8146.0.55.001 - Patterns of internet access in Australia, 2006  
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Contents >> Combined Analysis >> Chapter 8 Internet Connectivity by Combined Geographic and Socio-Economic Characteristics.

CHAPTER 8 INTERNET CONNECTIVITY BY COMBINED GEOGRAPHIC AND SOCIO-ECONOMIC CHARACTERISTICS.

In chapters 3 through 6 of this paper, Internet connectivity has been analysed from regional and socio-economic perspectives. In chapter 7, Internet connectivity for Indigenous people has been investigated. Higher income, presence of school going children in families and geographic location (with regard to remoteness) emerged as factors having relatively strong take-up of the Internet in cross-tabular outputs and Chapter 8 combines key outputs of this analysis. This chapter analyses Internet connectivity, disaggregated by remoteness area, by selected income ranges and household characteristics. The analysis by income is extended further to indigenous and non-indigenous people.

Table 14: Access to Any Internet and Broadband Connection , by Remoteness and Weekly Equivalised Household Income

Nil, negative or between
$1 and $399
Between $400 and $1,299
$1,300 or more
Any Internet
BB connection
Any Internet
BB connection
Any Internet
BB connection
%
%
%
%
%
%

Major Cities
42
26
72
48
87
66
Inner Regional
39
19
67
37
82
52
Outer Regional
37
15
64
32
79
46
Remote
35
14
63
33
79
50
Very Remote
19
10
59
33
79
50

Table 15: Access to Internet by Indigenous Status , by Remoteness by Weekly Equivalised Household Income

Nil, Negative or Between
$1 and $399
Between $400 and $1,299
$1,300 or More
Any internet
BB Connection
Any internet
BB Connection
Any internet
BB Connection
%
%
%
%
%
%

Non-Indigenous
Major Cities
42
26
72
49
87
66
Inner Regional
40
20
68
37
82
52
Outer Regional
38
16
65
32
79
46
Remote
38
15
65
33
79
50
Very Remote
37
21
65
37
80
50
Indigenous
Major Cities
36
22
64
43
80
59
Inner Regional
34
19
60
33
74
46
Outer Regional
26
13
50
27
69
42
Remote
15
8
44
25
65
42
Very Remote
6
3
29
16
62
39


The results suggest that for the overall population income has a strong relationship with Internet connectivity which is more sensitive to income than geographic spread. For a selected income range (such as equivalised household income of between $400 and $ 1,299 per week) there is a difference of 16 percentage points in Broadband connectivity rates for outer regional (even lower than very remote) Australia and major cities. However, the difference in Broadband connectivity rates between the lower income range (between $1 and $399 as well as nil or negative income) and the higher income range ($1,300 or more) is 40 percentage points in both major cities and very remote Australia.


In relation to the Indigenous population, the analysis reveals that in addition to income, remoteness has a strong influence on connectivity. For example, the lowest income group has only 3% Broadband connectivity in very remote Australia compared with 22% in major cities.


Analysed with regard to family composition (see Table 16), couple families with children under 15 have the highest Broadband connectivity in all areas, ranging from 34% in very remote Australia, and 64% in major cities. There is also considerable difference within remoteness areas between couple families with and without children under 15. Compared across regions, connectivity rates for one parent families, with or without children under 15, are similar to couple families without children under 15, and are considerably lower than couple families with children (differences ranging from 15 percentage points for Outer Regional Australia to 24 points for very remote Australia. Connectivity for one parent families with or without children under 15 is particularly low (10% and 15% respectively) in very remote Australia, perhaps reflecting a combination of low income and regional disadvantage for these families.


The above analysis brings out the complex relationship between Internet connectivity and relevant regional and socio-economic variables. Readers may have obtained enough information from this analysis, however those who wish to consider analysis undertaken in even greater details (and complexity) can consider Chapter 9 which tests relationships between such variables using regression analysis.


With the likelihood of collinearity between explanatory variables such as remoteness and income, cross-tabular analysis has its limitations. Multivariate regression analysis becomes a useful analytical tool for examining more complex situations.

Table 16: Access to the Internet and Broadband Connection, by Remoteness and Family Composition

Couple family with no children under 15
Couple family with children under 15
One parent family with no children under 15
One parent family with children under 15
Other family
Any
Internet
BB
connection
Any Internet
BB
connection
Any
Internet
BB
connection
Any
Internet
BB
connection
Any Internet
BB
connection
%
%
%
%
%
%
%
%
%
%

Major Cities
65
43
86
64
65
43
65
42
64
45
Inner Regional
59
30
82
49
57
30
59
32
44
24
Outer Regional
56
26
78
41
50
26
52
26
39
21
Remote
59
29
78
43
44
24
44
23
33
17
Very Remote
55
31
54
34
25
15
18
10
17
8






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