The world’s largest community of scientists disintegrated following the dissolution of the Soviet Union. With extremely scarce resources and limited academic freedom as starting points, researchers in this region have been creating new knowledge; they have been building on rich scientific traditions in selected disciplines and, at times, paving new paths in non-traditional disciplines. At present, the cumulative contribution of post-Soviet countries to global research output is only three percent, indicating that these countries are not key players on the global research scene. This study uses bibliometric methods to offer novel empirical insight into the quantity and impact of academic publications; it also looks at the quality of journals in which the output is published. The findings reveal that fifteen post-Soviet countries differ considerably in terms of how much they have prioritised research, as well as the quantity, quality, and impact of their publications. The research productivity across the region has not been high and, taken together, these countries have produced publications of considerably lower quality and lower impact when viewed in the context of global research output. At the same time, researchers from post-Soviet countries tap into international collaborative networks actively, resulting in an exceptionally large proportion of publications from this region being internationally co-authored. In the historical context of Soviet research being known as one of the least collaborative globally, this finding indicates that researchers in the region are attractive to international collaborators and may be seeking such partnerships due to relatively modest research capacity at home.
This paper introduces a systematic technology trend monitoring (TTM) methodology based on an analysis of bibliometric data. Among the key premises for developing a methodology are: (1) the increasing number of data sources addressing different phases of the STI development, and thus requiring a more holistic and integrated analysis; (2) the need for more customized clustering approaches particularly for the purpose of identifying trends; and (3) augmenting the policy impact of trends through gathering future-oriented intelligence on emerging developments and potential disruptive changes. Thus, the TTM methodology developed combines and jointly analyzes different datasets to gain intelligence to cover different phases of the technological evolution starting from the ‘emergence’ of a technology towards ‘supporting’ and ‘solution’ applications and more ‘practical’ business and market-oriented uses. Furthermore, the study presents a new algorithm for data clustering in order to overcome the weaknesses of readily available clusterization tools for the purpose of identifying technology trends. The present study places the TTM activities into a wider policy context to make use of the outcomes for the purpose of Science, Technology and Innovation policy formulation, and R&D strategy making processes. The methodology developed is demonstrated in the domain of “semantic technologies”.
The main aim of this study is to compare Russian regions according to their ability to create new technologies efficiently and to identify factors that determine these differences over a long period of time. We apply data envelopment analysis (DEA) to assess the relationship between the results of patenting and resources of a regional innovation system (RIS). Unlike previous studies, we apply the DEA method over a long period, comparing regions to one another and over time. In general, RIS efficiency in Russia increased during the period, especially in the least developed territories. There was significant regional differentiation. The most efficient RIS were formed in the largest agglomerations with leading universities and research centers: the cities Moscow and Saint Petersburg and the Novosibirsk, Voronezh, and Tomsk regions. Econometric calculations show that RIS efficiency was higher in technologically more developed regions with the oldest universities and larger patent stock. Time is a crucial factor for knowledge accumulation and creating links between innovative agents within RIS. Entrepreneurial activity was also a significant factor because it helps to convert ideas and research into inventions and new technologies and it enhances the interaction between innovative agents. It is advantageous to be located near major innovation centres because of more intensive interregional knowledge spillovers. Public support of more efficient regions can lead to a more productive regional innovation policy.
Researchers focus on understanding the nature of ecosystems and societies as well as explaining how paradigms change. These efforts are presented and disseminated through scholarly work in scientific literature. The pool of knowledge generated through databases allows one to track how our understanding changes and how paradigms shift through time. The present study is concerned with the domain of innovation policy, which is affected directly by societal and technological change and is a good archetype for demonstrating the scientific change perspective. In recent years, scientometrics has been frequently used to measure and analyze progress in science, technology and innovation. This study makes use of a combination of scientometric analysis and evolutionary framework analysis to demonstrate the evolution of innovation policy domain. Kuhn’s seminal approach is applied for classifying and interpreting the phases across the evolution of the domain within a 30-year timeframe. The analysis demonstrates that the innovation policy domain is at the “crisis stage” as a result of ongoing with transformations in the society, technology, economy and policy. These transformations affect both supply and demand sides of innovation and call for an evolution in the innovation policy domain. Although this by no means represents that the innovation policy domain is in a “deadlock”, the present study asserts that there is a new quest in innovation policy by adapting, re-framing or re-constructing the scope of the domain. The anticipated paradigm shift is expected to lead to a more de-centralized and distributed understanding of the world for innovation policy making.
