Efficiency analysis of China’s energy utilization system based on the robust network DEA-Malmquist productivity index with common weights

Jingjing Qu (), Xiaohong Liu () and Baohui Wang ()
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Jingjing Qu: Shandong University
Xiaohong Liu: Shandong University
Baohui Wang: Shandong University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 1, No 34, 1069 pages

Abstract: Abstract Improving energy utilization is of great significance for energy saving and emissions reduction, so this paper explores the efficiency of China’s energy utilization. The energy utilization in this study is considered as a two-stage network system consisting of the energy processing and conversion stage and the economic growth stage instead of regarding it as a ‘black box’ without the internal transformation like in most existing studies. Uncertainty analysis of system efficiency is necessary due to the underlying data uncertainty in production variables which is evitable, whereas the energy or environmental efficiency in academia is normally evaluated on the premise of no data uncertainties. This paper uses robust optimization to handle the data uncertainty during efficiency analysis, involves the common set of weights method to assure the comparability of static and intertemporal efficiency, and then proposes the robust network data envelopment analysis-Malmquist productivity index with common weights. The proposed method is applied to the efficiency analysis of China’s energy utilization system during 2007–2018. Results show that the efficiency of the energy utilization system decreases except for 2012–2013, and the economic growth stage efficiency reduces by 12.32%, while the energy processing and conversion stage efficiency grows by 11.93%. Technical progress is the driver of efficiency improvement for both the energy utilization system and its two stages. Besides, the sensitivity analysis shows that the proposed method is resistant to a certain degree of data disturbance compared to the deterministic model not considering uncertainty.

Keywords: Energy utilization system; Network data envelopment analysis; Malmquist productivity index; Robust optimization; Common set of weights (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-023-03894-7

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