Features and vectors of cluster transformation in the digital economy

Ganchenko D.N.1
1 Kuzbass Humanitarian and Pedagogical Institute of Kemerovo State University

Статья в журнале

Экономика, предпринимательство и право (РИНЦ, ВАК)
опубликовать статью | оформить подписку

Том 11, Номер 11 (Ноябрь 2021)

Цитировать:
Ganchenko D.N. Features and vectors of cluster transformation in the digital economy // Экономика, предпринимательство и право. – 2021. – Том 11. – № 11. – С. 2537-2550. – doi: 10.18334/epp.11.11.113797.

Эта статья проиндексирована РИНЦ, см. https://elibrary.ru/item.asp?id=47379112
Цитирований: 10 по состоянию на 30.01.2024

Аннотация:
Cluster technologies are gaining their pace, expanding the scope and application range. Their abilities to develop economy are under intense scrutiny of theorists and practitioners. The paper presents an attempt to determine one of the cluster functioning aspects related to the digital economy integration into cluster technologies and their transformation. The paper is intended to identify the factors and determine the transformation vectors of cluster technologies in the digital economy. The methodological basis of the research is the works of domestic and foreign authors that reveal the essence of the economy cluster model and digitalization phenomenon. The research is based on general scientific methods as well as a system approach to the study of both domestic and foreign practice and scientific methodological base containing clusters functioning parameters in the industrial and digital economy. The research identified possible negative and positive cluster technology transformations that occur under the digital economy influence. The conceptual elements of collaboration of the authorities and business community are proposed to contribute to establishing sustainable innovative effects when using cluster technologies under the influence of the global economy digitalization. The results presented in the paper can be used when designing cluster development programs, including government participated ones.

Ключевые слова: cluster, clusters development, digitalization, digital economy, innovation

JEL-классификация: O31, O32, O33

В издательстве открыта вакансия ответственного редактора научного журнала с возможностью удаленной работы
Подробнее...



Introduction

Despite its relatively short history, cluster is represented in the economy as one of the advanced and efficient tools that stimulate and increase economic development pace. Due to their efficiency, clusters have spread worldwide and now are functioning in almost every country. Such cluster’s peculiarity contributed to the fact that practical experience has significantly outpaced a theoretical economic clustering concept. Today, a lot of researchers try to find and provide the missing snippets of this theoretical dimension. Rapidly changing environment creates a lot of difficulties here, as it forms new precedents of cluster "responses" to "challenges".

Today, the cluster is experiencing one of the most significant metamorphoses concerning the global world economy digitalization. The metamorphosis determines the conditions and potential of cluster technologies usage in an economy. In some cases, it creates precedents beyond cluster efficiency in innovations production, while in other cases, it demonstrates their failure. Such circumstance is the subject of this research.

Research objective

The research is intended to identify the factors and determine transformation vectors of cluster technologies in the digital economy. Identifying the transformation factors and vectors will enable to provide favorable conditions for cluster technologies development and their adaptation, while keeping their innovative economy development potential at the optimum level.

Research methodology

The research is based on consideration of conditions, parameters and system elements of clusters’ origin, functioning, and development in an economy, the peculiarities of cluster economy model transformation to the Russian realities and its prospects in the context of digitalization on a step-by-step basis. The methodological basis of the research is represented by the papers of domestic and foreign authors that reveal the essence of the economy cluster model and digitalization phenomenon. The research is based on general scientific methods as well as a system approach to the study of both domestic and foreign practice and scientific methodological base containing clusters functioning parameters in the industrial and digital economy.

Research results

Cluster economy mode development

A scientific community assumes pro-cluster formations in an economy field were first mentioned in Principles of Economics by A. Marshall [1] (Marshall, 1920). He believed that sustainable interactions of economic agents, located close to each other and collaborating, receive positive externalities: information exchange, access to specialized goods suppliers and skilled labor. This approach to simultaneous boundaries determination of economic and organizational effect provided by entities interaction and their territorial belonging predetermined the key parameters of modern clusters.

The Marshall’s conceptual idea about the agent interaction was further developed in the scientific works by his numerous followers. In particular, it is represented in works by A. Weber and H. Hoover that laid the basis of location theory and conducted research on the economic effects that come from agglomeration formations.

