Decision support method for estimating monetary value of post-renovation office buildings

Abstract

The construction industry engages in renovation work to improve the physical, economic, and environmental aspects of office buildings. During consideration of renovation of deteriorated office buildings, it is critical for project owners to estimate the change in monetary value of the office buildings due to the completed renovation work. Nevertheless, related research and methods for predicting this value remain insufficient. In this study, the monetary value prediction model for post-renovation office buildings was developed by using artificial intelligence techniques and multivariate data analysis techniques based on 90 actual cases of renovated office buildings. The model application results showed (i) relatively high prediction performance (average error rate of 14.12%) and (ii) advantages in various aspects compared to existing approaches. It is expected that project owners considering office building renovations can be supported in decision-making by the developed proposed model. Furthermore, this research will contribute to promoting the office building renovation market.