Multimodal Investment Analysis: Phase 1

PART I: APPENDIX

A. SURVEY: QUESTIONS, SAMPLE

A survey was sent to each state transportation department to assess how their planning programs have been adjusted to reflect the new direction set by ISTEA. A four-page questionnaire was sent to the planning director in each of the 50 states. The objectives of the questionnaire were to: 1. identify states' multimodal perspectives and barriers encountered in developing multimodal plans; 2. determine resources and skills needed for multimodal planning; and 3. identify preferences for future ISTEA-type legislation. Forty-six states returned the surveys in complete or partially usable form.

B. RESULTS

States' Responses

Following passage of ISTEA, 96 percent of the states responding had produced new or updated transportation plans by the end of 1996. When asked about their progress in developing the transportation management and monitoring systems, the state planners indicated that the intermodal transportation management system was tied with public transportation for last place; 52 percent of the states reported that system as complete or in-process. Seventeen states (37 percent) indicated no plans to complete this management system. ISTEA may have increased the attention given to transportation involving more than one mode but, as Table 1 shows, systems for the more traditional topics like managing pavement and monitoring highway traffic drew more than twice the attention of intermodal transportation. (Graphs corresponding to the tabulated data appear at the end of this Appendix.)

The states were next divided into two groups by geographic area (e.g., largest 25 states in square miles vs. smallest 25), by population, by population density (people per square mile), and by percent urban population. For each grouped comparison, the number of positive responses in the first group were compared with the number of positive responses in the second, and chi-square values calculated, to test the null hypothesis: "The progress toward completing a particular Transportation Management System does not vary by group (when states are grouped by area, population, density or urban concentration)." Table 1 lists the chi-square values and critical values of chi-square for differences significant at the .05 and .10 levels. There was no indication that states' efforts for their Transportation Management Systems varied by size of state, population, density or urban portion.

Table 1

Transportation Management Systems, Completed or In-process

Percent of states (n = 46)

Chi-square (df = 3)

Pavement of Federal aid highways

100

.52

Bridges

98

.45

Highway safety

85

.49

Traffic congestion

83

.71

Public transportation

64

2.34

Intermodal transportation

63

1.48

Traffic monitoring for highways

91

.19

Chi-square critical values: .05 = 7.815; .10 = 6.251.

 

Specific modes or transportation system combinations

Another indication of the attention given to intermodal transportation was furnished by responses to a question of which modes or systems were addressed by the states' new or updated plans. Responses for passenger and freight transportation were separately accumulated and ranked in Tables 2 and 3. As might be expected, passenger travel by automobile received specific mention by nearly all states, but bicycle and pedestrian travel were a close second. The attention given the bicycle and pedestrian modes may reflect interest in an inexpensive way for states to not let others outrank them in environmental conscientiousness. The three intermodal combinations--bus-rail, bus-air, and air-rail--were included in 59 percent, 52 percent and 45 percent, respectively, of state plans. Passenger transportation by water was included by only 16 states (36 percent) in their transportation plans.

The chi-square test of the null hypothesis, "Passenger modes and combinations included in state transportation plans do not vary by area, population, density or urban concentration," produced no values exceeding the critical levels.

Table 2

Passenger-related modes and combinations

Percent of states (n = 44)

Chi-square (df = 3)

Private passenger vehicles

98

.93

Bicycle/pedestrian

98

1.96

Urban transit (all modes)

91

.68

Intercity bus

89

1.85

Air passenger

84

1.38

Intercity railroad passenger

84

1.19

Light trucks and vans

80

2.06

Bus-rail

59

1.66

Bus-air

52

2.58

Air-rail

45

.97

Water passenger

36

1.02

 

The freight combination of truck-rail was included in 82 percent of the state plans, just behind the individual modes of rail and truck. The other intermodal freight combinations of truck-air, rail-water, and truck-water were included in over one-half (59 to 61 percent) of the states' plans; see Table 3. The truck-rail combination received the most emphasis of any passenger or freight intermodal combination, on par with the dominant single modes. The remaining combinations were of lessor importance in the states' plans.

The null hypothesis, "Freight related modes and combinations included in state transportation plans do not vary by area, population, density or urban concentration," was rejected for pipelines (at the .10 level). The transportation plans of larger states (12/44 vs. 4/44), less dense states (11/44 vs. 5/44), and more urbanized states (10/44 vs. 6/44) were more likely to include pipelines. This result is consistent with the observation that the oil-producing states tend to be large, with dispersed populations, and the oil-refining states tend to be industrialized with major population centers.

Table 3

Freight-related modes and combinations

Percent of states (n = 44)

Chi-square (df = 3)

Freight railroads

89

3.28

Freight motor carriers

84

2.03

Truck-rail

82

4.53

Air freight carriers

73

.34

Truck-air

61

1.30

Rail-water

59

2.27

Truck-water

59

2.27

Water freight carriers

59

.46

Pipeline

36

7.28*

Other

14

1.96

* Differences significant at the .10 level.

