A simulation-based binomial model for building development appraisal

Purpose: Building developments are often capital intensive, have a long payback period and many associated risks and uncertainties. This makes investments in building projects to be a big challenge. This study aims to develop a computerized simulation-based binomial model (CSBBM) for building investment appraisal with a view to improving the economic sustainability of proposed building projects. Design/methodology/approach: Mathematical equations and algorithms were developed based on the binomial method (BM) of real options analysis and then implemented on a computer system. A hybrid algorithm that integrates Monte Carlo simulation (MCS) and BM was also developed. A real-life project was used to test the model. Sensitivity analysis was also conducted to explore the influence of input variables on development option value (DOV). Findings: The test result shows that the model developed provides a better estimate of the value of an investment when compared with traditional net present value technique, which underestimate the value. Moreover, inflation rate (i) and rental value (Ri) are the most sensitive variables for DOV. An increase in i and Ri by just 5% causes a corresponding increase in DOV by 202% and 132%, respectively. While the least sensitive variable is the discount rate (r), as an increase in r by 5% causes a corresponding decrease in DOV by just 9%. The CSBBM is capable of determining the optimal time of development of buildings with an accuracy of 80.77%. Practical implications: The hybrid model produces higher DOV than that of only the BM because MCS considers randomness in uncontrollable variables. Thus, building investment decision-makers should always use MCS to complement the BM in an investment analysis. Originality/value: There is limited evidence on the use of this kind of hybrid model for determining DOV in practice.