MEASURING IMPROVEMENTS IN THE MOVEMENT OF HIGHWAY AND INTERMODAL FREIGHT

*Final Report*

*Prepared for:*

*Federal Highway Administration*

*400 Seventh Street, SW*

*Washington, DC 20590*

*Prepared by:*

Hagler Bailly Services, Inc.

1530 Wilson Boulevard

Arlington, VA 22209

703-351-0300

*Under Contract:*

DTFH61-97-C-00010, BAT 99-021

March 20, 2000

Measuring Improvements in the Movement of Highway and Intermodal Freight

# Executive Summary {#executive-summary .unnumbered}

The Government Performance and Results Act (GPRA) of 1993 established a
requirement for Federal agencies to identify goals and measurable
outcomes to gauge performance in meeting program objectives. In response
to this requirement and in seeking to advance its own performance, the
Federal Highway Administration (FHWA) has developed a National Strategic
Plan. In order to measure performance under the plan, FHWA has sought to
develop performance measures for productivity and efficiency
improvements in relation to the highway system. Productivity is one of
the five strategic goals in the plan: to "continuously improve the
economic efficiency of the Nation\'s transportation system to enhance
America\'s position in the global economy."

In this regard, it is important that FHWA develop measures of the
performance of the highway system in carrying freight and supporting the
intermodal freight system. FHWA contracted with Hagler Bailly Services
to provide a limited, introductory review of what indicators may be
available for use by FHWA to detect and assess, on an annual basis,
productivity and efficiency in the movement of commercial goods by motor
vehicles.

The work began with a review of the results of a number of recent
studies and conferences where various groups and individuals made
efforts to identify performance measures for freight. These results were
summarized, evaluated, and passed through a preliminary screening
process to identify measures potentially valuable enough to warrant
further analysis and development by FHWA. That preliminary screen
yielded thirteen potentially valuable indicators (referred to as
"first-tier" indicators in the report). These were:

**Cost of highway freight per ton-mile**

**Cargo insurance rates**

**Fuel consumption of heavy trucks per ton-mile**

**On-time performance for highway-freight deliveries**

These measures all address the cost or quality of freight service to
shippers.

**Point-to-point travel times for selected freight-significant
highways**

**Hours of delay per 1000 vehicle-miles on freight-significant
highways**

**Ratio of peak period travel time to off-peak travel time at
freight-significant nodes**

### Ratio of variance to average minutes per trip in peak periods at freight-significant nodes {#ratio-of-variance-to-average-minutes-per-trip-in-peak-periods-at-freight-significant-nodes .unnumbered}

**Hours of incident-based delay on freight-significant highways**

These measures all address travel time and reliability of highway
performance as it relates to freight.

**Annual miles per truck**

This is a measure of freight equipment utilization that may be affected
by highway condition.

**Crossing time at international border crossings**

International border crossings are of particular importance to efficient
international freight movement.

### Conditions on connectors between NHS and intermodal terminals {#conditions-on-connectors-between-nhs-and-intermodal-terminals .unnumbered}

The conditions on the connecting links between the NHS and intermodal
freight terminals are an important measure of the highway system's
ability to handle intermodal freight.

### Customer Satisfaction {#customer-satisfaction .unnumbered}

The judgments on performance of the firms and people that use the system
every day could be very valuable to FHWA as an indicator of how well the
system is performing.

The final screening and evaluation led to recommendation of the
following seven indicators for further development by FHWA:

Cost of highway freight per ton-mile

Cargo insurance rates

Point-to-point travel times on selected freight-significant highways

Hours of delay per 1,000 vehicle miles on selected freight-significant
highways

Crossing times at international borders

Condition of connectors between NHS and intermodal terminals

Customer satisfaction.

These measures were selected in an evaluation process that balanced the
inherent value of an indicator as a measure of performance against the
difficulty and cost of obtaining the necessary data. No rigid scoring
methodology was used for the selection of recommended indicators. In
general, the measures that were recommended are those that ranked
highest in terms of descriptive value and technical appropriateness.
Data availability and costs are important considerations for FHWA as it
considers the use of these measures. However, this does not mean that
measures with relatively high data costs should not be pursued. Customer
satisfaction, for example, would require considerable effort to design a
survey, obtain the cooperation of private firms, and carry out the
survey on an annual basis. Nonetheless, it was recommended because of
the high value of the information it could provide to FHWA.

Further development, and use, of this set of measures will provide FHWA
with valid measures of the effectiveness of the highway system's
contribution to national productivity through the efficient movement of
domestic and international freight.

