Translation

1. Business Risks of SMEs in Slovakia
November 2014
JEL Classification: G32, G39
Abstract
The aim of this paper is to define, quantify and compare the current business risks of small
and medium-sized enterprises in selected regions of Slovakia in the context of loan finance
and business optimism that business segment in Slovakia. In 2013 we conducted a research
among small and medium businesses in which we tried to find out their views on current
business risks to which they face. We analyzed companies operating in Bratislava, Trencin
and Zilina. The survey was part of an international research project undertaken under the
name of current trends in the business risks of small and medium-sized enterprises in selected
regions of the Czech Republic and Slovakia.
Abstrakt
Cieľom príspevku je definovať, kvantifikovať a porovnať aktuálne podnikateľské riziká
malých a stredných podnikov vo vybraných regiónoch Slovenska v kontexte úverového
financovania a podnikateľského optimizmu toho segmentu podnikov na Slovensku. V roku
2013 sme uskutočnili prieskum medzi malými a strednými podnikateľmi, v ktorom sme sa
snažili zistiť ich názor na aktuálne podnikateľské riziká, ktorým sú vystavení. Analyzovali
sme podniky pôsobiace v Bratislavskom, Trenčianskom a Žilinskom kraji. Prieskum bol
súčasťou medzinárodnej výskumnej úlohy: Aktuálne trendy v oblasti podnikateľských rizík
malých a stredných firiem vo vybraných krajoch ČR a SR, na ktorej sa podieľali Paneurópska
vysoká škola, Žilinská univerzita, Trenčianska univerzita a UTB v Zline.
Kľúčové slová: malé a stredné podniky, podnikateľské riziko, trhové riziko, finančné riziko,
personálne riziko, úvery, podnikateľský optimizmus
Key words: small and medium sized enterprises, business risk, market risk, financial risk,
personnel risk, loans, business optimism

2. INTRODUCTION
Small and medium-sized enterprises (SMEs) are the most important parts of market
economy. Moreover, European Union and the USA holds 99% of all enterprises (Bhaird,
2010). This segment creates in our country almost 50% of the national added value and
provides about 70% of employment. SMEs are becoming ever more important component of
all economies in the world (Karpak, Topcu, 2010). In this context, Henderson and Weiler
(2010) pointed out that SMEs can be characterized as the most important entity of economic
growth. The latest statistics of the National Agency for Development of Small and Medium
Enterprises 2012 reported that on Slovakia SMEs represent 99.9% of all enterprises.
After the outbreak of the financial and economic crisis started to be SMEs, which have
been characterized by considerable vulnerability, even more exposed to business risk. In other
words, decline in orders, in production and profitability caused a rise in unemployment and in
this context of global instability resulted to reduce of access to financial resources, in sum
number of SMEs decreased.
1. Business risk of SMEs
Shadbolt et al. (2010) agreed with Chavasom (2004), they defined the risk that any
situation where events are not known with certainty. Smejkal and Rais (2003), associate the
risk with the following concepts: uncertainty of outcome - if we talk about risk, there must be
at least two variants. Another condition is that at least one of the possible outcomes is
undesirable. Similar to the definition endorses the OECD (2008), where the risk is uncertainty
that in various forms such as loss of money or events has potentially harmful effects on health
and other events that affect human well-being.
Veber (2004) perceived business risk as the danger of failure associated with the hope to
achieve good economic results. Despite many approaches to dealing with the risk, Adaskova
(2009) presents the results of research where 76% of surveyed companies implemented
frequently address the risk through intuitive access, 36.5% use set systems, 33% use plans,
and 24% have a designated person responsible for risk management.
Fotr and Hnilica (2009) identify business risk as the possibility that the achieved results
will deviate from the expected results with the deviation may be desirable (towards higher
profits) or side (toward the loss), respectively, depends on different sizes (small deviations
from never to variations in screen). A similar approach to understanding business risk and

