Acta Geographica Sinica ›› 2022, Vol. 77 ›› Issue (8): 2113-2130.doi: 10.11821/dlxb202208018
• Geopolitics andWorld Geography • Previous Articles
SUN Kang1,2(), SI Yuefang1,2(
)
Received:
2021-07-14
Revised:
2022-04-07
Online:
2022-08-25
Published:
2022-10-25
Contact:
SI Yuefang
E-mail:51193902009@stu.ecnu.edu.cn;yfsi@re.ecnu.edu.cn
Supported by:
SUN Kang, SI Yuefang. The geographical structure and influencing factors of talent mobility:The resume analysis of highly cited Chinese scientists[J].Acta Geographica Sinica, 2022, 77(8): 2113-2130.
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Tab. 1
Talent flow evaluation index
研究主题 | 对应理论 | 一级指标 | 二级指标 |
---|---|---|---|
人才分布 | 新经济迁移理论 | 教育水平 | 万人高校学生数、985/211高校数量、中学生师比、人均教育事业费 |
经济发展与家庭因素 | 平均工资、家庭支出占收入比、失业率和住房均价、人均GDP、二产与三产产值比重 | ||
社会网络理论 | 人才政策 | 人均政府财政收入、引进海外高端人才资金、人均财政支出收入比 | |
世界体系理论 | 城市因素 | 城市等级、是否为省会/直辖市、市辖区人口密度 | |
消费城市理论 | 公共服务 | 每万人医院卫生院床位数、万人医生数、万人网民数、城市公路交通通达性、平均铁路客运量 | |
环境质量 | 二氧化硫排放量、绿地率、污水处理达标率、自然舒适度指数 | ||
科研环境 | R&D经费占GDP比重、人均科研事业费、政府研发资金 | ||
流动网络 | 推拉理论/人口迁移理论 | 教育水平 | 世界大学学术排名前500强的大学数量、目的国高等教育生师比、目的国高等教育入学率、目的国政府对高等教育的支出占GDP的比率、平均受教育年限、高校在校生数量 |
经济发展 | 目的地国人均GDP、两国人均GDP的差异、平均GDP增长率、平均收入、失业率、工资房价比 | ||
人口迁移理论 | 迁移距离 | 迁出地和迁入地省会城市之间空间距离、目的地国与来源国的地理距离、两城市之间的地理距离 | |
社会网络理论 | 人才政策 | 人才落户、人才安居、人才就业指数 | |
世界体系理论 | 全球化水平 | 国家或地区的商品进出口总额与GDP的比值、各省外商直接投资占GDP比重 | |
消费城市理论 | 公共服务 | 常住人口数量、电影院数量、人均公共汽车运营数量 | |
环境质量 | 平均温差 | ||
科技创新 | 人均专利授权量 |
Tab. 2
Descriptions and expected effects of factors
变量 | 指标 | 变量描述 | 预期效应 | 均值 | 标准差 |
---|---|---|---|---|---|
因变量 | 核心城市(lntcdegree) | 人才流动迁入城市的城市度中心性的自然对数 | 3.54 | 1.43 | |
自变量 | 个体特征 | ||||
被引用量(lncitations) | 科学家总被引用量的自然对数 | 未知 | 3.90 | 2.79 | |
论文数量(lnpapers) | 科学家发表论文的数量的自然对数 | 未知 | 1.78 | 1.07 | |
制度邻近(samecountry) | 虚拟变量,科学家的迁出城市与迁入城市处于同一个国家为1,反之为0 | + | 0.63 | 0.48 | |
阻碍因素 | |||||
地理距离(lndistance) | 科学家移动迁出城市与迁入城市距离的自然对数 | - | 14.81 | 1.30 | |
迁出城市因素: | |||||
迁出城市度中心性(lnocdegree) | 人才流动迁出城市的城市度中心性的自然对数 | - | 3.39 | 1.32 | |
迁出城市科技活跃度(lnocsize) | 人才流动迁出城市的城市论文数量的自然对数 | - | 8.03 | 2.06 | |
迁出城市为中国城市(oc_c) | 虚拟变量,迁出城市为中国城市为1,反之为0 | - | 0.30 | 0.46 | |
迁出城市大学数量(ocuniversitynum) | 人才流动迁出城市所包含进入世界大学学术排名前500强的大学数量 | - | 1.70 | 1.82 | |
迁出城市研究集群(ocresearchcluster) | 表示相同的研究集群,人才流动迁出城市是否包含科学家所在学科排名前100的高校,有则为1,反之为0 | - | 0.70 | 0.46 | |
迁入城市因素 | |||||
迁入城市科技活跃度(lntcsize) | 人才流动迁入城市的城市论文数量的自然对数 | + | 8.26 | 2.25 | |
迁入城市为中国城市(tc_c) | 虚拟变量,迁入城市为中国城市为1,反之为0 | + | 0.36 | 0.48 | |
迁入城市大学数量(tcuniversitynum) | 人才流动迁入城市所包含进入世界大学学术排名前500强的大学数量 | + | 2.14 | 2.24 | |
