Prioritization of Freight Investment Projects (2019)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

35 A P P E N D I X A Matrix of Factors Discussed in Freight Prioritization by Information Source

Potential Factors Literature Review Survey Case Examples Assets owned State-owned assets that are involved in freight movement, including roads, rail lines, ships and seaports, aviation, and intermodal connectivity facilities Forty-one respondents from the survey answered a question on freight asset ownership. Findings indicate that an average of 35% of freight assets are owned by states, including the asset categories of airports, seaports, rail, and inland ports. The private sector retains the largest share of freight assets related to rail, inland ports, and intermodal freight facilities, averaging approximately 87% ownership of these asset categories. Local authorities, public–private partnerships, and long-term lease concessions predominantly own airports, seaports, and inland ports, averaging 71% ownership stakes on these freight asset categories. Type of assets owned were not discussed during the case examples. Freight planning and investment funding mechanisms with freight prioritization processes One question asked if sources and mixes of funds affect project prioritization, and 66% of respondents indicated that this was not the case. Respondents who affirmed that this was the case (34%) also provided examples of how federal sources have different project requirements that affect prioritization (i.e., surface transportation funds cannot be used for many water-based port projects).

Thirty-nine respondents answered questions on methods for general freight project prioritization. The highest marks for critical importance of method used went to “performance measures analysis” at 62%, “project readiness scores” at 62%, and “data- driven current and future freight deficiency analysis” at 54%. Of little importance was “elected official inputs,” receiving the largest score for “not important at all” at 33%. Forty respondents answered questions on methods and processes used to prioritize freight projects in comparison to other modes. Among the highest selections, 43% selected “benefit-cost analyses for highway only” as a preferred process for selection of freight projects and 48% selected “use of other economic factors or state plans,” with many indicating in comments that they developed distinct freight plans with connections to asset condition and safety projects. Innovative policies, strategies, and practices to develop freight planning expertise within agencies On the question of methods to improve freight project prioritization processes, one selection was marked “internal freight planning training and resources.” On this selection, 51% of 39 respondents indicated that this was somewhat important, 34% indicated that it was critical, and 16% indicated that it was not important at all.

As a barrier to effective freight project prioritization, 24% thought that lack of staff resources is a somewhat significant barrier, 16% thought that it is a very significant barrier, and 59% thought that it was not a significant barrier at all. Project evaluation— research for the development and implementation of performance measures to evaluate effectiveness, efficiencies, and performance Of 40 respondents to a question on the importance of freight data in freight project prioritization and evaluation, 63% agreed that it was necessary to improve freight project prioritization processes; and 45% thought that it would help to develop a broader multimodal project selection framework. Development and implementation of performance measures are associated closely with performance measure analysis as a method; 62% of respondents indicated that it is of critical importance to freight project prioritization methods. Potential Factors Literature Review Survey Case Examples Economic impact analysis Economic impact analyses were a part of a few prioritization methodologies. Of 40 respondents to a question on the importance of freight data in freight project prioritization and evaluation, 55% believed that it will help to improve the understanding of the link between transportation and economic development. As a goal within the state agency, economic impacts were generally ranked lower, at the fifth rank, compared with safety and infrastructure condition. States need to have more data pertaining to economic impact to understand the effect of freight at the local level. They also wished to have more standardized data to help make better comparisons among other local areas.

Agency organization While many agencies reported that they have the flexibility and independence to implement new freight project prioritization methods and strategies (66%), they also indicated that they sometimes do not have the necessary information to effectively measure performance and prioritize freight projects (42%–58%) and are sometimes reliant on external stakeholders to provide this information (49%). Decision-making level Yes Responding agencies (54%) reported that they have a freight program lead with an open invitation to provide direct input to the agency executive committee to advocate for freight and champion efforts to improve freight project prioritization efforts. Thirteen 33% reported that this is sometimes the case. Institutional barriers Lack of funding, staffing/organizational capacity, lack of policymaker support, right-of-way constraints, neighborhood opposition, business/receiver opposition, opposition by truckers/delivery persons, lack of interagency coordination, lack of data or data processing ability, environmental concerns As a factor in freight project prioritization, 46% of respondents indicated that institutional barriers are somewhat important, 41% indicated that they are critical, and 3% indicated that they are not important at all. The remaining 10% indicated that they did not know. Lack of funding. percent indicated that this is not the case, and

