged that 400,000 small businesses in Kenya did not celebrate their second anniversary in
the last five years (Douglas, Douglas, Muturi, & Ochieng, 2017). Although different factors
contribute these failures, pandemic outbreak is a major one due to the fact that it disrupts
supplies, increases the cost of availing inputs, reduces purchasing power of the customers,
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reduces cash flow, reduces human capital, and affects every aspect that contributes the
profitability of the business.
However, pandemic outbreak of this magnitude that caused the closure of many businesses in
different sectors of the country never happened in Kenya. Compounding the problem, 82% of
small businesses borrowed the fund that they started with their businesses (Mwangi, & Muturi,
2016). On the other hand, Central Bank of Kenya (CBK) removed capping of interest rate and
gave lenders free hand to charge as they wish, while the pandemic disrupted all profit
generating aspects. Citing a study conducted in April by (Aluga, 2020), CBK Governor Patrick
Njoroge said that small businesses surveyed, 75% indicated that without help such as credit
buffers and other resources to cushion against the slowdown caused by the Coronavirus, they
would close by the end of June. The pandemic disruptions of business operations has caused
the acceleration of business failures, thus causing unemployment, insecurity, and loss of
government revenue in terms of income and excise duties.
Although few studies have been done about covid-19 effects on different business sectors like
Kimani, et.al (2020), and (Ogenga, & Baraza, 2020), this study is the first to focus how covid-
19 affected loan repayment of small businesses in Eastleigh, Kenya, which is the biggest
market for small businesses in East and Central Africa. Since majority of businesses are
repaying a very expensive loans, the study will focus how covid-19 disruptions affected the
repayment of these loans. Using the result of this study, the government will be able to
establish policies safeguarding the wellbeing of small businesses and avoid the consequences
of their collapse to the economy, labor market, security, and the society in general. The lenders
would be able to understand objectively the root cause of their dwindling revenue from small
businesses during pandemic outbreaks, and come up with counter productive measures against
the disruptors of their clients. Finally, since this market is a hub for different business sectors
and sizes, the outcome of this study could be generalized to the rest of Kenyan small
businesses.
Objective of the Study
The objective of this study is to establish the effect of Covid-19 disruptions on loan repayment
of small businesses in Kenya. To examine the effect of supply disruption, supply cost, reduced
cash flow, reduced operating period, and missed sales target on loan repayment of small
businesses in Kenya.

2.0 LITERATURE REVIEW
Bartik, et.al (2020) researched “The impact of COVID-19 on small business outcomes and
expectations in USA.” They surveyed 5800 small businesses to explore the disruptions caused
by COVID-19 on the operations of their businesses. They found that, few weeks into the crises,
mass layoffs of the 48% Americans employed in small businesses sector had already struck.
The result showed that the risk of closures was negatively correlated with the expected length
of the pandemic. At the time of the survey, the study found that the median businesses with
more than $10000 monthly expenses had enough cash to survive only two weeks, while small
businesses were more fragile and had cash to survive only one week. The study also found that
more than 70% of the businesses planned to seek funding from Coronavirus Aid, Relief, and
Economic Security (CARES), though many anticipated problems in accessing the funds.

