|
All the variables of ISSP 2007 are not used in this study. Only those that are related to the concerts, theatre and exhibitions are used according to the purpose of the study. The questionnaire has the following question: How often during the past 12 months on your leisure did you go to concerts, theatrical performances, art exhibitions, etc.?” The descriptive statistics are presented in table 4-3.
Table 4 : ISSP 2007, ”How often in your leisure do you go to concerts, exhibitions, theatre etc.?”
|
Daily
|
Several times per week
|
Several times per month
|
Less often
|
Never
|
Missing
|
Frequency
|
0
|
4
|
71
|
1040
|
209
|
30
|
%
|
0
|
0,3
|
5,2
|
76,8
|
15,4
|
2,2
|
% of responses
|
0
|
0,3
|
5,4
|
78,5
|
15,8
|
--
|
Women, %
|
0
|
0,3
|
6,6
|
81,2
|
11,3
|
n = 741
|
Men, %
|
0
|
0,3
|
3,9
|
74,3
|
21,5
|
n = 568
|
|
|
|
|
|
|
|
Women, %
|
|
|
|
|
|
|
15 < age < 24
|
0
|
1,1
|
4,5
|
78,7
|
15,7
|
n = 89
|
25 < age < 34
|
0
|
0
|
1,9
|
85,5
|
15,5
|
n = 103
|
35 < age < 44
|
0
|
0
|
0,8
|
88,9
|
10,3
|
n = 117
|
45 < age < 54
|
0
|
0
|
6,7
|
85,2
|
8,1
|
n = 135
|
55 < age < 64
|
0
|
0
|
10,2
|
80,8
|
9,0
|
n = 167
|
65 < age
|
0
|
0,7
|
12,3
|
74,6
|
12,3
|
n = 130
|
Men, %
|
|
|
|
|
|
|
15 < age < 24
|
0
|
0
|
5,2
|
58,6
|
36,2
|
n = 58
|
25 < age < 34
|
0
|
1,3
|
2,7
|
78,7
|
17,3
|
n = 75
|
35 < age < 44
|
0
|
0
|
4,2
|
80,2
|
15,6
|
n = 96
|
45 < age < 54
|
0
|
0
|
3,5
|
76,3
|
20,2
|
n = 114
|
55 < age < 64
|
0
|
0,8
|
4,7
|
73,2
|
21,3
|
n = 127
|
65 < age
|
0
|
0
|
3,1
|
73,5
|
23,5
|
n = 98
|
|
|
|
|
|
|
|
It is most reasonable to divide from the point of view of further analysis the visit activity into three classes: regularly (daily, several times per week, several times per month), occasionally (less often) and never. The results of the analysis of variance are presented in table 4-4.
Table 4 : Visitor density: concerts, theatrical performances, art exhibitions, ANOVA
Grouping variable
|
F-value (sig.)
|
ή2
|
Grouping variable
|
F-value (sig.)
|
ή2
|
ANOVA
|
|
|
|
|
|
Gender (S)
|
26,218 (0,000)
|
0,019
|
Year of birth(Y)
|
1,319 (0,055)
|
0,062
|
|
|
|
|
|
|
Province (A)
|
2,624 (0,000)
|
0,037
|
Education (E)
|
10,175 (0,000)
|
0,060
|
|
|
|
|
|
|
MANOVA
|
Gender (S)
|
20,068 (0,000)
|
|
Gender (S)
|
12,695 (0,000)
|
|
Year of birth (Y)
|
1,366 (0,036)
|
|
Province (A)
|
2,612 (0,000)
|
|
S*Y
|
1,025 (0,426)
|
0,130
|
S*A
|
0,663 (0,857)
|
0,064
|
|
|
|
|
|
|
Gender (S)
|
25,716 (0,000)
|
|
Year of birth (Y)
|
1,099 (0,291)
|
|
Education (E)
|
9,638 (0,000)
|
|
Province (A)
|
1,755 (0,022)
|
|
S*E
|
2,115 (0,032)
|
0,089
|
Y*A
|
1,029 (0,363)
|
0,523
|
|
|
|
|
|
|
Year of birth (Y)
|
1,655 (0,002)
|
|
Province (A)
|
1,188 (0,260)
|
|
Education (E)
|
9,394 (0,000)
|
|
Education (E)
|
3,594 (0,000)
|
|
E*Y
|
1,127 (0,102)
|
0,374
|
A*E
|
1,054 (0,328)
|
0,193
|
|
|
|
|
|
|
Gender (S)
|
7,485 (0,006)
|
|
Gender (S)
|
11,581 (0,001)
|
|
Year of birth (Y)
|
1,295 (0,078)
|
|
Province (A)
|
1,429 (0,104)
|
|
Province (A)
|
1,569 (0,060)
|
|
Education (E)
|
3,329 (0,001)
|
|
S*Y
|
1,171 (0,193)
|
|
S*A
|
1,221 (0,231)
|
|
S*A
|
0,681 (0,813)
|
|
S*E
|
1,598 (0,121)
|
|
Y*A
|
1,123 (0,100)
|
|
A*E
|
1,144 (0,137)
|
|
S*Y*A
|
1,178 (0,126)
|
0,688
|
S*A*E
|
1,403 (0,010)
|
0,314
|
|
|
|
|
|
|
Gender (S)
|
15,496 (0,000)
|
|
Year of birth (Y)
|
1,764 (0,002)
|
|
Year of birth (Y)
|
