Liquidation of Micro-Enterprises as a Seasonal Phenomenon: Evidence

from Poland

DOROTA JEGOROW, JUDYTA PRZYŁUSKA-SCHMITT

Faculty of Social Sciences, Institute of Economics and Finance,

The John Paul II Catholic University of Lublin,

POLAND

Abstract: - The study aims to develop a quantitative model of the liquidation of microenterprises on the

example of the Polish experience in 2013-2021. The primary objective is to isolate seasonal variations from the

time series of monthly observations. The cognitive dimension of the study is in line with whether the

liquidation of enterprises has the characteristics of a phenomenon repeated over time. Our research is

pioneering in the cognitive issues it covers, including the instrumentation used. The analysis uses methods and

research tools that identify statistically significant differences between average values of the number of

business entities that deregistered from CEIDG (Central Registration and Information on Business). The study

includes a post hoc test preceded by the analysis of variance (ANOVA), Welch and Brown-Forsythe tests, and

the Kruskal-Wallis test. In the next step, we conducted seasonal decomposition based on additive and

multiplicative variations and examined the correlation. The analysis enables positively verifying the hypothesis

on the seasonality of the liquidation of enterprises.

Key-Words: closing a business, entrepreneurs, entrepreneurship, micro-enterprise, small business, COVID-19

pandemic.

Received: September 24, 2021. Revised: July 14, 2022. Accepted: August 4, 2022. Published: September 5, 2022.

1 Introduction

Self-employment involves making decisions mainly

of a conceptual, organizational, and financial nature.

On the other hand, business success results from

many factors in the internal and external

environment of the organization. In the former, the

entrepreneur can shape this area to a large extent,

while the latter of these possibilities are already

considerably limited. Generally, success is

determined by the long-term staying of a profitable

organization in the market [12]. In this light, there is

a research field related to the liquidation of

enterprises in quantitative and qualitative terms.

This topic is not reflected in the current scientific

achievements, even though analyzes of

microenterprises are present in a rich catalog of

publications.

This study analyses the time series of the

monthly applications submitted to the Central

Registration and Information on Business (CEIDG)

for liquidating an enterprise in the form of a natural

person engaged in business activity (so-called self-

employment) over the period 2013-2021 in Poland.

An acceptable generalization is to assume that

micro-enterprises are the subject of the study.

According to the January 2022 data, 99.03% of

natural persons engaged in business activity are

entities employing up to 9 persons, i.e., entities that

meet the definition criterion of micro-enterprise

(3.41 million out of 3.45 million entities). The ratio

of micro-enterprises to the total number of

enterprises is 98.65%. On the other hand, natural

persons engaged in business activity represent

71.27% of these entities, whereas in the general

micro enterprises’ population, 73.08% of them.

The study’s primary objective is to develop a

model of statistical repeatability of entrepreneurial

behavior in terms of the decision-making on the

liquidation of enterprises based on seasonal

variations. Separate analyses were conducted during

the crisis of the COVID-19 pandemic.

This study uses the classic approach to

entrepreneurship that an entrepreneur is a person

who, using appropriate personality traits, takes risks,

initiates activities, and is the creator of economic

activity [24]. An entrepreneur is a person who starts

a business and makes organizational decisions.

Failures that lead to business termination should be

considered in this regard.

The cognitive aspect of the study is a

methodology that includes the applied set of tools

used in economic analysis. The research verifies the

hypothesis of the occurrence of seasonality in the

liquidation of all micro-enterprises in Poland. It

determines existing differences in this respect under

the conditions of a relatively stable regulatory,

economic-financial, technical-organizational, and

market environment (without an analysis of

industries that are assumed to be seasonal). This

article enriches the current literature on the subject

of microenterprises and their survival on the market

or liquidation. Practical implications of the study

include the environment of micro-enterprises,

especially government and local government

institutions, which, having their appropriate tools,

can introduce instruments as a positive stimulation

for entrepreneurs or at least not hinder their

activities.

