| R&D投入强度的演变规律及预测研究 |
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| 引用本文： | 许大英,田晓琴.R&D投入强度的演变规律及预测研究[J].科技管理研究,2021,41(3):46-52. |
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| 作者姓名： | 许大英 田晓琴 |
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| 作者单位： | 贵州省科学技术情报研究所,贵州贵阳 550004;贵州省科学技术情报研究所,贵州贵阳 550004 |
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| 基金项目： | 贵州省科技计划项目"贵州加快高科技企业引进研究";贵州省科技计划项目"贵州科技进步综合指数和区域创新能力指数'增长补短'及'增比进位'政策建议" |
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| 摘 要： | 通过分析我国各省(市)R&D投入强度不同水平不同阶段的变化特征,探索其演变规律,并在此基础上,采用趋势外推法预测2030年各省(区、市)R&D投入强度。研究结果表明,目前我国有2/3的省(区、市)R&D投入强度滞后于当前工业化程度;R&D投入强度低于1%和超过2.15%的地区符合"国际R&D强度增长一般规律",但在1%~2.15%之间的大部分地区未出现快速增长;若各省(市)继续加大研发投入,预计2030年有2/5的地区R&D投入强度将超过2.8%,为我国进入创新型国家前列和世界科技强国奠定坚实的基础。
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| 关 键 词： | 工业化进程 R&D投入强度 规律 趋势 预测 |
Research on Evolution and Prediction of R&D Input Intensity |
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| Xu Daying,Tian Xiaoqin.Research on Evolution and Prediction of R&D Input Intensity[J].Science and Technology Management Research,2021,41(3):46-52. |
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| Authors: | Xu Daying Tian Xiaoqin |
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| Institution: | (Department of Strategic Research,Guizhou Institute of Science and Technology Information,Guiyang 550004,China) |
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| Abstract: | This paper analyzes the change trend of R&D input intensity in each province(city) of China, summarizes the change characteristics of different levels and stages in each region, and explores its evolution law. On this basis, the trend extrapolation method is used to predict the R&D input intensity of each province(city) in 2030, which provides reference for the growth of R&D investment in China and the prediction of the construction level of innovative country. The results show that the R&D investment intensity in two-thirds of China’s regions lags behind the current level of industrialization;regions with R&D investment intensity lower than 1% and more than 2.15% conform to the "general law of international R&D intensity growth", but most regions between 1% and 2.15% do not have rapid growth;if provinces(cities) continue to increase R&D investment, it is expected that two fifths of regions will have R&D investment intensity higher than 2.8% in 2030, which will lay a solid foundation for China to enter the forefront of innovative countries and the world’s leading country in science and technology. |
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| Keywords: | industrialization process R&D input intensity law trend prediction |
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