Exploring the Influence of an Urban Water System on Housing Prices: Case Study of Zhengzhou
Abstract
:1. Introduction
2. Research Area
3. Data and Method
3.1. Variable Setting
3.2. Data Collection and Processing
3.3. Model Specification
4. Research Results
4.1. Results Analysis of Traditional Model
4.2. Result Analysis of Spatial Lag Model
4.3. Results Analysis of GWR Model
4.4. Results Analysis of Exploratory Research
5. Discussions and Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Classification | Variable Name | Variable Type | Expected Sign |
---|---|---|---|
Structural factors | Building age | Continuous | Negative |
Property category | Discrete | Negative | |
Plot ratio | Continuous | Negative | |
Property fee | Continuous | Positive | |
Total number of houses | Discrete | Negative | |
Greening rate | Continuous | Positive | |
Total number of buildings | Discrete | Positive | |
Location factors | Distance to CBD | Continuous | Negative |
Distance to nearest top 3 Hospital | Continuous | Negative | |
Distance to nearest business circle | Continuous | Negative | |
Neighborhood factors | Number of bus stops within 500 m | Discrete | Positive |
Number of supermarket within 500 m | Discrete | Positive | |
Whether there is a metro station within 1 km | Discrete | Positive | |
Whether there is a park within 1 km | Discrete | Positive | |
Number of elementary school within 1 km | Discrete | Positive | |
Number of junior high school within 1 km | Discrete | Positive | |
Whether there is key school within 1 km | Discrete | Positive | |
Water factors | Distance to water system | Continuous | Negative |
Distance to river | Continuous | Negative | |
Distance to lake | Continuous | Negative | |
River surface width | Continuous | Positive | |
Lake surface area | Continuous | Positive | |
River water quality | Discrete | Negative |
Classification | Variable Name | Unit | Average | Standard Deviation |
---|---|---|---|---|
Structural factors | Average price in the community | Yuan/m2 | 15,911 | 3568.4569 |
Building age | Years | 12 | 4.2631 | |
Property category | 0/1 | 0.99 | 0.0146 | |
Plot ratio | —— | 3.93 | 0.0750 | |
Property fee | Yuan/m2 | 1.22 | 0.6071 | |
Total number of houses | Unit | 1315 | 848.1046 | |
Greening rate | —— | 0.33 | 0.0576 | |
Total number of buildings | Unit | 14 | 9.5716 | |
Location factors | Distance to CBD | km | 10.97 | 3.9394 |
Distance to nearest top 3 hospital | km | 1.72 | 0.7986 | |
Distance to nearest business circle | km | 2.57 | 1.1837 | |
Neighborhood factors | Number of bus stops within 500 m | Unit | 8 | 2.9497 |
Number of supermarket within 500 m | Unit | 25 | 10.2882 | |
Whether there is a metro station within 1 km | 0/1 | 0.27 | 0.3928 | |
Whether there is a park within 1 km | 0/1 | 0.86 | 0.2452 | |
Number of elementary school within 1 km | Unit | 2.71 | 1.3817 | |
Number of junior high school within 1 km | Unit | 2.00 | 1.4357 | |
Whether there is key school within 1 km | 0/1 | 0.25 | 0.3728 | |
Water factors | Distance to water system | km | 1.21 | 0.7646 |
Distance to river | km | 1.21 | 0.7687 | |
Distance to lake | km | 4.41 | 1.7499 | |
River surface width | m | 28.79 | 8.7005 | |
Lake surface area | 10,000 m2 | 76.14 | 85.4995 | |
River water quality | Level | 3.78 | 0.6042 |
Name of Model | Setting of Model |
---|---|
Model 1 | |
Model 2 | |