2 Literature Review

There is no doubt that a driver of economic growth

in all countries is micro-enterprises that enable

small entrepreneurs to create new jobs. In this way,

they can combat poverty and increase social welfare

[25, 27]. However, the current knowledge of

entrepreneurship in developing countries is limited

[9, 17]. Researchers agree that the institutional

environment has a significant influence on "how"

and "how many" aspects of entrepreneurial activities

are implemented in a country [10]. At the same

time, there is no ideal entrepreneurship model,

especially in the application aspect. A study

concerning the Silicon Valley entrepreneurship

model provides evidence in this regard. This model

was limited in adapting and solving the most

contemporary relevant economic and social

problems [1].

The COVID-19 pandemic is one of the current

main issues affecting entrepreneurship. This

problem emerged in late 2019, pointing out the

socio-economic implications [22, 23]. While some

analysts believe that the COVID-19 pandemic will

cause a protracted global recession, others argue that

the virus will stop soon, and the global economy

will quickly return to normal. In general, epidemics

affect the economy in multiple ways. However,

economists' expectations may be proved wrong by

Russia's special military operation against Ukraine.

The impact of these Russian activities has been a

subject of numerous estimates, but mainly of an a

priori nature.

In this study, separate analyses focus on the

economic impact of the COVID-19 pandemic on the

liquidations of enterprises. Almost all sectors have

experienced disruptions, for example, by restricting

business activities. According to some authors, the

pandemic has hurt start-ups, especially in

developing countries where government support is

limited [21]. The literature identifies the fear factor

as a meaningful indicator that limits entrepreneurial

activity [18, 20].

Stimulating entrepreneurship and creating

conditions conducive to its development is a

concept of most public policies. On the one hand,

organizational and fiscal improvements offer grants

or low-interest repayable instruments. On the other

hand, the barriers are erected and lead to a real

market imbalance, which discriminates against

entrepreneurial units that cannot meet many of the

defined criteria for accessing offered support.

Empirical research conducted over the past years

does not give a clear answer as to the effectiveness

of applied solutions. The success of the Italian

model, introduced in 2012, provides a benefits

package in tax incentives, public loan guarantees,

and more flexible labor laws for firms registered as

"innovative start-ups" [5]. At the same time, there

are also very different opinions. The failure of pro-

entrepreneurial solutions is related to the concept of

dependent entrepreneurship, the empirical

exemplification of which is the example of the

wastefulness of public funds allocated for financing

new enterprises [11, 15]. The evidence of the

ineffectiveness of public action by design to be pro-

entrepreneurial is also to find in recent research

from Singapore, according to which the

entrepreneurial state, which paradoxically creates a

vision of the Singaporean state engaging in

entrepreneurial activity, in reality, delays the

transition to an entrepreneurial society. Thus,

institutional actions may inadvertently create

barriers to a more inclusive entrepreneurial

community [2].

Regardless of public support, organizational and

fiscal mechanisms, business environment, and

individual entrepreneurial motives and aptitudes, a

relational analysis requires permanent monitoring of

national economy entities' quantitative structure. It

is necessary from the perspective of each country

[14].

Systematic quantitative analyses in an

unchanging environment confirm or deny the

effectiveness of existing regulations. These analyses

identify negative global phenomena such as the

COVID-19 pandemic or the Russian-Ukrainian

armed conflict. The empirical research conducted

immediately aftermath the COVID-19 pandemic

outbreak and in the subsequent years of the

pandemic indicates its devastating impact on small

companies [6, 7, 19]. In Europe and the US, the

COVID-19 pandemic more directly affected the

self-employed than the non-self-employed, whereas

small companies were more directly affected by the

pandemic than large ones [4]. At the time of the

pandemic outbreak, micro-enterprises were

particularly vulnerable to organizational and

financial problems that could eventually result in the

termination of their business. Governments

supporting small and mid-size enterprises (SMEs)

offered various assistance programs. The example

of the United Kingdom, while demonstrating

positive effects of implemented solutions to rescue

organizations or maintain the sufficient financial

strength of supported companies, at the same time

proves that public support has largely failed to reach

the companies in need of real help [3]. The research

the small businesses in the US also proves the

questionable effectiveness of government support.

[8].

