Abstract
The increasing mobility of elite research talents has become a widely discussed topic in recent years. This study aims to explore the effect of mobility experiences on the research performance of Chinese scholars by collecting work experience data from 666 recipients of the National Natural Science Foundation for Distinguished Young Scholars (Jieqing) and their publicly available research output data. The study employed the entropy balancing matching method to minimize endogeneity bias in the sample. The study yielded several new findings. Firstly, the enterprise mobility experience has a positive effect on the quality of research output but does not affect the quantity of research output. Secondly, unlike in developed countries where "downward mobility" is found to have a suppressive effect on research performance, job mobility of elite research talents in China who move to non-first-class universities significantly contributes to research performance. This paper constructs the theoretical conditions for the innovative knowledge production of elite research talents and explains it. Using this theoretical condition, not only can we explain the mobility of Chinese scientific research talents, but we can also predict and explain the effect of the mobility of other research objects that have not been verified by data validation on scientific research performance in combination with their region environment.
Similar content being viewed by others
Change history
10 September 2023
A Correction to this paper has been published: https://doi.org/10.1007/s11192-023-04832-0
Notes
There are various methods to measure research quality, such as "the number of citations" and the "H-index," which are more scientific and accurate indicators. However, in most universities in China, the quality of faculty members' publications is generally assessed based on the journal ranking of their publications. From the perspective of overall performance evaluation for all university faculty members, it is more convenient to use journal ranking rather than "the number of citations" as it is an easier and more practical approach.
In this paper, high-impact journals are defined as those within the top 20% based on the journal impact factor, which follows the definition of the Chinese Academy of Sciences regarding Q1 and Q2 journals. The research conducted by the authors of this paper falls within the field of natural sciences. In China, the evaluation of the natural sciences field mostly adopts the classification standards of SCI journals set by the Chinese Academy of Sciences. The Chinese Academy of Sciences defines Q1 journals as those with a three-year average impact factor ranking within the top 5% and Q2 journals as those ranking between 6 and 20% in terms of impact factor. In line with the practices of most universities in China, this paper sets the requirement for the assessment of faculty members to publish papers in Q1 and Q2 journals. In this study, high-level journals were defined based on the requirement of being included in the top tier (Q1 and Q2) of journals indexed by the Chinese Academy of Sciences. These journals comprise some of the top and excellent Chinese science and engineering journals.
It is refers to China's official definition of "long-term exchange" for scholars, which indicates that a period of 6 months or longer is considered sufficient for acquiring specialized knowledge in a certain field according to the Chinese authorities.
This article did not study upward mobility in the group study because there is very little upward mobility data. Similarly, there is very little data on the horizontal mobility of researchers who have obtained the National Natural Science Foundation for Distinguished Young Scholars (Jieqing) among non-first-class universities.
References
Abramo, G., D’Angelo, C. A., & Di Costa, F. (2022). The effect of academic mobility on research performance: The case of Italy. Quantitative Science Studies, 3(2), 345–362.
Arrow, K. J. (1962). The economic implications of learning by doing. The Review of Economic Studies, 29(3), 155–173.
Cañibano, C., D’Este, P., Otamendi, F. J., & Woolley, R. (2020). Scientific careers and the mobility of European researchers: An analysis of international mobility by career stage. Higher Education, 80(6), 1175–1193.
Dang, Y. (2018). Current Situation, Problems and Countermeasures of Teacher Mobility in colleges and Universities under the background of “Double First-class” Construction. Heilongjiang Higher Education Research, 36(09), 1–4.
Eisenberg, T., & Wells, M. T. (2000). Inbreeding in law school hiring: Assessing the performance of faculty hired from within. The Journal of Legal Studies, 29(S1), 369–388.
Fernández-Zubieta, A., Geuna, A., & Lawson, C. (2016). Productivity pay-offs from academic mobility: Should I stay or should I go? Industrial and Corporate Change, 25(1), 91–114.
Franzoni, C., Scellato, G., & Stephan, P. (2014). The mover’s advantage: The superior performance of migrant scientists. Economics Letters, 122(1), 89–93.
Gomez, C. J., Herman, A. C., & Parigi, P. (2020). Moving more, but closer: Mapping the growing regionalization of global scientific mobility using ORCID. Journal of Informetrics, 14(3), 101044.
Hainmueller, J. (2012). Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies. Political Analysis, 20(1), 25–46.
