Determining value at risk for estimating renovation building projects by application of probability-based fuzzy set theory

Abstract

Building renovation projects are mainly affected by not only the design constraints of existing buildings but also various influential factors (e.g., building age, structural stability, site condition). However, conventional estimation methods deal with renovation projects similar to new construction and do not effectively consider potential risk factors. Thus, unexpected problems can make it difficult to proceed with the initial project execution plan. A three-phase framework is proposed for a probabilistic cost estimation process model that reflects the uncertainties of residential building renovation: (1) roughly estimating the cost based on industry means data; (2) converting the estimated costs to probabilistic values to consider the project characteristics; and (3) adjusting the converted probabilistic values according to risk factors. The value at risk of a specific construction can then be calculated to improve the reliability of the cost estimation. The proposed model was applied to a case study to demonstrate its feasibility. The results showed that the distribution of cost estimates reflecting the project characteristics and risk factors could be objectively confirmed at the initial stage. Thus, the method can help facilitate the decision-making process for homeowners, especially those reluctant to choose renovation.