Individual entrepreneurial failures,

environmental failures, and those resulting from

organizational and legal barriers contribute to the

liquidation of enterprises. However, failure is not

always at stake. Liquidation of enterprises is part of

the theory of exit routes based on various

determinants, both in business failure and success

[16]. The issues of repeatability in this respect and

periodic or point peaks are not represented in

scientific research. In addition to the scientific and

cognitive aspects, the concept of shaping the

paradigm by identifying emerging deviations in the

structure of the enterprise population is relevant for

entrepreneurial countries.

3 Methods and Data

The formal and legal environment of enterprises can

create significantly different constitutive conditions

for entrepreneurial initiatives and the functioning of

registered entities. Optimization solutions, including

the building of structural organizational and

financial dependencies, are the domain of large

entities, or large ones, i.e., based on complex

networks. The use of more favorable market

conditions for the functioning of enterprises in the

financial aspect is not the domain of sole

proprietorships, although it is the type of entity that

is the economic and social foundation of national

economies. The simple legal form includes the

registration aspect, and financial settlements are an

encouragement for amateur entrepreneurs who, from

the perspective of the benefits they bring to the

economy, should be referred to as entrepreneurial

leaders [14].

The main problem of the study provides a

question: is the propensity to liquidate enterprises of

a seasonal nature?

Based on the incremental analysis, the approach

remains unrelated to the motivation inherent in

entrepreneurship, which is treated as a separate

scientific discipline and fulfills a strictly economic

policy. [26]. The implementation of the issue of the

study introduces the verification of three hypotheses

(assuming the existence of a relatively stable formal,

legal and socio-economic environment of Polish

enterprises).

H1: Liquidation of micro-enterprises is recurrent

on an annual basis.

H2: Liquidation of micro-enterprises is seasonal.

H3: The COVID-19 pandemic has not

contributed to an increase in the number of micro-

enterprises liquidation in the short term.

The study used analytical tools, narrowed down

to instruments that, based on monthly analysis based

on one-way ANOVA (F-test), preceded by

verification, meet the criteria of normal distribution

(Kolmogorov-Smirnov and Shapiro-Wilk test) and

homogeneity of variance (Levene's test). The

criterion of homogeneity of variance is not met, and

the second one of normality of the distribution of

individual features is only partially met. Therefore,

the number of deregistered enterprises in subsequent

months, the Kruskal-Wallis (KW) non-parametric

analysis of variance

, and the Brown-Forsythe and

Welch tests

we used to verify the research

hypotheses. The authors used a post hoc test to

isolate groups of months with significant differences

to then determine which pairs of mean values differ

the most from each other. The analytical process

also included the separation of additive and

multiplicative seasonal variations based on the 5-

period moving average model. Using seasonal

decomposition and correlation analysis allowed us

to confirm or reject the presence of a pattern in the

values of the trait analyzed.

4 Results and Discussion

Visual presentation of the time series (Fig. 1) makes

it possible to identify unusual observations and

possibly eliminate them, provided there are

reasonable grounds for doing so. Deviations from

the average values of the number of liquidated

enterprises in the subsequent months in 2013-2021

appear in the form of one extreme size in April and

nine outliers, two of which occurred in December.

The number of extremes identified is small, and the

data insignificant.

It is often used instead of a standard one-way ANOVA when

data are from a suspected non-normal population.

There are preferred to the F-statistic if the assumption of the

equality of the variance fails.

Fig. 1: Diagnostics of the dispersion of closure of

micro-enterprises in the following months

The juxtaposition of the arithmetic mean with the

standard deviation (Fig. 2) indicates the relatively

high variation among the recorded values in January

(CV=23.74%; CV - Coefficient of Variation),

although it was classified as statistically

insignificant. December was ranked second in terms

of internal variance (CV=20.29%).

Arithmetic means were determined for twelve

independent subgroups creating two different

groups. One group covers two months - January and

December - and the other the remaining months.

The existence of the identified distribution is also

confirmed by cluster analysis.

Fig. 2: Descriptive statistics

The existence of differences does not directly

imply statistical significance in this regard.

Determining this fact requires appropriate testing.

