1. 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 Cieom prspevku je definova, kvantifikova a porovna aktulne podnikatesk rizik malch a strednch podnikov vo vybranch reginoch Slovenska v kontexte verovho financovania a podnikateskho optimizmu toho segmentu podnikov na Slovensku. V roku 2013 sme uskutonili prieskum medzi malmi a strednmi podnikatemi, v ktorom sme sa snaili zisti ich nzor na aktulne podnikatesk rizik, ktorm s vystaven. Analyzovali sme podniky psobiace v Bratislavskom, Trenianskom a ilinskom kraji. Prieskum bol sasou medzinrodnej vskumnej lohy: Aktulne trendy v oblasti podnikateskch rizk malch a strednch firiem vo vybranch krajoch R a SR, na ktorej sa podieali Paneurpska vysok kola, ilinsk univerzita, Trenianska univerzita a UTB v Zline. Kov slov: mal a stredn podniky, podnikatesk riziko, trhov riziko, finann riziko, personlne riziko, very, podnikatesk optimizmus Key words: small and medium sized enterprises, business risk, market risk, financial risk, personnel risk, loans, business optimism
2. 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. 3. have Chodasov 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. 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. 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 Majkov (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. 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. 7. Significance level was determined to traditional 5%, or 0.05. Pearson's chi-square test is calculated as follows: (2) where 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 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. 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