1,510 (0,010)
|
|
Province (A)
|
1,775 (0,027)
|
|
Education (E)
|
8,314 (0,000)
|
|
Education (E)
|
4,735 (0,000)
|
|
S*Y
|
1,233 (0,120)
|
|
Y*A
|
1,162 (0,101)
|
|
S*E
|
1,575 (0,129)
|
|
Y*E
|
1,324 (0,018)
|
|
Y*E
|
1,226 (0,018)
|
|
A*E
|
1,174 (0,188)
|
|
S*Y*E
|
1,149 (0,152)
|
0,535
|
Y*A*E
|
0,975 (0,532)
|
0,861
|
Education: 1 = pupil, student, 2 = elementary school, 3 = comprehensive school, 4= vocational school or course, 5= upper secondary school, 6 = college 7= university of applied sciences, 8 = bachelor, university, 9 = master, university
(significance in parenthesis)
|
The statistical programme (PASW 18) available did not conduct the multivariate analysis of variance (MANOVA) with four explanatory variables (gender, year of birth, place of province and education). On the basis of the results it is clear that the first hypothesis is supported: performing arts visitor density depends on gender, person’s age and education. Moreover, the regional supply has an effect. The variance analysis shows that every explanatory variable (gender, year of birth, place of province, and education) would alone separate into classes: regularly, occasionally and never. The joint effect of the explanatory variables is nearly always significant if the education variable is present. In the table 7 different genders have been examined separately. Both for women and men, education would seem to be the crucially important variable.
Table 4 5:
Table 4 : Visitor density, concerts, theatrical performances, art exhibitions. Anova and Manova, Women and Men separately
Grouping variable
|
F-value (sig.)
|
ή2
|
Grouping variable
|
F-value (sig.)
|
ή2
|
ANOVA Men
|
|
|
ANOVA Women
|
|
|
Year of birth
|
1,007 (0,465)
|
0,112
|
Year of birth
|
1,454 (0,017)
|
0,116
|
Province
|
1,870 (0,014)
|
0,061
|
Province
|
1,202 (0,249)
|
0,031
|
Education
|
6,501 (0,000)
|
0,087
|
Education
|
5,186 (0,000)
|
0,055
|
MANOVA
|
Men
|
|
|
Women
|
|
|
Year of birth (Y)
|
1,007 (0,473)
|
|
Year of birth (Y)
|
1,198 (0,169)
|
|
Province (A)
|
1,208 (0,203)
|
|
Province (A)
|
0,655 (0,861)
|
|
Y*A
|
1,238 (0,066)
|
0,746
|
Y*A
|
1,002 (0,495)
|
0,621
|
|
|
|
|
|
|
Year of birth (Y)
|
0,829 (0,807)
|
|
Year of birth (Y)
|
2,281 (0,000)
|
|
Education (E)
|
5,062 (0,000)
|
|
Education (E)
|
5,888 (0,000)
|
|
Y*E
|
1,035 (0,395)
|
0,527
|
Y*E
|
1,335 (0,006)
|
0,525
|
|
|
|
|
|
|
Province (A)
|
1,413 (0,116)
|
|
Province (A)
|
1,021 (0,434)
|
|
Education (E)
|
2,724 (0,006)
|
|
Education (E)
|
1,819 (0,071)
|
|
A*E
|
1,447 (0,006)
|
0,370
|
A*E
|
0,924 (0,699)
|
0,232
|
|
|
|
|
|
|
Year of birth (Y)
|
1,575 (0,051)
|
|
Year of birth (Y)
|
1,612 (0,018)
|
|
Province (A)
|
2,209 (0,013)
|
|
Province (A)
|
0,756 (0,752)
|
|
Education (E)
|
3,817 (0,001)
|
|
Education (E)
|
3,111 (0,004)
|
|
Y*A
|
1,533 (0,044)
|
|
Y*A
|
1,098 (0,303)
|
|
Y*E
|
1,573 (0,051)
|
|
Y*E
|
1,324 (0,078)
|
|
A*E
|
0,944 (0,514)
|
|
A*E
|
0,927 (0,566)
|
|
Y*A*E
|
--
|
0,948
|
Y*A*E
|
--
|
0,885
|
Even if the ISSP 2007 data would make it possible to use other explanatory variables, these are not used since, based on rather high values of ή2, the variables are adequate to explain consumers’ performing arts behaviour. Any single variable alone is not good enough, but a combination of the variables explains more.
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