Assessment of ecological well-being performance and its spatial correlation analysis in the Beijing-Tianjin-Hebei urban agglomeration

Abstract

Due to the lack of coordination between economic development on the one hand and environment and human well-being on the other, the problem of improving human well-being within the ecological threshold has led to ecological well-being performance (EWP) gaining importance as a subject of research. In this paper, an innovative approach to making a comprehensive evaluation of EWP has been presented to reveal, from a network perspective, the complex interactions of EWP in the coordinated development of the Beijing-Tianjin-Hebei urban agglomeration (BTH). Based on an improved human development index and ecological consumption, this paper constructs an evaluation index system of EWP and decomposes the EWP into two stages of ecological-economic transformation and economic well-being transformation, which lays open the “black box” of the ecological well-being transformation process. The two-stage DEA model and Malmquist index are used to dynamically measure the EWP in BTH from 2006 to 2019. Then, applying the social network analysis method, the spatial correlation network structure of EWP has been explored from aspects of the overall characteristics of the network, and the status and role of cities in the network. ArcGIS software is utilized to analyze the spatial visualization and evolution characteristics. It revealed a positive trend of improvement in EWP. The reason for this was the efficiency improvement at the stage of ecological-economic transformation. While the spatial correlation of the two stages showed a complex and multi-threaded network structure, the network structure of economic well-being transformation stage was relatively loose. During the study period, the network density fluctuated and increased. There was no rigid hierarchical structure, and the network robustness improved continuously. As cities with a high level of EWP received related benefits from other cities and had a driving effect on other cities, the distribution structure of “core-periphery” was weakening. Furthermore, in the ecological-economic transformation stage, the spatial correlation of EWP broke through the traditional geographical spatial constraints to show a “multi-center” complex network pattern and tended towards balanced development. In the economic well-being transformation stage, a radial spatial structure emerged, imbalances among the cities were still obvious. This research is beneficial for developing recommendations for policymakers. These findings will facilitate the improvement of EWP toward sustainability and also the coordinated development of cities within the BTH, by providing insights into the heterogeneous characteristics of the two-stage EWP spatial correlation network.