3. have Chodasová and Bartosova and also Belanova (2012). They defined risk as the two basic
components of business risk and financial risk.
Business risks (market, production, legal, security, etc..) are integrated into the
financial risk. Optimal management of these risks determine the existence of the company in
the market, respectively her bust and out of business.
More to the point, financial risk relates primarily to the availability of funds, changes
of interest rates, respectively using of different forms of capital. Research of financial risk, but
from different points of view globally addressed from several authors. Torre et al. (2010)
presents a group of SMEs as a core business for banks due to credit lines. According to the
authors the big banks can offer to SMEs a lot more services, on the other hand where the
relationships were problematic precisely in times of crisis.
Few scientific studies analyzed financial products, but focused instead on credit
products. (Bitler et al, 2001) Agostino, M., Gagliardi, F., Trivieri, F. (2012) examined
whether the concentration on the local credit market affects the riskiness of SMEs. Boyd and
De Nicolo (2005) reported that less competition leads to increasing bank charges for loans
and earn more. This fact increased the risk of bankruptcy of the debtor. Dierkes et al. (2013)
found that business credit information sharing improves predictions of default and thus are
better, the lower the failure rate. Other authors Ono, Ueshugi a Role (2009) found that the
riskiness of firms has a significant impact on whether the use of collateral. But they showed
that banks that have claims secured by collateral monitor these borrowers intensively.
Authors Behr and Guttler (2007) proposed a new model to predict the probability of
default of German SMEs, they used advantage of the unique data of the German SME loans.
They consider financing of banks for the dominant source of external finance for German
SMEs. That is a new approach for analyzing the relationship between the Bank and the
customer, and a new feature that allows you to measure the risk of default of the borrower.
Behr with Norden and Noth (2013) found that an increase in lending by local state-owned
banks significantly reduces corporate financial threat, in the other words effect is not in the
private banks.
Moreover, italian researchers such as Gambini a Zazzaro (2013) examined whether
borrowing of firms from banks get beneficial effect on their growth. The basic finding is that
borrowing money from the bank brings to smaller businesses the opportunity to grow, while
on the other hand, credits can alleviate problems of medium-sized firms.

4. Problems in the SME sector is also limited awareness of enterprises. This status confirms
in Slovakia Sobekova (2011), as well as foreign authors Dierkes, Erner, Langer and Norden
(2013), who argued that firms in the SME segment are small businesses less informed, more
risky and more dependent on trade and bank loans.
The question is: How looked financial risks on companies in Slovakia during the crisis?
Sobekova (2011) analyzed on published results of the banking sector, the situation in credit
financing in times of crisis and on supply and on demand. Demand declined for the
consumers and for businesses as well. On the other hand, the number of defaults began to
increase. Banks responded to this problem by tightening credit conditions, which began in the
second half of 2008 when 69% of banks tightened their standards.
However, standards for banks tightened lending especially in the SME segment. More
than 50% of banks did not record significant change of credit conditions for large companies.
The most noticeable change was in the amount of margin for risky loans. Third largest
tightening occurred in the category of required collateral loans. This can be a major barrier to
accessing credit just for the segment of small and medium enterprises. It SMEs suffer from
weak capital strength and often have problems with liability.
Market risk according Veber (2004) understand the particular risks associated with the
success of products in the domestic and foreign markets. Nature of the risks are more sales or
demand and thus the price, more to the point their lives resource of competition or changes in
consumer preferences. If we want to understand this risk in a broader respectively, broadest
sense, can be considered for market risk and the risk associated with changes in the market
where SMEs operate. These types of risks concerned, for instance authors Petrik, Lesakova or
Workie (2001, 2008).
Petrik (2001) perceived market risk as the risk that affects the operation of the enterprise
market. The author deals with the influence of factors such as the economic cycle, GDP,
inflation, interest, public finances and the other on the business environment. He presented
that the most important is the stabilization of economic conditions and immediately after the
functional system supporting of institutions.
Lesakova (2008) examined the impact of global change on the business environment in
which operate small and medium-sized enterprises. She monitored new types of businesses
and implementing innovations. Workie et al. (2008) examined the effects of globalization on
SMEs.
The Surveys of practice on risk in businesses

