Development of digital technologies in Russia: regional aspects
DOI:
https://doi.org/10.17059/2019-3-4Keywords:
digital economy, digital technologies, digital divide, regional development, integrated indicator, multivariate analysis, panel data models, clustering, innovationsAbstract
The modern economy is on the way to a new technological order based on knowledge-intensive industries relying on digital technologies. This transition’s possible effects are yet to be sufficiently studied as they require thorough analysis and the use of the appropriate tools. Moreover, it is necessary to develop new indicators considering the specificity of the economy’s digitalization. The article presents a methodology for studying the phenomena of the digital economy and digital divide in Russian regions. Using the methodology, we developed new indicators, approaches and techniques for studying the changes at different levels of hierarchy and the effects of their impact. In the first block we established a composite indicator for studying regional imbalances in the development of digital economy. This indicator has several advantages as it takes into account the availability of the basic information and communication technologies and wired network services. In the second block we introduced the method of classifying the Russian regions by the level of digital technologies development. Differences in the mean values of variables across clusters allow determining the magnitude of the inequality in the technology’s dissemination between the groups of regions. In the third block we identified the key determinants of digital development and information inequality based on the panel data regression models. We built separate models for the information and communication technology accessibility index and its two sub-indices, assuming they were influenced by different and divergent factors. Defining the effective institutional mechanisms for digital development will determine the direction for boosting the competitiveness of the Russian regions and engage additional sources of economic growth. Furthermore, it will help increasing innovation activity and reducing the digital divide.References
Romer, P. M. (1990). Endogenous Technological Change. The Journal of Political Economy, 98(5), Part 2, 71–102.
Billon, M., Marco, R. & Lera-Lopez, F. (2009). Disparities in ICT adoption: A multidimensional approach to study the cross-country digital divide. Telecommunications Policy, 33(10–11), 596–610.
Bagchi, K. (2005). Factors contributing to Global Digital Divide: Some empirical results. Journal of Global Information Technology Management, 8(3), 47–65. DOI: http://dx.doi.org/10.1080/1097198X.2005.10856402.
Chinn, M. D. & Fairlie, R. W. (2007). The Determinants of the Global Digital Divide: A Cross-Country Analysis of Computer and Internet Penetration. Oxford Economic Papers. New Series, 59(1), 16–44. DOI: https://doi.org/10.1093/oep/gpl024.
Dasgupta, S., Lall, S. & Wheeler, D. (2001). Policy Reform, Economic Growth and the Digital Divide: An Econometric Analysis. Policy Research Working Paper №2567. Washington: The World Bank Development Research Group Infrastructure and Environment, 24.
Emrouznejad, A., Cabanda, E. & Gholami, R. (2010). An alternative measure of the ICT-Opportunity Index. Information & Management, 47(4), 246–254. DOI: 10.1016/j.im.2010.04.002
Pohjola, M. (2003). The adoption and diffusion of ICT across countries: Patterns and determinants. In: D. C. Jones (Ed.), The New Economy Handbook (pp. 77–100). San Diego: Academic Press.
Caselli, F. & Coleman, I. (2001). Cross-country technology diffusion: The case of computers. American Economic Review, 91(2), 328–335.
Doong, S. H. & Ho, S.-C. (2012). The impact of ICT development on the global digital divide. Electronic Research Commerce and Applications, 11, 518–533.
Huang, C.-Y. & Chen, H.-N. (2010). Global Digital Divide: A Dynamic Analysis Based on the Bass Model. Journal of Public Policy & Marketing, 29(2), 248–264.
Cerno, L. & Amaral, T. P. (2006). Demand for Internet access and use in Spain. In: B. Preissl, J. Müller (Eds.), Governance of Communication Networks (pp. 333–353). Hidelberg: Physica-Verlag.
Dudek, H. (2007). Determinants of access to the internet in households — Probit model analysis. Polish Association for Knowledge Management. Series Studies & Proceedings, 11, 51–56.
Çilan, Ç. A. & Özdemir, M. (2013). Measuring domestic digital divide by using latent class analysis: A case study of Turkey. Istanbul University Journal of the School of Business, 42(2), 219–234.
Nishijima, M., Ivanauskas, T. M. & Sarti, F. M. (2016). Evolution and determinants of digital divide in Brazil (2005–2013). Telecommunications Policy, 41, 12–24. DOI: https://doi.org/10.1016/j.telpol.2016.10.004.
Loo, B. P. Y. & Ngan, Y. L. (2012). Developing mobile telecommunications to narrow digital divide in developing countries? Some lessons from China. Telecommunications Policy, 36, 888–900. DOI: https://doi.org/10.1016/j.telpol.2012.07.015.