A Triple Helix (TH) network of bi- and trilateral relations among universities, industries, and governments can be considered as an ecosystem in which uncertainty can be reduced when functions become synergetic. The functions are based on correlations among distributions of relations, and therefore latent. The correlations span a vector space in which two vectors (P and Q) can be used to represent forward “sending” and reflexive “receiving,” respectively. These two vectors can also be understood in terms of the generation versus reduction of uncertainty in the communication field that results from interactions among the three bi-lateral channels of communication. We specify a system of Lotka–Volterra equations between the vectors that can be solved. Redundancy generation can then be simulated and the results can be decomposed in terms of the TH components. Furthermore, we show that the strength and frequency of the relations are independent parameters in the model. Redundancy generation in TH arrangements can be decomposed using Fourier analysis of the time-series of empirical studies. As an example, the case of co-authorship relations in Japan is re-analyzed. The model allows us to interpret the sinusoidal functions of the Fourier analysis as representing redundancies.
For several decades the Soviet academic psychology community was isolated from the West, yet after the collapse of the Soviet Union each of the 15 countries went their own way in economic, social, and scientific development. The paper analyses publications from post-Soviet countries in psychological journals in 1992–2017, i.e. 26 years after the collapse of the Soviet Union. Over the period in question, 15 post-Soviet countries had published 4986 papers in psychology, accounting for less than one percent of the world output in psychological journals. However, the growth of post-Soviet countries’ output in psychological journals, especially that of Russia and Estonia, is observed during this period. Over time, post-Soviet authors began to write more papers in international teams, constantly increasing the proportion of papers in which they are leaders and main contributors. Their papers are still underrepresented in the best journals as well as among the most cited papers in the field and are also cited lower than the world average. However, the impact of psychological papers from post-Soviet countries increases with time. There is a huge diversity between 15 post-Soviet countries in terms of contribution, autonomy, and impact. Regarding the number of papers in psychological journals, the leading nations are Russia, Estonia, Lithuania, Ukraine, and Georgia. Estonia is the leader in autonomy in publishing papers in psychological journals among post-Soviet countries. Papers from Estonia and Georgia are cited higher than the world average, whereas papers from Russia and Ukraine are cited below the world average. Estonia and Georgia also boast a high number of Highly cited papers.
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.
We consider the “Matthew effect” in the citation process which leads to reallocation (or misallocation) of the citations received by scientific papers within the same journals. The case when such reallocation correlates with a country where an author works is investigated. Russian papers in chemistry and physics published abroad were examined. We found that in both disciplines in about 60% of journals Russian papers are cited less than average ones. However, if we consider each discipline as a whole, citedness of a Russian paper in physics will be on the average level, while chemistry publications receive about 16% citations less than one may expect from the citedness of the journals where they appear. Moreover, Russian chemistry papers mostly become undercited in the leading journals of the field. Characteristics of a “Matthew index” indicator and its significance for scientometric studies are also discussed.
Impact factors for 20 journals ranked first by Journal Citation Reports (JCR) were compared with the same indicator calculated on the basis of citation data obtained from Scopus database. A significant discrepancy was observed as Scopus, though results differed from title to title, found in general more citations than listed in JCR. This also affected ranking of the journals. More thorough examination of two selected titles proved that the divergence resulted mainly from difference in coverage of two products, although other important factors also play their part.
Technologies may have significant effects on productivity in the agricultural sector as documented in the related literature. However, those impacts vary from country to country. These differences could partially reflect the distinct scientific landscapes, science technology and innovation (STI) policies and approaches to R&D. In order to explain the cross-country volatility of agricultural productivity, we aim to study issues of STI development in the agricultural sector in each country. Among other characteristics of STI in general and the scientific landscape, in particular, we looked at the diversification of research publication between subfields of agricultural science. We estimated the research diversification parameter and studied its relation to economic performance of an agricultural sector. Our main finding shows that R&D funding, if carefully balanced with the diversification of agricultural science, could improve research performance and eventually productivity in an agricultural sector.
In this study, the evolution of the connected health concept is analysed and visualized to investigate the ever-tightening relationship between health and technology as well as emerging possibilities regarding delivery of healthcare services. A scientometric analysis was undertaken to investigate the trends and evolutionary relations between health and information systems through the queries in the Web of Science database using terms related to health and information systems. To understand the evolutionary relation between different concepts, scientometric analyses were conducted within five-year intervals using the VantagePoint, SciMAT, and CiteSpace II software. Consequently, the main stream of publications related to the connected health concept matching telemedicine cluster was determined. All other developments in health and technologies were discussed around this main stream across years. The trends obtained through the analysis provide insights about the future of healthcare and technology relationship particularly with rising importance of privacy, personalized care along with mobile networks and mobile infrastructure.
