Statistical Analyses of Digital Divide Factors

The digital divide has become an extremely important issue for many international organizations and a major challenge for policy makers and academic researchers. We have to know the factors of digital divide to find solutions for eliminating disparities in ICTs.The first goal of our research is to measure or calculate the digital divide in Hungary. The digital divide is a complex and multidimensional issue, which requires taking into account diverse technologies, variables, and territories. In this context, factor analysis has revealed as a useful tool to capture the overall dimension of the digital divide. Therefore our research is based on different ICT indicators from Eurostat statistics and the Empirica survey results. Our research focuses on the digital divide circumstances in Hungary. The investigated fields are the followings: Percentage of households with access to the Internet; Percentage of households with a broadband connection; Percentage of individuals regularly using the Internet at least once a week; Percentage of individuals who have never used a computer; Percentage of individuals who ordered goods or services online for private use. The correlation matrix in our research (which comes from factor analysis) shows that all variables are closely related to each other, with correlation coefficients larger than 0.8. For instance, the percentage of individuals who have never used a computer is highly and negatively correlated with using the Internet and having access at home because most people are connected to the Internet through a computer. Furthermore, the high and positive correlations of broadband infrastructural and usage indicators show the increasing importance of high-speed connections: many of the latest online services, are only possible through fast networks. Given these strong correlations, factor analysis seems to be appropriate.Since the EU has been paying special attention to bridging the rural-urban digital divide the relationship between ICT factor and population density has also been analyzed. Furthermore, the percentage of population aged 65 and over is included to capture the potential influence of regional demographic differences on the extent of ICT adoption. In this sense, older people often face more barriers to use ICT than younger individuals. The highest correlations with ICT factor are found for GDP per capita, human resources in science and technology, in contrast to population density, which shows the lowest one among the considered variables. This article shows our research results on the field of digital divide factors using by statistical analyses.