Recently, the market environment of construction industry in Korea is undergoing rapid changes and construction companies are struggling to survive in keen competition. One of those is the change of project delivery system, which results that decision making related to a project should be made in the early stage of the project. Thus, the importance of schematic cost estimating is being emphasized. Using a case study, this research analyzes and validates the Quantity Based Active Schematic cost Estimating (Q- BASE) model and prototype developed and proposed on the precedent paper to improve accuracy and reliability compared with the traditional method in building projects. Case study result on structure cost of two real residential complex building projects using proposed model shows that difference between actual cost and estimated cost was smaller than using the existing model by regression analysis technique or artificial neural network technique. Considering that within 5% deviation is small amount in the early stage of cost estimating, the results suggest that the proposed model guarantees accuracy and reliability. In addition, the sensitivity analysis in case study
suggests that this model is capable of tracing change in quantity and of items and change in material cost and labor cost. This enables us to more actively cope with changes of design alternatives and market environment. Moreover, it takes into account relationship with detailed cost estimating.
영어초록
Recently, the market environment of construction industry in Korea is undergoing rapid changes and construction companies are struggling to survive in keen competition. One of those is the change of project delivery system, which results that decision making related to a project should be made in the early stage of the project. Thus, the importance of schematic cost estimating is being emphasized. Using a case study, this research analyzes and validates the Quantity Based Active Schematic cost Estimating (Q- BASE) model and prototype developed and proposed on the precedent paper to improve accuracy and reliability compared with the traditional method in building projects. Case study result on structure cost of two real residential complex building projects using proposed model shows that difference between actual cost and estimated cost was smaller than using the existing model by regression analysis technique or artificial neural network technique. Considering that within 5% deviation is small amount in the early stage of cost estimating, the results suggest that the proposed model guarantees accuracy and reliability. In addition, the sensitivity analysis in case study
suggests that this model is capable of tracing change in quantity and of items and change in material cost and labor cost. This enables us to more actively cope with changes of design alternatives and market environment. Moreover, it takes into account relationship with detailed cost estimating.
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