"Digital Strategic" Regions Of Russia

Abstract

The study aimed to determine the profile of the digital-strategic region of Russia by analyzing the growth rates of the development indicators of the information society, and the KPI of regional authorities. The objective of the study is the hierarchical structuring of the digital economy potential of the regions and KPI. The essence of the "digital-strategic" regions of Russia, its relationship with the KPI of regional authorities, integrated economic, industrial and government policies, a digital development strategy, and a role in the country reproduction process. For identifying the digital-strategic regions of Russia, an assessment is made of the growth rates of the development indicators of the information society and KPI. The result of the study is the identification of regions of leaders and outsiders in terms of growth in the development of the information society and KPI, as well as the determination of the profile of the digital-strategic region of Russia. The digital-strategic profile of the Russian economy is an industrial region that requires a radical change in the technological structure and entry into the path of sustainable digital development. Unlike the leader, the outsiders are the classic commodity regions, in the sectoral structure of the industry which is occupied by the oil and gas industry.

Keywords: Activityregionstrategydigital economyefficiency

Introduction

The digital-strategic regions of Russia are a completely new concept in economic science. This concept is introduced into vocabulary terminology to indicate the relationship between the digital economy and the strategy of managing the regions of Russia. The regions are digitally strategic, significantly affecting the process of the digital transformation of the economy and a paradigm shift in the strategic management of territories to maintain the integrity of the country and the security of the state.

The problems of the modern economy of the Russian regions are associated with the lack of a comprehensive economic, industrial and state policy, digital development strategy. Given the intensification of the globalization process and the periodic recession, an urgent requirement is the shift of the target vector from the country's economy to the region. In this context, the country is presented in the form of a corporation - namely, a legal entity pursuing the goal of "making a profit" as its main activity, providing for the participation of regions that have a separate property complex used in the process of reproduction.

There is a legitimate need to assess the role of each region in the country reproduction process. This fact makes it possible to hierarchically rank regions according to the "Key Performance Indicators" (KPI) level, to identify opportunities to improve the performance of management bodies, focusing on the best practices of active regions.

Russia is characterized by a vast territory, a variety of natural and socio-economic conditions, a multinational population and a multiconfessional society, a territorial organization of the state unique in its complexity. Under these conditions, ensuring the development of the information society and the digital economy is one of the necessary conditions for overcoming social, economic, institutional and political instability, maintaining the territorial integrity and federal structure of Russia in modern conditions. The process of formalizing differences in the economic, social, political, climatic and environmental conditions of the development of the Russian regions has established the need to find a rational set of optimal management solutions for digitizing the economies of the Russian regions. The requirements of market relations for the digitalization of the economies of the Russian regions, namely, related types of economic activity, raise many challenges that need to be addressed. One of the challenges is the need to determine a methodological approach to solving the problem of the functioning of economic systems through understanding the unity of the processes of agglomeration and management. It is necessary to search for a reasonable compromise between public administration and social self-organization and actualizing the need for the formation and implementation of optimally adequate state policy for the development of the information society.

At the moment, government policy includes numerous facts of the displacement of functions and tasks from the targeted provision of the development of the information society and the digital economy of the Russian regions. The imperative of state regional policy should be the concept of transforming the Russian economy into a dynamically developing state focused on modernization and innovation (Smirnov, Semenov, Zakharova, Kadyshev, & Dulina, 2019), increasing labour productivity and business initiative, a reasonable and consistent economic policy, and average European quality standards of life. The systemic indicator of development that should be sought is the efficiency of the economy. When analyzing the development potential of the regions, it is necessary to take into account that each region of Russia has its specific conditions for economic development and the possibility of efficient use of limited resources within the framework of the existing set of different types of labour activity that determine the level of production of material goods and provide general conditions for the life of the population in the format of the ethnic structure of public relations.

The scientific community has conducted many studies on the functioning and development of the economic system of the region. However, typologically stable theoretical and methodological models and practical recommendations for designating a complementary process of innovative and digital development (Smirnov, Osipov, Babaeva, Grigorieva, & Perfilova, 2019), as well as the formation of a regional economy management strategy, have not yet been constituted. Moreover, this, of course, is the way the theoretical principles of the digital strategy were laid down only at the end of the twentieth century by D. Tapscott.

