AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
Table 3: R2 Trends in related economic branch
Likert scale
Frequency (%)
Mann – Whitney U
test
TE
TO
0
5.6
13.3
p=0.451537
1
12.5
53.3
2
29.2
20.0
3
30.6
6.7
4
18.1
6.7
5
4.2
13.3
Source: results of own research calculated in program
STATISTICA
In case of evolution the risk related to trends in related economic
branch, 53,3% of tourism respondents perceived this risk
category as a risk with very low level of risk. On the contrary,
30,6% of technological SMEs perceived this risk as a risk with
middle level of risk. If we compare the risk perception of
respondents evaluated by value 5 on Likert scale, 13,3% of
tourism respondents and only 4,2% of technological respondents
evaluated this risk category by this value. The p-value of Mann-
Whitney U test confirm null hypothesis. It means, that three are
no differences in perception of this risk category between two
groups of respondents.
Table 4: R3 Financial support of clusters from the government
Likert scale
Frequency
(%)
Mann – Whitney U test
TE
TO
0
18.06
13.3
p=0.765878
1
18.06
33.3
2
25.00
13.3
3
26.39
33.3
4
6.94
6.7
5
5.56
13.3
Source: results of own research calculated in program
STATISTICA
Financial support of government is important factor for existing
and functioning of clusters in other economies. In Slovakia, the
support is low and clusters rely mainly on own resources. If we
evaluate the results of respondents’ risk perception it seems, that
this risk category is more important for technological than
tourism SMEs. However, the level of p-value showed that
between perceptions between two groups of respondents are not
differences.
Table 5: R4 Investment
Likert scale
Frequency
(%)
Mann – Whitney U
test
TE
TO
0
9.7
20.0
p=0.116995
1
6.9
13.3
2
15.3
20.0
3
29.2
20.0
4
19.4
20.0
5
19.4
6.7
Source: results of own research calculated in program
STATISTICA
The common investment in clusters is important factor for
building competitiveness as well as cluster as well as their
stakeholders. For Slovakia is typical the low volume of private
investments in research and development and a low level of
cooperation of educational institutions with the private sector in
research and development. (Fabuš, 2015) If we take into account
the evaluation of the respondents on the Likert scale, the value 5
was significant for 19,4% of technological respondents and only
6,7% of tourism respondents. The results of Mann-Whitney test
showed, that null hypothesis could not be rejected. It means that
there are no differences between respondents’ perception.
Individual actors influence the innovative processes and
collaboration being necessary for creation and operation of an
innovative environment. Collaboration takes place in a number
of ways. It is a support for innovative networks and cooperation,
provision of knowledge and information for businesses to reduce
uncertainty in their economic activities, a support for incentives
structure that will ensure the profitability of innovation in long
run and so on (Kordoš and Kraj
ňáková,2018). The results of
realized questionnaire surveys showed, that the innovation are
perceived as a risk with very high level of risk by 20,0% of
tourism SMEs and only 6,9% of technological SMEs. The
results of Mann-Whitney test showed, that we couldn’t observe
the differences in perception of respondents.
Table 6: R5 Innovation
Likert scale
Frequency (%)
Mann – Whitney U test
TE
TO
0
5.6
20.0
p=0.261155
1
11.1
13.3
2
22.2
20.0
3
33.3
20.0
4
20.8
26.7
5
6.9
20.0
Source: results of own research calculated in program
STATISTICA
We can observe various relationships and hierarchy of them
among partners in cluster. For future competitiveness and
activities of clusters the relationships among partners are very
important. Around 20% of respondents in both group perceived
this risk factor as a risk with high level of risk. The result of
Mann-Whitney test showed, that there are not differences among
respondents’ answers.
Table 7: R6 Partners
Likert scale
Frequency
(%)
Mann – Whitney U test
TE
TO
0
4.2
13.3
p=0.113111
1
8.3
26.7
2
25.0
20.0
3
31.9
13.3
4
20.8
20.0
5
9.7
6.7
Source: results of own research calculated in program
STATISTICA
For risk assessment, we used the tool – Pareto analysis. This
technique helps to identify the top 20% of causes that need to be
addressed to resolve 80% of the problems. (Erdil and
Taçgın).The average values of respondents' answers were used
as the baseline data for the Pareto’s analysis. With Pareto's
analysis, we have identified the most important risk categories
for SMEs with cluster’s experience that need to be prioritized.
Figure 4: Results of Pareto’s analysis
Source: results of own research
Figure 4 showed, that most important risk categories for SMEs
are: R4. Investment, R6. Partners, R5. Innovation, R1.
Macroeconomic problems in regions.
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