Document,Informaiton & Knowledge ›› 2020, Vol. 0 ›› Issue (2): 16-23.doi: 10.13366/j.dik.2020.02.016
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Abstract: [Purpose/Significance]In recent years, the mobility of researchers around the world has become more and more frequent, which has great influence on both inflow and outflow countries. This study aims to explore the patterns of scientific researchers’ international mobility and the corresponding impact factors.[Design/Methodology]This paper obtained resumes of 357,000 researchers with Ph.D. degree from all over the world on the ORCID website which also mentioned their educational and working experiences. According to the criteria including where researchers were born, where they received Ph.D. degrees and where they gained the first job after graduation, the mobility of researchers were divided into five categories which are AAA, AAB, ABB, ABA, ABC (A, B, and C refer to different countries/territories respectively). We explored the impact factors of researchers’mobility patterns with statistical analysis and multinomial logistic regression.[Findings/Conclusion]Several findings have been gained. Firstly, researchers’transnational mobility accounts for a small percentage, which is approximately 40%. Secondly, those originally from developed countries who possess abundant academic achievements or have more papers published in high quality publications before employment are more inclined to find jobs across countries. Thirdly, those originally from developing countries who have average performance in the amount of publications but publish more papers in high-quality publications before employment are more inclined to get employment in the countries where they get their Ph.D. degrees.[Originality/Value]It’s innovative to track researchers’mobility with the use of ORCID database. Meanwhile, the study on researchers’mobility patterns all over the world and their impact factors may provide reference for talent development strategies in China.
Keywords: Scientific researchers, Mobility pattern, Impact factors, Multinomial logistic regression, Open Researcher and Contributor ID(ORCID)
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URL: http://dik.whu.edu.cn/jwk3/tsqbzs/EN/10.13366/j.dik.2020.02.016
http://dik.whu.edu.cn/jwk3/tsqbzs/EN/Y2020/V0/I2/16