Urban land use Projects were already dedicated to long-haul freight use. As a factor in freight project prioritization, 68% of respondents indicated that urban land use is somewhat important, 24% indicated that it is critical, 5% indicated that it is not important at all, and 3% indicated that they don’t know. States wish to have better data at the local level. Right now they depend on information from the local level to understand urban land use. They want more standardized data to help make comparisons better. New technologies Regarding the ranking of goals in agencies, one respondent indicated that technology deployment was ranked fourth out of seven possible selections. Political influence Political barriers; multistate or multinational corridors may have projects with competing interests; ensuring stakeholders keep in mind As a factor in freight project prioritization, 54% of respondents indicated that political influence is somewhat important, 15% indicated that it is critical, 18% indicated that Agencies try to develop stakeholder groups that represent the interest of many different people. Potential Factors Literature Review Survey Case Examples the good of all the corridors; setting goals for the corridor and not the individual stakeholder it is not important at all, and 13% indicated that they don’t know. First- and last-mile experiences and influences Right now, states rely on information at the local level to understand first- and last-mile experiences and influences. They want more standardized data to make better comparisons.

Partnerships in the decision-making process As a method, cooperative and coordinated freight partnerships were rated as somewhat important by 59% of respondents, with 23% finding them critical, and 18% finding them not important at all. As a resource barrier, lack of coordinated scheduling of cost and benefit assessments across freight stakeholders was rated as not significant at all by 33% of respondents, somewhat significant by 39%, and very significant by 28%. Metropolitan planning organizations (MPOs) Regarding the importance of methods, 49% of respondents felt it was critical to develop a freight section in statewide and local MPO long-range planning documents; 46% found it somewhat important; and 5% found it not significant at all. Regarding barriers to freight planning processes, 38% of respondents felt that gathering the MPO and regional state DOT district needs assessments was not a barrier to stakeholder input into the freight planning process, while 18% found it was a significant barrier, and MPOs are part of the stakeholder groups. 44% found it was a somewhat significant barrier.

Private industry On the question of barriers to freight planning processes, 53% of respondents felt that gathering the needs assessment inputs from the private sector was a somewhat significant barrier to the freight planning process, while 21% found that it was a significant barrier, and 26% found it was not a significant barrier. Private industry does not play much of a role in the decision-making process but is represented by members on the technical advisory committees and freight advisory committees. Motivation of prioritization To comply with the FAST Act and Map-21 to receive additional funding States did not change their prioritization process because of the FAST Act and MAP-21, stating that freight projects have always been a priority. The only state that did something different was Minnesota, which conducted a formal freight prioritization process with a call for projects because of the FAST Act. Many states began to highlight their Potential Factors Literature Review Survey Case Examples Act. process as part of the FAST

Qualitative vs. quantitative balance There is a nice mix of qualitative vs. quantitative strategies, and many of the prioritization methodologies include both. The prioritization process includes a mix of qualitative and quantitative factors. Most processes begin with quantitative factors, and then, with stakeholder input, qualitative factors are applied. Decision factor weighting (how are scoring criteria decided) Economic competitiveness, safety and security, system performance, environmental stewardship, infrastructure preservation or maintenance, congestion relief, livable communities, increased connectivity, coordination, and technology Survey respondents indicated, from 1 to 7 (1 being the highest and 7 being the lowest), how agencies ranked common topic areas related to freight based on agency goals. Weighting is applied based on how these ranks percolate down to the freight project selection process. Rankings are (1) safety; (2) infrastructure condition; (3) optimized system efficiency; (4) reduced congestion; (5) economic vitality; (6) environmental sustainability; and (7) other, which included project readiness, connectivity, modal diversity, accessibility, and consistency with long-range plans. Truck volume, safety, mobility, facility access, cost-effectiveness, and project readiness. Final scoring criteria were based on input from stakeholder groups. Multimodal framework Many methods have multimodal frameworks (see assets owned). Fifty-three percent of respondents indicated that their states prioritize freight projects using a multimodal framework, 45% indicated that they do not, and 2% indicated that they did not know. Because respondents provided numerous notes on their multimodal framework approach, additional information is posted in the worksheet titled “Multimodal Framework Notes.”

Data sources and gaps According to survey respondents, private data sources with types of data that include commodities (63%), capital investment (45%), operations (25%), and capacity (33%) are in greater use. Federal data sources are in greater use for commodities (63%), capacity (53%), environment (25%), and safety (35%). State data resources are in greater use in maintenance (85%), safety (85%), finance (60%), and environment (50%). Local data resources are in greater use in land use data (53%), environment (20%), and finance (15%). More standardized data would help the process attain a more level playing field. It is hard to compare local data with each other without a standardized mechanism. Private data States indicated the need for private data, especially in terms of economic data, to better understand freight patterns and needs at the local level. By knowing this information, states will be able to use their funds more efficiently by prioritizing funding where there is need. Potential Factors Literature Review Survey Case Examples