Measuring Improvements in the Movement of Highway and Intermodal Freight

# Introduction

## Background and Purpose

The Government Performance and Results Act (GPRA) of 1993 established a
requirement for Federal agencies to identify goals and measurable
outcomes to gauge performance in meeting program objectives. In response
to this requirement and in seeking to continually advance its own
performance, the Federal Highway Administration (FHWA) has developed a
National Strategic Plan to chart goals and objectives over the ten-year
period, 1998 to 2008. The agency is also developing annual Performance
Plans in connection with the its budget submittals to define and report
on the performance goals and indicators that measure progress toward
achieving strategic goals.

In developing its performance plans, FHWA has sought to develop
performance measures for productivity and efficiency improvements in
relation to the highway system. "Productivity" is one of the five
strategic goals in FHWA's National Strategic Plan, with a target to
"continuously improve the economic efficiency of the Nation\'s
transportation system to enhance America\'s position in the global
economy." An efficient and productive transportation system is viewed as
important for advancing America's economic growth and competitiveness
domestically and internationally.

FHWA is interested in development of performance measures for freight.
Highway freight movement is a key area of program responsibility for
FHWA, and the agency needs indicators to assess progress toward the
"productivity" goal in relation to freight movement. FHWA contracted
with Hagler Bailly Services to provide a limited, introductory review of
what indicators may be available for use by FHWA to detect and assess,
on an annual basis, productivity and efficiency improvements in the
movement of commercial goods by motor vehicles. This work involved two
tasks:

> **Task 1: A Review and Assessment of Previous Efforts to Develop
> Indicators**
>
> This task involved a summary and assessment of previous efforts to
> develop indicators for highway and intermodal freight. Indicators
> developed in previous studies were identified and categorized into
> four groups based on their potential usefulness for FHWA: 1)
> potentially valuable (first-tier) indicators; 2) second-tier
> indicators; 3) corridor or facility measures; and 4) not-useful
> measures.
>
> **Task 2: An Initial Analysis of Potential Indicators**
>
> This task involved further evaluation of first-tier indicators
> identified in Task 1. Based on this work, a small set of indicators
> worthy of further analysis and development by FHWA is recommended in
> this report.

This report presents the results of both Tasks 1 and 2.

## Report Organization

The remainder of this report is organized as follows:

> **Section 2: Overview of Indicators Identified in Previous Efforts**
> ---This section provides a summary and assessment of various studies
> and conferences that attempted to develop freight performance
> measures. It categorizes potential measures and assesses their
> potential usefulness for FHWA and other highway-related organizations.
>
> **Section 3: Recommendations** --- This section recommends performance
> measures worthy of further investigation by FHWA. It begins by
> grouping potential measures into four categories: 1) potentially
> valuable (first-tier) indicators; 2) second-tier (less valuable)
> indicators; 3) corridor or facility measures; and 4) not-useful
> measures. First-tier indicators are then evaluated along various
> criteria and the indicators with the most potential are selected.
>
> **Appendix A: Reviews of Individual Efforts** ---This section provides
> a synopsis and assessment of each of the prior studies and conferences
> reviewed.
>
> **Appendix B: Contacts** ---This section lists individuals contacted
> for this research.

# Overview of Indicators Identified in Previous Research

## Focus of Past Research and Policy Efforts

This review draws on papers and reports that address attributes of
freight movement and characteristics of the highway system. The papers
that resulted from these efforts, as well as conversations with
contacts, suggest that prior efforts to develop measures to gauge the
performance of the highway system as a mover of freight have been
limited. Previous research efforts have largely looked at one of two
issues:

> 1\) Measures of transportation industry productivity that are not
> clearly linked to the performance of the highway system; or
>
> 2\) Measures of highway system performance that are important to
> highway users in general but not specifically linked to freight.

The first set of measures addresses the efficiency of freight service,
but does not address the link between freight productivity and the
transportation system. Indicators of labor productivity (e.g., ton-miles
per employee), logistics efficiency, and equipment utilization (e.g.,
percent of truck-miles empty) fall into this category, as do multifactor
productivity measures (output per unit of combined labor, capital, and
intermediate outputs, weighted in some fashion). These indicators are
only indirectly affected by the highway system and fail to provide any
indication of the quality of service that shippers are receiving.

The second set of measures addresses aspects of the highway system that
are important to highway users, such as speed, safety, and pavement
condition. While these characteristics affect freight movement, most
studies do not attempt to develop indicators of particular relevance to
the productivity of freight movement. They are focused on general
indicators of highway performance that affect both commercial traffic
and personal travel.

The challenge for FHWA is to identify, and focus on, attributes of the
highway system that have a particular significance for freight movement
and can be linked to the characteristics of freight service that are
important for shippers. The prior effort that most directly tackled the
issue of identifying and assessing freight performance indicators is
FHWA's Workshop on Productivity Performance Indicators, held in March
1998. This effort, however, was not focused exclusively on freight
movement. A number of other efforts yield useful insights into aspects
of the transportation system that are important to freight movement,
including costs and quality of service, and potential indicators for
measuring freight performance. Taken together, these studies provide a
basis for further exploration of this problem.

