## 4 Spatiotemporal Evolution Characteristics
### Diverse Changes in Spatial Influencing Factors
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{\begin{tabular}{c} **Primary Indicator** \\ **(Weight)** \\ \end{tabular} } & \multirow{2}{*}{**Secondary Indicator**} & \multicolumn{2}{c}{**Correlation Statistics**} & \multirow{2}{*}{**Change Rate (\%)**} \\ \cline{3-3} \cline{5-5}  & & **2012** & & **2023** \\ \hline \multirow{3}{*}{\begin{tabular}{c} **Traffic Factors** \\ **(0.172)** \\ \end{tabular} } & Distance to main roads & 0.53936 & 0.63574 & +17.87 \\  & Distance to subway stations & 0.52692 & 0.46789 & \(-11.20\) \\  & Weighted Average & 0.533762 & 0.5602075 & +4.95 \\ \hline \multirow{3}{*}{\begin{tabular}{c} **Workplace Factors** \\ **(0.309)** \\ \end{tabular} } & Density of company facilities & 0.34709 & 0.56404 & +62.51 \\  & Density of financial facilities & 0.69659 & 0.72737 & +4.42 \\  & Density of government and & & 0.75311 & 0.77281 & +2.61 \\  & social institutions & & & \\  & Weighted Average & 0.59687 & 0.68838 & +15.33 \\ \hline \multirow{3}{*}{\
\begin{tabular}{c} **Living Factors** \\ **(0.382)** \\ \end{tabular} } & Density of residential facilities & 0.69168 & 0.79187 & +14.49 \\  & Density of dining facilities & 0.82755 & 0.88691 & +7.17 \\  & Density of educational facilities & 0.70940 & 0.73561 & +3.69 \\  & Density of medical facilities & 0.85434 & 0.83116 & \(-2.71\) \\  & Density of leisure facilities & 0.56287 & 0.70431 & +25.13 \\  & Density of shopping facilities & 0.77154 & 0.76472 & \(-0.88\) \\  & Weighted Average & 0.73634 & 0.79672 & +8.21 \\ \hline \multirow{3}{*}{
\begin{tabular}{c} **Trade Factors** \\ **(0.137)** \\ \end{tabular} } & Density of tourist facilities & 0.65296 & 0.37868 & \(-42.01\) \\  & Density of hotel facilities & 0.68924 & 0.76438 & +10.90 \\ \cline{1-1}  & Density of service facilities & 0.78694 & 0.82866 & +5.30 \\ \cline{1-1}  & Weighted Average & 0.70403 & 0.62938 & \(-10.59\) \\ \hline \multicolumn{3}{c}{**Weighted Total**} & 0.65926 & 0.70364 & +6.73 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Statistical Analysis of POI Band Set Statistics for Xi’an City Center Paomo Restaurants. in individual indicators, the overall traffic factor shows a modest improvement (4.95% increase), indicating better general accessibility for customers relying on road transport. There was a substantial increase in the density of company facilities (62.51% increase), which may reflect a strategic move to locate Paomo restaurants near business centers to attract office workers. Slight increases in financial and government facility densities suggest steady growth in these areas. A significant rise (15.33% increase) in the overall workplace factor indicates a strengthening relationship between workplace density and restaurant placement, aligning with a growing lunchtime business market. Marked increases in the density of residential facilities (14.49% increase) and dining facilities (7.17% increase) point to an expanding urban population and a growing food service industry. These changes suggest Paomo restaurants are becoming more integrated into residential zones. The living factor shows a healthy increase (8.21%), reflecting an overall improvement in life service accessibility around these restaurants. The stark decrease in the density of tourist facilities (\(-\)42.01% decrease) contrasts with the increase in hotel facility density (10.90% increase), possibly indicating a shift in tourism dynamics or changes in tourist preferences. The decline in the overall trade factor (\(-\)10.59% decrease) could be concerning as it might reflect reduced commercial vitality in areas typically frequented by tourists. The overall weighted total indicates a positive change (6.73% increase), suggesting that, on balance, the factors influencing the placement and success of Paomo restaurants have improved from 2012 to 2023. The varying performance across different categories highlights the complex interplay between urban development, market dynamics, and consumer behavior that influences the spatial distribution of culinary services.