Measuring efficiency and technology inequality of China's electricity generation and transmission system: A new approach of network Data Envelopment Analysis prospect cross-efficiency models

Ruchuan Zhang, Qian Wei, Aijun Li () and LiYing Ren

Energy, 2022, vol. 246, issue C

Abstract: In the power sector, electricity transmission is highly linked with electricity generation. However, quite limited number of studies have considered the combined performance of electricity generation and transmission system. To do so, this study adopts network DEA models. To the best of our knowledge, the existing network DEA cross-efficiency models may suffer from one important drawback, since these models generally assume that DMUs are completely rational and neglect the potential effects of DMUs' risk attitudes that may play an important role in the evaluation process. To relax thisassumption, this study proposes a new type of network DEA prospect cross-efficiency models. To our knowledge, such work cannot be found in the existing studies. Empirically, this study focuses on the case of China's electricity generation-transmission system from 2010 to 2019. The main conclusions are summarized as follows. First, China succeeded in achieving an overall improvement with an annual growth rate of 2.84% during the analysis period. Second, within-group 2 was the most important driving factor affecting technology diffusion, accounting for 63.32% of the overall Gini coefficient. Finally, significant method heterogeneity has been confirmed among alternative DEA models, implying that method selection is important for modelers to perform empirical analysis.

Keywords: Data envelopment analysis; Prospect theory; Efficiency Gini coefficient; Electricity generation and transmission system; Group heterogeneity (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:246:y:2022:i:c:s0360544222001773

DOI: 10.1016/j.energy.2022.123274

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