Publications

Using digital technologies for technology roadmapping has the advantage of significantly extending the range of information sources used for the roadmap. Thus, a more solid evidence-based foundation for the integrated roadmap is provided, and the risk of biased individual judgements limited. The main challenge of extending the information base lies in processing information and integrating into aggregate indicators for the final roadmap. The revised methodology was pilot tested for a roadmap on the development of artificial intelligence technologies and their applications in a large Russian company. The roadmap is being already used by a large state-owned Russian corporation for strategic and investment decision making and project management including investment priority-setting, identification of technological forks and strategic alternatives, revelation of areas of presence and lack of competence, risk assessment, identification of potential consortia and the potential tasks for them, project expertise, and proactive project search.

The paper discusses existing trends and prospects for decarbonization in the Commonwealth of Independent States (the CIS), an international organization that regroups Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, and Uzbekistan. The CIS occupies a significant share of Eurasia, representing a large share of global energy consumption and production with a corresponding carbon footprint. These countries and their decarbonization prospects are rarely discussed in the English-language scientific literature. This paper fills in this gap by offering a comprehensive analysis based on statistical data, policy documents, and scenario-based future projections. The results underline that revisiting Nationally Determined Contributions, increasing energy efficiency, and decoupling GDP growth from greenhouse gas emissions are essential to the implementation of the Paris Agreement. The future energy mix should include larger shares of renewable energy, hydrogen, fossil fuels (highly efficient with carbon capture), and nuclear energy to achieve energy security and decarbonize the economy of the region in the long term.

This pocket data book contains the most recent statistical data representing the level and dynamics of the digital economy development in the Russian Federation. International comparisons are provided for a number of indicators.

The data book includes information of the Russian Federal State Statistics Service (Rosstat), Ministry of Digital Development, Communications and Mass Media of the Russian Federation, Federal Customs Service of Russia, Russian Central Bank (Bank of Russia), European Statistical Office (Eurostat), Organisation for Economic Cooperation and Development (OECD), International Telecommunication Union (ITU), United Nations Conference on Trade and Development (UNCTAD), UN Department of Economic and Social Affairs, World Intellectual Property Organisation (WIPO), Scopus database, and results of own methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.

Currently distributors ensure the operation of the whole value chain in the music industry, while most researchers focus on technological, streaming and copyright impact in light of digitalization. This paper tries to understand the influence of digitalization on business models and the role of music distributors in a value chain. Research identifies operational processes that were changed due to digitalization, barriers that arose, and actions taken to overcome them on the corporate level. Through retrospective case study based on an interview with the CEO, the experience of the Russian music distribution company Broma16 is analyzed. This paper describes the goals of business model transformation, drivers, performed activities and their results. The research derives four consequences of digitalization for the firm’s business model and role in a value chain: the firm can be considered as a technological company rather than a music company. Distribution relies on digital instruments for management and marketing. Local intermediaries get more opportunities to enter foreign markets, but they have to perform innovations in these markets. Music distributors operate at the complicated intersection of copyright and technological aspects. The research applies a general theoretical framework for the study of digital transformation of business models. A similar approach can be used to do research on companies in music and other creative industries, and to conduct workshops with industry representatives. The paper provides value for practitioners in emerging music markets, for example, Brazil, Argentina and Mexico, due to the presentation of management practices towards digitalization and the consequences of transformation for the distribution role.

One of the central objectives in foresight development is increasing its effectiveness and impact upon decision-making. This paper is focused on improving the link between foresight and science, technology, and innovation (STI) policy by overcoming the barriers that stand in the way at the very beginning of a foresight study. For this purpose, the key challenges for integrating foresight into STI policy are identified, summarized and systematized. They include challenges and barriers from the external environment, internal political situation and shortcomings in the planning and implementation of foresight. For deeper understanding the connection between foresight and STI policy three types of gaps between foresight and STI policy are considered. As the possible answer to these different challenges and gaps the pre-foresight integrative methodology for STI Policy is proposed. The practical case of the Russian foresight programme is used to illustrate challenges for integrating foresight into STI policy in the real practice and their possible solution accordingly to the proposed methodology.

The article contributes to the research discussion around the human-natural and social-ecological systems by identification of a comprehensive list of global trends related to integrated interaction between environmental systems and human development, including climate change, pollution, new quality of economic growth, and challenges for education and healthcare. The foresight study behind it encompasses a combination of quantitative (big data ) and qualitative (expert) methods. This approach allows for a systemic vision of structural shifts, assessing their probability and impact. The outcomes of the study include the list of global environmental and human development trends and factors classified by STEEPV categories, their effects that split into opportunities and threats, and an assessment of their inter-relation and mutual impact. Policy implications focus on possible areas of intervention for sustainable growth.

Since banks are competing in challenging and dynamic market environments, an anticipatory system generating futures-relevant knowledge is of primordial importance for an effective bank strategy. The objective of this research is to investigate how corporate foresight and competitive intelligence, considered as parts of an anticipatory system, create knowledge. Our main contribution lies in arriving at a better understanding of these processes in the mainstream of knowledge creation grounded in the SECI model. To this end, we followed a longitudinal case-study methodology for more than eight months within a leading bank in Morocco. The findings show that while the competitive intelligence unit focuses more on commercial and competitor intelligence targeting hence other banks market strategies, the corporate foresight unit tries to identify the bank market weak signals and major trends in the banking sector. Knowledge creation is mainly triggered in the social interaction context in the competitive intelligence unit, while the externalization phase involving interacting Bas is critical to knowledge creation in the corporate foresight unit. The results also confirm the presence of a black hole strategy problem and a lack of coordination between competitive intelligence and corporate foresight processes, thus highlighting the need for dynamic integrated anticipatory systems.