5. The survey NADSME (2013) showed that 45% of respondents used during their starting
of businesses support from the Office of Labour. On the other hand, only 4% of businesses
used during starting of business a bank loan, because the bank requires collateral for the loan,
which they were unable to meet. One of the biggest problems identified by the survey is
obtaining a financial resources for challenging projects. In this light, it is alarming that none
of the surveyed businesses used credit resources for the development of international
activities.
The results of NADSME (2011) showed that after outbreak of the crisis had a relatively
decline in earnings primarily of small businesses. Negative impact of the crisis experienced
87% of SMEs but with different intensity.
Most researchers, however, deals with the financial and business risks. For example
Majková (2008) identified as the main obstacles-weak capital strength that makes impossible
for small businesses to get loans and provide guarantees and low awareness of the various
opportunities of funding.
In this light, survey of needs of young entrepreneurs and obstacles in their business
implemented according to the survey of the Association of Young Entrepreneurs (ZMPS) in
cooperation with Jakubec, Sobekova and Solik (2012), they perceived hurdle in business is
lack of start-up capital (77.64%) and second most marked is a lack of experience, knowledge
and professional contacts (71.70%).
2. OBJECTIVE AND METHODOLOGY OF RESEARCH
The aim of this paper is to define and compare the current trends in the field of business
risks and business optimism SMEs in selected regions of Slovakia - especially in Bratislava,
Trencin and Zilina Region.
We conducted a survey about risks of business in selected regions of Slovakia using a
questionnaire inquiring in 2013. Our selection file contains: 102 enterprises from the region of
Bratislava, 164 enterprises from the region of Zilina and 105 companies from Trencin region.
Range of the sample ranged from 0.2% to 0.09%.
Bratislava region is economically the strongest of all regions, shows that almost double
the number of small and medium-sized enterprises than in other regions. While in Bratislava
Region unemployment rate is about 6% in Trencin region is 11% and 13% of Zilina.
2.1 Testing hypotheses

6. In the research we use estimation techniques that set the following hypothesis, which we
used mathematical and statistical analysis of NHTSA (null hypothesis significance testing)
where we tried to verify or reject. We set the null hypothesis, which assumes that exist
differences between regions, the statistical test, we searched for evidence of rejection,
respectively accept a null hypothesis.
(1)
In the survey, we put 23 questions to respondents, after that we formulated alternative
working hypotheses.
H1: The main risk in all regions was market risk. Enterprises in the Bratislava region perceive
this risk less intense than those in other regions.
H2: All businesses suffer as a result of the financial and economic crisis it means worse
business conditions, which is reflected in the decline in their revenues and profits. Businesses
in the Bratislava region, however, profits and profitability are falling less than in other
counties.
H3: The level of optimism of business is quite high even at a difficult time. However, we
estimate that firms from Bratislava regions are more optimistic than firms from Zilina and
Trencin region. All businesses trying to manage the financial the risk to get the lowest
negative variations. We assume that firms in the Bratislava region can manage financial risk
and to obtain necessary financial resources.
In the case, that we confirmed our statistical hypothesis, we reject the null hypothesis
and we forwarded to analyze statistically significant differences between pairs of regions as
follows: Bratislava Region - Zilina Region, Bratislava Region - Trencin and Zilina - Trencin
Region.
2.2 Research Methods
During process of getting results of the questionnaire, we used the spreadsheet program
Excel (from Office 2007) and the possibility to process data by using pivot tables, so that we
can more easily use the tools of descriptive statistics: averages and percentages. That resulted
to frequency of table, which allowed us to focus on those data, which required a more detailed
statistical analysis.
For these case, we used the statistical software R, which allowed us to make a calculations
of the Pearson chi-square and P-values.

