## 3 Results
### Spatial Characteristics of the Contributions of LPRO's Elements
#### 3.3.2 Regional Characteristics of the Contributions of LPRO's Elements  
This study further examines the differentiated characteristics of the macro effects of various elements of LPRO in northeastern, eastern, central and western China under various economic foundations and geographical conditions (Table 6 and Figures 7-10). \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Northeastern Region**} & \multicolumn{2}{c}{**Eastern Region**} & \multicolumn{2}{c}{**Central Region**} & \multicolumn{2}{c}{**Western Region**} \\
**Term** & **St.** & **St.** & **St.** & **St.** & **St.** & **St.** & **St.** & **St.** & **St.** \\  & **Error** & **Coefficient** & **Error** & **Coefficient** & **Error** & **Coefficient** & **Error** & **Coefficient** \\ \hline Intercept & 0.014 & 0.213 & 0.017 & 0.2 & 0.014 & 0.242 & 0.01 & 0.194 \\ X1 & 0 & \(-\)0.002 & 0 & \(-\)0.021 * & 0 & \(-\)0.04 * & 0 & \(-\)0.036 * \\ X2 & 0 & 0.012 & 0 & \(-\)0.055 *** & 0 & \(-\)0.029 * & 0 & \(-\)0.046 ** \\ X3 & 0 & \(-\)0.417 * & 0 & \(-\)0.053 * & 0 & 0.061 * & 0.008 & 0.002 \\ X4 & 0 & 0.092 * & 0 & \(-\)0.025 & 0 & 0.009 & 0 & 0.109 * \\ X5 & 0 & \(-\)0.028 & 0 & 0.029 & 0 & 0.08 * & 0 & 0.085 *** \\ X6 & 0 & \(-\)0.055 & 0 & 0.058 ** & 0 & \(-\)0.032 & 0 & 0.019 \\ X7 & 0.02 & 0.027 & 0.019 & 0.006 & 0.018 & \(-\)0.161 *** & 0.014 & \(-\)0.108 *** \\ X8 & 0.014 & \(-\)0.068 & 0.01 & \(-\)0.03 & 0.011 & \(-\)0.014 & 0.008 & \(-\)0.041 \\ X9 & 0.016 & \(-\)0.076 & 0.014 & 0.038 * & 0.014 & \(-\)0.08 & 0.009 & \(-\)0.003 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Regression coefficients of LPRO’s elements in different regions. Figure 6: Spatial pattern of standard residuals and regression coefficients for each factor in the GWR model. For northeastern China, the scales of commerce and residence use in the transfer process are significantly negatively correlated and significantly positively correlated with LPRO's macro effects, respectively, indicating that to improve LPRO's macro effects, the LPR transfer structure should be based on the actual development of northeastern China to reduce the amount of commercial land and increase the amount of residential land. There are positive associations between the land price and LPRO's macro effects in northeastern China (R = 0.646, \(p<1\%\)), implying that appropriately increasing the land price helps enhance LPRO's macro effects. In the utilization process, the rational and advanced levels of industry utilization are significantly positively correlated with LPRO's macro effects, which means that the more reasonable and advanced the industry structure is, the more conducive it is to promoting LPRO's macro effects. In the supervision link, regulating by a given FAR and setting a lower limit of the FAR are negatively and positively related to LPRO's macro effects, with coefficients of \(-0.057\) (\(p<5\%\)) and \(0.154\) (\(p<1\%\)), respectively, which demonstrates that to give full play to LPRO's macro effects in northeastern China, it is better to adopt the regulation method of setting the lower limit of the FAR rather than the regulation method of a given FAR. In short, in the northeastern region, five indicators significantly promote LPRO's macro effects. Among them, the contribution of the land price is as high as 61.60%, followed by the contributions of the rational utilization level (12%) and advanced utilization level (7.93%), whereas the contributions of setting the lower limit of the FAR and the scale of residential land are relatively low, at 5.60% and 3.48%, respectively. In addition, two factors, a given FAR and the scale of commercial land, significantly curb LPRO's macro effects, with contributions of 5.14% and 4%, respectively (Figure 7).