Problem Statement

The digital economy is based on information and communication technologies (ICT) - innovative business management through markets via the Internet. D. Tapscott, in his book Digital Economy: Promise and Danger in the Age of Network Intelligence, described how the Internet would change the way we do business (Tapscott, 1996). The emphasis of the concept of the "digital economy" is shifted to e-business infrastructure; a way to conduct electronic business; e-commerce.

In the digital economy, communication infrastructure provides a global platform on which people and organizations develop strategies, interact, communicate, collaborate, and seek information (Nadiri, Nandi, & Akoz, 2018). The foundation of the digital economy is hyperconnectedness, which means the growing interconnectedness of people, organizations and machines. Hyperconnection is the result of the Internet, mobile technology and the Internet of things (IoT).

The Internet of Things is the concept of a computer network of physical objects ("things") equipped with built-in technologies for interacting with each other or with the external environment. The organization of such networks is a phenomenon that can restructure economic and social processes, eliminating the need for human participation from part of actions and operations (Brown et al., 2013).

Business Success in the digital economy is determined by the prospect of work, the flexibility of a global enterprise; consumer experience, a convenient way of interaction between Business-to-business (B2B) and Business-to-consume (B2C), IoT, the global merger of the physical and digital world. Each asset consumers, enterprises, devices and processes move into the digital domain, where software dominates (Maras, 2015).

Economists are studying how digital technologies are changing economic activity in various areas of the national economy. For example, digitization has reduced the number of economic costs: search, reproduction, transportation, tracking and verification. Changes in economic behaviour are the result of changes in costs inherent in the digital context. These changes are not as apparent as the underlying economic models imply (Goldfarb & Tucker, 2017).

Digital markets allow agents jointly investing in shared infrastructure and digital utilities without assigning market power to the platform operator, and are characterized by increased competition, lower barriers to entry and lower privacy risk (Catalini & Gans, 2019).

Blockchain presents a new application of cryptography and ICT to solving the problems of financial accounting. Major players in the financial industry began investing in new technology, and stock exchanges suggested using Blockchain as a method of trading corporate stocks and tracking their ownership (Yermack, 2017).

Ащк identifyштп the digital-strategic regions of Russi; it is necessary to use the criteria for assessing the achievement of strategic and tactical economic goals. These criteria may be KPI indicators. KPI allows orienting the Corporation "Russia" to achieve strategic and tactical goals, to monitor the business activity of the regions of Russia.

Going deeper into the etymology of the word "performance", two principles should be distinguished - effectiveness and efficiency (Badawy, El-Aziz, Idress, Hefny, & Hossam, 2016; (Banu, 2018; Domínguez, Perez, Rubio, & Zapata, 2019). According to ISO 9000: 2015 ("International Organization for Standardization"), productivity is the degree of achievement of planned results, and efficiency is the ratio between achieved results and resources expended (Cai & Jun, 2018; Javorcik & Sawada, 2018; Terziovski & Guerrero, 2014).

KPI is considered as a vital indicator of the result of activity – the degree of achievement and the cost of obtaining the result. Most enterprise performance management systems originate from models developed over a hundred years ago for discrete production by Frederick Taylor. The evolution of performance management over the past 30 years has led to the development of non-financial motivation tools, as well as to the rise and subsequent popularity of the idea of ​​rigidly ranking employees depending on the results achieved (Komm & Ewenstein, 2019).

The role of employees in the corporation "Russia" are the regions, thereby simplifying the problem of evaluating the performance of government bodies. Evaluation of the effectiveness of regional authorities is carried out bypassing the subjective performance indicators of individual officials, focusing on the KPI of the development of the region by objectives. Management by goals is a method of managerial activity, which provides for: predicting the possible results of activities and planning ways to achieve results. Peter Ferdinand Drucker (Rosenberg, 1999) is the founder of the Office for Goals and the corresponding system for evaluating the achievement of results (goals through KPI). According to Drucker, only a few areas of management have such a significant impact on the organization as the assessment of KPI. For example, 60 % of top managers in the United States are dissatisfied with their performance measurement systems, in Russia – more than 80 %. This discontent is expressed in the absence of a link between plans, execution, and outcome (Cohen, 2013).

KPIs are part of a balanced scorecard that establishes a causal relationship between goals (strategy) and performance (quality effects – project performance). The purpose of establishing these relationships is to see the patterns and mutual factors of influence in business – the dependence of some performance on others (Parmenter, 2007).

