Abstract
We use citation data of scientific articles produced by individual nations in different scientific domains to determine the structure and efficiency of national research systems. We characterize the scientific fitness of each nation—that is, the competitiveness of its research system—and the complexity of each scientific domain by means of a non-linear iterative algorithm able to assess quantitatively the advantage of scientific diversification. We find that technological leading nations, beyond having the largest production of scientific papers and the largest number of citations, do not specialize in a few scientific domains. Rather, they diversify as much as possible their research system. On the other side, less developed nations are competitive only in scientific domains where also many other nations are present. Diversification thus represents the key element that correlates with scientific and technological competitiveness. A remarkable implication of this structure of the scientific competition is that the scientific domains playing the role of “markers” of national scientific competitiveness are those not necessarily of high technological requirements, but rather addressing the most “sophisticated” needs of the society.
Highlights
Measuring the quality of research on national scale is of great interest to stakeholders and policy-makers for deciding on, e.g., funding allocations and scientific priorities
Less successful nations are competitive only in sectors in which many other nations are active. Note that this picture defies the standard economic approach of the wealthiest nations producing only a few products with high complexity, which would result in a optimal strategy only in a static situation, whereas, the strongly dynamical situation of the world market suggests that flexibility and adaptability are mostly important to be competitive in a competition-driven changing system—in analogy with bio-systems evolving in a competitive dynamical environment [6, 7]
To quantify the triangularity of the matrices, we use the concept of nestedness—in particular, we measure the nestedness based on overlap and decreasing fill (NODF) [9]
Summary
Measuring the quality of research on national scale is of great interest to stakeholders and policy-makers for deciding on, e.g., funding allocations and scientific priorities. May [1] analyzed the output and outcomes from research investment over years 1981–1994, comparing scientific research outputs among several nations from a variety of viewpoints. King [2] presented a similar, more refined analysis over years 1993–2002. With the aim of determining the scientific impact of nations, King built a rank of nations ordering them according to their share of world citations. PLOS ONE | DOI:10.1371/journal.pone.0113470 December 10, 2014
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