A network analysis of research productivity by country, discipline, and wealth

PLoS One. 2020 May 13;15(5):e0232458. doi: 10.1371/journal.pone.0232458. eCollection 2020.

Abstract

Introduction: Research productivity has been linked to a country's intellectual and economic wealth. Further analysis is needed to assess the association between the distribution of research across disciplines and the economic status of countries.

Methods: By using 55 years of data, spanning 1962 to 2017, of Elsevier publications across a large set of research disciplines and countries globally, this manuscript explores the relationship and evolution of relative research productivity across different disciplines through a network analysis. It also explores the associations of those with economic productivity categories, as measured by the World Bank economic classification. Additional analysis of discipline similarities is possible by exploring the cross-country evolution of those disciplines.

Results: Results show similarities in the relative importance of research disciplines among most high-income countries, with larger idiosyncrasies appearing among the remaining countries. This group of high-income countries shows similarities in the dynamics of the relative distribution of research productivity over time, forming a stable research productivity cluster. Lower income countries form smaller, more independent and evolving clusters, and differ significantly from each other and from higher income countries in the relative importance of their research emphases. Country-based similarities in research productivity profiles also appear to be influenced by geographical proximity.

Conclusions: This new form of analyses of research productivity, and its relation to economic status, reveals novel insights to the dynamics of the economic and research structure of countries. This allows for a deeper understanding of the role a country's research structure may play in shaping its economy, and also identification of benchmark resource allocations across disciplines for developing countries.

MeSH terms

  • Developed Countries / economics
  • Developed Countries / statistics & numerical data
  • Developing Countries / economics
  • Developing Countries / statistics & numerical data
  • Economic Status
  • Efficiency*
  • Geography / statistics & numerical data
  • Humans
  • Publications / economics
  • Publications / statistics & numerical data
  • Publications / trends
  • Research* / economics
  • Research* / statistics & numerical data
  • Research* / trends
  • Scholarly Communication / economics
  • Scholarly Communication / statistics & numerical data
  • Scholarly Communication / trends

Grants and funding

The authors received no specific funding for this work. German Molina co-owned a private firm called Idalion Capital Group, but nobody else in that company worked on this manuscript. He was part of the project as an independent researcher during his free time, and this work was not performed as part of his work at said company. Idalion Capital Group did not provide financial support to German Molina, and did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section.