Gender disparities persist in several areas of society and scientific research is no exception. This study describes the evolution of the place of women in Russian science from 1973 to 2012, in terms of published research output, research productivity, international and national collaboration, and scientific impact, taking into account the socioeconomic, political and historic context of the country, which was marked by the fall of the USSR in 1991. The results show that gender parity is far from being achieved. Women remain underrepresented in terms of their contribution to research output and scientific impact in almost all disciplines, with Mathematics and Physics, research areas in which Russia is specialized, having the largest gap. Men and women show different collaboration patterns on the national and international level, whereas women are preeminent on the national scene, men are on the international one. Although the impact of women’s scientific output significantly increases after the fall of the USSR, the gap between both genders remains stable over time for most of the disciplines. As a result, this increase cannot be interpreted as an improvement of the women’s relative influence in Russian science, but rather an improvement of Russian science impact in general.
BRICS as an association of five major emerging national economies (Brazil, Russia, India, China and South Africa) has been expanding its international cooperation, in particular with developing countries. This process sometimes is referred as building of a BRICS Plus association. Science and technology, being a key driver of economic growth, is one of the most important area of socioeconomic development. It becomes increasingly complicated, requires expensive research infrastructure, skilled workforce, and high-tech laboratory equipment, therefore no one individual country in the world can afford a full-scale support to all areas of research and development. That is why collaboration in this area is considered a very promising activity. Following the BRICS Plus concept proposed by Chinese Foreign Minister Wang Yi in 2017, this paper presents one of the first attempts to identify key priorities to be addressed by BRICS in establishing and enhancing S&T cooperation with a number of major developing countries, primarily from Global South. Based on a set of criteria for country selection (population, economic potential, R&D sector capacities; research output; etc.), 21 countries are considered in this paper as a BRICS Plus group. A detailed analysis of publication activities of BRICS Plus countries and their international scientific collaboration based on a wide range of bibliometric indicators was applied for the identification of promising thematic areas for research collaboration between BRICS and BRICS Plus countries. A special analysis is presented for 14 science, technology, and innovation areas, which are regarded as common priorities for BRICS countries.
This paper investigates the social space of physics research institutions. Scientific capital is a well-known concept for measuring and assessing the accumulated recognition and the specific scientific power developed by Pierre Bourdieu. The scientific capital of a physics research institution manifests itself as a reputation, a high-profile name in the field of physics, symbols of academic recognition, and scientific status. Using citation statistics from the Web of Science Core Collection and sociological data of dedicated survey “The Monitoring of the Labor Market for Highly Qualified R&D Personnel” we construct the social space of Russian physics institutions. The analysis reveals generalized grounds of social space of Russian physics institutions: principles of visibility and scientific capital. The study highlights internal differentiation of physics institutions on three groups (“major”, “high energy”, and “secondary” institutions). The social space of physics research institutions provides a map of field of physics in Russia. This research may be a useful starting point for developing a more comprehensive study of the field of physics.
Since early 1960s, there has been a growing interest in the emergence and development of new technologies accompanied by a strong wish from decision makers to govern related processes at the corporate and national levels. One of the key categories that appeared to set up analytical and regulatory frameworks was the ‘advanced technology’ category. Primarily associated with computer electronics and microelectronics, it soon had new meanings derived from a variety of professional discussions primarily in the social sciences. Later in a new term, ‘emerging technologies’, appeared to highlight the speed of change in a wide range of promising research areas. This paper focuses on the evolution of academic discussions concerning advanced and emerging technologies in social sciences literature for the period from 1955 until 2015. In order to identify whether studies in these areas constitute separate research fields, the paper studies the evolution of co-citation networks and the centrality characteristics of transitionary references. It was shown that social studies in emerging technologies demonstrate better consistency in background in literature. However, an analysis of transitionary references and their centrality characteristics can hardly confirm the existence of separate research fields in both cases. The suggested method for the identification and tracking of papers mediating ongoing discussions in a selected knowledge network may be helpful in understanding the evolution of weakly conceptualized and growing research areas.