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Antonescu (2020) investigated a topic titled “Supporting small and medium size enterprises
through the COVID-19 crisis in Romania.” They indicated that small and medium businesses
in Romania were one of the hardest hit by COVID-19 pandemic globally and the government
must take urgent measures to keep the sector afloat. The study found that four out of every ten
companies are in the red zone of collapsing, with more expenditure than income from the
operations of their businesses. There were also mass layoffs of 850,000 employees, (one-fifth
of private sector employees in Romania) during first three months of the pandemic outbreak.
He recommended Supplementing financial programs for SMEs, national Program for
supporting industrial parks, and creation of support centers at regional level.
Turner, and Akinremi (2020) Studied the impact of COVID-19 on Chinese small and medium
firms. China was the epicenter of the pandemic and the effect was severe due to the
unpreparedness of the government. The study used data from 2000 small businesses across the
country and in February 2020 they found that 30% of respondents reported cash shortage due
to the pandemic outbreak and would not be able to sustain their businesses more than three
months, while another 30% reported that they will not be able to sustain their businesses more
than six months. Additionally, 30% reported that their income had dropped by more than 50%.
Although many employees were working from home, 75% of the businesses reported that they
are no longer working at full capacity. About 70% of the businesses also stated that their
supply was disrupted and trying to fix it. Finally, the study found that each ten day period of
the pandemic, Chinese economy reduces quarterly GDP growth by 0.39 to 0.46 percent.
Lakuma, Sunday, Sserunjogi, Kahunde, and Munyambonera (2020) studied how COVID-19
impacted small and medium enterprises in Uganda. Although Uganda adopted serous measures
of containment to curb the spread of the pandemic like closing schools, restricting the
movement of people in and out of the country, and social distancing, the virus took its toll
among the population and affected businesses of different sectors. The study showed that three-
quarters of businesses surveyed laid-off employees in the last three months due to reduced
business activities caused by COVID-19. Agriculture businesses have experienced the largest
constraints in accessing markets due to transport restrictions, quarantine, and sanctions of
weekly markets. More than 51% of the respondents indicated that if the current restriction
persists, they would close their businesses within three months, while 34% indicated that they
would be able to survive up to six months. About 35% of the respondents also stated that the
pandemic affected their loan repayment ability.
Wanjala (2020) investigate “The Economic Impact Assessment of the Novel Coronavirus on
Tourism and Trade in Kenya.” Citing central bank survey report of 2019 before the outbreak of
the pandemic, about 51% of Kenyans are living hand to mouth. This statistics stressed that
huge percentage of the society risk hunger incase of lockdown, restriction of movement, or
taking containment measures that can cause unemployment. The study found that tourism and
hospitality industry were the most hit hard by the -19 pandemic. The surveyed businesses from
this industry stated that they laid off 47% of employees, and 61% of them indicated they would
not be able to survive beyond three months if the current situation does not change. The study
concluded that the leaders and policy makers in Kenya have to learn from the countries that
contained the pandemic and prioritize health matters from other development programs. The
literature signposted lack of proper research about the effect of COVID-19 on loan repayment
in Kenya.

