Search results

This paper aims at assessing the impacts of the national cluster policy, cluster age, cluster development benchmarks of neighbouring regions and the cumulative level of regional innovative capacity on the quantity and quality of cluster initiatives in Russia.

Hypotheses’ testing was carried out by a series of calculations comparing the qualitative and quantitative characteristics of cluster initiatives; the number of new cluster initiatives to the number of neighbouring regions, where cluster initiatives had begun to develop earlier; and ranks of regions within the Russian regional innovation scoreboard to the quantity and quality characteristics of cluster initiatives therein.

The results of the study empirically confirm that the national cluster policy significantly influenced the emergence and advancement of cluster initiatives in Russia. The proximity to the regions, having previously launched cluster support programmes, also had an impact on the emergence of new cluster initiatives. The cluster initiatives’ age had an ambiguous effect on their performance. Finally, the level of regional innovative capacity was correlated only with the number of cluster initiatives localised therein.

The findings show that along with the direct effects of the national cluster policy for the government-supported clusters, there are positive externalities, e.g. the emergence of new cluster initiatives throughout the country.

The research database of 277 cluster initiatives has been drawn up as a part of the first national cluster mapping and covers almost a decade of clustering activity in Russia. The study analyses not only the cluster initiatives supported by the federal government but also those developed independently.

There is an increasing interest in the international management literature in cultural differences between in-country regions. Yet, the regions of any country may be merely political products and not necessarily cultural units. The goal of this article is to propose clear empirical criteria for deciding if a set of entities, such as a country's administrative regions, can be legitimate units of cross-cultural analysis and to test these criteria in an empirical study.

The authors review the literature on what constitutes a unit of cross-cultural analysis and propose empirical criteria. For instance, the regions of a given country are meaningful units of cross-cultural analysis if one can replicate (an) established dimension(s) of culture at the regional level, including some of the dimension(s)' antecedents and predictive properties. The authors apply this test in the context of the Russian Federation (RF), using an RF database (18,768 respondents from 60 administrative regions) with items borrowed from the World Values Survey.

The RF regions pass the authors’ test. At the regional level, the selected items yield an individualism-collectivism (IDV-COLL) dimension that is similar to its nation-level counterpart in the revised Minkov-Hofstede model in terms of concept and antecedents (wealth differences and geographic latitude) and outcomes that are relevant in business (innovation rates and quality of governance). The authors also find other patterns that confirm the properties of RF regions as meaningful units of cultural analysis.

The authors’ criteria and the test based on them are suitable for large countries, with significant geo-climatic variety and ethnic diversity, but may be inapplicable in small countries with less diversity. It is questionable if the latter countries contain enough cultural variation to justify a cross-cultural analysis of their sub-national regions.

The authors’ criteria can be used in future research in any large country to decide if its regions justify a cross-cultural analysis in the field of management and business or any other field.

Cultural differences within a country are important as they may inform political and management decisions. Yet, to demonstrate that those differences are real, and not imaginary, one needs a methodology like the authors’.

The study contributes to the discussion of the meaningfulness of in-country regions as cultural units for cross-cultural analysis in international business by focusing on the RF.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

The focus of this paper is the emergence of Russia's multinational companies. It aims to analyse their motives to internationalise as well as the approaches to internationalisation. While relevance of the theoretical perspectives is highlighted, the purpose of this paper is to contribute to the understanding of the present‐day phenomenon of emerging Russian multinationals.

The paper relies on a qualitative approach for the analysis of the nature of Russian multinationals. The phenomenon of the emerging Russian multinationals is analysed through the prism and using insights from a number of subjects, namely transition studies, politics, innovation studies and international business studies.

The paper traces the evolution of Russian companies; the idiosyncratic path of their formation serves as a background for understanding of their internationalisation strategies. A special attention is devoted to the R&D activities of Russian multinational companies, and access to foreign technology is found to be an important driver of internationalisation.

The paper highlights relevance of further research on Russian multinationals and outlines research avenues.

The paper is rich in its practical implications. Specifically, it elaborates on the European Union‐Russian bilateral relations and the role of Russian multinationals in the European economies. The issue of political involvement is raised, and the paper seeks to identify whether Russian companies serve as tools of foreign policy, or they operate as business agents.

Despite their increasingly important role in the global economy, Russian companies have been largely overshadowed by the emergence of Indian and Chinese multinationals and not sufficiently addressed, even neglected, in the literature. Therefore, the objective of this paper is to fill in some gaps in the literature regarding this research area.

Economic sanctions imposed by the EU and United States on Russia have brought significant changes into Russian foreign economic policy, in particular leading to deepening cooperation with Asian countries and China in particular. The present contribution aims to shed light on the influence of sanctions on Russian multinational enterprises (MNEs) internationalization toward China using the example of energy and information and communication technology (ICT) industries.

The chapter builds on case study analysis. The choice of sectors allows us to highlight the recent strategic trends in the internationalization of oil and gas industry, dominated by state-owned multinationals, and in ICT by privately owned companies.

Our results provide empirical data for understanding the influence of sanctions on MNEs from the country being under the sanctions. In the case of Russian oil and gas industry and ICTs, research indicates that the shift toward China was not initiated primarily by the sanctions. In both cases, expansion to Asian markets was correlated with business interests in the Chinese market. However, changes in geopolitical and macroeconomic business environment accelerated Russian MNE’s pivot to China, for the purposes of attracting capital and reaching new markets in context of deteriorating relations with western partners. The cases demonstrate a moderating role of the industry in the context of sanctions, helping compensate for the slowdown of economic relations with traditional partners.

The novelty of the chapter is to delineate the consequences of sanctions on MNEs from the country being under sanctions. In this way, it illustrates the role of geopolitical environment in intensifying internationalization of Russian MNEs toward China.

The paper aims to present the results of the first Russian pilot study on technological level of organisations upon the answers of 2,500 respondents out of nine sectors of economy to a broad specialised questionnaire. The purpose of the study is to assess the technological level of organisations on the basis of qualitative information that comprehensively reflects its most important characteristics, as well as identify factors that affect the technological level of production.

It offers a look at which methodological approaches were developed and what the survey shows on characteristics of the application of technology (the scope and extent of the application, level of technology, the problems solved by applying specific types of technology) and the application of intellectual property rights.

The paper also highlights some interesting findings that suggest that the majority of national organisations tend to pursue technological self-sufficiency strategies and quite a large part of them are not active in either domestic or foreign Science & Tecnology markets.

An originality lies in the proposed methodological approaches of the study, in the selected indicators of progressivity and the scale of application of technology related to the level of production capacities of the surveyed medium and large enterprises and organisations. This identifies significant incentives for organisations to increase their technology level as well as competitive advantages for the respondents themselves and for their competitors.

The purpose of this paper is to explore empirically the linkages among level of economic, managerial, financial, criminal risks and patent activity in Russia. This paper examines the relationship between the economic, managerial, financial and criminal regional risks ratings, on the one hand, and patent activity, as measured by regional patent applications for inventions, on the other.

A random effect model was performed for a data sample of 83 regions, covering the period 2006-2010 in Russia.

The empirical results show that increased levels of regional economic risks are significantly associated with decrease in patent activity in Russia.

This study fills a gap within the literature and offers a unique analysis of regional risks and their impact on patent activity. The empirical results showed that economic risk ratings have had considerable negative impact on the patent activities on regional level in Russia.

This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.