A Logical Approach to Real Options Identification with Application to UAV Systems
Name
Mikaelian_draft_IEEESMC.pdf
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1.12 MB
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Author(s)
Mikaelian, Tsoline
Rhodes, Donna H.
Nightingale, Deborah J.
Hastings, Daniel E.
Date Issued
January 2011
Journal
IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans
Publisher
Institute of Electrical and Electronics Engineers
Citation
Mikaelian, Tsoline et al. “A Logical Approach to Real Options Identification With Application to UAV Systems.” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 42.1 (2012): 32–47. Web.
Version
Author's final manuscript
Abstract
Complex systems are subject to uncertainties that may lead to suboptimal performance or even catastrophic failure if unmanaged. Uncertainties may be managed through real options that provide a decision maker with the right, but not the obligation, to exercise actions in the future. While real options analysis has traditionally been used to quantify the value of such flexibility, this paper is motivated by the need for a structured approach to identify where real options are or can be embedded for uncertainty management. We introduce a logical model-based approach to identification of real option mechanisms and types, where the mechanism is the enabler of the option, while the type refers to the flexibility provided by the option. First, we extend the classical design structure matrix and the more general multiple-domain matrix (MDM), commonly used in modeling and analyzing interdependencies in complex socio-technical systems, to the more expressive Logical-MDM that supports the representation of flexibility. Second, we show that, in addition to flexibility, two new properties, namely, optionability and realizability, are relevant to the identification of real options. We use the Logical-MDM to estimate flexibility, optionability, and realizability metrics. Finally, we introduce the Real Options Identification (ROI) method based on these metrics, where the identified options are valued using standard real options valuation methods to support decision making under uncertainty. The expressivity of the logic combined with the structure of the dependency model allows the effective representation and identification of mechanisms and types of real options across multiple domains and lifecycle phases of a system. We demonstrate this approach through a series of unmanned air vehicle scenarios.
MIT Department
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Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
MIT Sociotechnical Systems Research Center
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1109/tsmca.2011.2157133
