Information and Communication Evolution as a Factor of a Digital Divide Reduction

The digital divide is a significant problem of modern age. The relevance of this problem is reflected in official documents. In 2015, world leaders agreed to 17 goals for a better world by 2030. One of these goals is to reduce inequality within and among countries. Russia also participates in solving the digital inequality problem. In 2017, the president of Russia signed a decree “About the Development strategy of the information society in the Russian Federation for 2017 – 2030.”

Researchers single out three levels of the digital divide: the first level is based on access to information and communication technologies (ICTs), the second level relates to differences in ICT skills, and the third level results from the unequal distribution of important opportunities based on access to ICT and quality of ICT use.

Nowadays it is clear that developed countries and many developing countries are slowly overcoming the first-level digital divide. The purpose of the study is to reveal the causes of the first-level digital divide reduction in contemporary Russia. Understanding these causes is important because it might allow us to explain and control the digital gaps related to continuous information and communication changes in future.

Digital divide theorists M. Castells, Jan van Dijk, B. Wellman, M. Ragnedda, P. DiMaggio, E. Hargittai have pointed out that the first-level digital divide is influenced by traditional factors such as sex, age, race, nationality, health, occupation, education, country of accommodation, accommodation in city/rural areas, income, etc. At first, only the elite had Internet access, as elites usually get access to new technologies before others. Therefore, we can argue that Internet access distribution depends on the traditional factors influencing social inequality. This study argues that ICT evolution affects digital divide more than traditional factors.

I conducted a correlational analysis of traditional factors affecting digital divides in 36 countries by means of relevant statistical indicators:

Factor Statistical indicator Influence level on Internet

penetration

Sex Population, female (% of total) -0.14
Age Population, ages 0-14 (% of total) -0.75
Population, ages 15-64 (% of total) 0.51
Population ages 65 and above (% of total) 0.66
Health Health expenditure per capita (current US$) 0.71
Health expenditure, total (% of GDP) 0.59
Immunization, DPT (% of children ages 12-23 months) 0.48
Life expectancy at birth, total (years) 0.76
Education Government expenditure on education, total (% of GDP) -0.49
Income GNI per capita (current LCU) 0.84
Employment Unemployment, total (% of total labor force) -0.06
Working capacity Labor force, total -0.04
Accommodation in city/rural areas Urban population (% of total) 0.76

The results of the analysis make it clear that Internet penetration (percentage of the total population of a given country or region that uses the Internet) is influenced mostly by 4 factors: age, health, income, accommodation in city/rural areas. However, the analysis of dynamics of these factors from 2004 to 2016 in Russia shows that they correlate partially with dynamics of Internet penetration in Russia.

At the same time, it is possible to note 4 outliers in dynamics of the Internet penetration rate in Russia:

  • 2007 – IPR increased by 6.6% in comparison with the previous year;
  • 2010 – IPR increased by 14% in comparison with the previous year;
  • 2011 – IPR increased by 6% in comparison with the previous year;
  • 2012 – IPR increased by 14.8% in comparison with the previous year.

To better understand these outliers, I analyzed Internet development in Russia through 5 factors:

  • Type of Internet connection
  • Price of Internet access
  • Purpose of Internet use
  • Equipment for Internet access
  • Technological infrastructure for Internet access

The analysis of Internet development in Russia shows that each outlier is related to changes in the information and communication technologies field, such as significant price drops for Internet access, the emergence and growth of online social networks, providing free Internet access for using particular websites, the development of Internet infrastructure, the transition from WAP, GPRS, 2G (EDGE) to 3G and from 3G to 4G, development of equipment for Internet access (emergence of 3G and 4G mobile phones on the market), and the launching of paid and free public Wi-Fi networks.

This study attempts to show the influence of ICT evolution on digital divide reduction in Russia. I have argued that the digital divide is based on ICT evolution, and thus it differs from other types of social inequality. That is why traditional approaches to inequality are not sufficient for understanding the digital divide.

 

 

 


Daria Kushnarenko

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