Another pro-cluster formation type is a phenomenon, formed in Soviet Russia and introduced into scientific parlance in 1941 by Kolosovskiy N. [2] (Kolosovskiy, 1969), a territorial production complex. Initially, it was defined by the author as interrelated and interdependent facilities that provide additional economic effect in case of their optimal location, relevant to natural and geographical territory parameters, through the use of shared infrastructure, labor, and other production components. The development of such production formations had its rise in the 1960–1970s. Their distinctive feature was strict vertical planning and designing for both complexes layouts and their activities. Today, there is no consensus among scientists whether to consider the "complex" as the cluster formation. Nevertheless, in a number of researchers (L. Markov, N. Suslov, etc.) [20] a complex is regarded as an obvious pro-cluster formation.

The possibility to formalize an economic effect that comes from the relations between particular cycles or an entire manufacturing process within certain territorial boundaries enables to consider various effects faucets: specialization [4] (Piore, Sabel, 1984); industrial zoning (Brusco S., Becattini B.), etc.

However, only Porter M. [3], in his paper of 1990, defined an industrial cluster as a number of industries connected through buyer-supplier or supplier-buyer relations as well as through shared technologies, procurement or distribution channels, or labor associations (a specific entity of the competitive region or country economy strategy as well as a tool for stimulating innovation and economic growth).

Based on its etymology, cluster is a bunch, accumulation, concentration in the English translation. But only starting from Porter’s work, this "bunch" was divided from all other industries concentrated within certain boundaries by the presence of internal competition. This significant difference enabled to distinguish, in its time, organizational mega-structures involved in the general goods manufacturing from the total mass. According to experts [5] (Abashkin, Boyarov, Kutsenko, 2012), the first quarter of the clusters that meet the true cluster formation criteria was started before 1999 in the world practice. Besides, geographical concentration, innovation, internal competition, and “critical mass” stood as the key cluster features.

Later, practitioners have assessed the potential that cluster cooperation and integration have for the economy and begun to implement not only true clusters, but various pro-cluster formations as well. The latter are aimed at achieving various goals, targeting solving economy business tasks that go beyond the traditional economy: economic and social, environmental, housing, etc. Such practice has provided precious cluster initiatives developing and implementation experience in true market conditions, with certain administrative authority support [6] (Raevskiy, Vinokurova, 2007) as well as has given birth to several clusters types [7] (Tsikhan, 2003).

By the present, most researchers agree there is no universal definition of the cluster’s essence. This feature began to manifest itself due to the widespread practice of clustering the economy that is implemented by many countries despite their different relationship structures. However, there are three key approaches in understanding the cluster, each of which highlights the main feature of its functioning [8] (Dombrovskiy, 2011). Thus, a cluster is understood as:

· an area-limited form of an economic activity within related sectors, typically tied to certain academic institutions;

· a vertical production chain; quite narrow specific sectors in which adjoining manufacturing phases form the cluster core;

· industries specified at the high aggregation level (e.g. the chemical cluster) or a set of sectors at an even higher aggregation level (e.g. the agro-industrial cluster).

As it comes with any organized system, a created cluster can’t function forever. As it solves the set task, it must transform [9] (Bukhvald, Vilenskiy, Kiselev, Shestkaova, 2000). Such a transformation should be considered natural. An organizational system will either no longer exist or transform into another form, in compliance with general economic and life cycle laws.

Unlike the natural transformation, there should be highlighted the artificial or forced transformation. It is determined by the factors of its external environment in which clusters emerge or function. Only they provoke cluster changes during its life cycle [10] (Palt, 2015) and the nature of the technologies it uses.

Cluster technologies in Russia.