## Indicators Identified

Indicators identified from prior studies tend to fall into the following
seven categories:

1.  **Travel time** measures (e.g., average travel time in peak period,
    annual hours of delay, average time at border crossings)

2.  **Reliability** measures (e.g., variability of travel time; hours of
    incident-based/non-recurrent delay)

3.  **Cost** measures (e.g., average cost per ton-mile)

4.  **Safety or damage** measures (e.g., accident rate)

5.  **Highway condition** measures (e.g., percent of roads with surface
    condition classified as good, number of weight restricted bridges)

6.  **Economic impact** measures (e.g., contribution of investment to
    GDP growth, employment impacts)

7.  **Industry productivity** measures (e.g., ton-miles per employee,
    percent of truckloads empty)

Each of the seven categories of measures is discussed further below,
with an initial assessment of strengths and weaknesses.

### Travel Time Measures

Travel time-related performance measures include two general types of
measures:

Measures of average travel time, such as:

-   average travel time in peak period in major metro areas or corridors

-   freight transfer time between modes (for intermodal)

-   crossing time at border crossings

-   city-to-city travel time

-   shipper point-to-point travel time

Measures of delay (or added travel time), such as:

-   hours of delay per 1000 vehicle-mile

-   percent of PM peak travel experiencing delay

-   average hours of delay per 1000 vehicles processed at border
    crossings

-   hours spent waiting at toll plazas per 1000 vehicle-mile

-   hours spent waiting at weigh stations per 1000 ton-mile

***General Assessment***

A major strength of travel time measures as freight productivity
indicators is that travel time and congestion are very important to
shippers. Rapid service is a critical element of competition. Package
carriers and long haul truckers alike offer one-day and two-day service
in many markets, and customers expect rapid delivery of goods.
Businesses typically expect package delivery early in the morning and
pickups late in the afternoon, pressuring delivery services to be on the
roads during congested peak hours and to move goods as quickly as
possible. Transit time also affects the costs of shipping goods, which
is important for shippers. As a result, efforts to reduce traffic
congestion and bottlenecks are very important for freight movers. Travel
time measures are also generally easy to understand. Currently available
data streams, however, do not provide information on actual travel
times. Travel time would have to be measured directly at selected sites.

A weakness occurs when it comes to developing indicators that are
specific to freight but not too narrowly focused. Indicators such as
"average travel time in peak period in major metro areas" and "percent
of PM peak travel experiencing delay" are general mobility measures that
address both freight and passenger traffic. On the other hand, measures
that focus on specific freight bottlenecks, such as border crossings and
toll plazas, are limited because they focus on a very small portion of
total freight travel. In order for a travel time indicator to be most
useful as a national indicator, specific routes of importance to freight
or point-to-point combinations need to be identified.

> ***Average Travel Time***
>
> Using a measure of average travel time requires identifying specific
> point-to-point (or city-to-city) combinations to examine.
> Point-to-point transit time directly addresses what is important to
> freight movers. It accounts for the full range of components of travel
> time, including time on the road, in intermodal transfers, and at toll
> plazas. Although many companies maintain such data and have their own
> targets, these data may not be readily available (this issue will be
> explored further in Task 2).
>
> ***Time at Border Crossings, Weigh Stations, and Toll Plazas***
>
> International border crossings are of particular importance to
> international freight; as such, they are important from a national
> perspective. This indicator is limited, however, because it only
> addresses a portion of total freight traffic. Measures like hours
> spent waiting at weigh stations or toll plazas are also limited and
> are less relevant from a national perspective.
>
> ***Hours of Delay***
>
> An "hours of delay" measure focuses on "excess" travel time associated
> with incident-based or recurring congestion. The measure would be
> limited as a freight measure if data are only available for total
> traffic delays. Much of traffic delay is associated with commuter
> traffic during peak periods and freight traffic may be scheduled to
> avoid much of this delay.

### Reliability Measures

Indicators of reliability include:

-   hours of incident-based delay

-   ratio of variance to average minutes per trip in peak periods in
    major metro areas

-   percent of on-time arrivals

***General Assessment***

Reliability is an attribute of key importance to highway shippers. In
fact, a number of reports noted that having predictable travel times may
be even more important than average travel times. More than ever,
logistics management emphasizes "just-in-time" delivery to reduce or
eliminate storage and warehousing costs. Shippers schedule freight
movements to account for travel delays and avoid peak period congestion
to the extent possible. As a result, the rate of variation in travel
time (unexpected delay) is of key concern.

Just like travel time measures, reliability measures are less useful if
they focus on all travel. It would be important to focus on routes of
particular importance to freight. Another weakness of these measures is
that a high level of reliability does not necessarily reflect that
conditions are good, only that they are consistent (e.g., it could
reflect consistently slow or high-cost service). As a result, it would
be useful to combine a reliability measure with a travel time or cost
measure.

