The circular economy transformation in industrial parks: Theoretical reframing of the resource and environment matrix

Abstract

Checking the circular economy (CE) efficiency of industrial parks and exploring the potential reasons involved have not been systematically investigated. Recent researches lacked a unified and up-to-date framework toward CE in industrial parks emerging in high-quality development stage. It is therefore critical to build a new dimension and quantify the CE efficiency of industrial parks under the new historical period, so that appropriate policies can be formulated. This paper measures the CE efficiency of circular transformation by developing an original DEARA (Data Envelopment-Regression Analysis) model, and highlighting its advantages over the traditional DEA (Data Envelopment Analysis) model. To do this, an evaluation model is constructed that combines eight key indicators for environment, resources, economics and driving factors. The first batch of circular transformation pilot parks in China were selected for empirical analysis. The results show that the CE efficiency of sample parks has high variability from 0.112 to 1.030 in 2011. The efficiency matrix reveals a positive correlation between resources and environmental performance, with the driving factors for circular transformation being mainly GDP and leading industries. Compared with national indicators, the circular transformation of park levels is more effective in improving CE efficiency than the national average level of circular development, among which the experiences of the Beijing and Tianjin development zones are worthy of being exported to other industrial parks. Ultimately, this paper intends to contribute to policy instruments for developing viable and efficient industrial parks.