The Federal authorities initiated the large-scale use of the cluster approach in the country's economy as a whole was in 2005. The Ministry of Economic Development of the Russian Federation published a report stating "the only way to increase our economic potential is labor efficiency increase and economy diversification" [11] (Mironova, 2010). More details about clusters in the country's region economies were delivered in the Russian Federation’s Government Order in November 2008 that issued The Russian Federation Economic and Social Development Long-Term Concept, designed up to 2020. Developing two types of clusters was proposed in the country development concept to ensure innovation and social orientation of regional development:

· territorial-production clusters with following subtypes: for areas focused on high-tech production in priority economic sectors and for poorly developed areas focused on deep raw material processing and energy generation with modern technologies;

· tourism and recreation clusters in areas with unique natural wealth and landscapes as well as rich historical and cultural heritage.

More detailed industrial clusters classification (metallurgical, petrochemical, agricultural, etc) was presented in the Concept draft of improving regional policy in Russia. Moreover, a service cluster was set as an independent type.

At the present, in the country’s economy as a whole, the use of the cluster approach is dictated by the need to implement more effective incentives for country innovative development literary in all its sectors, as point-wise stimulation methods, based, as a rule, on the sectoral approach and its combination, do not ensure the desired development results neither in the industry nor in services sectors. For this reason, the creation and development of an innovative territorial clusters network is set as current government policy priorities for the country’s economic and social development. This is reflected in: the Russian Federation Economic and Social Development Long-Term Concept, designed up to 2020, the Policy Priorities of the Government of the Russian Federation to 2018, the Strategy for Russia’s Innovative Development to 2020 [12].

A competitive selection of pilot programs for innovative territorial clusters development was bid in 2012, the results of which the official list is approved and government support measures are prescribed. Support for innovative territorial clusters is provided within the framework of Federal budget subsidies for complex investment projects implementation. In turn, at the regional level, and in the Kemerovo region, in particular, main directions of region economy modernization are presented using the cluster approach and principles of current government economic policy are formulated in the conceptual and policy documents.

Based on the key parameters of the clusters functioning in Russia, presented in the strategic country and region development documents, Siberian district clusters were mapped (table 1).

Table 1
The Siberian clusters key parameters

Year of cluster creation / development stage
Specialization profile
Key technologies
Agrobiotechnological industrial cluster (Omsk)
2016
Initial
Industrial biotechnologies
Industrial clusters:
– import substitution;
– industrial cooperation;
– financing of joint projects
Barnaul industrial chemical cluster
2017
Middle
Chemical production
Altai agricultural engineering cluster
2009
Middle
Manufacturing of machines and equipment
Innovation clusters:
– support from the center for cluster development to support small and medium-sized businesses;
– project management;
– objective multicriteria;
– joint R&D projects;
– patenting R&D in foreign countries;
– subsidies to cluster constituent entities
Power plant engineering and energy efficient technology cluster (Altai)
2009
Middle
Manufacturing of machines and equipment
Altai polymer composite cluster
2014
Middle
New materials
Baikal pharmaceutical cluster
2014
Initial
Pharmaceutics
Biomedical cluster (Kemerovo)
2012
Initial
Medical industry
Machine-building cluster (Irkutsk)
2014
Initial
Aircraft manufacturing
Altai biopharmaceutical cluster
2008
Middle
Pharmaceutics
Pilot innovative territorial:
– administrative and centralized- organization order ;
– targeted subsidies to territories;
– program control;
– target – innovation infrastructure development
Innovation cluster (Krasnoyarsk)
2011
Initial
Nuclear and radiation technologies
Siberian scientopolis cluster (Novosibirsk)
2016
High
Information and communication technologies
Pharmaceuticals, medical equipment and information technologies (Tomsk)
2013
Initial
Pharmaceutics
Complex processing of coal and industrial wastes (Kemerovo)
2012
Middle
Environmental protection and waste management
Has two status and two managing approaches:
– as a pilot innovative territorial;
– via cluster development center
Cluster of high-tech components and systems (Омск)
2013
Initial
Defense industry
– Private investment;
– high competition;
– minimal government regulation
Petrochemical industrial cluster (Omsk)
2013
Initial
Chemical production
Petrochemical (Tomsk)
2015
Initial
Chemical production
Nuclear cluster (Tomsk)
2015
Initial
Nuclear and radiation technologies
Source: compiled by the author on the basis of [13, 14].