> ***Hours of Incident-based Delay***
>
> Incident-based delay reflects increases in travel time that are
> unexpected, and therefore would be of particular importance for
> freight delivery schedules. It may be difficult, however, to identify
> what portion of total delay results from recurrent versus
> incident-based congestion. A composite measure of delay in various
> metropolitan areas or key freight nodes would need to be developed to
> be used as a national measure.
>
> ***Variance in Travel Time***
>
> Variation in travel time also is a potentially useful measure that
> would be useful to examine for specific corridors or routes of
> importance to freight. However, depending on how the measure is
> developed it might reflect not only unexpected incident-based delay
> but also more expected seasonal, day-of-week, or time-of-day
> fluctuations in travel time.
>
> ***Percent On-time Arrivals***
>
> Percentage of on-time arrivals is a potentially useful measure since
> it focuses directly on freight movements and reflects highway
> conditions. The advantage of the other reliability measures is that
> they directly represent highway conditions; the percent of on-time
> arrivals may reflect other factors as well. In terms of tracking
> progress over time, the measure is also limited because it could be a
> "moving target" in that schedules may be adjusted to account for
> worsening congestion or other factors that reflect lower quality
> service. Data availability also is an issue. On-time arrivals are
> tracked by private firms, but such information may not be publicly
> available.

### Cost Measures

Cost measures were identified in a number of earlier efforts for
potential use as transportation system indicators. Transportation cost
measures identified in previous efforts include:

-   cost of highway freight per ton-mile

-   fuel consumption per ton-mile

-   total public and private costs of travel

-   maintenance cost of connector links

***General Assessment***

Transportation costs are important to freight shippers. Lower
transportation costs per unit shipped are beneficial to shippers; lower
transportation costs contribute to more efficient use of resources in
production and distribution. Greater efficiency ultimately benefits
consumers in better quality and/or lower prices for goods. Declining
costs, however, are not necessarily all positive for freight
performance. Lower costs could be the result of lower quality of service
(e.g., reduced reliability). There are a number of different types of
transportation costs that can be tracked, as described below.
Potentially useful cost measures focus on the costs associated with
freight transport. Less useful cost measures focus on highway
infrastructure costs and expenditures, which may or may not reflect
improved freight performance.

> ***Cost per Ton-mile***
>
> The first of these measures, cost of highway freight per ton-mile, is
> certainly a useful measure. It is specific to freight, and is affected
> by highway conditions. It is also affected by factors unrelated to the
> highway system, however, such as truck technology, drivers' wages,
> fuel costs, and trucking companies' skill in managing their fleets. As
> a result, it may be skewed by factors that have nothing to do with
> transportation infrastructure.
>
> ***Fuel Consumption per Ton-mile***
>
> Fuel consumption per ton-mile, is not really a "cost" measure but it
> does reflect one of the costs associated with transport that is
> related to highway condition. It reflects the same things as costs per
> ton-mile, but would not be affected by the prices of labor and fuel.
> As a result, it may be a better measure of the performance of
> highway-system performance in freight carriage because it reflects
> fewer costs unrelated to highway conditions. It may be more difficult
> to grasp intuitively as an indicator of freight performance, however.
>
> ***Total Public and Private Costs of Travel***
>
> As noted above, one weakness with cost measures is that they do not
> account for the quality of service. A measure of total costs attempts
> to account for this problem by focusing not only on the costs of
> shipping goods but also costs associated with damage to goods,
> constructing roads, expanding and maintaining highways, etc. As a
> result, a measure of total public and private costs of travel takes
> into account all the resource costs associated with travel.
>
> Unfortunately, tracking total costs instead of unit costs can be
> highly misleading. Total costs would be expected to increase due to
> increased population and economic growth (benefits would also
> increase: mobility, economic activity, etc.). As a result, rising
> total costs would be normal effects of an expanding economy. A
> composite measure of total travel costs is also analytically complex
> and difficult to develop.
>
> ***Maintenance Costs***
>
> A number of State DOT efforts identified funds expended on highway
> maintenance on roads of importance to freight or intermodal traffic as
> an indicator of freight performance. Although investment clearly
> signifies that priority is being placed on these routes, it is not a
> measure of freight productivity. It is not clear whether higher or
> lower maintenance costs is good or bad. More spending on highway
> maintenance does not necessarily indicate an improvement in road
> condition; it could indicate wasteful spending.

### Safety or Damage Measures

A number of efforts identified safety- or damage-related measures as
indicators of highway performance. These include:

-   accident rates

-   fatality rates

-   insurance cost (for freight)

***General Assessment***

Loss and damage to cargoes provides a measure of the quality of freight
service. A number of earlier efforts identified loss and damage of goods
through accidents and pilferage as important aspects of relevance to the
productivity and efficiency of freight service.