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2.1 Theoretical framework
Austrian Business Cycle Theory (ABCT) is a subset of Financial Crises Theories. The theory
originated from Austrian school of economics in 1930 by Friedrich Hayek and Gunner Myrdal
(Cachanosky, & Lewin, 2016). The theory states that business cycles are the consequences of
excessive growth of bank credits due to low interest rate set by the central bank of the state.
The advocates of the theory believe that low interest rate stimulates borrowing by businesses,
which lead an increase of capital spending funded by the bank credits. Availability of
inexpensive funds enables the entrepreneurs to invest in capital goods rather than basic
consumer goods such as clothing and food. But Credit Frictions and Market Freezes
proponents state that the problem in the financial sector is exogenous, because the quality of
loans is in equilibrium by the behavior of the borrowers and the banks. The moral hazards of
the borrowers, which can lead friction in the flow of credit in the economy, affect the amount
of credit available for borrowers and the return for the lenders. Chan, Kuo, Lin, and Lin (2020)
stated that trustworthiness is very important because, when entrepreneur borrows money in
order to finance a project, he/she can take activities that can reduce the value of the project by
increasing his/her own benefits. To avoid this, the lender needs to make sure that the
entrepreneur has enough incentives to improve the quality of the project and enable the
repayment of the loan.
The empirical researches about the theory were inconclusive, with different schools of thought
arriving at different conclusions. Friedman (1969) found the theory inconsistent with the
empirical evidence, and 25 years later, he reanalyzed the theory using newer data and
confirmed the previous findings. But Keeler (2001), an Austrian economist argued that the
theory is consistent with empirical evidence. Ismans, and Mougeot (2009) arrived at the same
conclusion with Keeler in 2009. According to Gorbatenko (2017), pandemic outbreaks will
inevitably wreak havoc on small businesses, people, communities, and countries that are not
strong enough to withstand the shock, and every country must set aside resources to contain the
outbreak and shield small businesses from these shocks to safe guard the economy as well as
employment. There is a vivid justification why the theory of Austrian Business Cycle Theory
(ABCT) is relevant to this study as it provides crucial information on unanticipated crises as
well as pandemic outbreaks.
2.2 Empirical Review
Rebmann, Wang, Swick, Reddick, and delRosario (2013) researched business continuity and
pandemic preparedness in USA. They administered restructured questionnaire to human
resources professionals during May-July 2011. Linear regression was used to analyze factors
associated with business continuity and pandemic preparedness scores. The determinants used
for business continuity were (1) type of business (2) business size (3) risk perception (4) having
human resources professionals. The study used Fisher Exact Test and chi-square to compare
health care vs non-health care businesses on preparedness indicators. They found that the
preparedness of health care businesses ranged from 0.5 to 27, while non-health care businesses
ranged from 0 to 15, with average of score of 13.2 and 7.3 respectively.
Fernandes (2020) researched the Economic effects of coronavirus outbreak (COVID-19) on the
world economy. The sample contained 30 countries under different scenarios. Although at the
date of this report, the extent of the lockdown as well as the recovery period is unknown, the
report indicated the GDP growth would take a hit ranging between 3-6% depending the

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specific country. The study found a median decline of -2.8% in the GDP of the sampled
countries with 2.5-3% further additional decline in each month of this crises and
countermeasures. The report projected a GDP fall of up to 15% in some countries with severe
outbreak and economic lockdown. Service oriented economies and those who depend foreign
trade will be extremely affected by these crises with more job losses. The study concluded that
the sampled countries are underestimating this pandemic due to over-reliance on historical data
of previous outbreaks and the economic consequences.
Ivanov (2020) studied predicting the impacts of epidemic outbreaks on global supply chains.
He used simulation-based methodology with logistic simulation and optimization software to
examine and predict the impact of epidemic outbreaks on the supply chain functioning. The
study found that the timing of opening and closing the business has more impact on supply
chain performance than the upstream disruptions. The study also found other factors that
impede supply chain as lead-time, speed of pandemic spread, and the duration of the
disruptions.
Sinagl (2020) studied Cash-flow Risk and Industry Response to COVID-19 Outbreak. The
objective of the study was how US industries react to long-term cash-flow risk caused by
covid-19 disruptions. Since different industries may react differently to cash flow risk, the
researcher used March 25, 2020 as the cut-off date for the analysis of cash-flow risk during
covid-19 crises. The study found that the industries which deal goods with low demand
elasticity to price shocks is associated with low cash-flow risk. This means that the industries,
which produce assets with less substitutes or produces necessities rather than luxuries, are more
insulated in cash-flow shocks than their peers who produce goods with elastic demand. Firms
in oil, steel works, and construction were found to have the highest systematic risk levels,
mostly caused by reduced cash flow. There is negative relationship between the industry cash
flow and the duration of the pandemic outbreak.
Lederman, Kurnia, and Lederman (2009) studied designing supply chain systems to cope with
catastrophes. The objective of the study was whether the processes used currently in supply
chain management are equipped with supply continuity in times of crises. The study used two
stages. The first stage was to identify strategies of supply chain used in the industry, and the
second stage was concerned exploring how different technologies and approaches could reduce
supply disruptions. Lee and Billing model of minimizing stock outs was used to analyze the
data. The study found that the usage of IT by food dealers reduced the problem of maintaining
supplies during crises. The cost of supply increases with the increase of the pandemic duration,
due to the fact the demand will exceed the supply.
Ntsomboh-Ntsefong, Shariati, Khan, and Karapetkovska-Hristova (2017) researched the
Incidence of avian flu shocks on poor household livelihoods of poultry farmers in Africa. They
said that many businesses developed continuity plan for the potential disruptions that the
pandemic may cause. The study applied System Dynamics Framework to evaluate the
mechanisms that amplify risks and the proposed solution. The study found that pandemic
outbreaks disrupt supplies, customers and their purchasing power, cash flow, and the expected
profits of the business. Lenders also increase interest rate due to risk increase in the economic
environment. The study concluded 5-point recommendations in order to survive pandemic
outbreaks, which are: review business continuity strategy, communicate with your employees,
contact local hospitals, and prepare physical workspace.