The document study showed the Russian cluster creation priority is given to government-controlled industrially and regionally oriented ones that can form the desired points of growth in the country's economy and ensure sustainable development in strategically important sectors of the national economy. However, presented clusters diversity also demonstrates specialization duplication by some clusters within one region (Siberia). As a result, not all clusters have the resources to cope with set program development pace. First of all, the reason here is the fact that the necessary innovative activity level not always can be achieved only through administrative methods of the national economy industry development, demanded at first glance. To achieve this, it is necessary to ensure an appropriate resource and infrastructure potential [15] (Ganchenko, 2019) as well as a high level of cluster technologies adaptability to the changing environment, where the key driver today is the Industry 4.0.

Cluster technologies future.

The integration of Industry 4.0 into the economy predetermines the origin and scaled development of economic and social transformation initiated by the mass digital technologies introduction and mastering [16, 17] (Ganchenko, Bodrov, 2019). Such transformation affects various functioning and development parameters, including the transformation of structures, forms, and ways, changing targeted activity orientation.

The implementation of Industry 4.0 technologies in most cases is performed within the framework of the basic digital economy business models: infrastructural, platform [18] (Garifullin, Zyabrikov, 2019) and cyber-physical [19]. In the first case, digitalization is presented in the market as an infrastructure service, when a consumer uses the supplier’s computing resources. At present, this approach is actively implemented by clusters in Russia. The government acts in this model as the main holder of the economy digitalization model functional. The second model is oriented on providing economic agents with tools and opportunities of using the original services concerning coordinating the processes and market players’ activities related to desired goods, works, and services. This model implementation assumes highly integrated IT infrastructure development as well as of IT competence of all parties without any exception. This model stimulates allocating an independent type of IT-clusters from a classic industrial clusters category. These clusters become an independent entity in the economy and are not always integrated with the final goods, works, and services manufacturer, while stimulating only innovation in priority economy fields. The third model assumes multifunctional computing resources complex building and functioning as well as for physical processes as a whole. Currently, this model is regarded as a sort of cluster technology pattern for a digital economy, where information technologies are used as an effective tool, rather than an innovative development target. In this model, it is possible to generate innovations in goods manufacturing based on information technology, instead of considering minor modifications of such technology as innovation that is often found during the implementation of the first and second models.

Apparently, the cyber-physical business model in the digital economy is preferable to the first two models. However, its formation is possible only due to their gradual development.

The background for the formation and implementation of the third digital economy model into the economy and its integration with cluster technologies, as one of the effective practices for intensive economic development, exists in almost every area. However, as practice shows, the model implementing process is accompanied by a number of factors related to cluster technologies and digital economy peculiarities (table 2).

Table 2
Factors determining the clusters development in the digital economy
Cluster practice factors
Digital economy factors
Methodological, related to developing a cluster approach, that generates the lack of established fundamental evaluation tools [20] Economic, related to the costs volume and their nature regarding global infrastructure transformations aimed at implementing digital technologies
Organizational, concerning cluster development homogeneity/heterogeneity in various economy fields [21]
Organizational and technical, determined by the level of digital infrastructure elements development and integration [22] (Bataev, 2018)
Economic, regarding the current priority of accelerated certain economy sectors development, profit-making, transaction costs reduce
Regulatory and methodological, caused by the established process coherence and duration, the nature of the power distribution in industrial documents and strategic planning ones
Resource and infrastructural, that are about the presence/absence of a necessary start-up manufacture platform for the cluster technologies usage
Professional, determined by the personnel training level and their ability to apply their knowledge and skills in practice
Methodological, related to developing a general or typical mechanism for integration IT in a manufacture process
Source: compiled by the author.

Each of the presented factor groups may have both positive and negative impacts, depending on the current economic and social situation of the area where a cluster functions in the digital economy. In case of negative impact predominance, the following practices are possible to develop:

· establishing fractal organizations [23] (Getts, 2019);

· insufficient consideration of the uniqueness formed by the individual clustering entity features [21], which cause zero effectiveness even for proven worldwide cluster practices;

· universalization of measures for developing cluster technologies related to building infrastructure conditions for development, with Cyberjaya, a Malaysian "city of the future" as a striking example [24] (Wilson, 2012);

· implementing popular cluster practices, so-called "the epidemic of imitation" [25] (Deroshe, 2011);

· unsystematic government policy [26], related to the desire to accelerate development pace using cluster technologies in the economy as well as to the "pendular motion" while selecting development priorities;

· erosion of an effect from government cluster policy measures, presented onto the whole state area [25] (Deroshe, 2011), in the desire to create the maximum number of growth points within the area, etc.

