# Vacant House Characteristics by Use Area and Their Application to Sustainable Community
## 4 Results of Analysis of Factors Affecting Vacant House
### Analysis of Factors Influencing the Occurrence of Vacant Houses by Use Area
For residential areas, the probability of vacant house occurrence increases when the residential area lot is narrow or irregular, indicating that lot size and shape are significant factors in residential vacant house occurrence. Building structure did not have a significant effect on vacant houses in either residential or commercial areas. The year of construction was only significant for commercial areas; a large number of old houses leads to more vacant houses. Commercial areas have a large floating population and frequent retail activities. The findings suggest that many old houses in the vicinity negatively affect the commercial district's formation and, the number of vacant houses in the commercial area also tends to increase. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Special-Purpose Areas**} & \multicolumn{2}{c}{**General Residential Area**} & \multicolumn{2}{c}{**Central Commercial Area**} \\ \cline{3-8}
**Variables** & & **B** & **S.E.** & **Exp(B)** & **B** & **S.E.** & **Exp(B)** \\ \hline \multirow{4}{*}{Residential Environment} & Intercept & \(-1.110\) & \(0.167\) & \(0.476\) & \(-1.253\) & \(0.427\) & \(0.163\) \\ \cline{2-8}  & Rate of old houses & \(0.148\)** & \(0.038\) & \(1.087\) & \(-0.041\)*** & \(0.039\) & \(0.877\) \\ \cline{2-8}  & Ratio of economically active population & \(-0.005\)** & \(0.002\) & \(0.022\) & \(0.016\)** & \(0.004\) & \(0.285\) \\ \cline{2-8}  & Rate of change in the number of businesses & \(-0.287\) & \(0.083\) & \(0.042\) & \(-0.960\)*** & \(0.135\) & \(0.134\) \\ \hline \multirow{4}{*}{Population and social} & Official land price & \(-0.017\) & \(0.002\) & \(0.131\) & \(-0.006\)** & \(0.002\) & \(0.949\) \\ \cline{2-8}  & Land price change rate & \(0.356\) & \(0.047\) & \(1.688\) & \(0.082\) & \(0.103\) & \(0.520\) \\ \cline{2-8}  & Ratio of elderly population & \(0.418\)* & \(0.442\) & \(1.361\) & \(0.076\)** & \(0.150\) & \(1.180\) \\ \hline \multirow{4}{*}{Physical Environment} & Undersized parcel & \(0.618\)*** & \(0.034\) & \(0.387\) & \(-0.589\) & \(0.032\) & \(0.495\) \\ \cline{2-8}  & Unstructured parcel & \(0.173\)* & \(0.066\) & \(0.978\) & \(-0.128\) & \(0.082\) & \(1.037\) \\ \hline \multirow{4}{*}{Individual building} & Building structure & \(0.153\) & \(0.054\) & \(1.061\) & \(0.044\) & \(0.069\) & \(1.078\) \\ \cline{2-8}  & Year of construction & \(-0.486\) & \(0.069\) & \(0.495\) & \(0.455\)** & \(0.069\) & \(1.282\) \\ \cline{2-8}  & Poor contact area & \(-0.104\)*** & \(0.003\) & \(0.935\) & \(0.108\)*** & \(0.002\) & \(0.431\) \\ \cline{2-8}  & Slope & \(0.227\)** & \(0.072\) & \(0.663\) & \(0.407\) & \(0.085\) & \(1.755\) \\ \hline \hline \end{tabular}  
* B: Regression coefficient; S.E.: Standard error; Exp(B): Odds ratio; statistically significant **
* \(p<0.01\), *
* \(p<0.1\).  
\end{table} 
Table 5: Firth logistic regression results: significant factors affecting vacant housing. Poor contact area was significant for both residential and commercial areas. In commercial areas, there is a high probability of vacant houses in places with poor contact, and accessibility and convenient transportation favorable to commercial activities affect vacant house occurrence. Conversely, in residential areas, the probability of vacant houses is high in places where safety is not secured because of poor accessibility and high slope or poor function location.