The regions of Russia, guided by the Federal Law.., (2014) "On Strategic Planning in the Russian Federation," use the list of indicators contained in it that are adapted to control regional targeted programs for regional development. The Kremlin has developed a standard KPI system. The level of trust in the president and governors will be evaluated; KPIs for elections are also being introduced. The government will evaluate the effectiveness of regional authorities under the "List of indicators for assessing the effectiveness of the activities of senior officials (heads of the highest executive bodies of state power) of the constituent entities of the Russian Federation and the activities of executive bodies of the constituent entities of the Russian Federation".

Research Questions

The subject of the study is the digital economy of the Russian regions. The theme of the work is the "digital-strategic" regions of Russia, which, by their definition, influence the process of the digital transformation of the economy and the paradigm shift of strategic territorial management. The essence of the digital-strategic regions of Russia is revealed in connection with the KPI of regional authorities.

Purpose of the Study

The study aimed to determine the profile of the digital-strategic region of Russia by analyzing the growth rate of indicators for the development of the information society, and KPI of regional authorities. The objective of the study is the hierarchical structuring of the digital economy potential of the regions and KPI. The method of statistical analysis used in the work of the dynamics of the development of the digital economy of the Russian regions and the KPI of their authorities, allowed determining the dependencies and characteristics of a hierarchically balanced system of indicators of the country's digital development.

Research Methods

The theoretical and methodological research platform is the fundamental scientific principles of economic theory, applied principles of economic and mathematical modelling, the theory of management of economic systems. In the process of research and in the formation of the main theoretical, methodological and practical provisions for identifying digital-strategic regions of Russia, the following are applied: mental and logical methods; morphological analysis; decomposition; stratification; generalization; typology; synthesis; conceptual and economic-mathematical modelling; descriptive and normative approach.

The combination of methods used allows a systematic approach classifying calls and identifying the possibilities of digital development of Russian regions. The result of the study is the theoretical, methodological and practical provisions of the digital organization of the Russian economy, taking into account the increment of knowledge in the field of economic theory, digital economy, strategic management, innovation management, regional and spatial economics.

Findings

For identifying the digital-strategic regions of Russia, we will evaluate the growth rates (RatesofGain, RG) of the indicators of the development of the information society in the Russian Federation (Monitoring the development of the information society in the Russian Federation…, 2019) and "key performance indicators" (KPI). That is, we will determine the performance indicators of senior officials and the activities of executive bodies of the constituent entities of the Russian Federation (Decree of the President of the Russian Federation…, 2019). The results of the assessment of ten leading regions by RGME indicators of the development of the information society are shown in Table 01 .

Table 1 -
See Full Size >

A summary analysis of the leaders' regions by RGME of the indicators of the development of the information society made it possible to distinguish: Sevastopol, the Republic of Crimea, Kabardino-Balkaria and Karachay-Cherkess; Bryansk, Kirov, Magadan, Tambov and Tula regions.

The results of the assessment of ten outsider regions by RG ME indicators of the development of the information society are shown in Table 02 .

Table 2 -
See Full Size >

A summary analysis of the outsider regions by RG ME indicators of the development of the information society made it possible to distinguish: the Republic of Mordovia; Astrakhan, Tomsk and Tyumen (except for the Khanty-Mansiysk Autonomous Okrug-Ugra and the Yamal-Nenets Autonomous Okrug) oblasts; Nenets Autonomous Okrug and Khanty-Mansiysk Autonomous Okrug – Ugra.

The results of the assessment of ten leading regions by ME KPI values ​​are given in (Table 03 ).

Table 3 -
See Full Size >

A summary analysis of the leader regions by ME KPI values ​​allowed distinguishing: the Republic of Dagestan, Ingushetia and Mari El; Astrakhan and Tambov regions; Chukotka Autonomous Okrug.

The results of the assessment of ten outsider regions by ME KPI values ​​are given in (Table 04 ).

Table 4 -
See Full Size >

A summary analysis of outsider regions by ME KPI values ​​allowed identifying the following regions: the Republic of Karelia, Amur, Jewish Autonomous, Tomsk and Tyumen Regions; Transbaikal region; Khanty-Mansiysk Autonomous Okrug – Ugra.

