Decision Support for IT Investment Projects - A Real Option Analysis Approach Based on Relaxed Assumptions

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Reference

Müller, M. P., Stöckl, S., Zimmermann, S., & Heinrich, B. (2016). Decision Support for IT Investment Projects - A Real Option Analysis Approach Based on Relaxed Assumptions. Business & Information Systems Engineering (BISE), 58(6), 381-396. (ABDC_2022: A; ABS_2021: 2; VHB_3: B)

Publication type

Article in Scientific Journal

Abstract

Managerial flexibilities have to be taken into account in ex-ante decision making on IT investment projects (ITIPs). In many papers of the IS literature, standard financial option pricing models are used to value such managerial flexibilities. Based on a review of the related literature, we critically discuss the assumptions of the most frequently used financial option pricing model, namely the Black-Scholes model, arguing for relaxed assumptions that better represent the characteristics of ITIPs. We find that existing real option analysis approaches featured in the IS, Finance, and Economics literature are unable to consider more than two of our relaxed assumptions. Consequently, we present our own approach in form of a simulation model for the valuation of real options in ITIPs which offers a better representation of the characteristics of ITIPs by taking the discounted cash-flows and the runtime to be uncertain as well as the market to be incomplete. Based on these modifications of the Black-Scholes models' assumptions, we find that the resulting option value contains idiosyncratic risk that has to be taken into account in ITIP decision making. For the realistic case of risk averse decision makers, the consideration of idiosyncratic risk usually leads to a lower risk-adjusted option value, compared to one calculated by means of the Black-Scholes model. This confirms the perception of managers who feel that financial option pricing models frequently overvalue ITIPs and hence may induce flawed investment decisions.

Persons

Organizational Units

  • Chair in Finance
  • Institute for Finance

DOI

http://dx.doi.org/10.1007/s12599-016-0423-7