Delivering job search services in rural labour markets: the role of ICT

In order to test the association between individual and labour market characteristics
and ICT access and use, a binary logistic regression model was used. The model
examined the association between two dependent variables (home Internet access;
weekly use of the Internet for job seeking) and selected job seeker and area
characteristics that emerged as potentially relevant from the above analysis. Dummy
variables for the ‘West Lothian’ study area and the ‘Sutherland’ TTWA (as opposed to
the broader ‘Wick and Sutherland’ area) were used. As Table 7 illustrates, the strong
association between job seekers’ skills and ICT access is confirmed. Both formal
qualifications and job seekers’ perceived ICT skills appear to be significantly associated
with Internet access (with those perceiving their skills to be ‘good or adequate’ more
likely to have on-line facilities at home). Home Internet access was also associated with
income status, reflecting the manner in which those with higher household incomes
(often reflecting the presence of a working partner) are better able to cope with the costs
of hardware purchase and connection charges. Although there was a positive association
between Internet access and residence in both West Lothian and Sutherland, the degree
of significance was a stronger for the latter.

INSERT TABLE 7 ABOUT HERE

The statistically significant association between factors such as gender and income status
and Internet access was not replicated when Internet job seeking was analysed. There
was, however, a strong association between measures of respondents’ skills (formal
qualifications and perceptions of ICT skills) and their use of the Internet as a job search
tool. While residence in West Lothian was not strongly associated with web-based job
seeking, there was a significant positive relationship between Sutherland residence and
the use of the Internet. Internet access and use therefore appears to be associated with a
combination of factors related to skills and qualifications, income and gender. Perhaps

17

<<   15   16   17   18   19   20   21   >>

More intriguing information