Infrastructure needs addressed by traffic network models

Intermodal freight facilities and intermodal passenger facilities were included in 11 and 9 percent, respectively, of the states' traffic network models. The infrastructure needs addressed by these models were dominated by state highways (39 percent) and county and city streets and roads (18 percent). As displayed in Table 4, terminals and facilities for other individual modes received scattered mention. If the "intermodal" objective of ISTEA is to be achieved, the traffic network models used by state planners will need to be updated to include trips or hauls involving more than one mode and the infrastructure required to allow the intermodal transfers of freight and passengers. The null hypothesis, "Infrastructure needs in traffic network models do not vary by area, population, density or urban concentration," was not rejected for any of the categories listed in Table 4.

Table 4

Infrastructure needs in traffic network models

Percent of states (n = 44)

Chi-square (df = 3)

State highways

39

.71

County & city roads & streets

18

.38

Intercity rail passenger facilities

14

.69

Urban transit facilities

14

1.85

Intercity bus terminals

11

1.67

Intermodal freight facilities

11

3.33

Commercial airports

9

3.20

Intermodal passenger facilities

9

2.79

Rail freight track & yard facilities

9

2.79

Air freight facilities

7

4.89

General aviation airports

7

4.89

Pipeline terminal facilities

5

5.87

Water freight port facilities

5

2.67

Water passenger terminals

2

4.00

Other

2

4.00

Multimodal issues in new or updated plan

When presented with a list of eleven specific multimodal issues, the top three identified by state planners were urban rail-highway conflicts (57 percent), rural rail-highway conflicts (55 percent), and intercity bus and rail terminal joint location (48 percent). As Table 5 indicates, highway-related issues appeared frequently--such as freight and passenger terminals' impacts on roads--and were included in comments in the "other" category.

Null hypotheses testing suggested two issues for further inquiry. First, rejecting (at the .10 level) the statement, "The inclusion of intercity bus and air terminal joint location in new or updated statewide plans does not vary by area, population, density or percent urban population," lends support to interpreting the data as showing that states with larger areas and lower densities were more likely to include this issue. Smaller states were less likely to have airports and lower density states may be more likely to employ intercity bus transportation rather than light rail.

The second null hypothesis to be rejected (also at the .10 level) concerned "other" multimodal issues: "The inclusion of other multimodal issues (see Table 4) does not vary by area, population, density or urban concentration." Geographically smaller states were more likely to list "other" multimodal issues in response to this question.

Table 5

Multimodal issues in new or updated statewide plans.

Percent of states (n = 44)

Chi-square (df = 3)

Urban rail-highway conflicts

57

.77
Rural rail-highway conflicts

55

1.52
Intercity bus & rail terminal joint location

48

1.67
Freight terminal impact on roads

36

3.19
Rail & water freight terminal joint location

36

2.26
Passenger terminal impact on roads

30

3.31
Reduces highway use due to rail freight

30

2.80
Intercity bus & air terminal joint location

27

6.26*
Highway investment on motor carrier terminal location

23

2.40
Passenger terminal impact on parking

20

.44
Highway investment on warehouse & DC location

20

2.22
Other multimodal issues: 20 6.74*
Access (friendly design, landside, intermodal)

Diversion from highway.

Focus on truck-rail transfer.

Integrating bicycle/pedestrian with roads & bridges.

Interconnected rail-freight-air-water service on highway operations.

Light rail-airport, commuter heavy rail.

Truck-rail movement of agricultural products.

* Differences significant at the .10 level.

 

Methods used for identifying future needs for transportation infrastructure investment

Explanations of the lack of integrated planning may be indicated by the methods which states use to identify future needs for transportation infrastructure investment. The rankings of Table 6 show that more than twice as many responding states (67 percent) employ non-network models than network models. In other words, individual projects were analyzed without full consideration of their effects upon the transportation network. Twenty-four percent had a passenger network model, but no freight model, while 9 percent had separate network models for passenger and freight transportation. Fifteen percent claimed single integrated network models. Given the complexity of a state's transportation system, resorting to less-than-complete analyses is not surprising. Forty-eight percent of the states employed benefit-cost analysis, a structured model that attempts to compare total societal benefits to total societal costs, "whether they be monetary or nonmonetary in nature" (1). Twenty-four percent also used regional economic impact models, a sign that wider analysis is taking place. Six individual states (13 percent) mentioned use or development of other network or regional models.

The chi-square test of the null hypotheses, "The use of mode specific network models for identifying future needs for transportation infrastructure investment does not vary by area, population, density or urban concentration," produced one value exceeding the critical value (at the .10 level). States with more urbanized population and with larger land areas were more mode-specific. Conversely, states with more dispersed population may have broader infrastructure needs.

 

Table 6

Methods for identifying future needs for transportation infrastructure investment. Percent of states (n = 46) Chi-square (df = 3)
Mode & system non-network models 67 .87
Benefit-cost analysis 48 1.09
Mode specific network models 26 7.27*
Passenger network model, but no freight model 24 1.76
Regional economic impact models 24 2.46
Single integrated network model 15 3.88
Separate passenger & freight network models 9 1.07
Other:

HPMS package, system-wide model is under development.

Person trip model, separate transit model.

Policies.

Public involvement

Regional prioritized needs.

REMI for economic impact analysis.

