“Determinants of innovativeness of Slovak SMEs”

The integration of the Slovak Republic into the European Union and the globalization process create conditions that significantly reduce barriers to entry into particular markets, but, on the other hand, enhance the intensity of competition. The relevance of the study lies in the extent of the European Union’s support for the effectiveness of innovation activities in Slovakia. This paper investigates the influence of endogenous and exogenous factors on the competitiveness of Slovak enterprises over the period 2006–2018. The study is aimed at determining the causal relationship of factors that determine the competitiveness of enterprises. To investigate the relationship between the endogenous and exogenous factors, the Granger causality method is used. Mathematical models are used to identify the relationship between innovation expenditures on the one hand and different types of innovation activity with market expansion on the other. The results of the study provide a statistically significant relationship between the performance measured by the percentage of revenues of enterprises that have introduced innovations with a two-year lag and the concentration measured by the total R&amp;D expenditure of an enterprise. The results of this study should also be used to ensure that, in the case of the Slovak SME sector, R&amp;D expenditure is a significant driver of innovation in enterprises, as innovation in enterprises is expected to improve the quality of products and services, increase profits and expansion in domestic and foreign markets.
AcknowledgmentThis paper has been supported by funds of the project VEGA No. 1/0240/20 and VEGA No. 1/0813/19 Managing the development of innovative and start-up forms of businesses in international environment and verification of INMARK concept, which has received funding from the Ministry of Education, Science, Research and Sport of the Slovak Republic.


INTRODUCTION
Innovation is a key mainspring of economic growth. Through innovation, enterprises can create new markets, increase their competitiveness and efficiency and ensure themselves higher economic growth. In the current turbulent time characterized by a high degree of openness, enterprises are forced to innovate to a much greater extent than in the past. R&D innovation and new knowledge are considered to be a way out of the economic crisis. Many of the European Union member states have high intellectual potential, but most of them do not have sufficient funds to conduct the necessary research and development, provide innovative activity and market innovation. The lack of funding is manifested in the tertiary sector of science, R&D, and in the case of individual enterprises that find it difficult to innovate and improve their production facilities. The European Union has been addressing the issue of R&D and innovation for a long time. It is clear that all these issues contribute to a country's economic growth, initiate job creation and increase its competitiveness. There are many obstacles linked to enterprise innovation in Slovakia such as the lack of financial resources (both own and foreign) or the quality of personnel capacities, which in many cases is considerably limited. In Slovakia, the share of enterprises that use innovation has a long-term declining trend, despite the growing volume of funds spent on research and development. In comparison with global or European innovation leaders, the innovation activity in Slovakia lags significantly behind in almost all evaluated areas. According to the European Commission (RIS, 2019), Slovakia took place below the EU average in evaluating innovation performance. Despite the year-to-year improvement by one place in the position of Slovakia within the EU27, the value of the innovation score of Slovakia has been decreasing from year to year. This indicates that innovation activities are not improving in Slovakia and therefore this topic is more than relevant and current. These objectives take into consideration individual conditions and characteristics of each member state. Europe 2020 set a target of increasing investment in R&D to 3% of GDP by 2020. Innovative small and medium-sized enterprises (SMEs) play a key role in the development of knowledge-based economies. The Slovak Republic is one of the countries with the lowest performance in the field of R&D activities of SMEs. Romania (0.07%), Cyprus (0.08%) and Greece (0.11%) have lower R&D expenditures in GDP (0.13%) than in the Slovak Republic. The highest ratios are reported by Slovenia (0.73%), Belgium (0.7%) and Denmark (0.51%). Slovak SMEs also lag behind other V4 countries. In Hungary, R&D expenditure in GDP reached 0.46%, 0.37% in the Czech Republic, and 0.17% in Poland. Innovation is a term used for a technological invention that is related to the development of new products or new production processes (Kijek, 2013). The first economist to focus on innovation goals was Joseph Schumpeter. He specified five kinds of innovation: the introduction of a new product or a change in the quality of an existing product, implementation of innovative production processes, acquisition of another and more efficient source of supply of domestic resources, and introduction of an innovative industrial organiza-tion (Schumpeter, 1934). Innovation can also be the result of a response to changes in the external environment or a preventive action affecting the environment (Mansfield, 1968). In some EU countries, there may be significant differences in overall innovation performance and performance across dimensions. On average, the EU's innovation performance has increased by 8.8% since 2011. Since 2011, innovation performance has increased in 25 EU member states. Performance increased the most in Lithuania, Greece, Latvia, Malta, the United Kingdom, Estonia and the Netherlands, and decreased the most in Romania and Slovenia. Figure 1 shows EU countries' innovation index in individual dimensions.