The article provides a statistical analysis of the properties of lexical and n-gram models of the Russian language based on the news text corpus. A specialized corpus of political news articles of recent years has been created, reflecting a narrow area of language use. The token and n-gram dictionaries are compiled, the coverage values are found, as well as the values of entropy. Lemmatization of the original text corpus and extrapolation of the dictionary volumes are performed.

This pocket data book contains the most recent statistical data representing the level and dynamics of the digital economy development in the Russian Federation. International comparisons are provided for a number of indicators.

The data book includes information of the Russian Federal State Statistics Service (Rosstat), Ministry of Digital Development, Communications and Mass Media of the Russian Federation, Federal Customs Service of Russia, Russian Central Bank (Bank of Russia), European Statistical Office (Eurostat), Organisation for Economic Cooperation and Development (OECD), International Telecommunication Union (ITU), United Nations Conference on Trade and Development (UNCTAD), UN Department of Economic and Social Affairs, World Intellectual Property Organisation (WIPO), Scopus database, and results of own methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.

Identifying and monitoring business and technological trends are crucial for innovation and competitiveness of businesses. Exponential growth of data across the world is invaluable for identifying emerging and evolving trends. On the other hand, the vast amount of data leads to information overload and can no longer be adequately processed without the use of automated methods of extraction, processing, and generation of knowledge. There is a growing need for information systems that would monitor and analyse data from heterogeneous and unstructured sources in order to enable timely and evidence-based decision-making. Recent advancements in computing and big data provide enormous opportunities for gathering evidence on future developments and emerging opportunities. The present study demonstrates the use of text-mining and semantic analysis of large amount of documents for investigating in business trends in mobile commerce (m-commerce). Particularly with the on-going COVID-19 pandemic and resultant social isolation, m-commerce has become a large technology and business domain with ever growing market potentials. Thus, our study begins with a review of global challenges, opportunities and trends in the development of m-commerce in the world. Next, the study identifies critical technologies and instruments for the full utilization of the potentials in the sector by using the intelligent big data analytics system based on in-depth natural language processing utilizing text-mining, machine learning, science bibliometry and technology analysis. The results generated by the system can be used to produce a comprehensive and objective web of interconnected technologies, trends, drivers and barriers to give an overview of the whole landscape of m-commerce in one business intelligence (BI) data mart diagram.

Entrepreneurial ecosystems research has largely focused on the profile of a handful of successful locations. This has prevented a deeper understanding of the mechanisms that shape entrepreneurial activity across the geographical space. Our goals in this research are (1) to identify the critical dimensions of entrepreneurial ecosystems, and (2) to assess whether successful ecosystems rely on heterogeneous configurations. Through fuzzy-set qualitative comparative analysis, we address this issue with data from the State of São Paulo, Brazil. Findings generate a typological hierarchy of attributes, where the range of critical dimensions seems to be much more restricted than previously argued, and alternative configurations appear to lead to similar outcomes. A first pivotal path toward establishing a thriving ecosystem is fundamentally based on the conditions of the knowledge Infrastructure. A second approach combines elements of the socioeconomic system with the knowledge environment. Although some elements are ubiquitous, contributing attributes differ across distinct configurations, suggesting some level of heterogeneity in the dominant dimensions of entrepreneurial ecosystems. Such evidence contributes to the debate on entrepreneurial ecosystems’ dimensions and elements, offering exploratory insights on alternative ways to promote an environment conducive to knowledge-intensive ventures.

The global challenges faced by the humankind encompass access to clean and affordable energy for all, shifting to the green development path and tackling the consequences of climate change. Success in addressing the related goals relies on the concerted efforts of society at large, whereby researchers may offer new solutions and media could raise awareness and organize public discussions. This chapter examines the policy landscape created for addressing the global energy and environment goals, as defined in the international documents. Moreover, the chapter analyses attention given to these goals by researchers, business and media. More specifically, the chapter focuses on goals set in the legally binding universal agreements and conventions formulated and adopted by the United Nations: “Transforming our world: the 2030 Agenda for Sustainable Development” (SDGs or SG), the Paris Agreement (PA), the “Future We Want” Resolution (FWW), and the Johannesburg Plan of Implementation (JPI). Research methods include policy analysis and the smart big data analysis of thousands of publications on the topic. The authors highlight controversial policy issues, as well as relatively low attention to global energy challenges on behalf of mass media. Researchers address these challenges much more often, however, focus primarily on a few SDGs. The outcomes underline further steps to be taken by global and national policymakers.

This paper aims at assessing energy inequality, which is at the center of SDG7, in the Eurasian Economic Union – a recently created international organization with arguably the closest integration in the energy sphere for all member states: Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia. The research was performed with the use of cross-disciplinary methods, including literature review, analysis of policy documents (applied policy analysis), and two quantitative tools widely used for energy policy analysis – the decomposition of energy consumption based on the Logarithmic Mean Divisia Index and the inequality estimation by using the Theil index. The study identified contribution of three types of factors to energy consumption of the entire Eurasian Economic Union: economic growth − the increase of GDP, the relative structural changes in the economy, and energy intensity shifts. Theil index allowed determining the level of inequality in the region's energy consumption. The quantitative analyses demonstrated that in 2000–2017 the increase of GDP and energy intensity in the region were the main reasons that had determined the growing energy consumption. Theil index analysis showed that inequality of GDP-related energy consumption is decreasing, whereas the population-related inequality is increasing. Additionally, policy implications for inclusive and sustainable energy integration in the region are discussed. The required policy changes range from introducing amendments to the Eurasian Economic Union Treaty and structural changes to very precise science and technology policy tools.