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3.0 RESEARCH METHODOLOGY
3.1 Research Design
In this study, Causal Design was applied, and the data will be collected using structured
questionnaire from a sample of 50 small business owners. The study used; supply flow, cash
flow, sales, cost of supply, and operation period as the independent variable, while ‘loan
repayment’ is the dependent variable. The data is collected within Eastleigh business
community in Nairobi Kenya in the period April-May2020. These respondents are suitable
because managers of SME have significant influence on firm’s direction, and are the main
decision makers (O'Regan, Sims, & Gallear, 2008). The questionnaire focused the general
environment that affects their operations and profitability.
3.2 Main characteristics of Eastleigh
Eastleigh was established in 1921 by the colonial administration and formerly called Nairobi
East Township, mostly populated by Somalis who had moved from Ngara plains. Eastleigh is
the biggest market in East and Central Africa hosting 40% of small businesses in Nairobi.
Apart from the general economic slowdown of the world caused by Covid-19, Eastleigh is
separately ghettoized from the rest of the world. This caused partial or total shutdown of the
majority of businesses, causing employment and profit loss in this vast district of Nairobi.
3.3 Models
To evaluate the relationship between loan repayment and business disruptions, the study used
equation (1) and conducted regression and correlation analysis, in which loan repayment was
used as the dependent variable and business disruptions as the independent variables.
Loanrepayment=β0+β1supplycost=β2supplyflow+β3cashflow+β4salestarget+β5operating
period +e.
To measure independent variables against loan repayment, we asked the respondent to rank the
questionnaire statements into five-point Likert scale (1=strongly disagree, 2=disagree,
3=neutral, 4=agree, 5=strongly agree). Descriptive statistics is used to summarize the collected
data, while regression and correlation were used to measure the strength and the direction of
the relationship between the dependent and independent variables with 95% confidence level.
The results of the analyzed data were then presented in tables.

4.0 FINDING AND PRESENTATIONS
4.1 Descriptive Statistics
The majority of the respondents were business owners (76%), while 24% were employees for
the businesses. 68% of the respondents were females, while 32% were males. 78% of the
respondents were between 20-39-age brackets, which shows that small businesses involve
people who are in the prime of their lives. 74% of the respondents have up to secondary
education level, while 20% have either certificate or diploma. Only 6% were found to be
graduates. In business sector, 32% were retailers, 26% merchants, 14% lodging and restaurants,
6% hawking, 5% transport, 4%wholsale, and 1% each from manufactures and agriculture. In
terms of fund-source, the study found that 30% of the respondents sourced their funds from
SACCOs, 26% personal saving, 22% bank loan, 14%, family, friends 6%, and venture capital
2%.

