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中国制造业产业结构高级度的时空格局与影响因素
引用本文:李建新,杨永春,蒋小荣,梁曼,郭泉恩.中国制造业产业结构高级度的时空格局与影响因素[J].地理研究,2018,37(8):1558-1574.
作者姓名:李建新  杨永春  蒋小荣  梁曼  郭泉恩
作者单位:1. 兰州大学资源环境学院,兰州 7300002. 兰州大学西部环境教育部重点实验室,兰州 7300003. 南昌大学旅游学院,南昌 330031
基金项目:国家自然科学基金项目(41571155);中央高校基本科研业务费专项(lzujbky-2016-269);兰州大学“一带一路”专项(2018ldbryb025)
摘    要:实现制造业产业结构的优化和空间结构的协调,是当下中国制造业结构调整亟需解决的两大核心问题。基于规模以上企业数据,运用产业结构高级度(UPG)指数、GIS方法考察1998-2013年中国制造业产业结构高级度从全国到地市的多尺度时空格局特征,并对比OLS和空间回归模型进一步探讨城市制造业产业结构高级度的影响因素。研究表明:① 国家尺度,随着制造业产值提升了10.67倍,制造业UPG指数实现了由5.987到6.225的提升,但金融危机后略有下滑。② 区域尺度,制造业UPG指数由东部地区→东北地区→西部地区→中部地区递次降低,东北地区在2003年后大幅下降,中、西部地区始终处于底端且在全国地位略有下降。③ 省域尺度,直辖市与东部沿海省份的制造业UPG指数相对较高且成长更快,而中西部尤其是多数边疆省份较低且成长缓慢,甚至下降。④ 市域尺度,制造业UPG指数热点区域由北方传统工业城市向东部沿海城市转移,逐步在全国形成一个以长三角地区为导向的核心—边缘模式。⑤ 劳动力工资的提升是城市制造业UPG指数提高的重要推手,创新能力和制造业集聚的促进作用在后期有所下降,居民消费和开发区的作用在后期逐渐显著,外资的集聚总体抑制了城市制造业UPG指数的提升,而沿海三大核心城市群的作用尚不显著。

关 键 词:制造业  UPG指数  时空格局  影响因素  中国  
收稿时间:2018-02-12
修稿时间:2018-05-30

The spatial-temporal patterns and influencing factors of the industrial structure upgrade of China's manufacturing
Jianxin LI,Yongchun YANG,Xiaorong JIANG,Man LIANG,Quanen GUO.The spatial-temporal patterns and influencing factors of the industrial structure upgrade of China's manufacturing[J].Geographical Research,2018,37(8):1558-1574.
Authors:Jianxin LI  Yongchun YANG  Xiaorong JIANG  Man LIANG  Quanen GUO
Institution:1. School of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China2. Key Laboratory of Western China's Environmental Systems, Ministry of Education of the People's Republic of China, Lanzhou University, Lanzhou 730000, China3. School of Tourism, Nanchang University, Nanchang 330031, China
Abstract:The optimization of the industrial structure and its coordination with the spatial structures are the two present core issues that need to be solved urgently in the restructuring of China's manufacturing industry. Based on the above scale enterprise data, this paper employs the up-grade (UPG) index of industrial structure and GIS tools to investigate the spatial-temporal patterns of UPG index of China's manufacturing from 1998 to 2013 at a multi-scale. Then it further explores the influencing factors of UPG index at the prefecture level by comparing the OLS regression and spatial regression model. The research shows that: on the national scale, with the manufacturing output increasing by 10.67 times, the UPG index increased from 5.987 to 6.225, but declined slightly after the 2008 financial crisis. On the regional scale, the UPG index has decreased successively in accordance with the eastern, the northeastern, the western, the central parts of the country. The UPG index of northeastern region has decreased sharply since 2003, while this index in central and western regions has kept the bottom position during the study period and experienced a slight decline. On the provincial scale, the UPG index in the municipalities and eastern coastal provinces are relatively high and growing faster while that in the central and western regions, especially in most frontier provinces, are relatively low and growing slowly, or even declining. On the prefecture scale, the hot-spot of UPG index is in the transition from the traditional industrial city to the eastern coastal city, which has gradually formed a core-periphery mode orientated by the center of the Yangtze River Delta. The increase of labor wage is the main driving force of the promotion of the UPG index at the prefecture level while the effects of innovation and manufacturing scale decrease gradually. The consumption level and development zones play a significant role in improving the UPG index in the later stage. The agglomeration of FDI has generally restrained the improvement of the UPG index, and the role of the three urban agglomerations in coastal regions is not significant in increasing the UPG index.
Keywords:manufacturing  UPG index  spatial-temporal pattern  influencing factor  China  
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