Horta, H., Birolini, S., Cattaneo, M., Shen, W., & Paleari, S. (2021). Research network propagation: The impact of PhD students’ temporary international mobility. Quantitative Science Studies, 2(1), 129–154.
Horta, H., Jung, J., & Santos, J. M. (2020). Mobility and research performance of academics in city-based higher education systems. Higher Education Policy, 33, 437–458.
Horta, H., & Yudkevich, M. (2016). The role of academic inbreeding in developing higher education systems: Challenges and possible solutions. Technological Forecasting and Social Change, 113, 363–372.
Huang H. (2017). From brain drain to brain circulation: The transformation of high-level international brain flow. Higher Education Research, (01), 90–97+104.
Huang, H., & Lian, J. (2020). Does occupational mobility Improve scientistsresearch productivity? Journal of Educational Research, Tsinghua University, 41(05), 127–135.
Jing, S., Ma, Q., Wang, S., Xu, H., Xu, T., Guo, X., & Wu, Z. (2023). Research on developmental evaluation based on the" four abilities" model: Evidence from early career researchers in China. Quality & Quantity. https://doi.org/10.1007/s11135-023-01665-0
Jonkers, K., & Cruz-Castro, L. (2013). Research upon return: The effect of international mobility on scientific ties, production and impact. Research Policy, 42(8), 1366–1377.
Jonkers, K., & Tijssen, R. (2008). Chinese researchers returning home: Impacts of international mobility on research collaboration and scientific productivity. Scientometrics, 77, 309–333.
Kahn, S., & MacGarvie, M. (2016). Do return requirements increase international knowledge diffusion? Evidence from the Fulbright program. Research Policy, 45(6), 1304–1322.
Li, B., & Bai, Y. (2016). Market signaling of educational background: evidence from a field experiment. Economic Research, 2020(10), 176–192.
Li, W., & Liu, Y. (2020). Is the "title" of project applicants more conducive to the improvement of scientific research performance? A reverse order evaluation for the output of education projects of National Social Science Foundation. Science and Technology Progress and Countermeasures, (21), 18–26.
Liang, W., Gu, J., & Nyland, C. (2022). China’s new research evaluation policy: Evidence from economics faculty of elite Chinese universities. Research Policy, 51(1), 104407.
Liu, J. (2015). University faculty mobility and academic labor market (Vol. 4). The Commercial Press.
Liu, W., Guo, J., & Shi, D. (2020). International Mobility and Knowledge Diffusion: Empirical Study of the Thousand Youth Talents Plan. Document Information & Knowledge, 194(2), 32–41.
Lu, H., & Cao, H. (2019). College teacher mobility and its rationality discrimination under the background of “Double First-class” construction. Journal of Hebei Normal University (Education Science Edition), 6, 57–63.
Netz, N., Hampel, S., & Aman, V. (2020). What effects does international mobility have on scientists’ careers? A Systematic Review. Research Evaluation, 29(3), 327–351.
Tavares, O., Sin, C., & Lança, V. (2019). Inbreeding and research productivity among sociology PhD holders in Portugal. Minerva, 57(3), 373–390.
Wang, H., Zhi, Q., & Fei, J. (2016). The Influence of Youth Science Fund on the research Performance of young teachers in Chinese universities—Based on the empirical analysis of the National Natural Science Fund from 1995 to 2013. Educational Research, 37(07), 91–99.
Wang, Y., Luo, H., & Yang, G. (2022). Research on the inter-provincial flow network and its evolution process. Science Research Management, 03, 79–88.
Xue, Q. (2022). A review of elite talent mobility from the perspective of academic life cycle. Chongqing Higher Education Research, 04, 118–127.
Yue, M. L., Li, R. N., Ou, G. Y., Wu, X., & Ma, T. C. (2020). An exploration on the flow of leading research talents in China: From the perspective of distinguished young scholars. Scientometrics, 125, 1559–1574.
Zhou, Y., Guo, Y., & Liu, Y. (2018). High-level talent flow and its influence on regional unbalanced development in China. Applied Geography, 91, 89–98.
Author information
Authors and Affiliations
Corresponding authors
Additional information
The original online version of this article was revised: In the original publication, affiliations were incorrect.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Jing, S., Xie, P., Yin, Q. et al. The effect of academic mobility on research performance: the case of China. Scientometrics 128, 5829–5850 (2023). https://doi.org/10.1007/s11192-023-04814-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-023-04814-2