Geography Reference
In-Depth Information
Table 9.5 Adjusted mean scores for consumerism, environmentalism, and environmental
behavior (maximum = 100)
DV
Environmental
behavior
IV
Consumerism
Environmentalism
Gender
Male (253)
NS
NS
NS
Female (247)
Age (years)
20-29 (156)
51.4
72.1
73.6
30-39 (132)
47.9
70.8
79.4
40-49 (80)
48.4
68.9
81.5
50-59 (67)
46.2
67.7
86.4
60 + (65)
45.7
69.5
84.7
Educational attainment
Primary (39)
44.7
67.3
85.3
Middle (42)
45.7
66.7
83.3
High (180)
47.8
69.6
82.7
University (239)
50.3
71.9
75.6
Residential area
Rural (149)
NS
NS
82.2
Urban (351)
78.4
Religion
None (164)
NS
70.5
75.8
Buddhism (179)
68.6
82.0
Christianity (122)
72.7
80.4
Other (35)
69.9
81.5
Monthly income (USD)
Less than 999 (49)
45.7
NS
85.9
1,000-1,999 (209)
49.0
79.6
2,000-2,999 (147)
48.5
80.8
3000 + (95)
49.0
74.3
Civic engagement
None (202) 50.3 68.8 77.2
Passive (216) 47.8 71.2 80.7
Active (82) 46.2 71.7 82.2
Total (500) 48.6 70.3 79.5
Note : DV dependent variable, IV independent variable; number of interviewees in parentheses;
NS no significant difference at the 0.100 significance level
scale items is termed underlying factor, and this cluster can be extracted by a factorial
analytic technique (for details of the technique, see Rummel 1979 : 323-348). I used
the principal components method for extracting the factor structure of consumerism,
environmentalism, and environmental behavior, respectively (for the advantages
and functions of the principal components method, see Jeong 2004 : 347-349),
using a varimax rotation such that each defines a separate cluster of highly inter-
related variables and is as specific to this cluster as possible (Rummel 1979 : 170-171).
 
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