A Comprehensive Performance Evaluation of Chinese Energy Supply Chain under “Double-Carbon” Goals Based on AHP and Three-Stage DEA
Abstract
:1. Introduction
2. Literature Review
3. Materials and Methods
3.1. Theoretical Model
3.1.1. Analytic Hierarchy Process (AHP)
Establishing a Hierarchical Structure Model
Constructing a Judgment Matrix
Hierarchical Single Sorting and Its Consistency Test
General Ranking and Its Consistency Test
3.1.2. Three-Stage DEA Analysis
The First Stage: Measuring the Initial Efficiency Value Using DEA-BCC Model and DEA-CCR Model
The Second Stage: SFA Regression Analysis Eliminates the Influence of Environmental Noise Interference
The Third Stage: Calculate the Adjusted DEA Model Efficiency Value
3.2. Comprehensive Performance Evaluation Model Based on AHP and Three-Stage DEA
- Using the AHP method, calculate the weight of each first-level index relative to the total target;
- Classify the secondary indicators and construct the evaluation set of decision-making units of each indicator;
- Considering the influence of two environmental variables, which are the GDP growth rate and the total population growth rate at the end of the year, this paper uses a three-stage DEA model to calculate the technical efficiency () under the fixed return on scale model (namely the model, hereinafter abbreviated CRS) and the technical efficiency () and scale efficiency () under the variable return on scale model (i.e., the model, hereinafter abbreviated VRS) of each first-level index, respectively, indicating that the jth energy supply chain has an impact on the ith first-level index.
- Using the weight obtained by the above calculation and the efficiency evaluation values, we calculate and compare the comprehensive efficiency values , and of the jth energy supply chain (, where means the Chinese energy supply chain in 2010 and so on). The calculation formulas are as follows:
4. Construction of Performance Evaluation Index System of Energy Supply Chain under “Double-Carbon” Goals
4.1. Constructing an Index System Based on Energy Supply Chain Architecture
4.1.1. Energy Supply
4.1.2. Energy Production and Treatment
4.1.3. Energy Transmission and Distribution
4.1.4. Energy Consumption
4.2. Performance Evaluation Index System of Energy Supply Chain under the Goal of “Double- Carbon”
5. Relative Performance Evaluation of Chinese Energy Supply Chain Based on Three-Stage DEA
5.1. Data Acquisition and Description
5.2. Determination of First-Level Index Weight
5.3. Relative Performance Evaluation of Chinese Energy Supply Chain
5.3.1. Establishment of Input–Output Index Evaluation Set
5.3.2. Relative Performance Evaluation of Chinese Energy Supply Chain
5.4. Comparative Analysis of Traditional Energy Supply Chain and New Energy Supply Chain
6. Discussion
6.1. Level of Energy Supply
6.2. Level of Energy Production and Treatment
6.3. Level of Energy Transmission and Distribution
6.4. Level of Energy Consumption
7. Conclusions
- (1)
- Based on the analysis of three-stage DEA and after excluding environmental variables, we found that the comprehensive efficiency of the Chinese energy supply chain showed a trend of increasing year on year on the whole, but there was a downward trend from 2010 to 2013; the comprehensive technical efficiency and comprehensive scale efficiency reached the lowest value in 2013 and began to rise after 2013. Compared with other years, 2019 can be considered the efficiency frontier in the development of the Chinese energy industry. Looking back on the development process of the Chinese energy industry management system, China established a sound and systematic energy management system combining professional supervision and comprehensive management in 2013. In 2013, the coal industry entered a period of structural optimization and various policies have been issued to support the use of clean energy and curb the consumption of coal, including an action plan for the prevention and control of air pollution, issued by the State Council in 2013, and the 2014–2015 action plan for energy conservation, emission reduction and low-carbon development (GBF [2014] No. 23). The support of a reasonable energy industry management system and energy conservation and emission reduction policies was conducive to the efficient operation of the Chinese energy supply chain, which also provided financial support and an efficiency guarantee to help it carry out a green and low-carbon transformation. From 2017 to 2018, the efficiency of the Chinese energy supply chain increased significantly and reached the efficiency frontier in 2019.