In further analysis, the authors used two

approaches. The first is based on the 2013-2021

time series, and the second on the truncated 2013-

2017 time series, corresponding to data obtained in

a relatively unchanged external environment for

companies. The research approach adopted was

preceded by numerous graphical and computational

simulations dictated by the COVID-19 pandemic

outbreak in 2020 and the amended regulations

governing sole proprietorship introduced in Poland

in 2018. New legal and financial solutions taking

into account, among others, exemptions from

compulsory social contributions, except for health

enterprises and the possibility of conducting limited

economic activity without registration, have created

more favorable - compared to existing solutions -

financial conditions for undertaking the economic

activity. This situation, however, has been exploited

not only by new entrepreneurs but also by

experienced ones, combining the operation of

several formally independent entities. Many

entrepreneurs have taken advantage of existing

preferences to open seemingly new entities, almost

entirely formed from liquidated entities [13]. The

rising inflation at the end of 2021 determined the

adopted concept of division of the primary time

series. Assessing the direction and intensity of

changes in the quantitative structure of enterprises

during periods of transition requires exceptional

diligence in the research process.

4.1 Microenterprises Liquidated between

2013 and 2021 - Comparative Analysis of

Means Values by Month (One-Way Analysis

of Variance)

The criterion of normality of distribution analyzed

by Shapiro-Wilk and Kolmogorov-Smirnov tests

does not yield positive verification (p<0.05) for two

months (April, and June) for the 2013-2021 time

series. The normality criterion was met for the

truncated 2013-2017 time series. This discrepancy

calls for further analysis (Table 1).

Table 1. Tests of Normality

Month

Kolmogorov-Smirnova

Shapiro-Wilkb

Statistic

Jan

.217

.333

.200*

.073

.217

.803

.226

.085

Feb

.199

.205

.200*

.199

.946

.799

.711

Mar

.231

.298

.183

.168

.231

.846

.579

.183

Apr

.340

.207

.004

.200*

.340

.928

.010

.583

May

.168

.329

.200*

.082

.168

.832

.789

.144

Jun

.267

.281

.064

.200*

.267

.791

.016

.068

Jul

.184

.289

.200*

.184

.794

.214

.072

Aug

.209

.245

.200*

.209

.840

.116

.165

Sep

.200

.296

.200*

.174

.200

.872

.475

.273

Oct

.161

.242

.200*

.161

.876

.471

.290

Nov

.217

.192

.200*

.217

.913

.272

.486

Dec

.271

.244

.055

.200*

.271

.956

.134

.781

Note: A. 2013-2021; B. 2013-2017; *. This is a lower bound of

the true significance; a. Lilliefors Significance Correction, b.

effect relevant to p>0.05.

Also, the criterion of homogeneity of variance

(p>0.05) was not positively verified by Levene's test

(Table 2). Failure to meet the above criterion

provides a substantive rationale for using ANOVA

analysis as a projection requiring verification by

subsequent tests in addition to the normality test.

Table 2. Tests of Homogeneity of Variances

Series

Levene’s

Statistic

1.000

2.000

3.000

4.000

5.000

10.000

15.000

20.000

25.000

Mean Std. Deviation

2013

2021

Based on Mean

3.882

.000

Based on Median

1.927

.045

Based on Median and with adjusted df

1.927

.065

Based on trimmed mean

3.646

.000

2013

2017

Based on Mean

1.786

.083

Based on Median

.681

.749

Based on Median and with adjusted df

.681

.736

Based on trimmed mean

1.501

.162

Note: Grouping Variable: Month.

The results obtained through a one-way ANOVA

analysis of variance (p<0.05) do not support the

hypothesis of equality of mean values in the

subgroups studied (Table 3). Thus, the results of the

test support the claim that there is a statistically

significant difference between monthly averages for

at least one pair in both the 2013-2021 and 2013-

2017 series. However, the failure to meet the

conditions of normality of distributions and

homogeneity of variance in the case of the 2013-

2021 time series also does not give grounds to

consider the above result as statistically significant.

Verification of the hypothesis of ascending seasonal

variations requires further testing.

Table 3. ANOVA (Analysis of Variance)

Series

Mean Square

2013

2021

Between

Groups

72,308,477.552

13.361

.000

Within

Groups

5,412,093.581

2013

2017

Between

Groups

25,081,556.230

7.096

.000

Within

Groups

3,534,524.842

Note: Grouping Variable: month.

