Decoding National Innovation Capacities: A Comparative Analysis of Publication Patterns in Cybersecurity, Privacy, and Blockchain

被引:4
作者
Bran, Emanuela [1 ,2 ]
Rughinis, Razvan [1 ,3 ]
Turcanu, Dinu [4 ,5 ]
Staiculescu, Ana Rodica [2 ,3 ,6 ]
机构
[1] Natl Univ Sci & Technol Politehn Bucharest, Fac Automat Control & Comp, Bucharest 060042, Romania
[2] Univ Bucharest, Doctoral Sch Sociol, Bucharest 010181, Romania
[3] Acad Romanian Scientists, 3 Ilfov, Bucharest 050044, Romania
[4] Tech Univ Moldova, Fac Elect & Telecommun, Kishinev MD-2004, Moldova
[5] Tech Univ Moldova, Natl Inst Innovat Cybersecur CYBERCOR, Kishinev MD-2004, Moldova
[6] Andrei Saguna Univ Constanta, Fac Psychol Behav & Legal Sci, Constanta 900196, Romania
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 16期
关键词
research productivity; cybersecurity; privacy; blockchain; Augmented Human Development Index; Web of Science; regression analysis; SCIENTIFIC PRODUCTIVITY; ECONOMIC-GROWTH; BIBLIOMETRIC ANALYSIS; COUNTRIES;
D O I
10.3390/app14167086
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Featured Application This analysis can guide national science policy for enhancing research in blockchain, privacy, and cybersecurity. Policymakers can use the findings to allocate resources effectively. For blockchain and cybersecurity research, countries might focus on economic development and research funding. To boost privacy research, nations could strengthen democratic institutions alongside economic factors. International organizations could use this analysis to identify high-potential countries for targeted support.Abstract This study examines the factors influencing scientific productivity in blockchain, privacy, and cybersecurity research across countries. While previous research has explored the determinants of general scientific output, less is known about the patterns of influence in these technological fields, which have been dominantly studied with a bibliometric focus. Using regression models, we analyze the impact of economic, political, educational, and social factors on the publication rates in these domains. Data from international databases on country-level indicators and scientific publications form the basis of our analysis. The results show that Gross National Income per capita is the strongest predictor of research output across all the fields studied. Research spending as a percentage of GDP also demonstrates a consistent positive relationship with publication rates. However, the impact of the factors varies across fields. This research provides insights for policymakers and institutions aiming to enhance research capabilities in these critical areas of technology.
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页数:21
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