- (2)
- Through data analysis, we found that the comprehensive performance of the energy supply chain has improved since 2016. In order to achieve the “double-carbon” goals, although the Chinese energy transmission and distribution infrastructure needed to be continuously improved and gradually expanded to cover the whole country in 2016 and the energy-storage technology had only entered the initial stage of commercialization, China had begun to introduce new environmentally friendly energy transmission and distribution infrastructure. We should innovate and develop double-carbon energy-storage technologies, realize the full marketization of new energy storage, increase the investment in clean raw materials at the source of energy production, develop clean energy conversion efficiency and so on. We also need to reduce the consumption and import of primary energy, such as coal and oil, improve production efficiency so as to increase the output of finished energy products and lay a solid foundation for achieving “double-carbon” goals.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Scale | Meaning |
---|---|
1 | The factor has the same influence as the factor. |
3 | The factor has a slightly stronger influence than the factor. |
5 | The factor has a stronger influence than the factor. |
7 | The factor has a obviously stronger influence than the factor. |
9 | The influence of the factor is extremely stronger than the factor. |
2, 4, 6, 8 | The median value of the above adjacent judgment |
reciprocal | The judgment of comparing factor with is , and the judgment of comparing factor with . |
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
RI | 0 | 0 | 0.52 | 0.89 | 1.12 | 1.26 | 1.36 | 1.41 |
Year | Energy Supply | Energy Production and Treatment | Energy Transmission and Distribution | Energy Consumption | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
2010 | 312,125 | 10.40 | 88.10 | 72.50 | 2.46 | 2.87 | 438,732.00 | 99.82 | 0.0013 | 2696 | 86.55 | 11.75 |
2011 | 340,178 | 9.60 | 86.30 | 72.20 | 2.43 | 2.97 | 474,937.00 | 99.77 | 0.0007 | 2880 | 87.89 | 13.00 |
2012 | 351,041 | 11.20 | 85.60 | 72.70 | 2.43 | 3.20 | 505,640.00 | 99.56 | 0.0017 | 2977 | 87.29 | 14.50 |
2013 | 358,784 | 11.80 | 84.60 | 73.00 | 2.45 | 3.72 | 543,896.00 | 98.36 | 0.0019 | 3071 | 86.06 | 15.50 |
2014 | 362,212 | 13.30 | 84.00 | 73.10 | 2.44 | 4.03 | 577,605.00 | 97.32 | 0.0025 | 3140 | 84.48 | 17.00 |
2015 | 362,193 | 14.50 | 84.20 | 73.40 | 2.46 | 4.01 | 607,643.00 | 96.95 | 0.0035 | 3166 | 83.27 | 18.00 |
2016 | 345,954 | 16.80 | 79.40 | 73.50 | 2.57 | 4.41 | 645,609.00 | 96.50 | 0.0056 | 3202 | 78.38 | 19.50 |
2017 | 358,867 | 17.40 | 80.00 | 73.00 | 2.52 | 4.43 | 685,567.00 | 96.35 | 0.0082 | 3288 | 78.76 | 20.80 |
2018 | 378,859 | 18.00 | 79.00 | 72.80 | 2.47 | 5.43 | 724,788.00 | 96.85 | 0.0176 | 3388 | 79.89 | 22.10 |