> ***Accident / Fatality Rates***
>
> Accident and fatality rates are general safety measures that are
> tracked by the National Highway Transportation Safety Administration
> (NHTSA) and are already included in FHWA's performance plan. Most data
> related to safety focus on the number of fatalities or injuries. The
> most important concern in regard to freight productivity is the value
> of goods damaged or lost due to accidents, and potentially greater
> insurance costs associated with accidents that cause loss of life or
> injury. Data on these costs are limited.
>
> ***Insurance Cost***
>
> Cost of cargo insurance could provide a useful proxy for loss and
> damage. From the shipper's perspective, loss and damage is an
> important aspect of quality. As a result, insurance cost is a
> potentially useful performance measure. There are certain limitations:
> it reflects factors other than road conditions, e.g., level of driver
> experience and levels of theft. The proper metric (e.g., cost per ton
> of cargo) would need to be developed and data availability examined.

### Highway Condition Measures

Many previous efforts identified measures of highway condition as
potential indicators for freight or intermodal freight. These relate to
either the degree of wear on facilities or design features that might
restrict freight movement (measures reflecting congestion are discussed
above either under travel time or reliability):

Measures of quality or wear:

-   lane-miles of high-level highway requiring rehabilitation

-   percent of roads with surface condition classified as good

-   percent of bridges in good condition

Measures related to design features:

-   number of at-grade railroad crossings

-   number of overpasses that have vertical clearance restrictions

-   number of weight restricted bridges

-   intersections with inadequate turning radii for large trailers

***General Assessment***

These indicators do not measure performance directly. They provide FHWA
with information on the highway system's *ability to perform* but not
actually *how it performs* as a freight mover. Information for tracking
most of these measures is available.

> ***Quality Measures***
>
> Measures of road quality or wear are generally available and reported
> to FHWA as part of the Highway Performance Monitoring System (HPMS). A
> weakness of these measures is that they are not specific to freight:
> they represent the quality of road conditions experienced by all
> travelers. If road conditions improve, presumably freight movement
> benefits, but it is not clear how much freight is affected. A way to
> focus on freight would be to identify a set of facilities of
> particular importance to freight movement and track their condition.
>
> ***Impedances to Freight Movement***
>
> Measures that focus on the number of impedances to freight movement
> are specific to freight but tend to be somewhat narrow. One problem is
> that the number of facilities with impedances is probably not a good
> measure of impact on freight movement. Many of these impedances may
> not be on segments of importance to freight.

### Economic Impact Measures

A number of the efforts identified measures of economic impact. These
measures include:

-   contribution of investment to GDP growth

-   

-   direct and indirect jobs created

-   

-   net present value of improvements

-   

-   benefit-cost ratio of highway improvements

-   

-   value of transportation-related goods and services delivered to the
    final customer

***General Assessment***

These measures focus on the economic benefits associated with investment
in transportation facilities. Although transportation investments
certainly can support efficient freight movement, the economic impacts
of infrastructure investment are greater than those associated solely
with freight movement. Transportation investment results in savings in
travel time, reduction in vehicle operating costs, and a reduction in
accident costs that accrue to all users, freight and non-freight.

Several economic studies supported by the Office of Transportation
Policy Studies have measured the effects of public highway capital on
national output and economic performance.[^1] This work has examined the
contributions of highway capital to the output growth and productivity
of various industry sectors comprising the U.S. economy. It provides
empirical evidence of the positive impacts of public highway capital on
private sector costs of production and calculates the net social rate of
return on highway infrastructure spending. This work is discussed
further below:

> ***Contribution of Investment to GDP Growth***
>
> This refers to the substantial body of work carried out by Professor
> Ishaq Nadiri of New York University. This is a statistical analysis of
> the relationship of businesses' costs to investment in highways
> (technically, changes in the highway capital stock). In large measure,
> response of business costs to highway investment reflects improvement
> in the highways as freight carriers. However, reduction in firms'
> costs could also reflect an improvement in passenger travel on
> highways (by expanding the pool of potential employees). There is no
> way to separate the effects of passenger travel from the effects of
> freight carriage in this type of analysis.
>
> In order to be useful as a performance measure, this kind of analysis
> would need to be carried out on an annual or biennial basis; some
> question might arise as to the statistical validity of year-to-year
> changes in these results.
>
> ***Jobs Created***
>
> While this measure can be important to a local community, it is not a
> measure of freight productivity. The number of direct jobs created by
> a highway project tells nothing of how the project will affect freight
> movement or whether the project is worthwhile. These figures relate to
> the impacts of project spending, not to the value of the project for
> freight.
>
> ***Net Present Value or Benefit/Cost Ratio***
>
> Net present value and benefit/cost ratios are a measure of the value
> of highway investments. Both measures involve a comparison of the
> benefits and costs associated with infrastructure investment, but with
> slightly different implications. Since the benefits of transportation
> projects include travel time savings, vehicle operating cost savings,
> safety improvements, etc., these measures capture a range of economic
> effects beyond the impact on freight movement. These measures do not
> isolate impacts associated with freight movement, and in fact, most of
> the economic benefits measured probably are associated with personal
> travel.
>
> ***Value of Transportation-related Goods and Services Delivered***
>
> The value of transportation-related goods and services delivered to
> customers provides a measure of the how much of the economy is
> associated with transportation. This is not really a measure of
> freight productivity or the implications of highway investment on
> freight.