The results of the Welch and Brown-Forsythe

tests, which by design do not require the criterion of

homogeneity of variance to be met, indicate that

there are significant differences between group

mean values (p<0.05) for at least two characteristics

for the 2013-2017 and 2013-2021 monthly data time

series (Table 4). The results indicate a fairly clear

and distinct correlation between empirical and

theoretical values determined by the additive and

multiplicative models. In turn, the mutual

dependence of theoretical models is very large.

Table 4. Robust Tests of Equality of Mean

Test

Statistica

df1

df2

Welch

(2013-2021)

5.680

37.294

.000

Brown-Forsythe

(2013-2021)

13.361

41.778

.000

Welch

(2013-2017)

6.141

18.546

.000

Brown-Forsythe

(2013-2017)

7.096

18.267

.000

Note: An asymptotically F distributed; Grouping Variable:

Month.

As the criterion for normality of distributions

was not met, the Kruskal-Wallis Test was also

applied in the analysis (Table 5). The results

obtained (p<0.05) confirm the existence of

statistically significant differences between at least

two group averages.

Table 5. Kruskal-Wallis Test

Time series

Statistica

2013-2021

54.816

.000

2013-2017

33.510

.000

Note: a. Grouping Variable: Month.

The number of liquidated enterprises by month

significantly increased in January and December

each year compared to the other months (Fig. 2).

The post hoc analysis of the 2013-2021 and 2013-

2017 time series, using all the tests available in the

SPSS package, confirms the existence of significant

differences between the results recorded in January

and December and the other months, respectively

(p<0.05 individual; p1 for tests). Due to the lack

of fulfillment of the criterion of normality of

distributions and homogeneity of variance, formally

not all post hoc tests meet the criterion of usefulness

for the 2013-2021 series, although in practice all the

results obtained confirmed the existence of

statistically significant intergroup differences for

January and December.

Taking into account the formal and financial

conditions of running micro-enterprises in Poland in

a legal form: for a sole owner running a business, an

increase in obligatory costs may be a problem that

appears at the turn of the years. For instance,

contributions paid to the Social Insurance Institution

(ZUS), are conditioned by the amount of the

average monthly salary in the national economy. In

the years 2013-2021, this remuneration

systematically increased by an average of 5.66%

y/y.

4.2 Seasonal Decomposition

Seasonal decomposition is used to extract a seasonal

component, a combined trend and cycle component,

and an "error" component from a time series. In

practice, this method enables the construction of

forecasts taking into account seasonal variations of

additive and multiplicative nature. A comparison of

the theoretical series with the original one meets the

requirements of ex-ante evaluation.

The analysis based on seasonality indicators

provides further confirmation of the hypothesis on

the seasonal nature of micro-enterprise liquidations.

The model based on the 5-period centered moving

average deviates from the series determined by the

data subject to the study. Consideration of both

additive and multiplicative seasonal variations in the

forecast significantly increases the precision of

fitting the theoretical model to the empirical data

(Fig. 3).

Fig. 3: The course of the original time series and the

forecasts taking into account seasonal fluctuations

of an additive and multiplicative nature

The values of the seasonal indicators coincide

with the results obtained from the post hoc analysis

(Fig. 4).

Fig. 4: Seasonal Factor

The correlation analysis confirms the outlined

convergence of the original series based on average

values for 2013-2021 with the forecast taking into

account seasonal variations of additive and

multiplicative nature (Table 6).

Table 6. Estimated correlation coefficients

among variables

Variables

Termination

Seasonal Adjusted Series

(MUL)

.655**

(.000)

.468**

(.000)

.585**

(.000)

Seasonal Adjusted Series

(ADD)

.646**

(.000)

.454**

(.000)

.546**

(.000)

Seasonal Adjusted Series (ADD)

Seasonal Adjusted Series

(MUL)

.971**

(.000)

.923**

(.000)

.989**

(.000)

Note: CC - Correlation Coefficient, a. Pearson Correlation, b.

Kendall's tau_b, c. Spearman's rho; **. Correlation is significant

at the 0.01 level (2-tailed).

The results of seasonal decomposition confirm

that most enterprises are liquidated in the winter

period, which covers the months December-January.

