AN INNOVATIVE APPROACH FOR THE EVALUATION OF EXPANSION OPTION IN BUILDINGS

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dc.contributor.authorLAWAL, Yarima Sallau IBRAHIM, Aliyu Makarfi ABUBAKAR, Muawiya ISHAQ, Ziyadul Hassan
dc.date.accessioned2024-05-14T11:37:32Z
dc.date.available2024-05-14T11:37:32Z
dc.date.issued2021-09-11
dc.descriptionDepartment of Building, Ahmadu Bella University, Zaria, Nigeria
dc.description.abstractExpansion 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.
dc.identifier.citationPROCEEDINGS OF THE WABER 2021 CONFERENCE
dc.identifier.urihttps://kubanni.abu.edu.ng/handle/123456789/12918
dc.language.isoen
dc.titleAN INNOVATIVE APPROACH FOR THE EVALUATION OF EXPANSION OPTION IN BUILDINGS
dc.typePreprint
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