迁入城市研究集群(tcresearchcluster) | 表示相同的研究集群,人才流动迁入城市是否包含科学家所在学科排名前100的高校,有则为1,反之为0 | + | 0.72 | 0.45 |
Tab. 3
Descriptive statistics on the city distribution of the scientists in the bachelor to working phase (top 10)
城市/国家 | 学士 | 硕士 | 博士 | 工作1 | 工作2 | 工作3 |
---|---|---|---|---|---|---|
北京 | 41 | 46 | 31 | 17 | 26 | 7 |
南京 | 28 | 25 | 10 | 4 | 4 | - |
合肥 | 21 | 14 | 4 | 4 | 6 | 2 |
上海 | 19 | 21 | 11 | 6 | 7 | 1 |
杭州 | 14 | 13 | 3 | 4 | 2 | 1 |
西安 | 14 | 11 | 5 | 3 | 3 | 1 |
长春 | 11 | 14 | 14 | 2 | 3 | 1 |
剑桥[美] | 4 | 8 | 16 | 8 | 8 | 1 |
新加坡 | 3 | 3 | 5 | 13 | 12 | 3 |
香港 | 2 | 2 | 7 | 17 | 9 | 5 |
Tab. 4
Mobility characteristics of highly cited Chinese scientists in their education stages (Top 20)
流动方向 | 学士—硕士 迁移人数(人) | 硕士—博士 迁移人数(人) | 总人数 (人) |
---|---|---|---|
北京—北京 | 29 | 15 | 44 |
南京—南京 | 20 | 4 | 24 |
长春—长春 | 10 | 12 | 22 |
合肥—合肥 | 12 | 3 | 15 |
上海—上海 | 9 | 6 | 15 |
杭州—杭州 | 10 | 3 | 13 |
西安—西安 | 9 | 4 | 13 |
哈尔滨—哈尔滨 | 7 | 4 | 11 |
剑桥[美]—剑桥[美] | 4 | 4 | 8 |
新竹—新竹 | 5 | 1 | 6 |
大连—大连 | 4 | 2 | 6 |
广州—广州 | 4 | 2 | 6 |
武汉—武汉 | 3 | 3 | 6 |
新加坡—新加坡 | 3 | 2 | 5 |
南京—北京 | 3 | 2 | 5 |
台北—台北 | 3 | 1 | 4 |
兰州—兰州 | 3 | 1 | 4 |
天津—天津 | 3 | 1 | 4 |
南京—上海 | 2 | 2 | 4 |
北京—纽约 | 2 | 2 | 4 |
合肥—剑桥[美] | 0 | 4 | 4 |
Tab. 5
Node characteristics of the mobility network of highly cited Chinese scientists in their working stage (Top 10)
城市/国家 | 入度 | 出度 | 入度出度差值 | 度中心性 | 接近中心度 | 中间中心度 |
---|---|---|---|---|---|---|
北京 | 26 | 10 | 16 | 36 | 0.363 | 0.11 |
香港 | 14 | 6 | 8 | 20 | 0.232 | 0.041 |
新加坡 | 11 | 4 | 7 | 15 | 1.000 | 0.007 |
圣路易斯 | 7 | 1 | 6 | 8 | 0.400 | 0.014 |
剑桥[美] | 6 | 12 | -6 | 18 | 0.367 | 0.028 |
帕罗奥多 | 6 | 11 | -5 | 17 | 0.388 | 0.076 |
伯克利 | 6 | 8 | -2 | 14 | 0.321 | 0.025 |
上海 | 5 | 6 | -1 | 11 | 0.276 | 0.01 |
洛杉矶 | 5 | 5 | 0 | 10 | 0.311 | 0.019 |
西雅图 | 4 | 9 | -5 | 13 | 0.274 | 0.016 |
Tab. 6
Mobility characteristics of highly cited Chinese scientists in the working stage (Top 20)
国内/跨国流动 | 上一次工作 所在国家 | 当前工作 所在国家 | 人数(人) | 国内/跨国流动 | 上一次工作 所在国家 | 当前工作 所在国家 | 人数(人) |
---|---|---|---|---|---|---|---|
国内流动 | 美国 | 美国 | 111 | 跨国流动 | 美国 | 新加坡 | 5 |
中国 | 中国 | 67 | 日本 | 中国 | 5 | ||
加拿大 | 加拿大 | 5 | 加拿大 | 中国 | 4 | ||
英国 | 英国 | 5 | 美国 | 加拿大 | 4 | ||
澳大利亚 | 澳大利亚 | 4 | 中国 | 日本 | 4 | ||
新加坡 | 新加坡 | 2 | 澳大利亚 | 中国 | 3 | ||
德国 | 德国 | 1 | 英国 | 中国 | 3 | ||
跨国流动 | 美国 | 中国 | 26 | 中国 | 沙特阿拉伯 | 3 | |
中国 | 美国 | 11 | 加拿大 | 美国 | 2 | ||
德国 | 中国 | 5 | 加拿大 | 新加坡 | 2 | ||
加拿大 | 新加坡 | 2 |
Tab. 7
Regression results of Heckman's two-stage selection model