The final analysis of the resulting indicators of the development of the information society and KPI (Тable 01–04) revealed digital-strategic regions: the leader – Tambov region; outsiders – Khanty-Mansi Autonomous Area – Ugrai Tomsk Region.

Tambov region is an average region. The industry of the Tambov region is one of the leading sectors of the regional economy. The specificity and significance of industrial production in the region are determined mainly by manufacturing. Six types of economic activity determine the dynamics of the development of manufacturing:

- the production of food products, including drinks and tobacco;

- manufacture of electrical equipment, electronic and optical equipment;

- manufacture of machinery and equipment;

- production of vehicles and equipment;

- chemical production;

- manufacture of other non-metallic mineral products.

The Tambov region is the digital-strategic profile of the Russian economy, requiring a radical change in the technological structure and entering the path of sustainable digital development.

Unlike the leader, the outsiders are the classic commodity regions – the Khanty-Mansiysk Autonomous Okrug – Ugra and Tomsk Oblast. In the industrial structure of the industry of the Khanty-Mansiysk Autonomous Okrug – Ugra, the dominant position is occupied by the oil and gas industry, whose share is more than 80 %; electric power industry is more than 6%; processing industries, which are based on six oil refineries and nine gas processing enterprises, which are more than 12 %. Of the industries in the Tomsk region, fuel is more developed than 52 %, including oil production more than 48% and machine-building more than 12 %, chemical and petrochemical industries.

Conclusion

The concept of “digital strategic region” combines the digital economy and strategic management. The introduction of this concept into economic science made it possible to identify regions of Russia that actively influence the process of the digital transformation of the economy and the paradigm shift of strategic territorial management. Thus, to reduce the severity of the problem of the modern economy of the regions of Russia associated with the absence of a related integrated economic, industrial and state policy, digital development strategy. In this context, the digital-strategic regional structure of Russia, the country is presented in the form of a corporation – a legal entity aimed at the goal of “making a profit” as its main activity, providing for the participation of regions that have a separate property complex used in the process of reproduction. For identify the digital-strategic regions of Russia, the KPI criteria were applied. KPI criteria are the criteria for achieving strategic and tactical economic goals, control of business activity in the regions. For identify the digital-strategic regions of Russia, an assessment was made of RG indicators for the development of the information society and KPI.

A summary analysis of the regions according to RG ME indicators of the information society development, allowed identifying leaders and outsiders.

The leaders are the city of Sevastopol, the Republic of Crimea, the Kabardino-Balkarian and Karachay-Cherkess regions; Bryansk region, Kirov region, Magadan region, Tambov region, and Tula region. The outsiders are the Republic of Mordovia; Astrakhan Oblast, Tomsk Oblast, and Tyumen Oblast (except for the Khanty-Mansiysk Autonomous Okrug-Ugra and the Yamal-Nenets Autonomous Okrug); Nenets Autonomous Okrug and Khanty-Mansiysk Autonomous Okrug – Ugra.

A summary analysis of the regions according to ME KPI values ​​allowed identifying the following leaders and outsiders. The leaders are the Republic of Dagestan, Ingushetia and the Republic of Mari El; Astrakhan and Tambov regions; Chukotka Autonomous Okrug. Outsiders are the Republic of Karelia, Amur Region, Jewish Autonomous Region, Tomsk Region and Tyumen Region; Transbaikal region; Khanty-Mansiysk Autonomous Okrug – Ugra.

The final analysis of the resulting indicators of the development of the information society and KPI revealed the digital-strategic regions of Russia: leader – Tambov region; outsiders – the Khanty-Mansiysk Autonomous Okrug – Ugra and Tomsk Oblast. Thus, the main profile of the digital-strategic region of Russia can be associated with the industrial region focused on manufacturing, requiring an active transition to innovation and the digital economy. Outsiders are the classic commodity regions that use foreign high-tech equipment for the exploration.