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4.1.1 Effects of pandemic disruptions on loan repayment
The respondents were asked to give their opinion about the extent of how different business
disruptions affect their operations. Results show that 63.3% of the respondents agreed or
strongly agreed that supply was disrupted by the COVID-19, while 72% indicated an increase
of supply cost during the pandemic outbreak. Some 45% of the respondents also indicated that
they missed their sales target, while 78% reported a reduction of cash flow. Majority of the
respondents, 66% of them confirmed that the operating period of their businesses was reduced.
Table 1 shows the result.
Table 1: pandemic disruptions
Strongly Strongly
Response Agree Neutral Disagree Total
Agree disagree
Supply flow 13 18 5 7 6 49
% 26.5 36.8 10.2 14.3 12.2 100
Supply cost 16 20 3 3 8 50
% 32 40 6 6 16 100
Sales target 12 10 8 10 9 49
% 24.5 20.5 16.2 20.5 18.3 100
Cash flow 17 22 4 3 4 50
% 34 44 8 6 8 100
Op. period 24 9 7 4 6 50
% 48 18 14 8 12 100
4.2 Correlation Analysis
Correlation analysis was conducted to test the relationship between supply flow, supply cost,
sales target, cash flow, operating period, and loan repayment ability. The correlation coefficient
for supply flow on loan repayment was 0.25 with p value=0.009. The value indicates the
existence of strong association between business supply and its ability to repay loan. There is
weak association between supply cost and loan repayment (r=0.24, p=0.07). Similarly, there is
weak but significant association between sales target and loan repayment (r=0.235, p=0.8).
There is also moderate association between cash flow and loan repayment (r=0.49, p=0.41).
Furthermore, there was weak association between operating period of the business and the
ability of loan repayment. The below table summarizes the results.
Table 2 correlations

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Operati
Supply Sales Cash Loan
Supply g
flow Repaym
Cost Target Flow Period
et
Pearson correlation 1 0.074 -0.188 -0.3 0.261 0.25
Supply
Sig. (2 tailed) - 0.61 0.19 0.838 0.67 0.09
flow
Covariance 1.408 0.096 -0.278 -0.43 0.348 0.102
Pearson correlation 0.074 1 0.14 -0.131 -0.007 0.24
Supply
Sig. (2 tailed) 0.61 - 0.333 0.366 0.963 0.07
cost
Covariance 0.96 1.194 0.19 -0.173 -0.008 0.027
Pearson correlation -0.188 -0.14 1 -0.042 0.018 0.235
Sales
Sig. (2 tailed) 0.19 0.333 - 0.366 0.963 0.07
target
Covariance 0.96 1.194 0.19 -0.173 -0.008 0.27
Pearson correlation -0.38 -0.131 -0.042 1 -0.116 0.49
Cash
Sig. (2 tailed) 0.838 0.366 0.773 - 0.42 0.041
flow
Covariance 0.043 0.173 -0.063 1.48 -0.159 0.002
Operatin
Pearson correlation 0.261 -0.007 0.018 -0.116 1 0.431
g
Period Sig. (2 tailed) 0.067 0.963 0.901 0.421 - 0.107
Covariance 0.48 -0.008 0.025 -0.159 1.264 0.264

Pearson
Loan correlatio 0.085 0.02 0.235 0.002 0.231 1
n
Sig. (2
Repayment 0.559 0.87 0.1 0.991 0.107 -
tailed)
Covarian
0.102 0.027 0.298 0.002 0.264 1.04
ce
The overall correlation between covid-19 and the ability of the business to repay loan was -.54,
p< 0.05. This means that higher the spread of covid-19, the lower the ability of the business to
repay the loan. This result is shown in the following table.
Loan repayment
Pearson correlation -.54
Covid-19
Sig. (2 tailed) 0.008
4.3 Regressions analysis
The study conducted a regression analysis of supply flow, supply cost, cash flow, operating
period, and sales target on loan repayment ability.
4.3.1 Model Summary

