AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
afford to define potential influence of these variables. During
analysis, there was applied test of dependency with paucity of
external influence. On base of described theory, there is assigned
hypothesis (see chapter 2), which had to be transformed into
statistical hypothesis. These statistical hypothesis are designed of
null form (as follow). In case of acceptation of alternative
hypothesis, there is change in explanation from “there is no
dependence” to “there exist dependence”, which could be
consider as statistical hypotheses (and could be put under
statistical evaluation):
H1
0
: working in educated profession does not arise threat;
H2
0
: control skills of more professions does not evoke
threat;
H3
0
: workers’ opinion of industry 4.0 does not provoke
threat;
H4
0
: foreknowledge of industry 4.0 does not set up threat.
Main problem of Industry 4.0 concept is that it is still unknown
by industrial environment, managers of manufacturing
companies and as well by appropriate employees. In case they
know this concept, they usually have kind of myth in their
minds. Therefore, authors want to answer if working
experiences, theoretical knowledge can impress potential
acceptation of the concept in individual corporate fields (with no
reference to the kind of industry).
There were participated 95 employees, which are employed in
three locations, in German (Stuttgart area) and in Czech
Republic (Brno area) and in Canada (Windsor are, Ontario).
These locations were chosen on connection to their focus in
heavy-machinery industry. For purpose of the research were
asked their employees, from which coincide to participate and
deliver fulfill questionnaire only 95 persons. Their answers were
categorized and put under evaluation by chosen statistical
methods.
To verify defined premises, a pivot table was created for
question “Do you except threat of position in next 10 years” with
(1) working in educated profession; (2) control skills of more
professions; (3) workers’ opinion of industry 4.0; (4)
foreknowledge of industry 4.0. Individual values of potential
connection between variables are displayed in Table 1.
Pivot table shows relations between factors of threat expectation
in the future and consciousness of industry 4.0 as concept. It is
obvious that employees consider their working positions as
substantial for the company and they don’t feel any potential
threat because of the implementing of automatization. The
biggest group includes respondents describes situation, that after
automatization there will be still required high qualified workers
(34 persons). In the second group of respondents there are 33
workers, which need of qualified workers. The third group didn’t
mention any specific reason for future need (17 persons).
Table 1 Pivot table of variables in linkage to potential future threat
No
a
n
swe
r
no
, m
y
pr
o
fe
ss
io
n
w
o
ul
d be
s
ti
ll
req
u
ired
(
la
ck
o
f
q
u
a
li
fi
ed
w
o
rk
ers
)
no
, m
y
pr
o
fe
ss
io
n
w
o
ul
d be
s
ti
ll
req
u
ired
no
, m
y
pr
o
fe
ss
io
n
w
o
ul
d be
s
ti
ll
req
u
ired
o
v
er
a
u
to
m
a
ti
za
ti
o
n
y
es
, a
u
to
m
a
ti
za
ti
o
n
d
ecr
ea
se
d
if
fi
cu
lt
y
o
f
wo
rk
y
es
, r
o
b
o
ts
rep
la
ce
w
o
rke
rs
due
st
a
nda
rd
iz
a
ti
o
n a
nd
a
u
to
m
a
ti
za
ti
o
n
Total
H1
educated
profession
qualified by
experience
1
8
6
19
1
0
35
95
yes
3
25
11
15
5
1
60
H2
multi-
profession
skills
no answer
0
0
1
0
0
1
95
no
1
13
1
15
3
0
yes
3
20
15
19
3
0
H3
comprehension
of industry 4.0
no answer
1
0
1
0
0
1
95
fiction
0
3
1
1
0
0
behind us
0
1
0
1
0
0
computer coming
0
1
0
0
0
0
Robots
0
9
4
9
0
0
digitalization
3
19
11
23
6
0
H4
foreknowledge
of industry 4.0
hear first time
3
19
9
11
0
0
95
do not know details
1
14
5
19
1
0
know details
0
0
3
4
5
1
Total
4
33
17
34
6
1
Source: own work by authors
According to premises there is kind of limitation because some
cells have zero value, which usually requires merging of
separated answers. All of these values were put into
determination of proposed affinities and evaluation by Pearson’s
chi-square test for variable independence.
From realized test of independence, there was employed
Pearson’s chi-square test for independence. Due the processing
of the data there was important to reach significance level of
95 %. This level could be described as the situation, in which
exist 5 % fault in case of choosing alternative hypothesis. This
error value is recall as significance, regard as level of reliability.
If the value of significance is less than 0,05, than is possible to
accept alternate hypothesis and is possible to conclude existence
of dependence between chosen variables.
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