7. Significance level α was determined to traditional 5%, or 0.05. Pearson's chi-square test is
calculated as follows:
(2)
where χ 2 - Pearson's chi-square statistic
Oi - the actual frequency
Ei - expected theoretical frequency
n - is the number of cells in the table.
In addition to the analysis of statistically significant differences, we selected the part
of the results and also used data mining (decision tree method). Calculations made by using
Weka software.
3. RESULTS AND DISCUSSION
By using the Pearson chi-square, we investigated the differences between these
regions. P-value for all kinds of risk greater than 0.05 so not reject the null hypothesis, on the
other hand, we do not have statistically relevant evidence, that H1 is true, as Pearson's χ 2 is
12.3648 at 10 degrees of freedom, the overall P-value is 0.2614 0.05. Tab. 1 presents results˃
in the perception of business risk.
Table 1 Identification of business risks in the Slovak Republic
During your work experience you met many
risks. Which do you consider the
currently as the key?
(Please indicate max. Three answers.)
2013
BA
2013
ZA
2013
TN
P-value
1. market risk (lack of orders) in% *
average value risk **
80,39
56,00
80,49
51,30
82,86
53,27
0,8672***
2.financial risk (poor access to financing companies)
in % average value ** 53,92
31,94
58,54
32,95
50,48
30,01
0,4179
3. operational risk (failure to manage processes) in%
average value **
20,59
24,17
22,56
30,09
14,29
20,71
0,2408
4. personal risk (poor staff) in%
average value **
41,18
31,04
38,41
30,89
47,62
30,77
0,3245
5. legal risk in%
average value **
16,67
37,5
37,20
28,76
32,38
32,01
0,001574

8. 6. security risks (accidents, incidents, etc..) in%
average value ** 29,41
20,28
32,93
24,73
27,62
28,76
0,63
Note: * Data are calculated as the number of respondents who said in response to a given total number of firms;
** Average of the values reported by the entrepreneurs in different regions. *** By using proportional test, we
investigated whether the different types of risk difference occurs between regions. P-value, we determined for
each risk separately.
In this light, the exception is the legal risk, which is in the Bratislava region (16.67%)
significantly lower than in Zilina (37.20%) and Trencin region (32.38%). Here is a P-value of
0.001574 <0.05, indicating that the regions are statistically significant differences in other risk
is at first glance the results of the percentages show that regional differences are not that big.
For more detailed analysis, we provide (Tab. 2) that between Bratislava and Zilina regions
reaches P-value of 0.005872 <0.05, χ 2 Pearson´s value is 11.8162 at 1 degree of freedom.
Similarly, we found a statistically significant difference between the Bratislava and Trencin,
where the P-value reaches 0.0132 <0.05. Difference is demonstrated between Zilina and
Trencin region, where the P-value reaches 0,499 0.05.˃
The results showed that although the alternative H1 can not be statistically verified, we
were able to reject the null hypothesis in the case of legal risk. We found statistically
significant differences in the Bratislava region. On the other hand, SMEs operating in this
region are statistically significant, that means less threatened by this risk as small
entrepreneurs in Zilina and Trencin region.
Table 2 P-value at legal risk
Legal Risk
2013
BA
2013
ZA
2013
TN
P-value
BA:ZA
P-value
ZA:TN
P-value
BA:TN
Share in percentage 16,67 37,20 32,38 0,0005 0,499 0,0132
We assumed that the average value of market risk is in the Bratislava region at least
40%, in comparison with other regions is even higher. Market risk businesses have been
threatened in each region, intensively in the Bratislava region, however, its average height of
56, in the Zilina region 51,30 and 53,27 Trencin region.
The second alternative research hypothesis H2 showed: All businesses suffer as a result
of the financial and economic crisis worsening of conditions of business, which is reflected in