### Transportation Industry Productivity Measures

Industry productivity measures include the following metrics:

-   average load factors / percent of vehicle miles empty

-   average length of haul

-   annual miles per truck

-   ton-miles per unit of labor

-   multi-factor productivity measures

***General Assessment***

These measures all are a measure of output per unit of input. They
provide information about the utilization of labor and equipment. They
are good measures of the productivity of the freight industry, but fail
to directly address the relationship to the highway system. They also
fail to address the quality of service. Of these measures, the one that
has the greatest linkage to the highway system is annual miles per
truck, since miles per truck is affected by road and traffic conditions.

# Recommendations

Section 2 reviewed and summarized types of freight performance-measures
presented in prior studies and investigations. This section indicates
which of the specific measures appear to be most promising for use by
FHWA. It recommends the following limited set of measures for further
analysis and development by FHWA:

Cost of highway freight per ton-mile

Cargo insurance rates

Point-to-point travel times on selected freight-significant highways

Hours of delay per 1,000 vehicle miles on selected freight-significant
highways

Crossing times at international borders

Condition of connectors between NHS and intermodal terminals

Customer satisfaction

These recommendations were developed based on a two-stage evaluation
process:

1)  **Initial Screening** - Potential indicators were screened and
    grouped into four general categories: 1) potentially valuable
    (first-tier) indicators; 2) second-tier national indicators; 3)
    corridor or facility measures; 4) not-useful measures.

> 2\) **Criteria-based Evaluation ---** The first-tier indicators
> identified in step 1 were further evaluated and a small set are
> recommended as meriting further development by FHWA.

## Initial Screening

This section summarizes the findings from the initial screening analysis
of potential indicators. Potential indicators were grouped into the
following categories:

> **Potentially Valuable (First-tier) Indicators *--- ***These
> indicators were judged as potentially valuable as national indicators
> based on an initial screening analysis.
>
> Second-tier Indicators--- These indicators have a definite bearing on
> freight performance but are limited in some way, so they were not
> recommended for further development; many of these measures may
> already be available to FHWA.
>
> **Corridor or Facility Measures ---** These indicators are potentially
> good measures of freight performance but are specific to a particular
> corridor, site, or facility (e.g., intermodal terminals). They were
> viewed as inappropriate for FHWA as national indicators but may be
> useful at other levels.
>
> **Not-Useful** **Measures** --- These indicators have little or no use
> as a measure of freight productivity.

The distinctions between potentially valuable, useful, and not useful
are necessarily somewhat subjective; however, these assessments were
based on best judgement regarding the nature of these indicators.
Indicators were categorized based on an initial screening assessment of
their technical appropriateness and descriptive value.

### Potentially Valuable (First-Tier) Indicators

Potentially valuable indicators are those that are most reflective of
the highway system's impact on freight performance or of the efficiency
of the freight system. These include direct measures of the quality or
cost of freight service nationally. They also include measures of the
performance of parts of the highway system that have special importance
for goods movement, e.g., highway segments or corridors that carry
comparatively large volumes of freight or are otherwise significant
links in the national freight system. Expenditure of resources to
develop these measures further may be justified. Potentially valuable
measures include:

> **Cost of highway freight per ton-mile**
>
> **Cargo insurance rates**
>
> **Fuel consumption of heavy trucks per ton-mile**
>
> **On-time performance for highway-freight deliveries**
>
> These measures all address the cost or quality of freight service to
> shippers.
>
> **Point-to-point travel times for selected freight-significant
> highways**
>
> **Hours of delay per 1000 vehicle-miles on freight-significant
> highways**
>
> **Ratio of peak period travel time to off-peak travel time at
> freight-significant nodes**
>
> **Ratio of variance to average minutes per trip in peak periods at
> freight-significant nodes**
>
> **Hours of incident-based delay on freight-significant highways**
>
> These measures all address travel time and reliability of highway
> performance as it relates to freight. Use of any of these measures
> would require that FHWA designate portions or segments of the National
> Highway System (NHS) as having special significance for freight
> carriage and designate certain cities or metropolitan regions as key
> nodes in the highway freight network. These could be referred to as
> freight-significant highways and freight-significant nodes.
>
> **Annual miles per truck**
>
> This is a measure of freight equipment utilization that also is
> affected by highway condition.
>
> **Crossing time at international border crossings**
>
> International border crossings are of particular importance to
> efficient international freight movement. As such, this measure is
> important from a national perspective, even though it only addresses a
> segment of travel time for a portion of all goods carried. This
> measure gives information on freight-system performance, but it
> largely reflects processing time required for immigration and customs
> on both sides of the border---not highway conditions or operations.

