Transportation investment projects rely on accurate predictions of benefits and costs as fundamental data to determine the feasibility of the project. These predictions also serve as important information to evaluate the investment's effectiveness and the level of fees. However, the predicted values of benefits and costs have become increasingly uncertain due to various factors, such as changes in population demographics, the emergence of new transportation modes, and changes in travel behavior. Despite this growing uncertainty, the current feasibility evaluation methods fail to reflect this uncertainty in predicted benefits and costs.

The purpose of this study is to empirically analyze the uncertainty of predicted traffic volume, costs, and benefits in the preliminary feasibility study of Korean roads, and to propose the need for a new economic feasibility evaluation method that can explore various alternatives for proceeding with the project in the face of such uncertainty, not only for determining whether or not to proceed with the project.

The uncertainty of future predicted traffic volume was characterized using a Geometric Brownian Motion (GBM) model composed of the growth rate( ) and volatility() of traffic volume changes for road projects that underwent preliminary feasibility studies. For the uncertainty of predicted traffic volume during the first year after the project's opening, a Gaussian mixture model probability distribution was considered. The uncertainty of cost predictions was characterized using a Frechet probability distribution, and the uncertainty of benefit predictions was characterized using a regression model using traffic volume and total project costs.

An analysis of the uncertainty of the economic feasibility results in preliminary feasibility studies of road projects revealed that the probability of predicted benefits presented in the preliminary feasibility report being larger than the benefits predicted through simulations was only 0.195, indicating that the benefits presented in the report were likely to be overestimated. In terms of costs, the probability of predicted costs through simulations being higher than the predicted costs presented in the preliminary feasibility report was as high as 0.588.

In summary, the economic feasibility results presented in the preliminary feasibility study were found to be vulnerable to the uncertainty of benefit realization and the possibility of cost increases, indicating that they are not robust. Although the BCR 1.0, which is the feasibility evaluation index for the target project, was provided in the preliminary feasibility study, the simulation analysis showed that the probability of the BCR being equal to or greater than 1 was only 0.048. In particular, the median and mean of the target project's BCR analyzed through simulation were 0.632 and 0.627, respectively.

Therefore, it is deemed necessary to introduce a bottom-up approach to economic feasibility analysis that can identify the factors that influence the economic feasibility results under the uncertainty of traffic volume, cost, and benefit predictions, in addition to the traditional economic feasibility analysis method that uses specific predicted values for traffic volume, cost, and benefit. This bottom-up approach can propose alternative business plans to achieve the investment goal set by the transportation project and assess the probability of achieving the goal with the current business plan, as well as suggest alternative business plans that can secure the investment goal set by the transportation project.

The introduction of a bottom-up approach to economic feasibility analysis proposed in this study is expected to enhance the primary function of feasibility analysis, which emphasizes efficient investment in the future. Through the introduction of the bottom-up approach, it is expected that project plans and contents can be prepared in advance to respond to the risks and negative effects that the investment may bring. In addition, it is anticipated that preparing alternatives for the risks and negative effects of the project in advance can also serve as a means to encourage the opinions and participation of not only feasibility analysis experts, but also the general public.

Publisher's Note
Summary

Chapter 1: Introduction
　Section 1: Background and Objectives of the Study
　Section 2: Scope of the Research
　Section 3: Content and Methodology of the Study

Chapter 2: Uncertainties in Feasibility Assessment
　Section 1: Uncertainties in Traffic Volume and Benefit Prediction
　Section 2: Uncertainties in Cost Prediction
　Section 3: Approaches to Consider Uncertainties in Feasibility Assessment

Chapter 3: Characterizing Uncertainty in Feasibility Assessment Results
　Section 1: Uncertainty in Traffic Volume Prediction
　Section 2: Uncertainty in Cost Prediction
　Section 3: Uncertainty in Benefit Prediction

Chapter 4: Analysis of Uncertainty in Feasibility Assessment Results
　Section 1: Target Project
　Section 2: Analysis Procedure
　Section 3: Estimation of Traffic Volume, Cost, and Benefit for the Target Project

Chapter 5: Incremental Feasibility Assessment

Chapter 6: Conclusion and Significance

References