LITERATURE REVIEW AND ANALYSIS
Innovation in small and medium-sized enterprises is the driving force behind economic growth. In comparison with global or European innovation leaders, the innovation activity of the Slovak Republic lags significantly behind in almost each of the evaluated areas. Slovak SMEs have significant shortcomings in the implementation of business innovations, which results not only from the internal but also the external environment. Apart from limited investment in innovation, they do not pay enough attention to new trends in digitization and R&D.

AIMS, HYPOTHESES AND RESEARCH VARIABLES
The paper deals with the assessment of the problem of innovation, its impact on family businesses and expenditure on innovation in the SME sector. It is very important to examine the causality of the rela-Source: Authors' calculations. tionship between spending on types of innovation activities and the impact of innovation on market expansion. The study focuses on the effectiveness of financial support for innovation. The aim of this study is to verify the basic hypothesis that declares the existence of causal relationships between the most problematic areas of innovation such as finance and support, the innovation environment and the underperformance of enterprises, using established independent and dependent variables. The following hypothesis is formulated to achieve this goal: H0: The most problematic areas in the field of innovation are finance and support, barriers to the innovation environment and insufficient competitiveness of enterprises represented by the set variables.
Adequate data has to be collected to analyze the relationship between innovation and enterprises. The variables used in the analysis are as follows: the percentage of revenues of organization that introduced innovations (P 2 ), the percentage of enterprises that implemented product innovation developed by other enterprises or institutions (P 7 ), and the percentage of enterprises that developed process innovation (P 8 ). The following variables were used as explanatory variables: total expenditure in extramural R&D at the enterprise (X 2 ), total expenditure of acquiring external knowledge (X 3 ), total spending on purchasing machinery, equipment, software and buildings (X 4 ).

METHODOLOGY AND DATA
The innovation statistical survey methodology is being developed as part of the process of implementing the statistical methodology of the EU member states. It is based on the OSLO manual methodology of OECD/Eurostat and it is harmonized with the Community Innovation of the EU member states. It refers to issues of product and process innovation, on-going and completed innovation activities and R&D spending. Enterprises are defined as statistical units in this study, and the set of the reporting detachment is based on the official statistical business register as a combination of transparent and stratified survey sample in specific sectors of economic activity.
This condition has to be confirmed before the Granger test of causality is used.
The condition is that the given data are stationary. The stationarity means that the probability function does not depend on time. It is important not to meet the condition of stationarity at the original level in the Granger analysis, however, it must be confirmed for the first differences. To determine the stationarity of the given variables that represent the subjects of interest, the Augmented Dickey-Fuller test (ADF) test was chosen to verify that the examined data have a single root. To study the mentioned relationship, the panel Granger causality approach was used.

RESULTS
This study analyzes the relationship between innovation expenditures and different types of innovation activity and market expansion applying the panel Granger causality framework. It can be stated that the support of business activities will have an effect only on the basis of a time lag. The exact time shift to the quantitative one is determined on the theoretical basis of the Schwarz condition. In this case, it is a two-year delay.
Before proceeding to determine the causality of the selected variables, it is necessary from a methodological point of view to conduct ADF tests on panel data. The specified variables must satisfy the condition of non-stationarity. It is assumed that not all variables for determining causation are stationary. Stationary data are tested using the ADF test. The null hypothesis in both tests assumes that the data show non-stationarity. The results show the stationarity analysis (see Table 1) and allow rejecting the null hypothesis at the 1st differences.
This statement is verified using F-statistics. The null hypothesis is accepted if the probability was  Table 2, both in the case of causality of relationships between the innovation expenditures and also for different types of innovation activity and market expansion. H0 hypothesis is tested to accept that there is no Granger causality between the variables. The zero hypothesis is rejected if the probability falls below 0.05. In this case, the alternative hypothesis is accepted. Table 3 shows only those results where the Granger causality is proved.
Granger causality results from the percentage of revenues of organization that introduced innovations to the total expenditure on extramural R&D, percentage of enterprises that implemented product innovation developed by other enterprises, the percentage of enterprises that developed process innovation separately to total procurement of machinery, equipment, software and premises.
It is declared that Granger causality occurs: P 2 to X 2 ; P 7 to X 2 ; P 8 to X 4 ; P 2 , P 7 k to X 2 ; P 2 , P 8 to X 2 ; P 8 , P 7 to X 2 ; P 8 , P 7 to X 4 ; P 8 , P 7 , P 2 to X 2 . It can be confirmed that the percentage of revenues of the organization that introduced innovation causes the total expenditure in extramural R&D at the enterprise; the percentage of enterprises that implemented product innovation developed by other enterprises or institutions, the percentage of enterprises that developed process innovation causes equipment, software and buildings.
These results are consistent with the hypothesis that there is a negative relationship between innovation spending and market expansion. Figure 2 presents the analysis of individual variables -the percentage of revenues of organizations introducing innovation, the percentage of organizations that implemented product innovation developed by other enterprises or institutions, and the percentage of organizations that developed process innovation on their own. As explanatory variables, the following variables were used: the total expenditure on extramural R&D at the enterprise, the total expenditure for acquiring external knowledge, the total expenditure for purchasing machinery, equipment, software and buildings. A Q-Q (quantile-quantile) plot is created by plotting two sets of quantiles against each other. If the two distributions are similar, then the points would lie close to the identity line.