In case the positive factors effect prevails, the change vector in cluster technologies, which contribute to the formation and spread of a cyber-physical economy business model, is needed to accumulate by a number of characteristics (table 3).

Table 3
Vectors of key cluster technologies parameters transformation

Traditional operational modalities
Digital society and economy
Formation determinant
Agglomeration (Marshall A.);
Co-operation (Porter M.)
Diversification
Geographical spread
Concentration, clear boundaries
Dispersion (no clear boundaries)
Organizational basis
Complex (Marshall A.);
Internal competition (Porter M.)
Virtualization of the organization
Purpose
Strategic (long-term) competitive advantages
Flexibility and fast integration into technical, informational, digital, and market processes [27] (Bataev, Gorovoy, Mottaeva, 2018)
Personnel
Professionalism, "knowledge transfusion"
Vocational and competence-based approach
Innovation
Implementing innovations and building innovative effects in the economy
Generating innovations in all potentially possible functioning fields, Innovations implementation and "transfusion"
Relations
Formalized, transparent
Mainly unformalized, multidimensional, virtual
Number of participants
Limited
Not limited, future development due to accompanying service industries
Finance
Predominantly direct investment
Predominantly indirect investment, cash flow virtualization
Source: compiled by the author.

The accumulated effects got from cluster models transformation in the digital economy will enable to prepare a basis for developing, implementing, and spatial distributing innovative products that create conditions for the next economic development stage. The consistency of such effects can be ensured by steady and mutually beneficial interaction between the authorities and the business community in the following directions:

· designing and evaluating the efficiency of innovative managerial business models in the context of a cluster approach:

· preparing and assimilating a technological platform that meets at least achieved informational and digital parameters;

· adapting organizational structures based on their structural flexibility to external changes;

· synchronization of transforming cluster technologies with government economic policy;

· individual approach to cluster formations clients via an expanded service portfolio, etc.

Conclusion

The vector of transformational changes in cluster technologies is determined not only by the transparency degree to interaction between the key modern clusters entities, but also by their readiness to take a direct part in digital components integration into any fields and stages of cluster activities. Compliance with the synchronization and consistency in actions implemented both by the government and business will ensure achieving a sustainable innovative effect in the development of individual areas and the state as a whole.

Further research directions

Further research on the topic is seen in the disclosure of general mechanisms and models of cluster technologies transformation under the influence of the digitalization process. Exploring the tools features and technologies of economy cluster model adaptation to Russian reality that provide it an ability to utilize the innovative potential both in the context of economic and social development strategy and economic security.


Источники:

