Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methodology
2.2.1. Three-Stage Super-SBM DEA
- Stage 1: The Super-SBM DEA
- Stage 2: The Stochastic Frontier Analysis (SFA)
- Stage 3: the adjusted DEA
2.2.2. Extra-Trees Algorithm
2.3. Data Sources, Descriptions, and Preprocessing
2.3.1. Variables for Super-SBM DEA
2.3.2. Variables for Stage-2 SFA
2.3.3. Variables for Extra-Trees
3. Results
3.1. Stage 1—Application of the Super-SBM DEA
3.2. Stage 2—SFA Analysis Results
- (1)
- Per Capita Gross Regional Product (GRP)
- (2)
- Proportion of Primary Industry in GRP
- (3)
- Proportion of Inner Expenditures of S&T Activity in GRP
- (4)
- Total Value of Imports and Exports Commodities
3.3. Stage 3—Analysis of the GPE and Adjusted DEA
3.4. Spatial Characteristics of Grain Production Efficiency in the Hexi Corridor
3.5. The Importance Analysis of Affecting Grain Production Factors by Extra-Trees
4. Discussion
4.1. Analysis of the Variation of Grain Production Efficiency in the Research Period
4.2. Grain Production and Its Influencing Factors
4.3. Policy Recommendations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable | Category | Description | Unit |
---|---|---|---|
Agricultural Labor Force (ALF) | IV of DEA; IV of ETS (HD) | The number of people actually participating in agricultural labor | 104 people |
Total Agricultural Machinery Power (AMP) | IV of DEA; IV of ETS (HD) | The sum of the power of all agricultural machinery | kWh |
Chemical Fertilizer Consumption (CFC) | IV of DEA; IV of ETS (HD) | The amount of chemical fertilizer actually used in agricultural production, converted to pure amount | ton |
Grain Crops Planting Area (GPA) | IV of DEA; IV of ETS (HD) | The sown or transplanted area of grain crops harvested by agricultural producers on all land | hectare |
Agricultural Pesticide Consumption (APC) | IV of DEA; IV of ETS (HD) | The amount of pesticide actually used in agricultural production | ton |
Agricultural Plastic Film Consumption (PFC) | IV of DEA; IV of ETS (HD) | The amount of plastic film actually used in agricultural production | ton |
Irrigation Water Consumption (IWC) | IV of DEA; IV of ETS (HD) | The amount of water introduced from the water source for irrigation in the area | 108 m3 |
Grain Production | OV of DEA; OV of ETS | The total amount of grain produced by agricultural producers | ton |
Per Capita Gross Regional Product | EV1 of SFA | The per capita final results of production activities of all resident units in the region | CNY |
Proportion of Primary Industry in GRP | EV2 of SFA | Ratio of primary industry to GRP | % |
Proportion of Inner Expenditures of S&T Activity in GRP | EV3 of SFA | Ratio of inner expenditures of S&T activity to GRP | % |
Total Value of Imports and Exports Commodities | EV4 of SFA | The total amount of goods actually entering and leaving China | 104 CNY |
Grain Production Efficiency (GPE) | IV of ETS (HD) | The performance of a DMU in the output of grain production | Dimensionless |
Annual Precipitation (AP) | IV of ETS (ND) | The amount of total precipitation depth in one year | mm |
Annual Average Temperature (AAT) | IV of ETS (ND) | The mean of daily average temperature of each day in the whole year | ℃ |
Average Sunshine Duration (ASD) | IV of ETS (ND) | An indicator measuring the daily duration of sunshine | hour |
Area Covered by Natural Disaster (ACD) | IV of ETS (ND) | The sown area of crops reduced by more than 10% due to disasters | hectare |
CO2 Emissions (CO2) | IV of ETS (HD) | The emissions stemming from the burning of fossil fuels and the manufacture of cement | 106 tons |
ALF | AMP | CFC | GPA | APC | PFC | IWC | |
---|---|---|---|---|---|---|---|
Constant | 1.202 *** (3.233) | 54,709.136 *** (54,627.162) | 8940.960 *** (5684.217) | −2644.35 *** (−75.312) | 383.137 * (1.693) | 651.793 (1.581) | −0.748 * (−1.884) |
EV1 | 0.000 ** (−2.225) | 3.578 * (1.966) | −0.176 ** (−2.117) | 0.031 ** (2.313) | 0.006 (0.491) | 0.005 (0.270) | 0.000 (1.030) |
EV2 | −6.197 *** (−7.979) | −1,177,984.300 *** (−1,177,631.100) | −40,455.221 *** (−20,828.845) | 5672.075 *** (39.612) | −3172.5 *** (−4.674) | −4686.751 *** (−6.090) | 2.478 *** (3.092) |
EV3 | −131.930 *** (−131.823) | −13,917,628.00 *** (−13,917,609.000) | −553,435.43 *** (−545,029.550) | 4193.428 *** (2900.085) | −55,454.8 *** (−539.108) | −91,847.74 *** (−863.222) | −113.6 *** (−117.229) |
EV4 | 0.000 *** (10.645) | −0.136 (−0.934) | 0.000 (−0.018) | 0.001 (0.654) | −0.001 * (−1.864) | −0.001 (−0.940) | 0.000 *** (27.155) |
σ2 | 111.142 | 615,589,410,000.00 | 1,322,312,200.00 | 19,830,247.00 | 9,316,170.90 | 25,419,789.00 | 43.471 |
γ | 1.000 | 0.982 | 0.994 | 1.000 | 0.994 | 0.995 | 1.000 |
LR | 54.104 | 33.478 | 36.930 | 69.548 | 44.653 | 33.626 | 58.976 |
Rank | Factor | Category | Importance |
---|---|---|---|
1 | Grain Crops Planting Area (GPA) | Human-Driven | 37.4181% |
2 | Agricultural Labor Force (ALF) | Human-Driven | 27.6876% |
3 | Chemical Fertilizer Consumption (CFC) | Human-Driven | 11.6299% |
4 | Irrigation Water Consumption (IWC) | Human-Driven | 6.1719% |
5 | Annual Precipitation (AP) | Nature-Driven | 4.0611% |
6 | Agricultural Plastic Film Consumption (PFC) | Human-Driven | 3.9515% |
7 | Total Agricultural Machinery Power (AMP) | Human-Driven | 2.6389% |
8 | CO2 Emissions (CO2) | Human-Driven | 2.3953% |
9 | Average Sunshine Duration (ASD) | Nature-Driven | 1.7584% |
10 | Agricultural Pesticide Consumption (APC) | Human-Driven | 1.6925% |
11 | Annual Average Temperature (AAT) | Nature-Driven | 0.2871% |
12 | Area Covered by Natural Disaster (ACD) | Nature-Driven | 0.1657% |
13 | Grain Production Efficiency (GPE) | Human-Driven | 0.1421% |
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Yan, Z.; Zhou, W.; Wang, Y.; Chen, X. Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China. Sustainability 2022, 14, 8881. https://doi.org/10.3390/su14148881
Yan Z, Zhou W, Wang Y, Chen X. Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China. Sustainability. 2022; 14(14):8881. https://doi.org/10.3390/su14148881
Chicago/Turabian StyleYan, Zhengxiao, Wei Zhou, Yuyi Wang, and Xi Chen. 2022. "Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China" Sustainability 14, no. 14: 8881. https://doi.org/10.3390/su14148881