주택재개발사업의 사업성 예측모형

Business Prediction Model of Housing Redevelopment Project: Focused on Seoul Redevelopment Projects

This study explores business prediction model by using discriminant analysis and logistic regression analysis which are based on the physical status of the business district, the project period and the change of the project area in the residential redevelopment project of the Seoul Metropolitan City. As a result, although the predictive degree of the two models is relatively high, more than 70%, predictive degree for low-feasibility areas is lower than that for high feasibility areas. The effects of variables on the business performance of the residential redevelopment project were examined by discriminant analysis and positive(+) and negative(-) effects of influence were examined through logistic regression analysis. The physical element, the number of removal buildings and the area variable had the highest influence, the area had the positive effect, and the removal structure had the negative effect. The duration of each step has the second highest impact, and all three variables have negative effects. Lastly, it is analyzed that the change of the zoning which is the urban planning factor shows the weak influence and the negative effect. However, unlike the existing studies, it is significant that the period of the housing redevelopment project, the physical factors of the district, and urban planning factors were used, and the linear regression analysis model was improved to present the discriminant analysis and the logistic regression model.