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Analysis on the Demand of Top Talent Introduction in Big Data and Cloud Computing Field in China Based on 3-F Method
Zhao Linjia, Huang Yuanxi, Wang Yinqiu, Liu Jia
National Academy of Innovation Strategy, China Association for Science and Technology, Beijing, P.R.China
AbstractBig data and cloud computing, which can help China to implement innovation-driven development strategy and promote industrial transformation and upgrading, is a new and emerging industrial field in China. Educated, productive and healthy workforces are necessary factor to develop big data and cloud computing industry, especially top talents are essential. Therefore, a three-step method named 3-F has been introduced to help describing the distribution of top talents globally and making decision whether they are needed in China. The 3-F method relies on calculating the brain gain index to analysis the top talent introduction demand of a country. Firstly, Focus on the high-frequency keywords of a specific field by retrieving the highly cited papers. Secondly, using those keywords to Find out the top talents of this specific field in the Web of Science. Finally, Figure out the brain gain index to estimate whether a country need to introduce top talents of a specific field abroad. The result showed that the brain gain index value of China’s big data and cloud computing field was 2.61, which means China need to introduce top talents abroad. Besides P. R. China, those top talents mainly distributed in the United States, the United Kingdom, Germany, Netherlands and France.
INTRODUCTION
Big data and cloud computing is a new and emerging industrial field[1], and increasing widely used in China[2-4]. Talents experience is a source of technological mastery[5], essentially for developing and using big data technologies. Most European states consider the immigration of foreign workers as an important factor to decelerate the decline of national workforces[6]. Lots of universities and research institutes have set up undergraduate and/or postgraduate courses on data analytics for cultivating talents[7]. EMC corporation think that vision, talent, and technology are necessary elements to providing solutions to big data management and analysis, insuring the big data success[8].
Bibliometrics research has appeared as early as 1917[9], and has been proved an effective method for assessing or identifying talents. Based on analyses of publication volume, journals and their impact factors, most cited articles and authors, preferred methods, and represented countries, Gallardo-Gallardo et. al[10] assess whether talent management should be approached as an embryonic, growth, or mature phenomenon.
In this paper, we intend to analysis whether China need to introduce top talents in the field of big data and cloud computing by using bibliometrics. In section 2, the 3-F method
for top talent introduction demand analysis will be discussed. In section 3, we will analysis the demand of top talent introduction in big data and cloud computing field in China.
METHOD
In general, metering indicators contain the most productive authors, journals, institutions, and countries, and the collaboration networks between authors and institutions[11, 12]. Based on the commonly used bibliometrics method, 3-F method for top talent introduction demand analysis is proposed. 3-F method has three steps:
Firstly, searching the literature database and forming a high-impact literature collection in a specific field. Focusing on the high-frequency keywords in the high-impact literature collection by using the text analysis method as the research hotspots. Just to be clear, the high-impact literature refers to the journal literature whose number of cited papers ranked in the top 1% in the same discipline and in the same year.
Secondly, retrieving those keywords in the Web of Science to find out where those top talents of this specific field are. Find the top talents by collected the information about talents country distribution, the institutions distribution and so on through the high-impact literature collection. Among them, the top talent refers to the first author or the communication author of the high-impact literatures.
Finlly, Figure out the brain gain index to determine the top talents introduction demand of a certain country. The brain gain index is calculated as following formulas:
Iik = (Twk / Tik) / (Pw / Pi) (1)
Among them, Iik means the brain gain index value of country (i) in the field (k), Twk means the number of worlds top talents in the field (k), Tik means the number of countrys (i) top talents in the field (k), Pw means the world population, Pi means the countrys (i) population. If Iik was more than 1, that means the country (i) has less top talents in the field (k), therefore the talent introduction demand will be relatively strong. In contrast, if Iik was less than 1, that means the countrys (i) has greater top talents in the field (k) than the world average, and the talent introduction demand will not be so strong.
Additionally, the literature information mainly from the ISI Web of Science (SCI, CPCI-S), and the the data analysis and visualization tools are TDA and Tableau.
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Excellent Quality 95-100%
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Introduction
45-41 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Literature Support 91-84 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Methodology 58-53 points Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met. |
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Average Score 50-85% |
40-38 points More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided. |
83-76 points Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration. |
52-49 points Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met. |
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Poor Quality 0-45% |
37-1 points The background and/or significance are missing. No search history information is provided. |
75-1 points Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration. |
48-1 points There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met |
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Analysis on the Demand of Top Talent |
Analysis on the Demand of Top Talent