TY  - JOUR
AB  - Purpose The power industry is the pillar industry of the Chinese economy, and also a major carbon emitter. The performances of both the production and operation of the power industry are crucial for a harmonious development of society. This study proposes an improved data envelopment analysis (DEA) model to analyze the sustainable performance of China's power supply chain (PSC).Design/methodology/approach To analyze the sustainable performance of PSC systems in China's provincial regions, this study proposes a two-stage directional distance function (DDF) model. The proposed model not only considers the leader–follower game relationship between the power-generation system and the retail system, but also considers the factors that measure the sustainability level of the PSC.Findings The proposed model is applied to assess the sustainable performance of the PSCs of China's provincial regions. The findings are valuable and mainly include the following aspects: First, compared with other models, this study regards the intermediate variable of the power system as a freely disposable variable; therefore, the efficiency of the proposed model is more realistic. Second, the average efficiency of China's power retailing system is generally lower than the average efficiency of its power-generation system. Third, significant regional differences affect the power-generation efficiency, while the regional differences in power retail efficiency are not significant. The power-generation performances of PSCs in East China and Northeast China are generally higher than in other regions.Originality/value This study introduces the convex technique into a DEA model and thus proposes an improved two-stage DDF DEA model. In response to the game-theoretic inherent in power systems, this study also introduces the leader–follower game into the two-stage model. In addition to the theoretic novelty, all PSCs can be classified with this model. Moreover, specific recommendations for each type of PSCs are proposed based on the efficiency results, thus providing vital guidance for the practice.
VL  - 34
IS  - 1
SN  - 1741-0398
DO  - 10.1108/JEIM-09-2019-0296
UR  - https://doi.org/10.1108/JEIM-09-2019-0296
AU  - Sun Jiasen
AU  - Xu Shuqi
AU  - Li Guo
PY  - 2020
Y1  - 2020/01/01
TI  - Analyzing sustainable power supply chain performance: Evidence from China’s provincial regions
T2  - Journal of Enterprise Information Management
PB  - Emerald Publishing Limited
SP  - 79
EP  - 100
Y2  - 2024/05/10
ER  -