Abstract
Data envelopment analysis (DEA) is a linear programming and production theory-based nonparametric approach that is generally used for efficiency analysis. Older DEA models, such CCR and BCC, can only identify decision-making units (DMUs) efficient or inefficient. The super-efficiency DEA model enables efficient DMUs to be ranked. A change in efficient DMUs can be measured using Malmquist index model, and the Malmquist productivity change index can be decomposed multiplicatively into an efficiency-change component (Effch) and a technical change component (Techch). This paper analyzes the water use efficiency in Shandong Province between 2006 and 2015 using Malmquist productivity index (TFP). The results show that: (1) the mean of super-efficiency scores of 17 cities in Shandong Province for the period 2006–2015 is between 0.965 and 2.760; (2) the water use efficiency was positive in 2006–2007, 2007–2008, and 2013–2014; however, it was negative in the other periods between 2006 and 2015; and (3) technical change is the key influencing factor on water use efficiency of 17 cities in Shandong Province. So, we suggest that Shandong Province encourage technological innovation to promote water use efficiency.
Highlights
Water is a basic natural resource and a strategic economic resource
The CCR, BCC, and SEDEA models are applied to a comparative analysis of the water use efficiency of 17 cities in Shandong Province for the period 2006–2015, and the Data envelopment analysis (DEA)-based Malmquist index method is used for a dynamic analysis
The super-efficiency DEA method ranks the performance of efficient decision-making units (DMUs)
Summary
Water is a basic natural resource and a strategic economic resource. It is essential to biodiversity, an ecological balance, socioeconomic development, and environmental goods or amenities. DEA is generally used to measure the efficiency of a resource’s utilization by its total input and output and can measure the relative effectiveness and rank the efficiency of a resource’s utilization This includes land utilization efficiency (Chen et al 2016), the efficiency of electric power production, and distribution processes (Khalili-Damghani and Shahmir 2015), agricultural water resources efficiency (Mousavi-Avval et al 2011; Speelman et al 2008), industrial water resources efficiency, and urban water supply efficiency (Molinos-Senante et al 2016; Byrnes et al 2010; Aida et al 1998), and so on. The CCR, BCC, and SEDEA models are applied to a comparative analysis of the water use efficiency of 17 cities in Shandong Province for the period 2006–2015, and the DEA-based Malmquist index method is used for a dynamic analysis. The change roots of the water use efficiency during the 11th and 12th Five-year Plan periods are identified by means of decomposing the Malmquist index into a technical progress component and a technical efficiency component, and further decomposing the technical efficiency component into a pure technical efficiency component and a scale efficiency component
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