AN INNOVATIVE APPROACH FOR THE EVALUATION OF EXPANSION OPTION IN BUILDINGS
AN INNOVATIVE APPROACH FOR THE EVALUATION OF EXPANSION OPTION IN BUILDINGS
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Date
2021-09-11
Authors
LAWAL, Yarima Sallau IBRAHIM, Aliyu Makarfi ABUBAKAR, Muawiya ISHAQ, Ziyadul Hassan
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Abstract
Expansion option (EO) in buildings is more valuable when it is easier to achieve.
Creating EO in initial building designs facilitate future expansion. However, this
requires additional investment and the future is unknown whether or not the option
would ever be exercised. This paper proposes an innovative approach for the
evaluation of EO in buildings to avoid under or over-investment. Mathematical
equations and algorithms were first developed based on the binomial method (BM)
of real options analysis which were then implemented on a computer system. An
algorithm was also developed for Monte Carlo simulation (MCS) and integrated
with the binomial model. To illustrate its applicability, a real-life project was used
to test the model. Sensitivity analysis was conducted to explore the influence of
input variables on expansion option value (EOV). The result shows that inflation
rate (i), borrowing rate (b), and rental value (Ri) are the most sensitive variables for
EOV. An increase in i and Ri by just 5% causes a corresponding increase in EOV by
16.26% and 10.60% respectively. While an increase in b by just 5% causes a
corresponding decrease in EOV by 14.61%. However, the least sensitive variables
appear to be the discount rate (r) and volatility (6), An increase in r by 5% causes a
decrease in EOV by 6.9% while an increase in 6 by 5% causes an increase in option
value by 5.85%. Also, the result shows that creating EO in the initial design adds
over 10% value to a building. More so, by integrating the BM with the MSC method,
EOV increases by 190%. The model builds upon a previously developed model for
evaluating building development option (DOV) which was found to have a result
accuracy of 80.77%. It was recommended that building investment decision-makers
should combine both BM and MCS to obtain more reliable and sustainable results.
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Department of Building, Ahmadu Bella University, Zaria, Nigeria
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PROCEEDINGS OF THE WABER 2021 CONFERENCE