A fuzzy linguistic ontology payoff method for aerospace real options valuation

► Captured domain knowledge of aerospace repairable parts utilizing the Protégé editor. ► Fuzzy linguistic ontology payoff method (FLOPM) developed. ► Present aerospace FLOPM business case scenario example. ► A combination of fuzzy linguistics and fuzzy numbers used as a decision-making aid. ► Determined real options for aerospace licensing projects. In this paper, we present a fuzzy linguistic ontology payoff method for the valuation of real options in the aerospace industry. Using real data, we apply the fuzzy linguistic approach to determine the credibility measures and the credibilistic expected value for the fuzzy real options valuation payoff method. This approach is used to obtain a multi-scenario modeling process by envisioning three scenarios: optimistic, most likely, and pessimistic. In addition, our experience with the scenario estimates is premised on results in an operating profit forecast. This forecast corresponds to a plausible outcome within the aerospace licensing maintenance, repair, and overhaul market and provides a decision-making tool. This tool can be utilized for determining real options for project valuation of aerospace licensing revenues based on unit costs, recurring costs, and quantity of units sold.