地理科学 ›› 2020, Vol. 40 ›› Issue (3): 335-343.doi: 10.13249/j.cnki.sgs.2020.03.001

• •    下一篇

中国工业生态效率时空分异特征及其影响因素解析

张新林1, 仇方道1(), 谭俊涛1, 王长建2   

  1. 1. 江苏师范大学地理测绘与城乡规划学院, 江苏 徐州 221116
    2. 广州地理研究所广东省地理空间信息技术与应用公共实验室, 广东 广州 510070
  • 收稿日期:2019-03-13 修回日期:2019-08-23 出版日期:2020-03-10 发布日期:2020-05-13
  • 通讯作者: 仇方道 E-mail:qiufangdao@163.com
  • 作者简介:张新林(1989-),男,山东泰安人,博士,讲师,主要从事经济地理与区域可持续发展研究。E-mail: smilezhang89@163.com
  • 基金资助:
    国家自然科学基金项目(41671123);国家自然科学基金项目(41501144);江苏高校优势学科建设工程项目、江苏师范大学自然科学基金项目资助(18XWRX004)

Spatial Pattern Change and Influencing Factors of China’s Industrial Eco-efficiency

Zhang Xinlin1, Qiu Fangdao1(), Tan Juntao1, Wang Changjian2   

  1. 1. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, Jiangsu, China
    2. Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, Guangdong, China
  • Received:2019-03-13 Revised:2019-08-23 Online:2020-03-10 Published:2020-05-13
  • Contact: Qiu Fangdao E-mail:qiufangdao@163.com
  • Supported by:
    National Natural Science Foundation of China(41671123);National Natural Science Foundation of China(41501144);A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, National Natural Science Foundation of Jiangsu Normal University(18XWRX004)

摘要:

基于2000-2016年中国工业数据,构建工业生态效率投入产出指标体系,测度不同区域的工业生态效率,构建不同空间权重矩阵,对空间分异特征进行解析,最后研究了工业生态效率影响因素的空间效应。结果如下: 中国工业生态效率均值呈现出波动趋势,在2016年达到最大值; 区域之间差距明显,绝对差异和相对差异也在2016年最大,空间分布上逐渐集中,逐渐形成了从东南向西北递减的阶梯状空间分布特征; 工业生态效率存在着明显的空间集聚性,并有高高集聚和低低集聚的空间俱乐部现象; 财政分权的直接效应值最高,对外开放和固定资产是抑制本地区工业生态效率提升的主要因素,科技创新、财政分权能够促进邻近区域工业生态效率的提升,产业集聚、对外开放不利于邻近地区工业生态效率的改善。

关键词: 工业生态效率, 窗口分析法, 空间效应, 中国

Abstract:

Industrial added value of China has been the largest in the world, and industrial sectors consumed a lot of energy and resources, which led to the destruction of the ecological environment. Thus, improving the industrial eco-efficiency is the important measure to realize the sustainable development. Eco-efficiency was first applied to measuring the environment performance of economic activities. The core connotation of eco-efficiency is to maximize economic benefits while minimizing environmental pollution and resources consumption, and the ultimate goal is to achieve sustainable development. Ecological efficiency has become an important tool for analyzing the impact of economic activities on the environment. This article takes different province as the research object and measures the industrial eco-efficiency with the aid of data envelopment analysis. Different spatial weight matrixes were constructed, and then the spatial evolution was analyzed by spatial autocorrelation analysis. On the basis of the optimal spatial weight matrix, spatial Durbin model was used to analyze the direct effect, space spillover effect, total effect of different influencing factors. Some conclusions were drawn as follows. The average value of the industrial eco-efficiency showed an obvious fluctuation trend during 2000-2015, and the absolute difference showed the similar trend, and the relative difference presented an “N” type change trend. The spatial distribution of the industrial eco-efficiency was characterized by “high in the southeast and low in the northwest”. The mean industrial eco-efficiency of Beijing and Shanghai was the highest, while the mean industrial eco-efficiency of Ningxia was the lowest. The spatial correlation feature of the industrial ecological efficiency was more accurately reflected under the comprehensive weight matrix combining geography and economy. The phenomenon of high and low clustering space club was also obvious. The overall effect of economic development, scientific and technological innovation and fiscal decentralization was positive, and showed that these 3 factors were the important driving force for promoting the improvement of overall regional industrial eco-efficiency, while the opening up had a negative impact on the improvement of industrial eco-efficiency. The direct effect value of fiscal decentralization was the highest, and opening to the outside world and fixed assets were the main factors to restrain the improvement of regional industrial eco-efficiency. Scientific and technological innovation and fiscal decentralization had positive spillover effect. Industrial agglomeration and opening to the outside world have negative spillover effects. On the basis of our study, we can find that industrial ecological efficiency had a spatial spillover effect, which was not only affected by various influencing factors in its region, but also affected by other regional influencing factors. Therefore, when formulating relevant countermeasures and suggestions, not only the regional influencing factors should be reasonably planned, but also the influence of different influencing factors in other regions should be taken into account.

Key words: industrial eco-efficiency, DEA-Window, spatial effect, China

中图分类号: 

  • F427