AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
Electrotechnical
cluster -
Western
Slovakia
unk.
Energetic
cluster –
Western
Slovakia
1
Cluster of
Regional
Development
- Western
Slovakia
unk.
Cluster for
support of
innovative and
green
technologies
unk.
TN
Slovak IT
Klaster
8
Cluster Váh
unk.
NR
Slovak plastic
cluster
14
Association
of Tourism –
Cluster
Topoľčany
4
Bioeconomy
Cluster
6
ZA
Z@ict
7
Cluster
LIPTOV –
Association
of Tourism
4
Cluster
ORAVA
12
Cluster
TURIEC –
Association
of Tourism
3
BB
1st Slovak
Engineering
Cluster
5
Cluster of
the border
castles
unk.
KE
Cluster AT + R
z. p. o.
10
Tourism
Cluster
Košice
unk.
Cluster
RADAR
2
BITERAP
7
Košice IT
Valley
19
PO
Cluster EKPK
1
-
-
Railway
transport cluster
1
Total
18
96
9
23
Source: own research, TE-Technological clusters, TO-Tourism
clusters, *analysis conducted in 2016-2017, data may currently
vary.
Qualitative data for this research were collected through the
questionnaire surveys. The relevant population of this research
are SMEs with experience in cluster cooperation. The population
consists of 87 SMEs. With reference to the typology of Slovak
clusters, 72 of 96 respondents belonged to the technological
SMEs while 15 of 23 belonged to the tourism SMEs.
Respondents were asked to evaluate the selected categories of
risks that could occur in the case of cluster cooperation and
which are significant from their point of view. A subjective
perception of risk was assigned by respondents on Likert scale
from 0 – the risk does not apply to the business, 1 – very low
level of risk, 2 – low level of risk, 3 middle level of risk, 4 –
high level of risk, 5 – very high level of risk.
For this paper authors selected risks categories from the areas
mentioned in the part Introduction and which are the most
important and negatively affect the entrepreneurial activities of
SMEs in case of cluster cooperation:
R1. Macroeconomic problems in regions,
R2. Trends in economic branch,
R3. Financial support of clusters from the government,
R4. Investment,
R5. Innovation,
R6. Partners.
To fulfill the main task of the article, we formulated the
following statistical hypotheses:
H0: There are not significant differences between evaluation of
risk categories in both groups of respondents (technological and
tourism).
H1: There are significant differences between evaluation of risk
categories in both groups of respondents (technological and
tourism).
To evaluate the statistical hypotheses we utilized
the tools of the
descriptive statistics (figures and relative frequency).
In order to meet main aim stated, we used empirical research
methods (questionnaire), statistical methods (non-parametric
Mann-Whitney U test that is appropriate for low research
sample), the Pareto analysis, a tool that is used in quality
management and statistical software Statistica.
3 Results
First we focused on descriptive statistics. In general the SMEs
from tourism area perceived risk categories in different way than
from technological area (Figure 2). When SMEs from category
of tourism clusters (Figure 3) assessed all risk categories on the
similar level – mean around 2,0 in technological SMEs the
differences in relevance of the risk categories are visible (mean
between 2,03 to almost 3,0).
Figure 2 Descriptive statistics Figure 3 Descriptive statistics
of Technological SMEs
of Tourism SMEs
Source: results of own research calculated in program
STATISTICA
Following tables show the results of respondents evaluation
expressed in % and the value of p - level of the Mann-Whitney U
test. In the case where the p - value is less than the level of 0.05,
the null hypothesis is rejected, and vice versa.
Table 2: R1 Macroeconomic problems in regions
Likert scale
Frequency (%)
Mann – Whitney U
test
TE
TO
0
5.6
6.7
p=0.551481
1
13.9
26.7
2
22.2
20.0
3
33.3
20.0
4
22.2
20.0
5
2.8
6.7
Source: results of own research calculated in program
STATISTICA
This category of risk was perceived by 26,7% of respondents
from category of tourism SMEs as a risk with low level and by
33,3% of respondents from category of technological SMEs as a
risk with middle level of risk. Only 2,8% of tourism SMEs and
6,7% of technological SMEs perceived this category of risk as a
risk with very high level of risk. The results of p –value of
Mann-Whitney U test showed, that null hypothesis could not be
rejected. It means that there are not differences in the perception
of this risk between tourism and technological SMEs.
- 116 -