Railways Projects Appraisal Using Reference Class Forecasting and Fuzzy Sets Theory

Abstract

The importance of this study is driven by the significant role the investment in railway projects plays in the national economy. The economic stability of many countries depends on the short and long term benefits of these projects. Decision makers often face difficulties in assessing the economic feasibility of infrastructure projects, given the number of risks and uncertainties associated with investing in these projects. Therefore, this study aimed to develop a methodology to address uncertainties related to quantitative and qualitative risks associated with costs and revenues estimations for railway projects.
To achieve this goal, a new mathematical model has been developed using Reference Class Forecasting method and Fuzzy Sets theory to improve costs and revenues estimations for railway projects. The applicability of the proposed model is illustrated using the feasibility study of the development of Aleppo-Damascus railway project, conducting sensitivity analyses and analysing associated results. The study concluded the possibility of using the proposed model as a tool to support the decision of sponsors and decision makers when selecting the economically viable investment option. The proposed model is easy to use in the field of uncertain decision-making, as it can be used as a tool for analysing the sensitivity of the economic feasibility of the project options under study.
The proposed methodology assumes: the availability of RCF data with high statistical quality; the performance of the project under study is similar to the projects used to inform Reference Class Forecasting data; excluding the inflation as one of causes for the increase in costs and revenues of railway projects.