Location Choice of Overseas High-Level Young Returned Talents in China

Jiang, Haining; Zhang, Wenzhong; Duan, Jian J.

doi:10.3390/su12219210

Cited by 12 publications

(18 citation statements)

References 44 publications

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“…It can be seen that talents, especially high-level talents, have become an important strategic resource for the country's innovative development and an indispensable force for realizing the goals of the national government. At the same time, talents are an important group that can achieve major breakthroughs through policy adjustment [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Huang

2022

Security and Communication Networks

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For the central cities, the transformation and upgrading of the industrial structure, the continuous deepening of innovation capabilities, and the improvement of sustainable development capabilities, human resources are playing an increasingly important role. In the modern era, assembling an army of highly educated, high-quality, and highly talented personnel has become a practical demand of talent development strategy. In order to respond to national policies, keep up with the trend of the times, and give play to the comparative advantages of talent competition, the primary task of central cities is to do a good job in the introduction of overseas high-level talents. It is necessary for the central cities to establish a mechanism for the introduction of overseas high-level talents with the government as an important task and to formulate targeted talent introduction policies according to the local characteristics of the central cities. It is very important to evaluate the impact of the introduction of overseas high-level talents on the development of central cities so that the central cities can formulate talent introduction strategies according to the actual situation. This work uses an artificial neural network to evaluate the impact of the introduction of overseas high-level talents on the development of central cities. Aiming at the problem that the evaluation accuracy and computing efficiency of the deep learning-based method decrease due to the proliferation of neural network layers, and the improved residual network model is proposed. On the one hand, a multiscale feature fusion block is designed in the first layer of the network model, which can extract the multiscale feature information in the original special. On the other hand, the residual block is optimized and improved by using depthwise separable convolution to remove the computational burden on the network.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Huang

2022

Security and Communication Networks

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“…There are many works in the scientific literature devoted to the so-called "geography of talent" (Andersson, 1985;Florida, 2002a;Kerimoglu & Karahasan, 2012;Burzynski et al, 2018;Jiang et al, 2020;Gu et al, 2021). J. Rauch defined talent as a local public good (Rauch, 1993;Tian & Liu, 2018).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

The role of talent in the economic development of countries in the modern world

Leikuma-Rimicāne¹,

Komarova²,

Lonska³

et al. 2021

JESI

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The purpose of this article is to empirically test the role of talent in the economic development of countries in the modern world. As the main research method, the authors use regression analysis, which involved variables characterizing the talent competitiveness of countries, as well as indicators of countries' economic development. The authors use two indicators to empirically measure the economic development of countries in the modern world. The first is a static indicator, GDP per capita, which measures the economic performance of the world's countries. Second, the dynamic indicator of the average change in GDP per capita over the previous 10 years measures the economic growth of the world's countries. Correlation analysis is used as an additional research method. The results showed that talent is a stable and practically the main determinant of such an important element of the economic development of countries as their achieved state of economic development. At the same time, the talent competitiveness of countries is not the engine of their short-term economic growth. For economic growth, it is enough to attract talent from outside, but for the economic development of the modern world's countries to be sustainable, it is also necessary to be able to grow talents and create conditions for their efficient work within the country. All of these elements are included in the Global Talent Competitiveness Index. Based on empirical results, the authors propose to replace the Global Competitiveness Index (GCI) with the Global Talent Competitiveness Index (GTCI) in research practice. Then the talent will also be included in the conceptual understanding of countries' competitiveness in the modern world.

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“…There has been growing scholarly interest in recent decades on the migration of the highly skilled to China (Dai & Liu, 2009; Hao et al, 2016; Jiang et al, 2020; Li et al, 2018; Lynn‐Ee Ho, 2011; Ma et al, 2018; Sun et al, 2017; Wang et al, 2015; Welch & Hao, 2012). While one body of literature has focused on the drivers and socioeconomic consequences of international skilled migration to China (Chen & Li, 2019; Dai & Liu, 2009; Lynn‐Ee Ho, 2011; Sun et al, 2017), another has focused on the work–life experiences of skilled migrants from abroad in China (Hao et al, 2016; Li et al, 2018; Wang, 2019, 2021; Welch & Hao, 2012).…”

Section: Introductionmentioning

confidence: 99%

Locational preferences of high‐level overseas talent returning to China: Evidence from microdata analysis

Liu

Huang

Zhang

et al. 2023

Population Space and Place

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While Chinese national and local governments have made every effort to attract high-level overseas talent, limited scholarly attention has been paid to their decision of where to stay in China. Using resume data of 3372 individuals involved in the "Thousand Talent Program", this study makes the first attempt to identify both regional and personal factors that affect locational choices of overseas talent in China. Descriptive results show that returned talent are unevenly distributed and are mostly concentrated in a few coastal provinces. Results from conditional logit models show that both academic career prospects and (natural and man-made) amenities play an important role in shaping overseas talent's choices of where to work, but regional prosperity exerts no effect. Alumni social networks, scientific collaboration networks, and educational trajectories are found to greatly influence their locational choices. Results from mixed models suggest that the effect of these provincial factors may vary by age, time spent abroad, the type of talent, the location of undergraduate study, and the country of stay before return. This study enhances our knowledge of the international return migration of the highly skilled by focusing on state-led academic migration and by challenging the conventional wisdom that high-level global talent are rootless and cosmopolitan elites with similar locational preferences.

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Location Choice of Overseas High-Level Young Returned Talents in China

Cited by 12 publications

References 44 publications

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

The role of talent in the economic development of countries in the modern world

Locational preferences of high‐level overseas talent returning to China: Evidence from microdata analysis

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