Paper Type
Completed Research Paper
Abstract
Over the last ten years Real Options Analysis (ROA) has become an increasingly important topic in both academia and industry. In industry ROA is now one of the suggested ways to evaluate Information Systems/Information Technology (IS/IT) projects using common governance frameworks. In academia, there have been numerous papers within top MIS journals discussing the issues involved when applying ROA to IS/IT. Most of the work has focused either on the Binomial option model or on the Black-Scholes option model, both of which have been used successfully to evaluate single projects. A more complex case that has been discussed in the literature is the use of ROA to evaluate multiple sequential IS/IT projects, i.e. where Project A enables Project B which in turn enables Project C. This paper uses Monte Carlo techniques to illustrate the pitfall known as “The Flaw of Averages” when using the Binomial or Black-Scholes to evaluate such programs.
Recommended Citation
Burke, John C. and OConnor, Scott F., "Valuing Sequential IT Projects Using Real Options Analysis" (2013). AMCIS 2013 Proceedings. 2.
https://aisel.aisnet.org/amcis2013/SystemsAnalysis/GeneralPresentations/2
Valuing Sequential IT Projects Using Real Options Analysis
Over the last ten years Real Options Analysis (ROA) has become an increasingly important topic in both academia and industry. In industry ROA is now one of the suggested ways to evaluate Information Systems/Information Technology (IS/IT) projects using common governance frameworks. In academia, there have been numerous papers within top MIS journals discussing the issues involved when applying ROA to IS/IT. Most of the work has focused either on the Binomial option model or on the Black-Scholes option model, both of which have been used successfully to evaluate single projects. A more complex case that has been discussed in the literature is the use of ROA to evaluate multiple sequential IS/IT projects, i.e. where Project A enables Project B which in turn enables Project C. This paper uses Monte Carlo techniques to illustrate the pitfall known as “The Flaw of Averages” when using the Binomial or Black-Scholes to evaluate such programs.