Within-group common benchmarking the environmental efficiency in China with data envelopment analysis

Abstract

Purpose

Economic growth of China in the past decades has caused rapid increase in energy consumption and environmental deterioration. Therefore, it is critical to make an environmental evaluation and to help decision makers to know each province’s distance to the optimal target and improve environmental performance.

Design/methodology/approach

In such background, the authors use a within-group common benchmarking model with data envelopment analysis for China’s environmental evaluation and target setting in this paper. This model considers a common treatment of decision-making units within groups but allows for the different circumstances across groups and gives a common reference set for benchmarking.

Findings

The results show that there are regional difference in economic development and environmental protection. The coastal area has the best average environmental efficiency, then followed by inland area and the lowest level is the western area. The target results show that in four inputs, namely, population, capital, energy consumption and water consumption, the water consumption is the significant variable which should be decreased largely. All provinces have room to improve their economic level under the condition of a better environment.

Originality/value

In this research, the authors consider the similarity in geography and economy for Chinese provinces and divide 30 provinces into eight economic zones; thus, provinces in the same zone are evaluated with the same weight. Environmental performance and efficiency for each province can be obtained. Efficient targets for those inefficient provinces are provided as a possible improvement direction as well.

Citation

Cheng, C. and Ang, S. (2018), "Within-group common benchmarking the environmental efficiency in China with data envelopment analysis", Journal of Modelling in Management, Vol. 13 No. 2, pp. 375-393. https://doi.org/10.1108/JM2-04-2017-0039