Deeney, Peter ORCID: 0000-0002-8112-8692, Cummins, Mark ORCID: 0000-0002-3539-8843, Heintz, Katharina and Pryce, Mary ORCID: 0000-0003-2270-2452 (2020) A real options based decision support tool for R&D investment: application to CO2 recycling technology. European Journal of Operational Research, 289 (2). pp. 696-711. ISSN 0377-2217
Abstract
We propose a practice relevant real options based decision support tool to aid in the practical
evaluation of R&D investments in technology. Using a Poisson process to simulate the discrete
progress typical of advancements in R&D, we take explicit account of the technical risk of the
technology development, while market risk exposure and the effect of learning-by-doing through
operating the technology is also explicitly modelled. We present a compound real option design,
where a European real option structure is used to model the fixed length term typical of early
phase research, which is exercisable into an American real option structure to model a subsequent
phase R&D. In this latter phase, a successful outcome is acted upon immediately to operationalise
the technology. We propose a simulation approach, which models R&D progress in a stylised
logistic function or ’S-shape’ form, capturing the typically slow rate of R&D progress at the start
of the early phase, through to more rapid improvement as the R&D advances, which then slows
again as the limitations of the R&D are approached. We propose a business appropriate and
workable economic meaning to this progress in the R&D process. We demonstrate the decision
support tool with an application to evaluating the R&D investment potential in CO2 recycling
technology, where an energy commodity is produced.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | Decision analysis; OR in research and development; Real options; Compound option structure; CO2; recycling technology |
Subjects: | UNSPECIFIED |
DCU Faculties and Centres: | DCU Faculties and Schools > DCU Business School DCU Faculties and Schools > Faculty of Science and Health > School of Chemical Sciences |
Publisher: | Elsevier |
Official URL: | https://doi.org/10.1016/j.ejor.2020.07.015 |
Copyright Information: | © 2020 Elsevier. (CC BY-NC-ND 4.0) |
ID Code: | 26770 |
Deposited On: | 15 Mar 2022 14:21 by Thomas Murtagh . Last Modified 14 Feb 2023 16:54 |
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