生态环境学报 ›› 2023, Vol. 32 ›› Issue (4): 814-824.DOI: 10.16258/j.cnki.1674-5906.2023.04.019

• 研究论文 • 上一篇    

京津冀城市群生态福利绩效时空格局及演进特征

夏美君1,2(), 李健2,*(), 闫永蚕2   

  1. 1.湖北汽车工业学院经济管理学院,湖北 十堰 442002
    2.天津理工大学管理学院,天津 300384
  • 收稿日期:2023-02-01 出版日期:2023-04-18 发布日期:2023-07-12
  • 通讯作者: *李健,男,教授,博士,博士研究生导师,主要从事循环经济与生态工业工程研究。E-mail: lijian631219@163.com
  • 作者简介:夏美君(1993年生),女(蒙古族),博士研究生,主要从事循环经济与生态工业工程研究。E-mail: xia1922649561@163.com
  • 基金资助:
    教育部人文社科规划基金项目(20YJA630085);天津市科技计划项目(21ZLZKZF00290)

Spatial-temporal Patterns and Evolution Characteristics of Ecological Well-being Performance in Beijing-Tianjin-Hebei Urban Agglomeration

XIA Meijun1,2(), LI Jian2,*(), YAN Yongcan2   

  1. 1. School of Economics and Management, Hubei University of Automotive Technology, Shiyan 442002, P. R. China
    2. School of Management, Tianjin University of Technology, Tianjin 300384, P. R. China
  • Received:2023-02-01 Online:2023-04-18 Published:2023-07-12

摘要:

提高生态福利绩效是协调经济增长、生态环境保护与民生福祉增进的重要途径。京津冀城市群作为中国极为重要的战略区域,深入探究其生态福利转化过程中生态经济转化阶段和经济福利转化阶段,有助于把握京津冀城市群生态福利绩效水平、薄弱环节和内部差距。运用两阶段DEA模型和Malmquist指数从动态视角考察京津冀城市群2006-2020年的生态福利绩效,并刻画生态福利转化过程各阶段效率的时空格局,借助Kernel密度估计、Moran指数、传统和空间Markov链揭示其动态演进特征。研究发现,(1)京津冀城市群生态福利绩效总体呈上升趋势,年均增长1.7%,两阶段的年均增长率分别为6.7%和?3.1%,经济福利转化阶段是制约生态福利绩效提升的关键环节。各城市在生态经济转化阶段呈现全片增长的发展格局,城市间差异在经济福利转化阶段相对较小,但增长表现相对较差,形成低效连片的发展格局,空间分布格局存在明显的阶段性差异。(2)城市间生态福利绩效的绝对差异出现不同程度的扩大趋势,两阶段分别于2020年和2019年达到研究期内城市间差异的最大值,生态经济转化阶段存在微弱的极化趋势,需要加强各城市在该阶段的均衡化发展。(3)各城市生态福利绩效在两阶段均具有较强的稳定性,也表现出空间正相关性特征,存在“俱乐部趋同”现象,很难实现短期内跃迁式发展。经济福利转化阶段虽然存在跨状态转移,但最大的转移概率仅为0.068,生态经济转化阶段向高水平转移的概率相对较高,且城市生态福利绩效在各阶段向上或向下转移受到邻域城市的差异化影响。

关键词: 生态福利绩效, 时空格局, 演进特征, 京津冀城市群, 生态经济转化阶段

Abstract:

Improving ecological well-being performance is an effective way to coordinate economic growth, ecological environmental protection and the enhancement of people's well-being. An in-depth exploration of the ecological-economic transformation stage and economic well-being transformation stage in the ecological well-being transformation process of the Beijing-Tianjin-Hebei urban agglomeration, an extremely important strategic region in China, can help identify ecological well-being performance level, its weakness and internal gaps in the urban agglomeration. In this paper, the two-stage DEA model and Malmquist index were applied to dynamically examine the ecological well-being performance of the Beijing-Tianjin-Hebei urban agglomeration from 2006 to 2020. Next, this paper portrayed the spatial-temporal patterns of efficiency at each stage of the ecological well-being transformation process. Finally, the dynamic evolution characteristics of ecological well-being performance and its sub-stages were revealed using Kernel density estimation, Moran index, and traditional and spatial Markov chains. The results showed that (1) ecological well-being performance of the Beijing-Tianjin-Hebei urban agglomeration showed an overall upward trend with an average annual growth of 1.7%. The average annual growth rates for the two sub-stages were 6.7% and ?3.1%, respectively. Thus, the economic well-being transformation stage is a crucial factor that restricts the improvement of ecological well-being performance. Meanwhile, there were obvious stage differences in the spatial distribution pattern. Particularly, cities showed a development pattern of all growth in the ecological-economic transformation stage, and the differences among cities were comparatively small in the economic well-being transformation stage, but the growth performance was relatively poor, forming an inefficient contiguous development pattern. (2) The absolute differences in ecological well-being performance among cities showed different degrees of expansion. The two sub-stages reached their maximum values of variance among cities in the study period in 2020 and 2019. There was a weak trend of polarization in the ecological-economic transformation stage, it is necessary to enhance the balanced development of the cities in this stage. (3) The ecological well-being performance of each city had strong stability in both stages, and also manifested positive spatial correlations, showing the phenomenon of “club convergence”, which made it difficult to achieve leapfrog development in a short term. Although there was a cross-state transfer in the economic well-being transformation stage, the maximum transfer probability was only 0.068. And the probability of shifting to a high-level ecological-economic transformation stage was relatively high. Furthermore, the upward or downward shift in ecological well-being performance of each city at each stage was differentially influenced by the ecological well-being performance of neighboring cities.

Key words: ecological well-being performance, spatial-temporal patterns, evolution characteristics, Beijing-Tianjin-Hebei urban agglomeration, ecological-economic transformation stage

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