The soaring number of natural hazards in recent years due largely to climate change has resulted in an even higher level of investment in flood protection structures. However, such investments tend to be made in the aftermath of disasters. Very little is known about the proactive planning of flood protection investments that account for uncertainties associated with flooding events. Understanding the uncertainties such as “when” to invest on these structures to achieve the most optimal cost-saving amount is outmost important. This study fills this large knowledge gap by developing an investment decision-making assessment framework that determines an optimal timing of flood protection investment options. It combines real options with a net present value analysis to examine managerial flexibility in various investment timing options. Historical data that contain information about river water discharges were leveraged as a random variable in the modeling framework because it may help investors better understand the probability of extreme events, and particularly, flooding uncertainties. A lattice model was then used to investigate potential alternatives of investment timing and to evaluate the benefits of delaying investments in each case. The efficacy of the proposed framework was demonstrated by an illustrative example of flood protection investment. The framework will be used to help better inform decision makers.
Identifer | oai:union.ndltd.org:PERUUPC/oai:repositorioacademico.upc.edu.pe:10757/651845 |
Date | 01 February 2020 |
Creators | Gomez-Cunya, L., Gomez-Cunya, Luis Angel, Fardhosseini, Mohammad Sadra, Lee, Hyun Woo, Choi, Kunhee |
Publisher | Elsevier Ltd |
Source Sets | Universidad Peruana de Ciencias Aplicadas (UPC) |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/article |
Format | application/pdf |
Rights | info:eu-repo/semantics/embargoedAccess |
Relation | International Journal of Disaster Risk Reduction, https://www.sciencedirect.com/science/article/abs/pii/S2212420919305217?dgcid=rss_sd_all, 43 |
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