2019 | 397,317 | 18.40 | 81.70 | 73.30 | 2.40 | 5.38 | 759,465.00 | 97.09 | 0.0207 | 3488 | 81.44 | 23.40 |
Primary Index | Input/Output Index | Secondary Index |
---|---|---|
Energy supply (0.2685) | Input index | Total primary energy production |
Output index | Low carbon raw material rate | |
Energy self-sufficiency rate | ||
Energy production and treatment (0.5531) | Input index | Carbon emission rate per unit output |
Output index | Energy processing conversion efficiency | |
Energy recovery rate | ||
Energy transmission and distribution (0.1201) | Input index | Dispatching broadness |
Output index | Delivery arrival rate | |
Energy storage rate | ||
Energy consumption (0.0583) | Input index | Per capita energy consumption |
Output index | Demand satisfaction rate | |
Proportion of clean energy consumption | ||
environmental index | GDP growth rate | |
Total population growth at the end of the year |
Year | Output Index | Input Index | Environmental Variables | ||
---|---|---|---|---|---|
Energy Processing Conversion Efficiency | Energy Recovery Rate | Carbon Emission Rate per Unit Output | GDP Growth Rate | Total Population Growth at the End of the Year | |
2010 | 72.50 | 2.87 | 2.46 | 0.1825 | 0.0048 |
2011 | 72.20 | 2.97 | 2.43 | 0.1840 | 0.0048 |
2012 | 72.70 | 3.20 | 2.43 | 0.1038 | 0.0050 |
2013 | 73.00 | 3.72 | 2.45 | 0.1010 | 0.0049 |
2014 | 73.10 | 4.03 | 2.44 | 0.0853 | 0.0052 |
2015 | 73.40 | 4.01 | 2.46 | 0.0704 | 0.0050 |
2016 | 73.50 | 4.41 | 2.57 | 0.0835 | 0.0059 |
2017 | 73.00 | 4.43 | 2.52 | 0.1147 | 0.0053 |
2018 | 72.80 | 5.43 | 2.47 | 0.1049 | 0.0038 |
2019 | 73.30 | 5.38 | 2.40 | 0.0731 | 0.0033 |
DMU | Cj | Vj | Sj |
---|---|---|---|
2010 | 0.981 | 0.993 | 0.987 |
2011 | 0.947 | 0.986 | 0.961 |
2012 | 0.944 | 0.990 | 0.954 |
2013 | 0.930 | 0.988 | 0.941 |
2014 | 0.935 | 0.989 | 0.945 |
2015 | 0.940 | 0.995 | 0.945 |
2016 | 0.936 | 0.997 | 0.938 |
2017 | 0.945 | 0.994 | 0.950 |
2018 | 0.980 | 0.999 | 0.981 |
2019 | 0.988 | 1.000 | 0.988 |
mean | 0.953 | 0.993 | 0.959 |
DMU | Number | Time | Investment in Fixed Assets | GDP Growth Rate | Total Population Growth at the End of the Year |
---|---|---|---|---|---|
2010 | 1 | 1 | −0.0038 | 18.2490 | 0.4803 |
2011 | 2 | 1 | −0.0040 | 18.3978 | 0.4803 |
2012 | 3 | 1 | −0.0028 | 10.3783 | 0.4965 |
2013 | 4 | 1 | 0.0001 | 10.0975 | 0.4933 |
2014 | 5 | 1 | −0.0029 | 8.5334 | 0.5218 |
2015 | 6 | 1 | −0.0049 | 7.0382 | 0.4971 |
2016 | 7 | 1 | −0.0020 | 8.3525 | 0.5885 |
2017 | 8 | 1 | −0.0009 | 11.4740 | 0.5330 |
2018 | 9 | 1 | 0.0005 | 10.4857 | 0.3813 |
2019 | 10 | 1 | −0.0030 | 7.3138 | 0.3347 |
Total Primary Energy Production | Carbon Emission Rate Per Unit Output | Scheduling Reasonable Rate | Per Capita Energy Consumption | |
---|---|---|---|---|
