The Research on Innovation-Driven Paths of High-tech Zone Under the New Normal in China
Xiang Fei, Qinghao Bu
Available Online February 2017.
- https://doi.org/10.2991/mmetss-16.2017.36How to use a DOI?
- High-tech zone, Innovation-driven, Talent aggregation, Content analysis, Analytic hierarchy process.
- Talent aggregation of high level is good for high-tech zone of one country's economic pattern to achieve new dynamics of innovation-driven development, and then to push forward regional industrial restructure and economic transformation and upgrading. From that, how to recognize the driving force of talent aggregation and construct its assessment system scientifically plays an important role in high-tech zone for achieving innovation advantage successively. This kind of correlation effect is very prominent in high-tech zone development in China's costal area. Among that, talent aggregation, as the catalyst of economic-coordinated development, has drawn extensive attention from theoretical cycle and industrial field. Therefore, this study, according to the systematic constructing thought proposed by Complex Systematic, explores the index assessment frame of talent aggregation system of China's high-tech zone by content analysis; assesses the weight of different indexes by analytic hierarchy process; and finally, summarizes theoretical deduction and empirical analyzing results to put forward the paths and strategies for the innovation-driven development of high-tech zone based on talent aggregation system evaluation and optimization.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xiang Fei AU - Qinghao Bu PY - 2017/02 DA - 2017/02 TI - The Research on Innovation-Driven Paths of High-tech Zone Under the New Normal in China BT - Proceedings of the 2016 International Conference on Modern Management, Education Technology, and Social Science (MMETSS 2016) PB - Atlantis Press SN - 2352-5398 UR - https://doi.org/10.2991/mmetss-16.2017.36 DO - https://doi.org/10.2991/mmetss-16.2017.36 ID - Fei2017/02 ER -