Quantitative Approaches for Project Prioritization: Case Study in Puget Sound, Washington

• Published in: Transportation research record Vol. 2303; no. 1; pp. 108 - 116
• Main Authors: Outwater, Maren L., Adler, Thomas, Dumont, Jeffrey, Kitchen, Matthew, Bassok, Alon
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2012
• Subjects: Economics; Estimates; Highways; Mathematical models; Regional; Sound; Transportation; Weighting; INE, USA, Washington, Puget Sound
• ISSN: 0361-1981; 2169-4052
• DOI: 10.3141/2303-12

Transportation projects in major metropolitan regions can vary widely in the types of benefits that they provide and in the scales of those benefits. Travel forecasting models and related procedures can provide reasonable estimates of those benefits, and many benefits can be distilled into equivalent monetary benefits by the use of consumer surplus or other valuation approaches. In theory, those methods could also be used to prioritize projects for funding consideration. However, an approach that simply chooses projects that provide the greatest net economic benefits may not result in a mix of projects that most effectively accomplishes broad regional goals. This paper describes an approach to project prioritization that was developed to support stakeholder-based weighting of multiple goals and, for each goal, multiple measures. The approach uses the analytic hierarchy approach to develop weights for each goal and a conjoint-based method to estimate stakeholder weights for each measure. The approach was applied as part of Washington State's Puget Sound Regional Council's Transportation 2040 process and achieved the goals in VISION 2040, the long-range land use plan. Weighting exercises were conducted with two stakeholder groups, and the results were applied to a set of proposed ferry, rail, highway, and local road projects. This paper describes the details of this case study and provides observations and conclusions from the work. The principal findings of the experiments were that statistically robust modeling conducted in real time during planning committee meetings can improve the transparency, equity, and collaboration of the project prioritization process.