#### Performance on connectors between NHS and intermodal terminals {#performance-on-connectors-between-nhs-and-intermodal-terminals .unnumbered}

The connecting links between intermodal freight terminals and the NHS
are the road segments that make intermodal freight transportation
possible. Pavement and traffic conditions on these links are an
important measure of the highway system's ability to handle intermodal
freight.

#### Customer Satisfaction {#customer-satisfaction-1 .unnumbered}

> An important measure of the performance of the highway-freight system
> is the degree of satisfaction of the principal customers: shippers,
> receivers, and carriers. The judgments on performance of the firms and
> people that use the system every day could be very valuable to FHWA as
> an indicator of how well the system is performing. A satisfaction
> indicator could be measured through surveys.

### Second-Tier Indicators

Second-tier indicators provide useful information about aspects of the
highway system that are meaningful for freight movement but are not
specific to freight. They are standard highway performance indicators
that reflect the quality of travel conditions for all users. If these
indicators are already available to FHWA, those interested in freight
performance might find it useful to track them. However, it is not
worthwhile to develop them solely for freight purposes.

> **Average travel time for all trips**
>
> **Average travel time for all peak-period trips in major urban areas**
>
> **Average speed for inter-city travel**
>
> All of these measures address travel time, which is important for
> freight, but do not focus on routes or links of particular importance
> to freight.
>
> **Hours of delay per 1,000 vehicle-miles on the NHS**
>
> **Percent of PM peak-travel in major urban areas experiencing delays**
>
> **Ratio of variance to average minutes per trip in all urbanized
> areas**
>
> These measures provide information about traffic delays, but are
> limited as a freight measure since they simply are based on average
> speeds for all vehicles. A large portion of traffic delay is
> associated with commuter traffic during peak periods and freight
> traffic may be scheduled or routed to avoid much of this delay.
>
> **Heavy truck accident / fatality rates**
>
> Although these indicators address freight, the focus is on human
> safety. The most important concern in regard to freight productivity
> is the value of goods damaged or lost due to accidents, and
> potentially greater insurance costs associated with accidents that
> cause loss of life or injury.
>
> **Percent of NHS with pavement meeting a certain standard**
>
> **Percent of non-deficient bridges on NHS**
>
> These measures provide an indication of the quality of highways.
> Although highway condition is important for freight, these measures do
> not focus on routes of particular importance to freight. As a result,
> the indicator may not reflect changes in quality experienced by
> freight movers.
>
> **Contribution of investment to GDP growth**
>
> In large measure, response of business costs to highway investment
> reflects improvement in the highways as freight carriers; it also
> reflects improvement in passenger travel on highways, and there is no
> way to separate the effects of passenger travel from the effects of
> freight carriage. Perhaps the greatest challenge for this kind of
> measures is that a fairly complicated analysis must be carried out on
> an annual or biennial basis, and it is likely that small year-to-year
> changes would be lacking in statistical significance.

### Corridor or Facility Measures

Many of the indicators identified above could also be used at a
regional- or local-level to examine freight performance along specific
corridors or at specific points. The indicators identified below provide
a measure of freight performance but are limited to specific routes or
facilities. As a result, they are not appropriate for FHWA to use as
national performance measures, but would be useful for other purposes.

> **Freight-transfer times at selected intermodal terminals**
>
> **Hours waiting at toll plazas**
>
> **Hours waiting at weigh stations**

### Not-Useful Measures

The following measures were judged to be not useful. These measures
focus on the economic impacts of highway investment, which include a
large number of effects unrelated to freight movement.

