Revealing the scientific comparative advantage of nations: Common and distinctive features

USA vs Russia in the scientific arena

This work contrasts the scientific standing of the USA and Russia in 146 scientific disciplines. We consider four dimensions of competitive positioning: the contribution to global scientific advancement, the researchers' productivity, the scientific specialization indexes, and the efficiency in resource allocation across disciplines. Differently from previous literature, we use discipline-normalized output to input indicators, thus avoiding distortions due to different intensities of publication across disciplines. Results show that the USA outperforms Russia in contribution to world scholarly impact in all but four disciplines, and is more productive in all but two disciplines. The USA is less efficient in allocating resources to the disciplines where it performs better, probably due to its higher research diversification.

Using Rasch KIDMAP to identify whether China dominates the research area of computer science (CS) based on the specialization index of article citations: Bibliometric analysis

BACKGROUND

Scientific comparative advantage is measured by using a specialization index (SI) of article citations. The profile data have been published in the literature. However, no such research has been conducted to determine which countries dominate the field of computer science (CS) (subject category [SC]) using the SI. A KIDMAP in the Rasch model has been applied to the display of individual student performance in school. Based on the SI of article citations, we used KIDMAP to determine whether China dominates the field of CS.

METHODS

The data were derived from published research in the Web of Science, which included 199 countries and 254 subject categories (SC, between 2010 and 2019). A total of 96 SC related to biomedicine were extracted. We examined 7 factors associated with CS using exploratory factor analysis. Based on the SI in CS under the Rasch model, 1-dimensional SCs on CS were displayed on Wright Maps and KIDMAPs. An analysis of the dominance of CS in China was presented on the basis of a scatter plot.

RESULTS

Our findings indicate that (1) CS domains are divided into 2 groups (traditional and advanced domains); (2) no evidence has been found that China dominates CS; based on SI indicators, China was ranked third with --2.62 and 0.79 logits after Taiwan and Slovenia (-(-2.62 and 9.24 logits in Factors 1 and 2) in the period from 2010 to 2019.

CONCLUSIONS

There is insufficient evidence to demonstrate that China has a dominant role over other countries/regions despite ranking third in CS. In future studies, it is recommended to include a KIDMAP visual to assess dominant roles in other areas of research, rather than to confine ourselves to CS as we did in this study.

Research Topic Specialization of Universities in Information Science and Library Science and Its Impact on Inter-University Collaboration

Universities significantly empower the development of science and technology, and inter-university research collaborations have been one of the major approaches. Considering each university has its expertise regarding research topics in a given discipline, the present paper examines the specialization of university research and its impact on inter-university collaborations. Based on a keyword network constructed via research articles in Information Science and Library Science, 10 research topics are identified. Accordingly, the research topic diversity of a university and the research topic similarity between two universities are quantified. The universities with diverse research topics are found to be more collaborative. A further collaboration network analysis based on the Quadradic Assignment Procedure reveals the important role of research topic similarity on the closeness and impact of collaborations. The different research topic specializations largely prevent close collaborations between two universities, but on the other hand, have the potential to form a complementary combination of knowledge leading to more impactful research output. The analysis and results highlight the important role of research topic specialization and provide insights for the university- or department-level strategy for research collaborations.

Researchers' transfer network reveals the evolution of national science and technology capabilities

Science and technology capability refers to the comprehensive capability of all factors that affect the development of science and technology, mainly referring to human and material factors related to science and technology, among which human resources are the foundation and driving force. Therefore, researchers become a unique research perspective for the evaluation of national science and technology capabilities. Taking the integrated circuit field as the analysis case, this article proposed a researchers' transfer network model based on the online open source literature database. From the published literature information, the model obtains the researchers' transfer network that has a core-periphery structure. The core nodes are the European Union, the United States, China, etc., and these nodes are the most closely connected. A country/region role evolution model is also proposed, which reveals the characteristics of the role evolution of the European Union, the United States, China, and other countries from the perspective of researchers' transfer, especially their transfer between countries.