National culture as a correlate of research impact and productivity

Juneman Abraham

doi:10.12688/f1000research.18283.1

Abstract

National culture has been overlooked in discussions related to research productivity and impact owing to individual, socio-political structure, and economic factors. This study shows the relationships between the dimensions of cultural value orientation of the nation and research performance indicators. More than 60 countries were included and Pearson correlation analysis was employed. The variables were taken from Geert Hofstede and Scimago Journal & Country Rank worksheets. This study found that (1) Individualism has significant correlations with the majority of the indicators; (2) Power distance and indulgence correlate with a country’s research impact in the form of citation per document; (3) Masculinity, long term orientation, and uncertainty avoidance do not correlate with the indicators. Owing to the fact that the national culture is relatively enduring, countries need to measure their elasticity of hopes and action plans in an effort to boost research productivity and impact, by integrating the national culture in the estimate.

Highlights

Makri (2018) recently released a report on the increasing number of publications in various countries
Among 68 countries, IND is positively correlated with CPD (r=0.506, p
power distance (PD) might manifest itself in academic writing in the form of rigid, authoritative, defensive, and dogmatic styles (Koutsantoni, 2005)

Summary

Introduction

Makri (2018) recently released a report on the increasing number of publications in various countries. Several predictors of research productivity and impact had been identified, i.e. author characteristics, co-authorship networks, citation history, journal impact factors, twits (Xiaomei et al, 2017), cohort effects (in terms of scientific discipline), age, career stages, gender, the country of origin of the PhD holders, and reward structure of the research enactment (Claudia & Francisco, 2007). They are mostly at the individual and institutional level. The predictors are the number of universities, GDP per capita, control of corruption, civil liberties (Mueller et al, 2016), country’s wealth and population size, country’s value of research tradition, tenure and promotion criterion, experimental costs, IRB (Institutional Review Boards) review flexibility, language barrier, and the training of new young researchers (Demaria, 2009)

Methods

Results

Discussion

Conclusion