Improvement Pathways for Urban Land Use Efficiency in the Beijing-Tianjin-Hebei Urban Agglomeration at the County Level: A Context-Dependent DEA Based on the Closest Target
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Index System and Data Sources
2.3. Research Methods
2.3.1. DEA
2.3.2. Paired-Samples t-Test and One-Way ANOVA
2.3.3. System Clustering Analysis
3. Results
3.1. Efficiency of the Closest and Furthest Targets
3.2. Intermediate Targets and Steps for Improvement
3.3. Improvement Elements of Inefficient Counties
3.4. Improvement Paths of Different Types and Regions
4. Discussion
4.1. Theoretical Implications
4.2. Policy Implications
4.3. Limitations and Future Improvements
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Types | Names | Details |
---|---|---|
Input index | Employees per land area | Number of employees in the secondary and tertiary industries/Construction land area |
Fixed asset investment per land area | Fixed asset investment of the whole society/Construction land area | |
Desirable output index | Added value of the secondary industry per land area | Added value of the secondary industry/Construction land area |
Added value of the tertiary industry per land area | Added value of the tertiary industry/Construction land area | |
Per capita disposable income of urban residents | Per capita disposable income of urban residents | |
Density of POI | Number of POI (medical care services, living facilities, science and education cultural services)/Construction land area | |
Green coverage rate in built-up area | Greenland area/Construction land area | |
Undesirable output index | Concentration of PM2.5 | Annual average concentration of PM2.5 concentration |
Samples | Mean | N | t-Value | Sig. | Correlation | Sig. |
---|---|---|---|---|---|---|
SBM | 0.364 | 197 | −38.009 | 0.001 | 0.822 | 0.001 |
MinDS | 0.731 |
Test Variable | Classification | Levene Statistic | F-Value |
---|---|---|---|
Global progress value | 2nd–7th level | 1.709 | 7.524 *** |
Test Variable | Classification | Mean | Levene Statistic | F Value |
---|---|---|---|---|
Local progress value (1st step) | 2nd–7th level | 1.436 | 1.178 | 0.856 |
Local progress value (2nd step) | 3rd–7th level | 1.367 | 1.359 | 1.554 |
Local progress value (3rd step) | 5th–7th level | 1.321 | 1.530 | 1.622 |
Samples | Mean | N | t-Value | Sig. | Correlation | Sig. |
---|---|---|---|---|---|---|
step-by-step | 1.327 | 184 | −12.913 | 0.001 | 0.826 | 0.001 |
one step | 1.504 |
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Tian, Y.; Li, J. Improvement Pathways for Urban Land Use Efficiency in the Beijing-Tianjin-Hebei Urban Agglomeration at the County Level: A Context-Dependent DEA Based on the Closest Target. Int. J. Environ. Res. Public Health 2023, 20, 4429. https://doi.org/10.3390/ijerph20054429
Tian Y, Li J. Improvement Pathways for Urban Land Use Efficiency in the Beijing-Tianjin-Hebei Urban Agglomeration at the County Level: A Context-Dependent DEA Based on the Closest Target. International Journal of Environmental Research and Public Health. 2023; 20(5):4429. https://doi.org/10.3390/ijerph20054429
Chicago/Turabian StyleTian, Ye, and Jiangfeng Li. 2023. "Improvement Pathways for Urban Land Use Efficiency in the Beijing-Tianjin-Hebei Urban Agglomeration at the County Level: A Context-Dependent DEA Based on the Closest Target" International Journal of Environmental Research and Public Health 20, no. 5: 4429. https://doi.org/10.3390/ijerph20054429