指标 | OLS | Heckman |
---|---|---|
lntcdegree | lntcdegree | |
lncitations | 0.0546* (0.0277) | 0.0634** (0.0285) |
lnpapers | -0.0232 (0.0680) | -0.0315 (0.0619) |
samecountry | 0.195 (0.153) | 0.191 (0.144) |
lnocdegree×lncitations | -5.74e-05 (0.000122) | -6.26e-05 (0.000111) |
lndistance | 0.100** (0.0495) | 0.0992* (0.0537) |
lnocdegree | 0.131 (0.0831) | 0.135* (0.0763) |
lnocsize | -0.0457* (0.0248) | -0.0454* (0.0266) |
oc_c | -0.131 (0.154) | -0.163 (0.165) |
ocuniversitynum | 0.00699 (0.0359) | 0.00632 (0.0389) |
ocresearchcluster | -0.315** (0.155) | -0.313** (0.156) |
lntcsize | 0.0769*** (0.0217) | 0.0783*** (0.0232) |
tc_c | 1.342*** (0.168) | 1.342*** (0.133) |
tcuniversitynum | 0.155*** (0.0485) | 0.155*** (0.0312) |
tcresearchcluster | 1.290*** (0.158) | 1.294*** (0.131) |
Constant | -0.421 (0.786) | -0.492 (0.884) |
move | ||
lncitations | 0.155*** (0.0493) | |
lnpapers | -0.120 (0.120) | |
lnocdegree×lncitations | -4.09e-05 (0.000194) | |
circulation | 0.911*** (0.281) | |
lnocdegree | -0.275* (0.159) | |
lnocsize | -0.0145 (0.0474) | |
oc_c | -0.270 (0.255) | |
ocuniversitynum | -0.0624 (0.0778) | |
ocresearchcluster | 0.183 (0.298) | |
IMR | 0.185 (0.319) | |
Constant | 1.039** (0.478) | |
Observations | 309 | |
R2 | 0.724 |
Tab. 8
Regression results of Probit regression model
指标 | 模型1 | 模型2 | 模型3 | ||
---|---|---|---|---|---|
国内—国内 | 国内—国外 | 国外—国内 | |||
lncitations | -0.0940 (0.0842) | -0.0567 (0.117) | 0.0285 (0.0682) | ||
lnpapers | 0.301* (0.159) | 0.287 (0.246) | 0.0505 (0.187) | ||
lnocdegree×lncitations | -0.000870* (0.000447) | 7.52e-05 (0.000994) | -0.000633 (0.000457) | ||
lndistance | -1.024*** (0.161) | 1.456*** (0.293) | 1.411*** (0.183) | ||
lnocdegree | 1.389*** (0.324) | 1.812*** (0.504) | -0.360* (0.189) | ||
lnocsize | -0.0349 (0.0755) | 0.0916 (0.118) | 0.133* (0.0782) | ||
ocuniversitynum | 0.101 (0.102) | 0.446*** (0.114) | -0.0733 (0.116) | ||
ocresearchcluster | -2.589*** (0.641) | -4.487*** (0.994) | 0.470 (0.382) | ||
lntcdegree | 1.032*** (0.285) | -1.149*** (0.286) | 1.246*** (0.245) | ||
lntcsize | -0.0643 (0.0662) | 0.688*** (0.260) | -0.119** (0.0562) | ||
tcuniversitynum | 0.223* (0.119) | -0.0167 (0.182) | 0.209*** (0.0613) | ||
tcresearchcluster | -2.645*** (0.642) | -0.283 (0.588) | -2.944*** (0.729) | ||
Constant | 8.363*** (2.045) | -32.08*** (6.461) | -25.39*** (3.116) | ||
Observations | 255 | 255 | 255 |
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