transportation research and development, program evaluation, real options, Monte Carlo Simulation
The purpose of this study was to research, develop, and test various methodologies, approaches, equations and guidelines that could be applied to proposed, existing and completed research projects to provide some measure of the benefit and return on research expenditures.
The approach to the study was to do the following:
- Gain an understanding of the kinds of projects traditionally sponsored by the FOOT Research Center;
- Investigate what work had already been accomplished in the field of quantification of research benefits;
- Determine certain kinds of research best measured by different measurement approaches;
- Gather data on completed projects to test various methods;
- Recommend to the FOOT research department an approach for quantifying the benefits of their research program;
This report begins with the premise that no universal measurement method could be applied to value the economic impact of transportation research and development (TR&D). Accordingly, an alternative TR&D project classification methodology to better match research activity with evaluation methodologies is proposed. Using this alternative classification, an extension of Option Pricing Theory to valuing the economic impact of TR&D and research evaluation is developed. The conditions of limited data availability, commonly found in transportation research agencies, are partially resolved through Monte Carlo simulation. The findings indicate how the Real Option Approach, combined with Monte Carlo simulation1 can be adopted to better capture the elements of risk and uncertainty to provide a more accurate economic evaluation of research projects.
Citation / Publisher Attribution
Valuing the Benefits of Transportation Research: A Matrix Approach, Center for Urban Transportation Research, University of South Florida, 97 p.
Scholar Commons Citation
Concas, Sisinnio; Reich, Stephen L.; and Yelds, Ashley T., "Valuing the Benefits of Transportation Research: A Matrix Approach" (2002). CUTR Research Reports. 135.