9. the decline in their revenues and profits. Businesses in the Bratislava region, profits and
profitability decreased less than in other regions. Results are presented in Tab. 3.
Table 3 The decline of profitability between regions
How did profitability change?
2013
BA
2013
ZA
2013
TN
P-value
Decreased in % 60 63 69 0,3512
Stabilizated in % 28 21 20 0,3005
Increased in % 12 15 11 0,5573
For the decline of profitability, we found the value of the Pearson χ 2, which is 3.6246,
at 4 degrees of freedom, P-value is 0.4592 0.05, so the second alternative hypothesis H˃ 2 can
not be statistically verified. Differences between regions are glance at least, so we do not start
to analyze individual P-values between pairs of regions.
The third alternative hypothesis H3 was: level of business of optimism is quite high even
at a difficult time. However, we estimate that firms from Bratislava regions are more
optimistic than firms from Zilina and Trencin region. All businesses trying to manage their
financial risk, in order to achieve the lowest possible negative deviations. We assume that
firms in the Bratislava region can better manage financial risk and easier to obtain the
necessary financial resources.
Tab. 4 presents the results on the level of business optimism. The total value of the
Pearson chi-square χ 2 is 8.1193 at 4 degrees of freedom, P-value is 0.0873 0.05. Overall, we˃
are unable to verify H3, that regional differences are not statistically significant. In the partial
P-values, we found that differences between Bratislava and Trencin are more pronounced.
Hypothesis H3 we verify as follows, small and medium enterprises clearly (P-value of
0.01529 <0.05) and with the same concerns (0.00959 <0.01) believe that within five years
will survive in the Bratislava region more than in Trencin region. In short, businesses in the
Bratislava region compared with the Trencin Region are optimistic.
We are interested, how entrepreneurs are able to manage their financial risk to which
they are exposed. Pearson's chi-square value of 9.3048 at 4 degrees of freedom, P-value was
0.05392, which is close to the threshold. The results showed that hypothesis H3 can not be
statistically verified, differences between regions are neither rejected, but even they are not
able to confirm.
Table 4 Rate of entrepreneurial optimism

10. Do you believe that your
company will survive in the
next 5 years?
2013
BA
2013
ZA
2013
TN
P-value
BA:ZA
P-value
ZA:TN
P-value
BA:TN
Absolutely in% 53 41 35 0,0712 0,4276 0,01529
With the same concerns in% 37 49 56 0,07051 0,3351 0,00959
With great concerns in% 10 10 9 1 0,9114 0,9471
During examination of the differences between individual regions, we found differences
between Bratislava and Zilina regions, that means that businesses in the Bratislava region can
better manage their financial risks than those in the Zilina region (see Tab. 5). Between the
Bratislava and Trencin, Trencin and Zilina statistically significant differences are not
confirmed.
Table 5 Ability to manage financial risk
Do you think that
you know to
manage financial
risk?
2013
BA
2013
ZA
2013
TN
P-value
BA:ZA
P-value
ZA:TN
P-value
BA:TN
Yes in % 40 23 32 0,00486 0,1599 0,2623
Sometimes v % 52 68 58 0,0149 0,1265 0,4924
No, i do not know
to assume v %
8 9 10 0,886 0,862 0,662
After analysis of the results by using the Pearson chi-square test and examination of P-
values, we tried to analyze businesses optimism by using the method of decision trees.
As being explained, as variable we chose question 20, which presents how they see their
business existence in the next 5 years. Codes in the program were assessed since zero, and by
zero started as the negative answers and growth escalated until yes.
As explanatory variables we chose the answers to question 19 (Can you manage the
financial risks?), 22 (How did profitability change?) And 13 (Do you know the criteria for
assessing credit?).
To question 20 firms responded as follows: a - do not survive in next 5 years (5
responses), b = survive, but with great concern (28 replies), c = survive, but with some
concerns (180 responses), d = definitely survive (158 responses).
Decision´s criterion was built as follows:
• Successful enterprises (ot20 = 0) - If 19 = 1, 13 = 1, 22 = 1

