Interval-Valued Credibilistic Real Options Modeling Under Optimism-Pessimism Level

Abstract

Fuzzy real options analysis has advanced greatly during the last decade, specifically, through the development of so-called fuzzy pay-off techniques. The practicality and intuitiveness of these methods allow their straightforward integration into any spreadsheet or other evaluation systems for easy applications of real options thinking to real investments and strategies in industry and to public policy. Real options valuation models are capable to reflect the value of flexibility, i.e., the inherent optional possible actions, which managers can take during the investment period or in public policy settings. Traditional NPV methods cannot value such optionalities. Fuzzy modeling is shown to account for high uncertainty and imprecision under which an expert evaluation is conducted. This paper generalizes the credibilistic pay-off method for real options valuation using interval-valued fuzzy numbers, IVFNs, by means of $m_{\lambda }$-measure for the optimism–pessimism level of an expert analyst. The $m_{\lambda }$-measure is defined using necessity and possibility measures to correspond to the optimism–pessimism level. Real options values, ROVs, will be obtained using the λ-parameter and fuzzy numbers. Similarly, ROVs are obtained using IVFNs. This paper introduces a novel credibilistic real options model, which is based on the optimism–pessimism measure and IVFNs. The model outcomes are compared to the original credibilistic real options model through a numerical case example in a merger and acquisition context.