13 .00

Differences significant at the .10 level.

 

 

Table 7

Training needs identified due to multimodal emphasis of ISTEA. Percent of states (n = 46) Chi-square (df = 3)
Geographic information systems 72 4.13
Transport economics 54 .64
Benefit-cost analysis 50 .83
Financial analysis 50 .83
Transport network development & modeling 50 1.05
Inter-city freight demand forecasting 48 .87
Railroad system planning 37 .94
Public finance 33 1.07
Public transit system planning 33 2.90
Inter-city passenger demand forecasting 30 5.69
Business logistics 26 .93
Air transport system planning 24 3.54
Water transport system planning 24 3.38
Intra-city passenger demand forecasting 13 2.22
Other:

Application of business planning practices to non-govt transportation.

Bicycle/pedestrian planning.

Dept. has extensive on-going training program.

Future planning skills and needs study.

Information systems in general, e.g., data warehousing, Oracle.

Not at this time, but see a need for GIS databases.

15 1.58

 

Training needs identified due to multimodal emphasis of ISTEA

Even if more states had integrated models available, the skills necessary for applying them may need upgrading. As Table 7 shows, a majority (67 percent) require backgrounds in Geographic Information Systems. Over 40 percent of the states required training in five additional categories: transport economics, benefit-cost analysis, financial analysis, transport network development and modeling, and inter-city freight demand forecasting. One-fifth to one-third of the respondents identified seven more training needs, further evidence of the education support that will enable implementation of multimodal transportation planning. Chi-square tests identified no null hypotheses of the form, "(Specific) training needs due to the multimodal emphasis of ISTEA do not vary by area, population, density or urban concentration," that were rejected.

Funding flexibility

Consistent with the shifting emphasis to multimodal transportation was increased flexibility in spending federal funds. Where most prior allocations were restricted to one mode, such as a highway project or Amtrak, the objective of ISTEA was to encourage projects involving more than one mode by reducing the restrictions on spending. When respondents were asked if they felt that ISTEA had accomplished the objective of making federal funding programs more flexible, 57 percent said yes and 43 percent said no.

While a clear majority agreed that the federal funding programs were more flexible under ISTEA, it is notable there were 19 states responding "no." Accompanying the negative responses were the following comments:

In general, funding is less flexible under ISTEA than under previous acts.

Flexibility between transit and highways, but between them and other modes has not occurred. Intent was good, but too many limitations.

Cannot easily use funds on intercity passenger and freight (rail, ports).

Important progress has been made but . . . the problem of less than full funding continues to hinder flexibility.

ISTEA changed very little unless states endorsed the change themselves.

Funding flexibility to allow, even promote, multimodal programs appears to be one step in the right direction. New legislation may build upon the partial success of the ISTEA in reducing funding restrictions.

Future legislation

The survey asked what features state transportation planners considered desirable for inclusion in a reauthorization bill. (The original provisions of ISTEA expired on September 30, 1997. Congress was debating nine bills for reauthorization during June 1997 (2).) Responses are ranked in Table 8. The leading requests were to expand the State Infrastructure Bank program, from the initial 10 states (3) to all states (41 percent), retain the current apportionment formula (35 percent), and a separate program for bridge replacement (also 35 percent). The least support was expressed for the ethanol tax exemption (2 percent) and appropriations for demonstration projects (2 percent); the use of federal taxes for deficit reduction received no support.

One null hypothesis was rejected: "The desirability of a set aside for rural areas in the reauthorization of ISTEA does not vary by area, population, density or urban concentration." States in the top 25 by land area but the lower half in terms of population and density included this feature more often than did less rural states.

Table 8

What features are desired in the reauthorization of ISTEA? Percent of states (n = 44) Chi-square (df = 3)
State infrastructure bank funding for all states 42 4.09
Current state apportionment formula 36 1.30
Separate program for bridge replacement 36 .25
Set aside for large urban areas 29 3.47
Set aside for enhancements 24 2.46
Separate program for congestion & air quality management 22 1.90
Separate program for safety improvements 22 .30
Special trade corridor funding 22 4.44
Amtrak eligibility for STP or FTA funds 20 .33
Set aside for rural areas 22 6.87*
Turn back federal taxes to the states 18 .42
Keep fuel tax exemption for ethanol 2 --
Special appropriations for demonstration projects 2 4.00
Use of federal tax for deficit reduction 0 --
Other:

Dedicated funding to solve rail/highway conflicts.

More flexibility (2 states).

NHS (2 states).

Support Step 21 initiative (4 states).

33 1.61

* Differences significant at the .10 level

 

REFERENCES FOR APPENDIX I

  1. Coyle, John J.; Bardi, Edward J.; and Novack, Robert A. Transportation, 4th ed. St. Paul: West Publishing Co., 1994, p. 113.
  2. David Barnes, "Washington Report: House Gridlock?" Traffic World, June 16, 1997, pp. 13-14.
  3. U.S. Department of Transportation, "29 Additional State Are Approved to Participate In State Infrastructure Bank (SIB) Pilot Program," June 19, 1997.

Multimodal Investment Analysis: Phase 1 Contents

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