Null hypothesis F statistics Probability Result
There is no evidence of causality between P 2 and X 2 5.7632 0.0257 Reject H0 There is no evidence of causality between P 2 and X 3 0.0020 0.9650 Accept H0 There is no evidence of causality between P 2 and X 4 0.4586 0.5057 Accept H0 There is no evidence of causality between P 7 and X 2 5.4332 0.0298 Reject H0 There is no evidence of causality between P 7 and X 3 0.2479 0.6237 Accept H0 There is no evidence of causality between P 7 and X 4 3.2548 0.0855 Accept H0 There is no evidence of causality between P 8 and X 3 0.9657 0.3369 Accept H0 There is no evidence of causality between P 8 and X 4 5.3103 0.0315 Reject H0 There is no evidence of causality between X 2 and P 2 0.6803 0.4187 Accept H0 There is no evidence of causality between X 2 and P 7 0.0371 0.8491 Accept H0 There is no evidence of causality between X 2 and P 8 2.1097 0.1611 Accept H0 There is no evidence of causality between X 3 and P 2 0.1950 0.6633 Accept H0 There is no evidence of causality between X 3 and P 7 0.1316 0.7204 Accept H0 There is no evidence of causality between X 3 and P 8 1.1962 0.2865 Accept H0 There is no evidence of causality between X 4 and P 2 0.9761 0.3344 Accept H0 There is no evidence of causality between X 4 and P 7 0.5886 0.4515 Accept H0 There is no evidence of causality between X 4 and P 8 0.164 0.6896 Accept H0 According to the obtained results, all variables show a negative correlation; the strongest correlation is found between the revenues measured by enterprises that have introduced innovation. A strong relationship is found between the performance measured by the percentage of companies

Null hypothesis F statistics Probability Result
There is no evidence of causality between P 2 , P 7 and X 2 5.5791 0.02576 Reject H0 There is no evidence of causality between P 2 , P 8 and X 2 6.1659 0.02155 Reject H0 There is no evidence of causality between P 7 , P 8 and X 2 4.3462 0.04948 Reject H0 There is no evidence of causality between P 7 , P 8 and X 4 5.0912 0.03483 Reject H0 There is no evidence of causality between P 2 , P 7 , P 8 and X 2 6.0230 0.02293 Reject H0 Source: Own calculations. Figure 2. Q-Q plots for X 2 , X 3 , X 4 , P 2 , P 7 , and P 8 that implemented product innovation developed by other companies or institutions.
The innovative activities of Slovak SMEs are compared with other EU countries at a low level. Despite the fact that not only entrepreneurs themselves, but also the government realize the importance of introducing innovations, the development of recent years does not indicate that the innovation environment in Slovakia is getting to be significantly improved.
Hypothesis H0 was confirmed -The most problematic areas in the field of innovation implementation are finance and support, barriers to the innovation environment and insufficient competitiveness of enterprises presented by the set variables P 2 , P 7 , P 8 , X 2 , X 3 , X 4 .

CONCLUSION
The financial crisis has affected the impact of innovation on Slovak small and medium-sized enterprises.
According to the available data, the level of R&D activities of SMEs, as measured by R&D expenditure, is improving slightly. Compared to EU countries and other V4 countries, the performance of Slovak SMEs in this area lags far behind.
Using the selected indicators such as the percentage of enterprises that have introduced innovations, the percentage of enterprises that implemented product innovations developed by other enterprises or institutions, the percentage of enterprises that developed process innovation separately, the total external spending enterprise R&D, total external business acquisition expenditure, total procurement of machinery, equipment, software and buildings, a significant causal relationship is confirmed between the percentage of sales of enterprises that have introduced innovations and total spending on external R&D at an enterprise and the relationship between product innovations developed by other enterprises or institutions and total spending on external R&D at the enterprise. This relationship is one-way, and the opposite effect has not been proven. The competitiveness of enterprises depends on the impact of many processes and mechanisms, both endogenous and exogenous. In the field of research, production, business, management and financial activities, innovation of their approach is an important factor determining the competitiveness of companies.
In the case of the Slovak SME sector, R&D expenditure appears to be a significant driver of innovation. The results of the study confirm that companies are aware of the importance of innovation. The main barriers to innovation are mainly the lack of financial resources, according to which financing innovation in Slovakia is one of the biggest problems. While companies are aware of the need for innovation, they do not pay enough attention to it. However, the COVID-19 pandemic has shown reality to many companies. Many small and medium-sized enterprises were unable to react quickly to the situation, which affected the functioning of many of them. However, the increased innovation activity of Slovak SMEs will certainly contribute to the creation of a more suitable innovation environment.