coefficient | 25,920.2670 | −0.0001 | 152,152.2900 | 11.3765 |
GDP growth rate | −607.7949 | −0.0001 | 7079.2817 | −0.2083 |
Total population growth at the end of the year | −30,857.7520 | −0.0022 | −621,362.4300 | −15.6923 |
sigma-squared | 365,948,740.0000 | 0.0000 | 344,854,240.0000 | 217.1391 |
gamma | 1.0000 | 0.0500 | 0.0495 | 1.0000 |
DMU | Cj | Vj | Sj |
---|---|---|---|
2010 | 0.981 | 0.993 | 0.987 |
2011 | 0.950 | 0.986 | 0.964 |
2012 | 0.949 | 0.990 | 0.958 |
2013 | 0.938 | 0.988 | 0.948 |
2014 | 0.939 | 0.989 | 0.949 |
2015 | 0.942 | 0.994 | 0.947 |
2016 | 0.953 | 0.998 | 0.956 |
2017 | 0.955 | 0.994 | 0.961 |
2018 | 0.989 | 1.000 | 0.989 |
2019 | 0.990 | 1.000 | 0.990 |
mean | 0.958 | 0.993 | 0.965 |
DMU | Energy Supply (0.2685) | Energy Production and Treatment (0.5513) | Energy Transmission and Distribution (0.1021) | Energy Consumption (0.0583) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
cij | vij | sij | cij | vij | sij | cij | vij | sij | cij | vij | sij | |
2010 | 1 | 1 | 1 | 0.965 | 0.988 | 0.977 | 1 | 1 | 1 | 1 | 1 | 1 |
2011 | 0.901 | 0.98 | 0.92 | 0.973 | 0.984 | 0.988 | 0.941 | 0.999 | 0.942 | 0.979 | 1 | 0.979 |
2012 | 0.904 | 0.981 | 0.921 | 0.98 | 0.991 | 0.988 | 0.892 | 0.997 | 0.894 | 0.982 | 1 | 0.982 |
2013 | 0.892 | 0.975 | 0.914 | 0.98 | 0.995 | 0.985 | 0.832 | 0.985 | 0.844 | 0.969 | 0.994 | 0.975 |
2014 | 0.914 | 0.982 | 0.931 | 0.981 | 0.996 | 0.985 | 0.784 | 0.975 | 0.804 | 0.974 | 0.988 | 0.985 |
2015 | 0.947 | 0.994 | 0.953 | 0.977 | 1 | 0.977 | 0.75 | 0.971 | 0.772 | 0.982 | 0.987 | 0.995 |
2016 | 1 | 1 | 1 | 0.94 | 1 | 0.94 | 0.9 | 0.98 | 0.918 | 0.975 | 1 | 0.975 |
2017 | 0.999 | 1 | 0.999 | 0.952 | 0.994 | 0.958 | 0.858 | 0.979 | 0.876 | 0.982 | 1 | 0.982 |
2018 | 0.993 | 1 | 0.993 | 0.985 | 1 | 0.985 | 1 | 1 | 1 | 0.99 | 1 | 0.99 |
2019 | 0.977 | 1 | 0.977 | 1 | 1 | 1 | 0.964 | 1 | 0.964 | 1 | 1 | 1 |
mean | 0.953 | 0.991 | 0.961 | 0.973 | 0.995 | 0.978 | 0.892 | 0.989 | 0.901 | 0.983 | 0.997 | 0.986 |
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Huang, X.; Lu, X.; Sun, Y.; Yao, J.; Zhu, W. A Comprehensive Performance Evaluation of Chinese Energy Supply Chain under “Double-Carbon” Goals Based on AHP and Three-Stage DEA. Sustainability 2022, 14, 10149. https://doi.org/10.3390/su141610149
Huang X, Lu X, Sun Y, Yao J, Zhu W. A Comprehensive Performance Evaluation of Chinese Energy Supply Chain under “Double-Carbon” Goals Based on AHP and Three-Stage DEA. Sustainability. 2022; 14(16):10149. https://doi.org/10.3390/su141610149
Chicago/Turabian StyleHuang, Xiaoqing, Xiaoyong Lu, Yuqi Sun, Jingui Yao, and Wenxing Zhu. 2022. "A Comprehensive Performance Evaluation of Chinese Energy Supply Chain under “Double-Carbon” Goals Based on AHP and Three-Stage DEA" Sustainability 14, no. 16: 10149. https://doi.org/10.3390/su141610149