Model 3 | |
Model 4 | |
Model 5 | |
Model 6 | |
Model 7 |
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | |
---|---|---|---|---|---|---|
R-square | 0.6414 | 0.6872 | 0.6528 | 0.6906 | 0.6393 | 0.6887 |
Adjusted R-square | 0.6316 | —— | 0.6428 | —— | 0.6284 | —— |
Prob(F-statistic) | 0.0000 | —— | 0.0000 | —— | 0.0000 | —— |
Log likelihood | 284.0520 | 324.0610 | 294.9640 | 328.5710 | 282.0740 | 324.8570 |
Akaike info criterion | −530.1000 | −608.1230 | −549.9270 | −615.1430 | −522.1480 | −605.7150 |
Schwarz criterion | −444.2400 | −517.7400 | −459.5440 | −520.2400 | −427.2460 | −506.2940 |
Model 1 | Model 2 | ||||
---|---|---|---|---|---|
Variable Name | Standard Coefficient | p-Value | VIF [c] | Standard Coefficient | p-Value |
Constant | 11.1037 | 0.0000 | —— | 6.2393 | 0.0000 |
Building age | −0.0164 | 0.0000 | 2.8060 | −0.0160 | 0.0000 |
Property category | −0.2431 | 0.0032 | 1.2820 | −0.3217 | 0.0000 |
Plot ratio | −0.0622 | 0.0018 | 2.2902 | −0.0495 | 0.0069 |
Property fee | 0.1003 | 0.0000 | 2.5632 | 0.0843 | 0.0000 |
Total number of houses | −0.0727 | 0.0000 | 2.8700 | −0.0607 | 0.0000 |
Greening rate | 0.0493 | 0.0302 | 1.1425 | 0.0576 | 0.0058 |
Total number of buildings | 0.1068 | 0.0000 | 3.0829 | 0.0913 | 0.0000 |
Distance to CBD | −0.2714 | 0.0000 | 1.5551 | −0.1575 | 0.0000 |
Distance to nearest top 3 Hospital | −0.0431 | 0.0001 | 1.4016 | −0.0377 | 0.0001 |
Distance to nearest business circle | −0.0814 | 0.0000 | 1.4719 | −0.0637 | 0.0000 |
Number of bus stops within 500 m | 0.0012 | 0.5534 | 1.3822 | −0.0017 | 0.3688 |
Number of supermarkets within 500 m | −0.0026 | 0.0000 | 1.6703 | −0.0010 | 0.0789 |
Whether there is a metro station within 1 km | −0.0214 | 0.1603 | 1.1840 | −0.0122 | 0.3836 |
Whether there is a park within 1 km | 0.0334 | 0.0758 | 1.1222 | 0.0393 | 0.0229 |
Number of elementary schools within 1 km | −0.0020 | 0.6461 | 1.4811 | 0.0026 | 0.5197 |
Number of junior high school within 1 km | 0.0264 | 0.0000 | 1.4111 | 0.0216 | 0.0000 |
Whether there is key school within 1 km | 0.0522 | 0.0004 | 1.0552 | 0.0422 | 0.0019 |
Distance to water system | −0.0278 | 0.0000 | 1.1721 | −0.0214 | 0.0002 |
W*lnP | —— | —— | —— | 0.4761 | 0.0000 |
Model 3 | Model 4 | ||||
---|---|---|---|---|---|
Variable Name | Standard Coefficient | p-Value | VIF[c] | Standard Coefficient | p-Value |
Constant | 11.1488 | 0.0000 | —— | 6.5951 | 0.0000 |
Building age | −0.0166 | 0.0000 | 2.8070 | −0.0161 | 0.0000 |
Property category | −0.2735 | 0.0008 | 1.2910 | −0.3347 | 0.0000 |
Plot ratio | −0.0591 | 0.0027 | 2.0990 | −0.0488 | 0.0075 |
Property fee | 0.0978 | 0.0000 | 2.5676 | 0.0839 | 0.0000 |
Total number of houses | −0.0705 | 0.0000 | 2.8735 | −0.0601 | 0.0000 |
Greening rate | 0.0572 | 0.0111 | 1.1514 | 0.0616 | 0.0031 |
Total number of buildings | 0.1036 | 0.0000 | 3.0925 | 0.0904 | 0.0000 |
Distance to CBD | −0.2630 | 0.0000 | 1.5786 | −0.1600 | 0.0000 |
Distance to nearest top 3 hospital | −0.0353 | 0.0011 | 1.4422 | −0.0334 | 0.0008 |
Distance to nearest business circle | −0.0628 | 0.0000 | 1.6936 | −0.0537 | 0.0000 |
Number of bus stops within 500 m | 0.0005 | 0.7872 | 1.3904 | −0.0019 | 0.3144 |
Number of supermarkets within 500 m | −0.0020 | 0.0013 | 1.7589 | −0.0008 | 0.1889 |
Whether there is a metro station within 1 km | −0.0292 | 0.0537 | 1.1985 | −0.0176 | 0.2097 |
