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Christopher Koliba Asim Zia Matthew Tucker David Novak University of Vermont

Christopher Koliba Asim Zia Matthew Tucker David Novak University of Vermont Presented during the American Political Science Association Annual Conference September 1, 2011 Seattle, WA.

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Christopher Koliba Asim Zia Matthew Tucker David Novak University of Vermont

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  1. Christopher Koliba Asim Zia Matthew Tucker David Novak University of Vermont Presented during the American Political Science Association Annual Conference September 1, 2011 Seattle, WA Fostering Innovation in an Intergovernmental Transportation Planning Network: results from a mixed- methods case study

  2. This study focuses on how one state uses a MCA process to prioritize projects, aligning more closely with those studies that examine real time scoring data. Employing a comprehensive case study approach combining qualitative analysis, regression analysis and gini-coefficient analysis we pose the following research question: How and to what extent has the utilization of a new multi- criteria analysis process lead to the derivation of innovative project prioritization patterns?

  3. Innovation within a system dynamics context Innovative outcomes: 1.) added transparency to the process; 2.): Reinforcement of system preservation; 3.) More equitable project distribution; 4.) More sensitivity to additional factors Innovative processes: Multi stakeholder use of the MCA tool. Innovative outputs: Project prioritization and implementation patterns Evaluation of tool and modification using multiple data sources and simulations Innovative inputs: Multi-Criteria Analysis (MCA)

  4. Figure 1. Intergovernmental Transportation Prioritization Network US DOT Congress Formula funding programs Grant funding programs (b) (b) Each town in the metropolitan area is represented on the MPO governing board and technical advisory committee (TAC), and votes on the prioritization of regional projects (a). Regional prioritization accounts for 20% of the statewide prioritization. Federal formula or competitive funding programs provide approximately 80% of funding for most projects (b). The State DOT planning department assimilates the regional prioritization ranking into its own assessments of projects, which accounts for 80% of the statewide ranking (c). The State DOT engineering operations department implements (builds/contracts to build) prioritized roadway, bridge, bike/pedestrian, traffic operations and pavement projects (d). State Leg. State DOT Engineering (c) Planning (d) (a) MPO RPO RPO RPO RPO Cities and Towns (in MPO region) New Roadways, Bridges, Bike/Ped, Traffic Ops., Pavement Projects

  5. Desired Outcomes of Multi-Criteria Analysis Tool by Stakeholder Interests: • All: To bring about greater transparency to the prioritization process; Limit the role of “politics” in the process. • USDOT & SDOT: To preserve the existing system. • MPO and Congressional Staff: To allow for additional criteria (eco. dev., environment, climate change). • Local Governments & State Representatives: To bring about greater equity in the system.

  6. Were Desired Outcomes of Stakeholder Interests met?: • All: To bring about greater transparency to the prioritization process; Limit the role of “politics” in the process. • USDOT & SDOT: To preserve the existing system. • MPO and Congressional Staff: To allow for additional criteria (eco. dev., environment, climate change) • Local Governments & State Representatives: To bring about greater equity in the system

  7. Were Desired Outcomes of Stakeholder Interests met?: • All: To bring about greater transparency to the prioritization process; Limit the role of “politics” in the process. Yes, but… • USDOT & SDOT: To preserve the existing system. • MPO and Congressional Staff: To allow for additional criteria (eco. dev., environment, climate change) • Local Governments & State Representatives: To bring about greater equity in the system

  8. Were Desired Outcomes of Stakeholder Interests met?: • All: To bring about greater transparency to the prioritization process; Limit the role of “politics” in the process. Yes, but… • USDOT & SDOT: To preserve the existing system. Yes… • MPO and Congressional Staff: To allow for additional criteria (eco. dev., environment, climate change). • Local Governments & State Representatives: To bring about greater equity in the system

  9. Were Desired Outcomes of Stakeholder Interests met?: • All: To bring about greater transparency to the prioritization process; Limit the role of “politics” in the process. Yes, but… • USDOT & SDOT: To preserve the existing system. Yes… • MPO and Congressional Staff: To allow for additional criteria (eco. dev., environment, climate change). No… not yet??? • Local Governments & State Representatives: To bring about greater equity in the system.

  10. Were Desired Outcomes of Stakeholder Interests met?: • All: To bring about greater transparency to the prioritization process; Limit the role of “politics” in the process. Yes, but… • USDOT & SDOT: To preserve the existing system. Yes… • MPO and Congressional Staff: To allow for additional criteria (eco. dev., environment, climate change). No… not yet??? • Local Governments & State Representatives: To bring about greater equity in the system. No… although the threshold of “inequity” is unclear.

  11. Innovation within a system dynamics context Innovative outcomes: 1.) added transparency to the process; 2.): Reinforcement of system preservation; 3.) More equitable project distribution; 4.) More sensitivity to additional factors Innovative processes: Multi stakeholder use of the MCA tool. Innovative outputs: Project prioritization and implementation patterns Evaluation of tool and modification using multiple data sources and simulations Innovative inputs: Multi-Criteria Analysis (MCA)

  12. Innovation within a system dynamics context Innovative processes: Multi stakeholder use of the MCA tool. Innovative outcomes: 1.) added transparency to the process; 2.): Reinforcement of system preservation; 3.) More equitable project distribution; 4.) More sensitivity to additional factors Innovative inputs: Multi-Criteria Analysis (MCA) Innovative outputs: Project prioritization and implementation patterns Evaluation of tool and modification using multiple data sources and simulations

  13. Using computational models for decision support

  14. STATE CHART FOR PROJECT PRIORITIZATION IN MPO REGION (Zia et al., under review) Congress FHWA & USDOT j MPO TAC i d c b MPO Staff MPO Board a SDOT a e f a g h a Legislative Committees Local communities

  15. Thank you • Contact information: Christopher Koliba, Ph.D. Associate Professor, Community Development & Applied Economics University of Vermont 103 Morrill Hall Burlington, Vermont 05405 802-656-3772; ckoliba@uvm.edu

  16. FIGURE 1. A hierarchical network with structure on many scales, and the corresponding hierarchical random graph.From the following article:Hierarchical structure and the prediction of missing links in networksAaron Clauset, Cristopher Moore & M. E. J. NewmanNature 453, 98-101(1 May 2008)doi:10.1038/nature06830

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