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Open AccessArticle

Sequencing Infrastructure Investments under Deep Uncertainty Using Real Options Analysis

Department of Civil and Environmental Engineering, National University of Singapore, Singapore 117576, Singapore
Author to whom correspondence should be addressed.
Water 2018, 10(2), 229;
Received: 8 January 2018 / Revised: 12 February 2018 / Accepted: 12 February 2018 / Published: 23 February 2018
(This article belongs to the Special Issue Sponge Cities: Emerging Approaches, Challenges and Opportunities)
The adaptation tipping point and adaptation pathway approach developed to make decisions under deep uncertainty do not shed light on which among the multiple available pathways should be chosen as the preferred pathway. This creates the need to extend these approaches by means of suitable tools that can help sequence actions and subsequently enable the outlining of relevant policies. This paper presents two sequencing approaches, namely, the “Build to Target” and “Build Up” approach, to aid in sub-selecting a set of preferred pathways. Both approaches differ in the levels of flexibility they offer. They are exemplified by means of two case studies wherein the Net Present Valuation and the Real Options Analysis are employed as selection criterions. The results demonstrate the benefit of these two approaches when used in conjunction with the adaptation pathways and show how the pathways selected by means of a Build to Target approach generally have a value greater than, or at least the same as, the pathways selected by the Build Up approach. Further, this paper also demonstrates the capacity of Real Options to quantify and capture the economic value of flexibility, which cannot be done by traditional valuation approaches such as Net Present Valuation. View Full-Text
Keywords: deep uncertainty; Real Options Analysis; sequencing approaches deep uncertainty; Real Options Analysis; sequencing approaches
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Manocha, N.; Babovic, V. Sequencing Infrastructure Investments under Deep Uncertainty Using Real Options Analysis. Water 2018, 10, 229.

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