The contractor's final report is available HERE.
The objective of this research was to evaluate and illustrate by means of examples a “mock” transportation capital budgeting exercise using (a) Data Envelopment Analysis (DEA); (b) Fair Division Analysis (FDA); and (c) Conjoint Analysis (CA). The product of the research will be a white paper showing the potential applications of these methods.
There are several ways to approach the difficult problem of capital budgeting of scarce transportation funds in a State DOT environment. It is recognized that combining several methods (e.g., by using an ensemble method in forecasting) it is possible to produce more defensible allocations and tradeoffs considering multiple, and sometimes competing, issues such as economic efficiency, fairness, and public, project, and modal preferences. When multiple modes of transportation projects/activities are being considered for selection, the objective beneficial characteristics of each must be explicitly considered. The usual quantitative approach is to produce an overall score for each candidate project/activity, much like the Consumer Price Index, combining weighted criteria and project/activity evaluations on each criterion. However, while this may appear “scientific”, the relative importance weightings of the criteria are subjective and often not reproducible, bringing into question the validity and transparency of the final project priority rankings.
Some methods that have been used by practitioners, statisticians, and economists include (a) Data Envelopment Analysis; (b) Fair Division Analysis; and (c) Conjoint analysis. Each of these approaches considers and models preferences, benefits, and costs in different ways. There is an increasing need to investigate and illustratively evaluate existing and new/alternate approaches to produce reasoned, defensible, and valid ways to allocate scarce funds to the most beneficial transportation projects/activities that have the highest public support and produce the most economic benefits.