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In the model, 82% of the variations can be explained by the independent variables (R2=0.82),
while the remaining 18% is explained by factors beyond this study.
Table 3: Model Summary
Change statistics
Std.
Adjusted error of F
Model R R2 R2change df1 Df2 Sig.
R2 the change
estimste
1 0.901 0.812 0.791 1.022 0.812 38.89 5 45 0.008
4.3.2. ANOVA
The study also conducted Analysis of Variance (ANOVA). The model is statistically
significant, f(5,45)=38.889, p=0.000, implying that the model was statistically significant and
good fit for the data. The below table summarizes the result of ANOVA.
Table 4: ANOVA
Model Sum squares df Mean square f Sig.
Regression 203.017 5 40.603 38.889 .000
Residual 46.983 45 1.044
Total 250.000 50
Dependent variable: loan repayment ability

Predictors: Supply flow *Supply cost *Cash flow *Operating period *Sales target

4.3.3 Regression of Coefficient
The multiple linear regression results showed that the model, pandemic effect, was significant
in predicting loan repayment,  = .681, t(49) = 2.46, p <.05. This result is shown in table.
Table 5: Coefficients*
Standardize
Unstandardized
d
Model Coefficients t Sig.
Coefficients

B Std. Error Beta
Constant 3.678 2.697 1.397 .175
1
Default risk .681 .256 .281 2.462 .016
*Dependent variable: loan repayment
*Predictor variable: COVID-19

5.0 SUMMARY, CONCLUSION, AND RECOMMENDATION
5.1 Discussion/Summary

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The study concluded that there is significant positive relationship between supply flow and
loan repayment ability. The relationship between supply cost and sales target on loan
repayment ability was weak but significant. The association between cash flow and loan
repayment was strong and positive, while the one between operating period and loan
repayment was significantly positive. In general, there was negative relationship between small
business disruptions and their ability to repay loan on time.
5.2 Recommendations
Once those businesses disappear, it will take years to rebuild and acknowledge their presence
in the economy again. The debt will continue to accumulate for those who borrowed even after
closure, making difficult for the entrepreneurs to start the same business or new one again. But
if the government provides adequately targeted stimulus, quick bounce back is possible. The
most basic problem that majority of small businesses complain is about the unblinking interest
rate and penalties on their loans. The government should compel the lenders to freeze the cost
of finances; at least at these challenging periods, so that small businesses will have a space to
breath and reduce their burden. The second problem is the mass layoffs of employees by small
businesses, which will create high crime rate and insecurity. It will be prudent if the
government can remove the payroll cost from the vulnerable businesses to avoid shedding their
workforce during this downturn. Government help, such as sending money directly to the
vulnerable households, may not support at all, when the shops and stores are closed, and the
country is under lockdown. Stipends will not help when the people are fearful of receiving
packages at their doorsteps?
Even at this time of hardship, a strong stimulus package won’t prevent closures for the owners
who depend their livelihoods on these businesses. A plan for rent, employees, and electricity
payment during quarantine would not replace their income and profits they used to feed and
educate their dependents, but could prevent widespread bankruptcies that may spread across
the country. It will also lessen the burden and give opportunity for quick recovery. But so far,
the stimuli of Kenya government for businesses on this phenomenon were a reduction of VAT
from 16% to 14%, which is an affront to the business community. How sales tax reduction can
help a business that is not selling in the first place? To make the matter worse, the curfew
started at the end of the month when bills are due straining already stretched resources. Bars,
shops, and restaurant owners are already contemplating whether to pay their cost of March and
anticipate for a miracle or close the business while they have some money in their pockets.
The government should provide immediate cash stipend to the most vulnerable small
businesses by at least covering their payroll. The information about SME employees will be
very easily available for the government in the payroll tax of every business. To qualify for this
fund, the condition will be that the business kept the same number employees after the
pandemic. The study also suggested that small businesses should adopt ideas of dealing with
unpredicted business disruptions like insuring against such incidents, and monitoring external
and internal environment of the business.
5.3 Limitations/implications:
The current study is limited to investigating a sample from small businesses in Eastleigh
covering a period between May to September 2020. Although the finding can be generalized to
other areas of the country and the world, environmental differences can impact the result of this

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study. further research in different industries, sectors, towns, counties, countries, and periods is
recommended.

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