The values of the seasonal fluctuation indices

recorded for the remaining months indicate slight

differences as compared to the mean values

determined for empirical data.

4.3 Enterprise Liquidation vs. the COVID-

19 Pandemic

Relating the monthly results of the number of

enterprise closures in the consecutive years 2018-

2021 to the model built on the averages covering the

years 2013-2017 (Fig. 5), it is clear that the values

are significantly lower in the year 2020, which

should be directly linked to the period of the

outbreak of the COVID-19 pandemic. In that year,

compared to the model, an 11.1% decrease was

recorded, in contrast to the year 2021, in which a

10.4% increase was recorded. Therefore, it appears

that, relative to the model, 2020-2021 did not

significantly change the total number of deregistered

enterprises y/y. In contrast, the number of

enterprises liquidated in 2020 concerning 2019

decreased by more than 18.1%.

Thus, it turns out that the years 2018-2019, the

period of introducing new rules on one-man

business, brought an increase in the number of

enterprise liquidations by 10.9% and 8.6% y/y,

respectively. At the same time, it should be noted

that during this period, compared to previous years,

more enterprises were registered due to financial

preferences (Jegorow et al., 2021).

5.000

10.000

15.000

20.000

25.000

30.000

Jan/13

Jun/13

Nov/13

Apr/14

Sep/14

Feb/15

Jul/15

Dec/15

May/16

Oct/16

Mar/17

Aug/17

Jan/18

Jun/18

Nov/18

Apr/19

Sep/19

Feb/20

Jul/20

Dec/20

May/21

Oct/21

Original Series

Seasonally Adjusted Series (ADD)

Seasonally Adjusted Series (MUL)

100

120

140

-3.000

-1.000

1.000

3.000

5.000

7.000

Seasonal Factor (ADD)

Seasonal Factor (%) (MUL)

Fig. 5: Deregistration of enterprises, the average for

2013-2017, absolute data for 2018-2021

The distinctly lower numbers of liquidated

enterprises in March and April 2020 can be

associated with the temporary suspension of the

operation of these entities. In March 2020, as many

as 48,624 entities were closed. It was the highest

result for liquidated enterprises from 2013-2021.

The second lowest result in the category of

suspensions is seen in December 2021, i.e., 42,237.

Business closures or suspensions may be related to

rising inflation, rising interest rates, and

macroeconomic outlooks because of the long-term

downturn in economic activity during the pandemic

period. These results are significantly higher than

the total recorded between 2013 and 2021, for

which the average was 13,574.

5 Conclusion

The analysis shows that the liquidation of

enterprises, similarly to their establishment [14], has

a cyclical nature and is part of the seasonality

determined by the monthly system. Most enterprises

are liquidated in December or January. However, no

month can be indicated as the month in which the

fewest enterprises are closed. The identified

quantitative aspect of the study is the contribution to

further qualitative research on the question of why

enterprises are going out. An important direction of

future research is also to conduct a comparative

analysis broken down into sectors or industries. An

important direction of future research is also to

conduct a comparative analysis broken down into

sectors or industries. With the resources of public

registers, such an analysis is currently not possible

to be carried out based on a comprehensive study.

The analysis showed that the pandemic scare was

of short duration and that the intensity of enterprise

liquidations immediately after the COVID-19

outbreak did not occur. On the contrary, the number

of liquidated enterprises decreased compared to

earlier years. Entrepreneurs opted for the institution

of business suspension, the significant scale of

which must be attributed precisely to the effects of

the pandemic. Perhaps government or local

government support helped entrepreneurs, and the

answer to this question requires further studies.

Given the differences from the outlined model,

further empirical research should take into account

the far-reaching effects of the COVID-19 pandemic,

rising inflation, and the context of the war in

Ukraine.

To conclude, the Polish government and local

institutions undertake various activities to support

entrepreneurship and entrepreneurs. Regardless of

numerous doubts about the effectiveness of these

instruments, it is worth considering the

implementation of systemic support programs for

entrepreneurs in the period of increased

intensification of their liquidation in conditions of a

relatively stable external environment. In this case,

the focus should be on the increase in contributions

paid by entrepreneurs to the Social Insurance

Institution (ZUS), the amount of which has been

systematically growing in recent years, becoming an

increasing financial burden.