Whether there is a park within 1 km | 0.0346 | 0.0617 | 1.1225 | 0.0397 | 0.0210 |
Number of elementary schools within 1 km | 0.0026 | 0.5666 | 1.5616 | 0.0051 | 0.2230 |
Number of junior high schools within 1 km | 0.0294 | 0.0000 | 1.4565 | 0.0238 | 0.0000 |
Whether there is key school within 1 km | 0.0502 | 0.0006 | 1.0561 | 0.0417 | 0.0021 |
Distance to river | −0.0231 | 0.0002 | 1.2160 | −0.0192 | 0.0010 |
Distance to lake | −0.0568 | 0.0000 | 1.5949 | −0.0342 | 0.0039 |
W*lnP | —— | —— | —— | 0.4439 | 0.0000 |
Model 5 | Model 6 | ||||
---|---|---|---|---|---|
Variable Name | Standard Coefficient | p-Value | VIF[c] | Standard Coefficient | p-Value |
Constant | 11.1992 | 0.0000 | —— | 6.1310 | 0.0000 |
Building age | −0.0171 | 0.0000 | 2.8840 | −0.0169 | 0.0000 |
Property category | −0.2646 | 0.0016 | 1.3079 | −0.3559 | 0.0000 |
Plot ratio | −0.0563 | 0.0050 | 2.1059 | −0.0474 | 0.0097 |
Property fee | 0.0983 | 0.0000 | 2.5671 | 0.0824 | 0.0000 |
Total number of houses | −0.0735 | 0.0000 | 2.8832 | −0.0593 | 0.0000 |
Greening rate | 0.0443 | 0.0535 | 1.1510 | 0.0541 | 0.0098 |
Total number of buildings | 0.1082 | 0.0000 | 3.0879 | 0.0922 | 0.0000 |
Distance to CBD | −0.2869 | 0.0000 | 1.9000 | −0.1503 | 0.0000 |
Distance to nearest top 3 hospital | −0.0342 | 0.0020 | 1.4594 | −0.0327 | 0.0012 |
Distance to nearest business circle | −0.0804 | 0.0000 | 1.5764 | −0.0575 | 0.0000 |
Number of bus stops within 500 m | 0.0016 | 0.4211 | 1.3906 | −0.0017 | 0.3613 |
Number of supermarkets within 500 m | −0.0023 | 0.0003 | 1.7546 | −0.0010 | 0.0924 |
Whether there is a metro station within 1 km | −0.0156 | 0.3117 | 1.1954 | −0.0045 | 0.7465 |
Whether there is a park within 1 km | 0.0336 | 0.0763 | 1.1350 | 0.0366 | 0.0350 |
Number of elementary schools within 1 km | −0.0052 | 0.2507 | 1.5644 | −0.0013 | 0.7622 |
Number of junior high schools within 1 km | 0.0242 | 0.0000 | 1.4238 | 0.0203 | 0.0000 |
Whether there is key school within 1 km | 0.0432 | 0.0045 | 1.1037 | 0.0347 | 0.0123 |
River surface width | 0.0021 | 0.0062 | 1.5138 | 0.0013 | 0.0633 |
Lake surface area | −0.0003 | 0.6919 | 1.6910 | −0.0001 | 0.1015 |
River water quality | −0.0244 | 0.0384 | 1.7957 | −0.0357 | 0.0009 |
W*lnP | —— | —— | —— | 0.5010 | 0.0000 |
Water System Accessibility | River and Lake Accessibility | Nature of the Water System | |
---|---|---|---|
R-square | 0.6145 | 0.6174 | 0.5687 |
Adjusted R-square | 0.6054 | 0.6089 | 0.5601 |
Akaike info criterion | −486.3656 | −491.5502 | −415.6654 |
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Li, J.; Hu, Y.; Liu, C. Exploring the Influence of an Urban Water System on Housing Prices: Case Study of Zhengzhou. Buildings 2020, 10, 44. https://doi.org/10.3390/buildings10030044
Li J, Hu Y, Liu C. Exploring the Influence of an Urban Water System on Housing Prices: Case Study of Zhengzhou. Buildings. 2020; 10(3):44. https://doi.org/10.3390/buildings10030044
Chicago/Turabian StyleLi, Junjie, Yaduo Hu, and Chunlu Liu. 2020. "Exploring the Influence of an Urban Water System on Housing Prices: Case Study of Zhengzhou" Buildings 10, no. 3: 44. https://doi.org/10.3390/buildings10030044
APA StyleLi, J., Hu, Y., & Liu, C. (2020). Exploring the Influence of an Urban Water System on Housing Prices: Case Study of Zhengzhou. Buildings, 10(3), 44. https://doi.org/10.3390/buildings10030044