References

  1. Badawy, M., Abd El-Aziz, A. A., Idress, A. M., Hefny, H., & Hossam, S. (2016). A survey on exploring key performance indicators. Future Computing and Informatics Journal, 1(1-2), 47-52. https://doi.org/
  2. Banu, G. S. (2018). Measuring innovation using key performance indicators. Procedia Manufacturing, 22, 906-911.
  3. Brown, M., Coughlan, T., Lawson, G., Goulden, M., Houghton, R. J., & Mortier, R. (2013). Exploring Interpretations of Data from the Internet of Things in the Home. Interacting with Computers, 25(3), 204-217.
  4. Cai, S., & Jun, M. (2018). A qualitative study of the internalization of ISO 9000 standards: The linkages among firms' motivations, internalization processes, and performance. International Journal of Production Economics, 196, 248-260.
  5. Catalini, C., & Gans, J. S. (2019). Some Simple Economics of the Blockchain. National Bureau of Economic Research. Working Paper 22952.
  6. Cohen, W. A. (2013). Peter Drucker Wants You to Be a Heroic Leader – Now. Organizational Dynamics, 42(1), 70–80.
  7. Decree of the President of the Russian Federation dated 25 April 2019, no. 193 (2019). “On evaluating the effectiveness of the activities of senior officials (heads of the highest executive bodies of state power) of the constituent entities of the Russian Federation and the activities of executive bodies of the constituent entities of the Russian Federation”. Meeting of the legislation of the Russian Federation, 04.29.2019, no 17, Art. 2078. Retrieved from: http://www.consultant.ru/cons/cgi/online.cgi?req=doc&base=LAW&n=323451&fld=134&dst=1000000001,0&rnd=0.7279449265292399#07372607554990825
  8. Domínguez, E., Perez, B., Rubio, A. L., & Zapata, M. A. (2019). A taxonomy for key performance indicators management. Computer Standards & Interfaces, 64, 24–40.
  9. Federal Law of 28 June 2014, no. (2014). 172-FL Meeting of the legislation of the Russian Federation of 30 June 2014, no 26 (Part I), Art. 3378 “On Strategic Planning in the Russian Federation”.
  10. Goldfarb, A., & Tucker, C. (2017). Digital Economics. National Bureau of Economic Research. Working Paper 23684. https://doi.org/
  11. Javorcik, B., & Sawada, N. (2018). The ISO 9000 certification: Little pain, big gain? European Econmy Review, 105, 103–114
  12. Komm, A., & Ewenstein, B. (2019). Luchshiye iz luchshikh: kakoye budushcheye zhdet sistemy upravleniya effektivnost'yu. Vestnik McKinsey. Teoriya i praktika upravleniya, 34.
  13. Maras, M. -H. (2015). Internet Things: security and privacy implications. International Data Privacy Law, 5(2), 99–104.
  14. Monitoring the development of the information society in the Russian Federation (2019). Digital Economy of the Russian Federation. Federal State Statistics Service of the Russian Federation. Retrieved from: http://www.gks.ru/free_doc/new_site/figure/anketa1-4.html
  15. Nadiri, M. I., Nandi, B., & Akoz, K. K. (2018). Impact of modern communication infrastructure on productivity, production structure and factor demands of US industries: Impact revisited. Telecommunicat. Policy, 42(6), 433–451.
  16. Parmenter, D. (2007). Key Performance Indicators: Developing, Implementing and Using Winning KPI's. New Jersey, USA: John Wiley & Sons, inc.
  17. Rosenberg, S. (1999). Management challenges for the 21st century: Peter F. Drucker. Business Horizons, 42(5), 86–87.
  18. Smirnov, V. V., Osipov, D. G., Babaeva, A. A., Grigorieva, E. V., & Perfilova, E. F. (2019). Parity of innovation and digital economy in the Russian management system. Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth (MTDE 2019). Advances in Economics, Business and Management Research (pp. 22–27).
  19. Smirnov, V. V., Semenov, V. L., Zakharova, A. N., Kadyshev, E. N., & Dulina, G. S. (2019). Innovative management in Russian production companies. IOP Conf. Ser.: Mater. Sci. Eng. 483 012060.
  20. Tapscott, D. (1996). The digital economy: Promise and peril in the age of networked intelligence. New York: McGraw-Hill.
  21. Terziovski, M., & Guerrero, J. -L. (2014). ISO 9000 quality system certification and its impact on product and process innovation performance. International Journal of Production Economy, 158, 197–207.
  22. Yermack, D. (2017). Corporate Governance and Blockchains, Rev. of Finance, 21(1), 7–31.

Copyright information

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

About this article

Cite this paper as:

Click here to view the available options for cite this article.

Publisher

European Publisher

First Online

07.12.2020

Doi

10.15405/epsbs.2020.12.94

Online ISSN

2357-1330