11. • failed (ot20 = 1 or 2) - where 19 = 3 or 4, if 19 = 22 = 3 and 3 = 3 and 13, or, if 19 and 22 =
4 = 3 = 3 and 13
The resulting matrix provides information of the actual placement of the undertakings:
a b c d
0 0 4 1 | a = 0
0 0 22 6 | b = 1
0 3 101 76 | c = 2
0 2 57 99 | d = 3
From 180 companies that expressed some concerns about the answer to question 20 c
by using the criteria we were able to correctly identify 101 out of 158 companies that have
expressed that they will survive, we were able to correctly estimate total 99.
Software lined up explanatory variables of importance - the results showed that question
19 was the most important explanatory variable to 20 questions, right behind her was
significant question 22 and then 13th.
Eight enterprises answered that they did not manage financial risks (answer to question
19 zero). Only six of them (75%), in fact, answered on question 20 with answer 2 - they think
that will survive with some concern, the other 25% think otherwise.
Conversely, from 112 companies that responded they think that can manage financial
risks, only 71 (64%) answered on the question 20 with answer 3 - they think that will
definitely survive. Other 41 firms believe in something else.
Results showed, it seems that companies that think that they can manage the financial
risks are more cautious in response to whether confidently surviving five years. Only 64% of
those who think that they can manage the financial risks they think that even with certainty
will survive next five years.
Figure 1 Decision tree as a result of questions do you think that your company will survive in
the next 5 years?

12. In sum, 75% of companies that state that can not manage the financial risks they think
will survive, but with some concern. It seems that even when companies think they can not
manage the financial risks its existence again seen so black, with only some concerns about
survival.
4 CONCLUSIONS
The aim of this paper was to define, quantify and compare the actual business risks of
small and medium-sized enterprises in selected regions of Slovakia in the context of loan
finance and business optimism that business segment in Slovakia. We present latest results of
a survey that we conducted among small and medium enterprises in 2013, in which we tried
to find out their views on current business risks to which a lamp.
Analysis, which is part of an international research project undertaken under the name of
current trends in the business risks of small and medium-sized enterprises in selected regions
of the Czech Republic and Slovakia, have been subjected to small and medium sized
enterprises in Bratislava, Trencin and Zilina. The results were evaluated by Pearson chi-
square, which allows us to identify statistically significant differences between regions.
The results of our research brings the following aggregate findings: An alternative
hypothesis 1, we managed to statistically verify only partially: we found that legal risk felt by
small and medium-sized enterprises in the Bratislava region is statistically significantly less
often than those in Zilina and Trencin Region.
H2 we were unable to verify statistically, we did not find statistical evidence supporting
the region and the decrease in profitability after the crisis broke out.

13. Alternative hypothesis H3, we managed to partially statistically verified. According to
the observed results were firms engaged in the Bratislava region optimistic than in Trencin
region. The second finding was that we got to the threshold P-value, when we came very
close to hypothesis that there are differences between the regions and the ability to manage
financial risks P-value of 0.05392 0.05, statistically significant differences detected between˃
Zilina and Bratislava region. Enterprises in the Bratislava region think statistically
significantly more likely to know to manage financial risks better than those in the Zilina
region.
Businesses surveyed report that they feel at higher risk than in the years before the
crisis. Nevertheless, most of them think that will survive (with some concerns). That seems to
have a similar view as well as businesses that think they can not manage financial risks.
The survey was initially focused on the differences between regions. Regional
differences exist, but not always we managed to statistically verify. However, we believe that
our findings will be challenging not only for further theoretical scientific study, but also
economic practice and to allow such rules to be significant differences between regions and
enterprises in their functioning blurred.
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970916.
Authors:
Ing. Monika Sobeková Majková, PhD.
Faculty of Economics and Business, Paneuropean University
monika.majkova@centrum.sk
doc. Ing. Jaroslav Belás, PhD.
Faculty of management and economics,
Univerzita Tomase Bati v Zline
belas111@gmail.com
doc. Ing. Jozef Habánik, PhD.
Faculty of social-economic relations,
Univerzita Alexandra Dubceka, Trencin
jozef.habanik@tnuni.sk

16. doc. Ing. Juraj Sipko, PhD. MBA
Faculty of Economics and Business, Paneuropean University
juraj.sipko@paneurouni.com
Translation to English:
Ing. Antonia Ficova
PhD Candidate at Faculty of Economics and Business, Paneuropean University
antoniaficova@zoho.com