Different research traditions have developed over time to study the quantitative aspects of information and knowledge production, such as scientometrics, bibliometrics, librametrics, informetrics, cybermetrics, webometrics, or altmetrics. These information metrics, or iMetrics, as they were labeled by Milojević and Leydesdorff in Scientometrics 95(1):141–157, 2013, are unified by the usage of quantitative data analysis, applying various statistical methods and techniques and are often used to supplement and complement each other. Representing different research traditions, they jointly form a common research field, a “discipline with many names”. In this article, we look at the development of iMetrics field and its evolution over time using bibliometric network analysis and identify its common basis, formed by the most important publications, journals, scholars and topics. The dataset consists of articles from the Web of Science database (26,414 records with complete descriptions). Analyzing the citation network, we evaluate the field’s growth and identify the most cited works. Using the Search path count (SPC) approach, we extract the Main path, Key routes paths, and Link islands in the citation network. The results show that in the last forty years the number of published papers increased, and it doubles every 8 years; the number of single author papers dropped from 50 to 10 %, and the number of papers authored by 3 or more authors is increasing. We make the conclusions about the field’s development and its current state. We also present the main authors, journals and keywords from the field, which form its common basis.
When scientists change jobs, they bring to their new workplace the experience, tacit knowledge and social ties they acquired at their previous workplace. Not only is the level of mobility important when discussing knowledge transfer between academic organizations or between regions, but the topology of a mobility network is also of crucial importance. This study presents a comparison of the structure of internal migration networks for Russian and American physicists, more specifically for scholars working in the field of applied physics. The comparison resulted in the set of hypotheses of how the features of the network are connected to the overall scientific productivity of the system.
In this study we compare internationalization of academic journals in six fields of science. Internationalization was investigated through journals’ concentration on publishing papers from particular countries, relationship between the geographical distributions of editors and authors, and relationship between language of publication and the geographical distribution of papers. Having analyzed more than 1,000 journals we can state that social sciences literature in the fields considered is still nationally and linguistically fragmented more than natural sciences literature, but in some cases the gap is not so big. One of the consequences concerning research output assessment is that usefulness of international databases having national disparity in coverage is still limited in social sciences.
This paper presents the analysis of journals publishing articles on Social Network Analysis (SNA). The dataset consists of articles from the Web of Science database obtained by searching for “social network*”, works intensively cited, written by the most prominent authors, and published in the main SNA journals up to July 2018. There were 8,943 journals in 70,792 articles with complete descriptions. Using a two-mode network linking publications with journals and a one-mode network of citations between articles, we constructed and analysed the networks of citations and bibliographic coupling among journals. Based on the analysis of these networks, we identify the most prominent journals publishing SNA and reveal their relationships to each other. Special attention is given to the position of journal Social Networks among other journals in the field. We trace the development of some relationships through time and look at their distributions for selected journals. The results show that the field is growing, which can be seen by the annual rise of the number of journals publishing papers in SNA, and the average number of papers on SNA per journal (almost 3 in recent years). The journals which are currently present in the field belong to social and natural sciences. The social sciences group is represented mainly by journals from sociology and management. Other journals mainly come from the fields of physics, computer science, or are general scientific journals. While journals from social and computer sciences are connected with journals from the same fields, physics journals Physica A and Physical Review E have developed their own niche. SNA’s main outlet Social Networks takes a very coherent and important position. It had explicit primacy up to the 2000s; in recent years its input has declined significantly due to the large number of papers published in other journals in the field.
This paper is devoted to the challenges of measuring, analyzing and visualizing research capacity of university. We identify the related methodological issues, propose solutions and apply these solutions to a complex analysis of the research potential of three departments of a Russian university. First, we briefly review the current literature on different aspects of an analysis of research capacity of university. The next step is a discussion on the key challenges faced when analyzing the publication activity of a university. Further, we discuss the opportunities offered by and limitations of using the Web of Science and Scopus databases to determine the research capabilities of universities. In the empirical section of the paper, we analyse the research capacity of university departments and individual employees using simple yet illustrative tools of bibliometric analysis. We also make recommendations for university administrative personnel, which can be derived from our analysis.
The article discusses the process of textually mediated communication in science and proposes an approach that complements citation analysis. Namely, it addresses the question of how the author’s text is read by the reader and whether the reader interprets the text in the same manner as the author. Fifty-seven scholarly contributions (articles, book chapters and book reviews), written by three social scientists, were content analyzed with the help of the QDA Miner and WordStat computer programs. The outcomes of the qualitative coding were compared with the outcomes of the analysis of word co-occurrences and the outcomes of the analysis on the basis of a dictionary based on substitution. Our findings suggest that texts have plural interpretations. Depending on the reading context, either the author’s or the reader’s perspective prevails. Also, both the author and the reader may read the text in a either deep or perfunctory manner. Deep reading necessitates spending significant time and cognitive resources.