Operational efficiency analysis of China's electric power industry using a dynamic network slack-based measure model

Meng, Ming; Pang, Tingting

doi:10.1016/j.energy.2022.123898

Cited by 13 publications

(4 citation statements)

References 34 publications

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“…An endogenously weighted DNSBM model was proposed by Huang et al (2022) to address the DNSBM model's shortcoming of requiring manual weight determination beforehand. Meng and Pang (2022) expanded the DNSBM model by specifying total-factor performance indices for the input factors. They also computed the technological gap between the group frontier and global frontier based on the meta-frontier concept.…”

Section: An Analysis Of Regional Green Innovationmentioning

confidence: 99%

The efficiency evaluation and influencing factor analysis of regional green innovation: a refined dynamic network slacks-based measure approach

Fang

Gui

Zhao-zhou

et al. 2023

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PurposeThis study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.Design/methodology/approachA two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.FindingsOn average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.Originality/valueThis study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

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Section: An Analysis Of Regional Green Innovationmentioning

confidence: 99%

The efficiency evaluation and influencing factor analysis of regional green innovation: a refined dynamic network slacks-based measure approach

Fang

Gui

Zhao-zhou

et al. 2023

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“…The mathematical technique for assessing eco-efficiency is based on the limitation that no DMU has a higher efficiency level than one and that each DMU has the same weight. This indicates that if a DMUs ratio value is one, it is deemed efficient [39,41,[59][60][61]. The final step (step 6) highlighted that the function may be approximated as the ratio of total weighted output divided by total weighted input:…”

Section: The Estimation Of Data Envelopment Analsysismentioning

confidence: 99%

Measuring Eco-Efficiency of the Global Shipping Sector Based on an Energy and Environmental Approach: A Dynamic Slack-Based Measure Non-Oriented Model

Parris,

Spinthiropoulos,

Ragazou

et al. 2023

Energies

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The compatibility of shipping with environmental protection is a subject that the international community is becoming increasingly concerned about, considering the threat of climate change. The current study aims to assess the worldwide shipping sector’s eco-efficiency performance for the first time using the Dynamic Slack-Based assess non-oriented Data Envelopment Analysis methodology, while the visualization of the results has been made with the geographic information system of ArcGIS. The findings show that the most vibrant shipping sectors in the world, such as the Marshall Islands, present the lowest eco-efficiency levels due to the nations’ roles as tax havens for shipowners. Furthermore, traditional maritime economies such as the Chinese one show a great growth in the eco-efficiency score due to the strategies of the shipping companies that are headquartered in the region to invest and adopt Environmental, Social, and Governance principles, which help them to achieve high scores in eco-efficiency. Finally, nations with small fleets have the greatest eco-efficiency score, as local governments have engaged in sustainable activities and initiatives over the previous four to five years to enable their marine industry to thrive and dominate the market.

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“…Reference [36] used two-stage DEA model to construct an index system to measure the mining technology innovation efficiency, mining eco-efficiency, and mining comprehensive efficiency of 30 provinces in China. Reference [37] simulated the operation process of the electric power industry through the network structure, introduced the dynamic slacks-based measure method, and evaluated the operation efficiency of the whole industry and each stage in each period. Reference [38] proposed a two-stage efficiency evaluation model of Chinese regional industrial system based on SBM-DEA.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency Evaluation of Chinese Provincial Industrial System Based on Network DEA Method

Zhu

et al. 2022

Sustainability

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The operation process of the Chinese provincial industrial system consists of four stages, namely the production (P) stage, wastewater treatment (WWT) stage, solid waste treatment (SWT) stage, and sulfur dioxide treatment (SDT) stage. Based on this structure, a four-stage data envelopment analysis (DEA) model is developed to evaluate the eco-efficiency, production efficiency, wastewater treatment efficiency, solid waste treatment efficiency, and sulfur dioxide treatment efficiency of provincial industrial systems in China, considering the undesirable output and variable returns to scale (VRS). Based on the objective data from 2011 to 2015, the following conclusions are drawn: Firstly, the eco-efficiency of the Chinese provincial industrial system has not been significantly improved during the study period, and the average eco-efficiency score is low, only 0.3805. Secondly, the reasons for the low eco-efficiency of the industrial system are different in the Eastern, Central, Western, and Northeastern regions. Thirdly, compared with the P stage, industrial WWT stage, and SWT stage, the efficiency of SDT stage is still relatively weak.

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Operational efficiency analysis of China's electric power industry using a dynamic network slack-based measure model

Cited by 13 publications

References 34 publications

The efficiency evaluation and influencing factor analysis of regional green innovation: a refined dynamic network slacks-based measure approach

The efficiency evaluation and influencing factor analysis of regional green innovation: a refined dynamic network slacks-based measure approach

Measuring Eco-Efficiency of the Global Shipping Sector Based on an Energy and Environmental Approach: A Dynamic Slack-Based Measure Non-Oriented Model

Efficiency Evaluation of Chinese Provincial Industrial System Based on Network DEA Method

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