## 4 Results
### Factors Impacting Industrial Location Selection
#### 4.3.2 Industrial Differences in Impact Factors  
The calculation results are shown in Table 5. Agglomeration effects have a significant impact on the spatial layout of industries, and the agglomeration effect coefficients for the 14 industries are positive, which indicates that external economies of scale and agglomeration effects are highly attractive to firms in the 14 industries. The development of Zhengzhou East railway station is rapid, and agglomeration economies are still dominant, which plays an important role in changes in the spatial layout and structure of industries. Additionally, there are obvious differences among the different industries. Land rents have a significant impact on the distribution of the accommodations and catering, real estate, transportation, wholesale and retail, and leasing and business services industries. Of these, leasing and business services are positively correlated with land rents, while the other industries are negatively correlated.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multicolumn{2}{c}{**Accommodation**} & \multirow{2}{*}{**Real Estate**} & \multirow{2}{*}{**Construction**} & \multirow{2}{*}{**Transportation**} & \multirow{2}{*}{**Education**} & \multirow{2}{*}{**Finance**} & \multicolumn{2}{c}{**Residential Services**} \\  & & & & & & & & \\ X1 & \(-\)0.0306 * & \(-\)0.237 ** & \(-\)0.050 & \(-\)0.204 * & 0.003 & 0.060 & \(-\)0.003 \\ X2 & 4.603 ** & 1.863 ** & 0.335 ** & 2.645 ** & 0.641 *** & 1.527 ** & 0.459 ** \\ X3 & \(-\)0.3495 ** & 0.267 & \(-\)0.348 & 0.529 & \(-\)0.026 & 0.042 & 0.049 \\ X4 & \(-\)0.0353 *** & 0.285 * & 0.321 * & 0.625 * & 0.297 & 0.083 & 0.084 \\ X5 & 0.2195 ** & \(-\)0.351 *** & \(-\)0.177 & \(-\)0.052 & 0.075 & \(-\)0.091 & \(-\)0.120 \\ X6 & \(-\)0.0160 & 0.158 & 0.059 & \(-\)0.485 & \(-\)0.048 & 0.195 & \(-\)0.290 ** \\ X7 & 0.6058 ** & \(-\)0.262 & 0.106 & \(-\)0.423 & 0.092 & \(-\)0.499 ** & 0.235 \\ X8 & \(-\)0.9089 * & 0.032 & \(-\)0.334 & 1.958 & 0.839 & \(-\)0.250 & \(-\)1.288 ** \\ X9 & 0.27812 ** & 0.194 & \(-\)0.055 & 0.017 & 0.081 & \(-\)0.061 & 0.090 \\ R\({}^{2}\) & 0.1723 & 0.121 & 0.111 & 0.115 & 0.122 & 0.171 & 0.223 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Regression results of different types of industries’ location selection.  
Distance from the HSR station has a significant impact on the distribution of the accommodation and catering, wholesale and retail, and leasing and business services industries, which indicates that the opening of the HSR station has attracted more basic service industries. Of these, the accommodation and catering industry has a negative correlation, and the other industries have a positive correlation. Distance to a subway station has a significant impact on the accommodation and catering, transportation, and construction industries, among which the impact on the transportation and construction industries is positive and that on the catering and accommodation industry is negative. Distance from a commuter bus stop has a significant impact on the accommodation and catering and real estate industries. The former is a positive correlation, and the latter is a negative correlation. Distance from a shopping center has a significant impact on the residential services and manufacturing industries. The former is a negative correlation, and the latter is a positive correlation. Distance from the bus station has a significant impact on the accommodation and catering, financial, wholesale and retail, manufacturing, and leasing and business services industries. Of these, the catering and accommodation industry is positively correlated, and the others are negatively correlated.