Vicente Cuervo, M. R. & Lopez Menéndez, A. J. (2006). A multivariate framework for the analysis of the digital divide: Evidence for the European Union-15. Information & Management, 43(6), 756–766. DOI: https://doi.org/10.1016/j.im.2006.05.001.
Ayanso, A., Cho, D. & Lertwachara, K. (2014). Information and communications technology development and the digital divide: A global and regional assessment. Information Technology for Development, 20, 60–77. DOI; https://doi.org/10.1080/02681102.2013.797378.
Bykov, I. A. & Hall, T. E. (2011). Tsifrovoe neravenstvo i politicheskie predpochteniya Internet-polzovateley v Rossii [Digital Divide and the Internet-users political preferences in Russia]. Polis, 5, 151–163. (In Russ.)
Minochkin, A. L. (2013). Informatsionnoe neravenstvo v sovremennoy politicheskoy sisteme: priroda i suschnost [Digital divide in the modern political system: the nature and essence] Vestnik Saratovskogo gosudarstvennogo sotsialno-economicheskogo universiteta [Vestnik of Saratov State Socio-Economic University], 3, 142–146. (In Russ.)
Rasulov, Z. A. (2013). Informatsionnoe neravenstvo regionov Rossiyskoy Federatsii i informatsionnaya politika (kak factory formirovaniya informatsionnogo obshchestva) [Information Inequality of the Regions of the Russian Federation and Information Policy (as Factors of Information Society formation)]. Izvestiya vysshikh uchebnykh zavedeniy. Povolzhskiy region. Obshchestvennye nauki [University proceedings. Volga region. Social sciences], 2(26), 42–49. (In Russ.)
Dronov, V. N. & Makhrova, O. N. (2015). Tsifrovoe neravenstvo Ryazanskoy oblasty [Digital Divide of Ryazan Region]. Saint-Petersburg: Saint-Petersburg University of Management and Economics, 148. (In Russ.)
Korotkov, A. V. (2003). Tsifrovoe neravenstvo v protsessakh stratifikatsii informatsionnogo obshchestva [Digital Divide in the Stratification Processes of Information Society]. Informatsionnoe obshchestvo [Information Society], 5, 24–35. (In Russ.)
Kuznetsov, Yu. A. & Markova, S. E. (2014). Nekotorye aspekty kolichestvennoy otsenki urovnya tsifrovogo neravenstva regionov Rossiyskoy Federatsii [Some aspects of digital inequality rating of the RF regions]. Ekonomicheskiy analiz: teoriya i praktika [Economic analysis: theory and practice], 32(383), 2–12. (In Russ.)
Volchenko, O. V. (2016). Dinamika tsifrovogo neravenstva v Rossii [Dynamics of the digital inequality in Russia]. Monitoring obshchestvennogo mneniya: Ekonomicheskie i sotsialnye peremeny [Monitoring of Public Opinion: Economic and Social Changes Journal], 5, 163–182. DOI: 10.14515/monitoring.2016.5.10. (In Russ.)
Arkhipova, M. Yu., Sirotin, V. P. & Sukhareva, N. A. (2018). Razrabotka kompozitnogo indikatora dlya izmereniya velichiny i dinamiki tsifrovogo neravenstva v Rossii [Development of a Composite Indicator for Measuring of the Value and Dynamics of Digital Inequality in Russia]. Voprosy statistiki, 5, 75–87. (In Russ.)
Aivazian, S. A., Stepanov, V. S. & Kozlova, M. I. (2006). Izmerenie sinteticheskikh kategoriy kachestva zhizni naseleniya regiona i vyyavlenie kluchevykh napravleniy sovershenstvovaniya sotsialno-ekonomicheskoy politiki (na primere Samarskoy oblasti i ee munitsipalnykh obrazovaniy [Measuring the synthetic categories of quality of life in a region and identification of main trends to improve the social and economic policy (Samara Region and its constituent territories)]. Prikladnaya Ekonometrika [Applied Econometrics], 2, 18–84. (In Russ.)
Mkhitarian, V.S., Arkhipova, M. Yu., Dubrova, T. A., Mironkina, Yu. N. & Sirotin, V. P. (2018). Analiz Dannykh [Data Analysis]. Moscow: Urait, 490. (In Russ.)
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 Marina Yuryevna Arkhipova, Vyacheslav Pavlovich Sirotin
This work is licensed under a Creative Commons Attribution 4.0 International License.