References:

[1] Audretsch, D. B., Have we oversold the Silicon

Valley model of entrepreneurship? Small Bus

Econ, vol. 56, 2021, pp. 849–856.

https://doi.org/10.1007/s11187-019-00272-4

[2] Audretsch, D. B. & Fiedler, A., Does the

entrepreneurial state crowd out

entrepreneurship? Small Bus Econ, 2022.

https://doi.org/10.1007/s11187-022-00604-x

[3] Belghitar, Y., Moro, A. & Radić, N., When the

rainy day is the worst hurricane ever: the

effects of governmental policies on SMEs

during COVID-19, Small Bus Econ, vol. 58,

2022, pp. 943–961.

https://doi.org/10.1007/s11187-021-00510-8

[4] Belitski, M., Guenther, C., Kritikos, A. S. &

Thurik, R., Economic effects of the COVID-19

pandemic on entrepreneurship and small

businesses, Small Bus Econ, vol. 58, 2022, pp.

593–609. https://doi.org/10.1007/s11187-021-

00544-y

[5] Biancalani, F., Czarnitzki, D. & Riccaboni, M.,

The Italian Start-Up Act: a microeconometric

program evaluation, Small Bus Econ, vol. 58,

2022, pp. 1699–1720.

https://doi.org/10.1007/s11187-021-00468-7

[6] Cucculelli, M., & Peruzzi, V., Post-crisis firm

survival, business model changes, and learning:

Evidence from the Italian manufacturing

5.000

10.000

15.000

20.000

25.000

30.000

5.000

10.000

15.000

20.000

25.000

30.000

Mean 2013-2017 2018

2019 2020

2021

industry, Small Business Economics, vol. 54,

no. 2, 2020, pp. 459–474.

https://doi.org/10.1007/s11187-018-0044-2

[7] Endris, E. & Kassegn, A., The role of micro,

small and medium enterprises (MSMEs) to the

sustainable development of sub-Saharan Africa

and its challenges: a systematic review of

evidence from Ethiopia, J Innov Entrep, vol.

11, no. 20, 2022.

https://doi.org/10.1186/s13731-022-00221-8

[8] Fairlie, R. & Fossen, F. M., Did the Paycheck

Protection Program and Economic Injury

Disaster Loan Program get disbursed to

minority communities in the early stages of

COVID-19? Small Bus Econ, vol. 58, 2022, pp.

829–842. https://doi.org/10.1007/s11187-021-

00501-9

[9] Govindarajan, V. & Ramamurti, R., Reverse

innovation, emerging markets, and global

strategy Glob, Strategy J., vol. 1, no. 3-4, 2011,

pp. 191-205. https://doi.org/10.1002/gsj.23

[10] Gupta, V. K., Guo, C., Canever, M., Yim, H.

R., Sraw, G. K. & Liu, M., Institutional

environment for entrepreneurship in rapidly

emerging major economies: the case of Brazil,

China, India, and Korea, Int. Entrep. Manag. J.,

vol. 10, no. 2, 2014, pp. 367-384.

https://doi.org/10.1007/s11365-012-0221

[11] Jegorow, D., Kreacja przedsiębiorczości

zależnej od funduszy publicznych, Optimum.

Studia Ekonomiczne, vol. 6, no. 90, 2017a, pp.

93-106.

https://doi.org/10.15290/ose.2017.06.90.08

[12] Jegorow, D., Przeżycia przedsiębiorstw a

kwestia dotacji publicznych na podejmowanie

działalności gospodarczej, In: M. Miszczuk, M.

