Developing a new and innovative transportation system requires a comprehensive investment strategy that ascertains the optimal time to invest in the project considering market conditions. Underground freight transportation (UFT) systems offer a sustainable and modernized use of underground space to transport freights and mitigate the challenges associated with this growing need. Revenue from freight shipment is one of the most key variables affecting investment decisions in freight transportation systems, such as UFT systems. However, the freight rate is not a fixed variable and fluctuates over time. Real options (RO) analysis is an analytical approach to evaluate investment projects under uncertainties. While conventional RO models assume a random stochastic behavior (geometric Brownian motion) for the underlying variable, freight rate follows a mean-reverting process. Thus, using a regular RO model could lead to a flawed decision making derived from unrealistic evaluations. This study presents a calibrated RO model that characterizes the stochastic behavior of the UFT revenues more accurately. An optimization approach is adopted to provide an optimal investment schedule for developing UFT systems. A numerical case example is used to demonstrate the implementation of the proposed RO model. Results are compared with the evaluations obtained from a conventional RO model to show the significance of the appropriate calibration. While the conventional RO model results in an overestimation/underestimation of the project, the proposed RO model offers a more pragmatic evaluation of the investment options. The proposed RO model provides transportation decision makers with a more realistic perspective for evaluating UFT development projects.
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