1. Marshall А. Principles of Economics. - _Macmillan and Co_, 1920.
2. Колосовский Н.Н. Теория экономического районирования. - Москва, 1969.
3. Кластерные политики и кластерные инициативы: теория, методология, практика. / Под. ред. Ю.С. Артамоновой, Б.Б. Хрусталева. - Пенза: Тугушев С.Ю., 2013. – 230 c.
4. Piore M. J., Sabel C. F. The Second Industrial Divide. Possibilities for Prosperity. - N.Y. BasicBooks, 1984. – 120 p.
5. Абашкин В.Л., Бояров А.Д., Куценко Е.С. Кластерная политика в России: от теории к практике // Форсайт. – 2012. – № 3. – c. 16- 27.
6. Раевский С.В., Винокурова Ю.В. Кластерная концепция организация структуры экономики региона // Региональная экономика: теория и практика. – 2007. – № 5(44). – c. 27.
7. Цихан Т.В. Кластерная теория экономического развития // Теория и практика управления. – 2003. – № 5. – c. 22-25.
8. Домбровский М.А. Экономические проблемы регионов и отраслевых комплексов // Проблемы современной экономики. – 2011. – № 2 (38). – c. 276-279.
9. Бухвальд Е.М., Виленский А.В., Киселев А.Н., Шесткаова М.В. Кластерные принципы организации производственного взаимодействия. / Информационно-аналитический сборник» Взаимодействие малого и крупного бизнеса». - Москва: Институт предпринимательства и инвестиций, 2000.
10. Палт М.М. Особенности этапов жизненного цикла кластеров // Управленческое консультирование. – 2015. – № 3. – c. 187-197.
11. Миронова М.Н. Мировой опыт кластерного подхода в государственной экономической политике: особенности и возможности применения в России // Известия Уральского государственного экономического университета. – 2010. – № 32(28). – c. 32–38.
12. Министерство экономического развития России. [Электронный ресурс]. URL: http://economy.gov.ru/minec/references/faq/201601125474568 (дата обращения: 11.11.2021).
13. Российская кластерная обсерватория. [Электронный ресурс]. URL: https://cluster.hse.ru (дата обращения: 11.11.2021).
14. Ассоциация кластеров, технопарков и ОЭЗ России. [Электронный ресурс]. URL: https://akitrf.ru/ (дата обращения: 11.11.2021).
15. Ганченко Д.Н. Инфраструктурный аспект инвестиционной привлекательности сферы услуг региона: активизация «точек роста» или … // Экономика и управление: теория и практика. – 2019. – № 2. – c. 9-17.
16. The Transformative Economic Impact of Digital Technology. Geneva 2015. [Электронный ресурс]. URL: http://unctad.org/meetings/en/Presentation/ecn162015p09_Katz_en.pdf (дата обращения: 11.11.2021).
17. Ganchenko D.N., Bodrov A.A. Digitalization of housing and communal services in the context of new industrialization // Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth: Proceedings of the 1st International Scientific Conference. (MTDE 2019). "Advances in Economics, Business and Management Research". 2019. – p. 192-197.
18. Гарифуллин Б.М., Зябриков В.В. Виды бизнес-моделей компаний в цифровой экономике // Креативная экономика. – 2019. – № 1. – c. 83-92.
19. Цифровая экономика: глобальные тренды и практика российского бизнеса / Под ред. Д.С. Медовникова. 2018. [Электронный ресурс]. URL: https://kc.hse.ru/wp-content/uploads/2018/02/VSHYE-2017Cifrovaya-yekonomika-globalnye-trendy-i-praktika-rossiyskogo-biznesa-2.pdf (дата обращения: 11.11.2021).
20. Инновационные кластеры цифровой экономики: теория и практика. / Под ред. А.В. Бабкина. - Санкт-Петербург: Издательство Политехнического университета, 2018. – 676 c.
21. Теоретико-методологические основы кластерного подхода. / Под ред. Н. И. Суслова. - Новосибирск: Изд-во ИЭОПП СО РАН, 2015. – 299 c.
22. Bataev A.V. Analysis and development the digital economy in the world // 31st IBIMA Conference: 25-26 April 2018, Milan, Italy. 2018.
23. Гетц М. Потенциал кластеров по формированию востребованных компетенций и развитию гибкости компаний // Форсайт. – 2019. – c. 72-83.
24. Wilson E. J. How to Make a Region Innovative. Strategy+business. February 28, 2012. – Spring 2012. Issue 66. [Электронный ресурс]. URL: http://m.strategy-business.com/article/12103 (дата обращения: 11.11.2021).
25. Дероше П. Возможна ли новая Кремниевая долина?. [Электронный ресурс]. URL: http://polit.ru/article/2011/04/08/deroche/ (дата обращения: 11.11.2021).
26. Обзор инновационных кластеров в иностранных государствах. Москва: Минэкономразвития РФ, 2011. 300 с. [Электронный ресурс]. URL: http://www.economy.gov.ru/wps/wcm/connect/economylib4/mer/about/structure/dep Svod/doc20110531_04 (дата обращения: 11.11.2021).
27. Bataev A., Gorovoy A., Mottaeva A. Evaluation of the future development of the digital economy in Russia // 32nd IBIMA Conference: 15-16 November 2018, Seville, Spain. 2018.

Страница обновлена: 19.03.2024 в 23:34:50