Sosińska-Wit (Eds.), Otoczenie a wartość

biznes, pp. 29-44. Politechnika Lubelska,

2017b.

http://www.bc.pollub.pl/dlibra/doczip?id=1311

[13] Jegorow, D., Rozwój przedsiębiorczości

indywidualnej przy wsparciu funduszy

europejskich, Prace Naukowe Uniwersytetu

Ekonomicznego we Wrocławiu, vol. 475,

2017c, pp. 65-76.

https://doi.org/10.15611/pn.2017.475.06

[14] Jegorow, D., Pazdzior, M., Marzec, P. &

Bednarz, K., The Establishment of New

Businesses as a Seasonal Phenomenon: A

Polish Example, European Research Studies

Journal, vol. 0, no. 4B, 2021, pp. 120-137.

https://doi.org/10.35808/ersj/2636

[15] Jegorow, D. & Gruszecki, L., Co-financing of

start-ups from public funds – post-

implementation evaluation of e-services

developed as part of the Operational

Programme ‘Innovative Economy’, Roczniki

Ekonomii I Zarządzania, vol. 9(45), no. 3,

2017, pp. 21-32.

http://dx.doi.org/10.18290/reiz.2017.9.3-2

[16] Kato, M., Onishi, K. & Honjo, Y., Does

patenting always help new firm survival?

Understanding heterogeneity among exit

routes, Small Bus Econm, 2021.

https://doi.org/10.1007/s11187-021-00481-w

[17] Kiss, A. N., Danis, W. M. & Cavusgil, S. T.,

International entrepreneurship research in

emerging economies: a critical review and

research agenda, J. Bus. Ventur., vol. 27, no. 2,

2012, pp. 266-290.

https://doi.org/10.1016/j.jbusvent.2011.09.004

[18] Li, Y., Emotions and new venture judgment in

China, Asia Pacific Journal of Management,

vol. 28, no. 2, 2011, pp. 277-298.

https://doi.org/10.1007/s10490-009-9145-4

[19] Liguori, E. W. & Pittz, T. G., Strategies for

small business: Surviving and thriving in the

era of COVID-19, Journal of the International

Council for Small Business, vol. 1, no. 2, 2020,

pp. 106–110.

https://doi.org/10.1080/26437015.2020.177953

[20] Morgan, J. & Sisak, D., Aspiring to succeed: A

model of entrepreneurship and fear of failure,

Journal of Business Venturing, vol. 31, no. 1,

2016. 1-21.

https://doi.org/10.1016/j.jbusvent.2015.09.0024

[21] Nasar, A., Akram, M., Safdar, M. R. & Akbar,

M. S., A qualitative assessment of

entrepreneurship amidst COVID-19 pandemic

in Pakistan, Asia Pacific Management Review,

2021.

https://doi.org/10.1016/j.apmrv.2021.08.001

[22] Parnell, D., Widdop, P., Bond, A. & Wilson,

R., COVID-19, networks and sport, Managing

Sport and Leisure, 2020, pp. 1-7.

https://doi.org/10.1080/23750472.2020.175010

[23] Ratten, V., Coronavirus (covid-19) and

entrepreneurship: Changing life and work

landscape, Journal of Small Business and

Entrepreneurship, vol. 32, no. 5, 2020, pp. 503-

516.

https://doi.org/10.1080/08276331.2020.179016

[24] Say, J. B., Traktat o ekonomii politycznej,

PWN, Warszawa, 1960.

[25] Si, S., Ahlstrom, D., Wei, J. & Cullen, J.,

Business, entrepreneurship, and innovation

toward poverty reduction, Entrep. Reg. Dev.,

vol. 32, no. 1-2, 2020, pp. 1-20.

https://doi.org/10.1080/08985626.2019.164048

[26] Smith, B. R., McMullen, J. S. & Cardon, M. S.,

Toward a theological turn in entrepreneurship:

How religion could enable transformative

research in our field, Journal of Business

Venturing, vol. 36, no. 5, 2021, 106139.

https://doi.org/10.1016/j.jbusvent.2021.106139

[27] Sutter, C., Bruton, G. D. & Chen, J.,

Entrepreneurship as a solution to extreme

poverty: a review and future research

directions, J. Bus. Ventur., vol. 34, no. 1, 2019,

pp. 197-214.

https://doi.org/10.1016/j.jbusvent.2018.06.003

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

-Dorota Jegorow was the creator of the concept and

responsible for the Statistics.

-Judyta Przyłuska-Schmitt was responsible for the

literature review and linguistic correctness.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

This work was supported by The John Paul II

Catholic University of Lublin [grant numbers 05-

0501-2].

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en

_US