An Options Approach to the Project Activation Decision in the Aerospace Industry

This paper develops a Bayesian real options model to determine the optimal amount of sampling information to acquire before project activation. The approach is then applied to evaluate parts manufacturing approval (PMA) licenses for an aerospace firm in the maintenance, repair, and overhaul industry. The model explicitly accounts for project and sampling uncertainty, estimated cash inflows, capital outlays, and sampling costs. Upper and lower thresholds for delay option inputs are identified for immediate project activation and indefinite delay scenarios. In general, it is shown that high sampling costs encourage and low sampling costs postpone project activation, the magnitude of which dependent upon sampling reliability, project uncertainty, and moneyness of the delay option.