From the various recent conditions of residential market, there have been numerous studies with regards to the feasibility of housing business. However, most of the studies relate to either qualitative studies such as decision-making, analysis model, ...
From the various recent conditions of residential market, there have been numerous studies with regards to the feasibility of housing business. However, most of the studies relate to either qualitative studies such as decision-making, analysis model, and research aspects of feasibility analysis, or aspects of market price of residences, hedonic models, factor comparison analysis, risk analysis, short-term market forecast, demand forecast, and formation of residential market. However, there are not many systematic studies on feasibility analysis through organized examination of profit margin.While examining the feasibility of a project, the important variables in determining the financial analysis are namely, construction cost, land price, and sales rate. These variables can fluctuate within a certain range at feasibility analysis phase but studies on their tendency and statistical analysis are hard to find.Moreover, the cost of apartment can be induced through regression analysis when factors such as construction cost, land price, and the sales rate change in a certain range at same project. The regression method takes the cost of apartment as a dependent variable, and it takes construction cost, land price, and sales rate as independent variables. Thus, the regression method would hold different values depending on the inherent characteristic of each project. However, it is hard to find such studies that concentrate on either the definition of these inherent characteristic of projects or the influence which these inherent characteristic have on business profits. These inherent characteristic of projects can be observed from various perspectives, but this study assumes that the characteristic of planning such as the scale of a project, floor space, the ratio of basement area or number of floors would bear significant meaning as the inherent characteristic. Through analytical procedures, this study observed that floor area ratio, sales area ratio, and the term of works bear high significance among all other inherent characteristic.Thus, in the analysis of feasibility for apartment housing business, this study attempted a statistical approach towards a break-even analysis, beginning from the notion that qualitative factors are measured in monetary value through preliminary feasibility analysis and marketing analysis. As the parameter of this study, construction cost, land price, and sales rate were chosen as the first set of independent variables; and floor area ratio, sales area ratio, and the term of works of a project were selected as the second set of independent variables. The sales area ratio was defined as the ratio of sales area relative to the total area of project.The purpose of this study can be divided into 2 stages of analysis. The first phase would be the sensitivity analysis of financial analysis item and statistical propensity of financial analysis item. The second phase comprises of analysis for the influence of characteristic of planning on the profit of housing development business.For these procedures, definite conditions have been established and 26 projects have been selected for financial analysis. In the first phase, there has been sensitivity analysis for 12 items of financial analysis. In addition, by simulating the construction cost, land price, and sales rate as variables of inputs, statistical analysis and analysis for propensity of financial analysis item were executed on condition that each project''s debts is repaid or kept.In the second phase, the cost of apartment was taken as dependent variables. The first regression analysis that takes independent variables of construction cost, land price, and sales rate yielded a total of 26 regression equations. These 26 regression coefficients (construction cost coefficients, land price coefficients, constants) will hold different values according to the characteristic of each project. As the explanatory variables for the different coefficients for the each project, characteristic of planning (floor area ratio, sales area ratio, term of works) were selected. The regression coefficients (construction cost coefficient, land cost coefficient, constant) were taken as dependent variables and they were used to undertake second regression analysis, which takes floor area ratio, sales area ratio, and term of works as independent variables.In the second regression analysis, by using the regression equations that take construction cost coefficient, land price coefficient, and constant as dependent variables, a more generalized regression equation was created by placing floor area ratio, sales area ratio, term of works, construction cost, land price and sales rate as independent variables and by placing cost of apartment as dependent variable. Unlike the first regression equation that depends on each project''s characteristic, the generalized regression equation would be able to explain the shifts in the returns of projects with regards to the changes in characteristic of planning that is determined during project design.The focus of this study is as follows:1) Through the sensitivity analysis for 12 items of financial analysis on profits, the study will not only be limited to the process of financial analysis, but it will reflect decision making priorities related to cost reductions among the overall process of development business.2) Through propensity of financial analysis item under the break-even analysis, the propensity of financial analysis item can be determined depending on the change of land price and construction cost. In this way, accuracy in feasibility analysis would be enhanced and risk factors will be distinguished more easily.3) By using the statistical analysis under the break-even analysis, the statistics such as mean value, maximum value, minimum value or range in relation to land price and construction costs can be determined. This approach will help determine the appropriate sales ratio of financial analysis items.4) By using the generalized regression equation, the influence of the factors of characteristic of planning such as floor area ratio, sales area ratio, and term of works can be quantified. Particularly, the procedure that shows the influence of sales area ratio on project profits is significant. Moreover, during the early stages of evaluation for a project, this approach can be used as a way of approximation rather than having to work out the entire process of computation. In the perspective of policy making, by using the generalized regression equation and the analytical method from this study, this study would help determine the influence of floor area ratio and sales area ratio on sales price and land value.