CHINA POPULATION RESOURCES AND ENVIRONMENT Vol. 24 No Park RF. And Burgess EW. 2. K. Lewin
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1 CHINA POPULATION RESOURCES AND ENVIRONMENT Vol. 24 No C962 A doi /j. issn Park RF. And Burgess EW. 2 K. Lewin
2 Ravestein 6 - Larry Sjaastad 7 Michael Todaro 8 Dasgupta and Partha 9 134
3 1 Tab. 1 Evaluation system of science and technology talents social eco-environment and grey correlation degrees and ranks afeach inden Blue Economic Zone 4 Comprehensive Absolute Relative First Second index correlation degree of index correlative degree incidence degree GDP GDP m m % km
4 m X 0 = x 0 1 x 0 2 x 0 m m X i = 1 2 m i = 1 2 n i 1 + s 0 + s i ε 0i = 1 + s 0 + s i + s i - s 0 i = 1 2 n s 0 = n - 1 x 0 0 k x0 0 n s i = n - 1 x 0 i k x0 i n X' i = X i 1 = m 1 i = s 0 ' + s i ' ε 0i ' = 1 + s 0 ' + s i ' + s i ' - s 0 ' i = 1 2 n θ = 0. 5 ρ 0i = ε 0i θ ε 0i ' i = 1 2 n k = 2 k = 2 2 n
5 6 n p X 1 X 2 X p F 1 F 2 F m m < p F 1 = α 11 X 1 + α 12 X α 1p X p F 2 = α 21 X 1 + α 22 X α 2p X p F m = α m1 X 1 + α m2 X α mp Xp 1 α 2 k1 + α 2 k2 + + α 2 kp = 1 k = 1 2 m α 2 kj j = p k F k 2 F i F j i j j = 1 2 m 3 F 1 X 1 X 2 X p F 1 4 X 1 X 2 X p λ k F k 5 i α i = λ i / k k = 1 2 p SPSS 2 27 SPSS % F % F % F % % % F = % F % F % F % F % F 5 / % F F 4 F Tab. 2 and rank of science and technology talent eco-environment of each city in Blue Economic Zone in 2012 City F 1 F 2 F 3 F 4 F 5 F
6 SPSS F 1 X 7 X 12 X 14 X 15 X 17 X 21 X 22 F 1 F 2 X 2 X 4 X 6 X 8 X 16 X 18 X 19 X 20 X 23 X 28 F 2 References F 1. J. 3 GDP Xu QianZhang Tiqin. Talent X 1 X 3 X 5 X 24 X 25 X 29 2Park R FBurgess E W. An Introduction to the Science of Sociology M. Chicago University of Chicago Press F 4 J Meng Lingyao X 9 X 10 X 11 Zhang DaipingZhang Lizhen. Study on the Social Eco-environment X 13 in Shijiazhuang J. Geography and Territorial Research F 4 X J. X Wang Shun. Study on the Synthetic 3 F 1 Evaluation Indicator System of China's City HR Environment J. F 2 China Soft Sciences J F Zhu Daming. Strategy of Building Talent Eco-environment J. China Talent Ravenstein E G. The Laws of Migration J. Journal of The F 4 Statistical Society of London Larry A. Sjaastad. The Costs and Returns of Human Migration J. F 5 Journal of Political Economy Michael Todaro P. A Model of Labor Migration and Urban Unemployment in Less Developed Countries J. The American Economic Review DasguptaPartha. Human Well-Being and the Natural Environment M. London Oxford University Press J Zhang Zaisheng. Analysis on Flow Situation and Influence Factor of Talent J. Population Journal J Zhu Xingzhen. The Analysis on Herd Instinct in Talent Assemble Process J. The Journal of Quantitative and Technical Economics M Gui Agglomeration based on City Environment J. China Population Resources and Environment Zhaoming. The Economics of Talent Resource M. Beijing
7 Lantian Press on Innovative Path and Mechanism of High-tech Industry CLuster J Jiang LuquanWu RuimingLiu Hengjiang. Analysis and Design of the Evaluation Framework for Industrial Cluster Competitiveness J. Economic Geography J Zhu Xiumei. An Empirical Analysis J. China Industrial Econmics N Zhao Lin. Blue Zone Appeal Occupational Education Chang to Blue N. Dazhong Daily Study on Evaluation System of Science and Technology Talent Social Eco-environment LIU Rui-bo 1 BIAN Zhi-qiang 2 1. School of FinanceShandong University of Finance and EconomicsJinan Shandong China 2. School of EconomicsDongbei University of Finance and EconomicsDalian Liaoning China Abstract As strategic resources and the core factor of improving competitivenessscience and technology talent becomes the object that every regions fight for. Providing a well social eco-environment contributing to growth and development of talent is the key of attracting and retaining science and technology talent. This paper built an evaluation system of science and technology talent social ecoenvironment including science and technology development environmentscience and technology personal environmentopen system environmentsecurity and harmony environmentliving space environmentthrough analyzing the common environment and special environment that needed by science and technology talent. Shandong peninsula blue economic zone for examplewe investigated the correlation degree between science and technology talent and the indexes of evaluation system by using grey correlation degree. The results showed that every index had significant influence on science and technology talentand this proved the accuracy and rationality of the evaluation system. We can get the favorable science and technology development environment and science and technology personal environment are the most important factors to attract and retain science and technology talent. The governments need increase and encourage science and technology inputpromote cluster of high and new technology industryspeed up the economic development and raise talents' wageswhile strive to build favorable security and harmony environmentoptimize living space environment and increase open degree. We got the orders of scores of science and technology talent social eco-environment of cities in blue economic zone by carrying out factor analysis based on the evaluation system. The order of composite environment is QingdaoYantaiWeifang WeihaiRizhaobizhouDongying. For the single environmentthe open system environment of Qingdaothe security and harmony environment of Yantaithe science and technology development environment of Dongyingthe science and technology personal environment of Weifang and living space environment especially natural environment are the best. This was nearly in accordance with the actual condition of each cityand proved the rationality of the evaluation system further. Each city can clear and definite advantages and disadvantages of themselvesand make up for the disadvantages targetedwhile exploit advantages of themselves. Then they can propose some working thoughts of optimizing science and technology talent social eco-environment definitely and effectively. Key words science and technology talent social eco-environment evaluation system grey correlation degree factor analysis 139
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