> **Total public and private costs of travel**
>
> This measure would be very much dominated by effects that have little
> or nothing to do with freight movement given that most travel takes
> places for personal mobility. Further, even if it were limited to
> costs of freight movement, it would not be providing a useful measure
> of performance. Rising total costs could simply reflect rising freight
> shipments in an expanding economy, or rising use of freight movement
> relative to other inputs to production and distribution.
>
> **Maintenance costs**
>
> Spending on highways is not a measure of freight productivity, even if
> one focuses on routes of particular importance to freight. More
> spending could indicate an improvement in road condition or it could
> indicate wasteful spending.
>
> **Jobs created**
>
> The number of direct and indirect jobs created by a highway project
> tells nothing of how the project will affect freight movement or
> whether the project is worthwhile.
>
> **Net present value or benefit/cost ratio**
>
> These are measures of the value of highway investments. They do not
> tell one the degree to which project benefits reflect freight
> performance.
>
> **Value of transportation-related goods and services delivered**
>
> This is not really a measure of freight productivity or the
> implications of highway investment on freight.
>
> **Number of at-grade railroad crossings**
>
> **Number of overpasses with inadequate vertical clearance**
>
> **Number of weight-restricted bridges**
>
> **Number of intersections with inadequate turning radii for large
> trailer**
>
> These are all design features which can be impedances for freight
> movement. Their total number is not a useful measure because many of
> them are likely to be on routes not heavily used for freight purposes.
> Further, these features are unlikely to be common on the NHS.
>
> **Average load factors / percent of vehicle miles empty**
>
> **Average length of haul**
>
> **Ton-miles per unit of labor**
>
> **Multi-factor industry productivity measures**
>
> These are all measures of equipment utilization or labor productivity
> used within the motor carrier industry. They do not bear a direct
> relationship to the highway system or address quality or satisfaction
> with freight service.

## Evaluation of First-Tier Indicators

### Criteria Used

First-tier indicators were evaluated using the following criteria:

> **Descriptive value** --*Is the indicator clear and understandable for
> a range of audiences? Does it communicate clearly or does it require a
> detailed explanation in order to be understood?*
>
> This criterion concerns the comprehensibility of the indicator for
> general audiences. A useful performance measure might require some
> explanation to make it understandable to a generalist audience, but
> the best indicators according to this criterion would be readily
> understood without more than a paragraph or two of plain English.
>
> **Technical appropriateness** -- *How useful is the indicator in
> describing the productivity of freight movement in the U.S.? Is it
> conceptually appropriate as a measure of productivity or a measure of
> FHWA\'s contribution to productivity?*
>
> This criterion concerns the usefulness of the indicator as a measure
> of productivity. Technical appropriateness depends on the degree to
> which the measure truly reflects a significant aspect of cost,
> quality, or productivity of the highway-freight system and its
> intermodal connections. A major thrust of this effort is to measure
> the contribution of highway-freight movement to overall U.S.
> productivity, not just the productivity of highway freight. Therefore,
> it is appropriate to measure quality and cost of the highway system as
> it related to freight.
>
> **Data Availability and Cost** -- Data issues include the following
> considerations:
>
> **Availability** -- *Are data available in existing databases? If data
> are available, is it easy to collect, or are there difficulties in
> obtaining the data? Are there new ways to develop or collect the
> data?*
>
> This criterion addresses the issues of data measurability and
> collectability. One key issue is whether data are collectable even if
> the data are available, e.g., some potentially useful data may be
> proprietary to private firms.
>
> **Cost** -- *How expensive would it be to collect the appropriate
> data?*

For descriptive value and technical appropriateness, numerical scores on
an ascending scale of one to three were used. For data availability and
cost, qualitative descriptors were used. For availability, the following
descriptors were used: easy, not easy, and difficult. Easy means the
data series already exists or the required information is readily
obtainable. Not easy means some extra institutional effort is required
to obtain the data, e.g., if FHWA would have to go to State or local
governments to get some additional information, that is scored as not
easy. Difficult is used for cases where FHWA would have to obtain the
cooperation of private firms, and such firms might regard the data as
proprietary. For cost, the following descriptors were used: low, medium,
and high.

### Findings

The following table provides a summary of the ratings for each potential
measure.

Summary of Evaluations

+---------------------+---------+--------------+----------+-----------+
| Indicator           | **Desc  | **Technical  | **Data   | **Data    |
|                     | riptive | Appro        | Availa   | Cost**    |
|                     | Value** | priateness** | bility** |           |
+---------------------+---------+--------------+----------+-----------+
| Cost per ton-mile   | 3       | 3            | Easy     | Low       |
+---------------------+---------+--------------+----------+-----------+
| Fuel Consumption of | 1       | 2            | Easy     | Low       |
| Heavy Trucks per    |         |              |          |           |
| ton-mile            |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Cargo Insurance     | 2       | 2            | Easy     | Low       |
| Rates               |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| On-time Performance | 3       | 1            | D        | High      |
|                     |         |              | ifficult |           |
+---------------------+---------+--------------+----------+-----------+
| Point-to-Point      | 2       | 3            | Not easy | Medium to |
| Travel Times on     |         |              |          | High      |
| Freight-Signif.     |         |              |          |           |
| Hwys.               |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Hours of Delay on   | 2       | 3            | Not easy | Medium to |
| Freight-Signif.     |         |              |          | High      |
| Hwys.               |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Incident Delay on   | 2       | 3            | Not easy | High      |
| Freight-Signif.     |         |              |          |           |
| Hwys.               |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Ratio: Peak Travel  | 1       | 2            | Not easy | High      |
| Time to Off-peak    |         |              |          |           |
|                     |         |              |          |           |
| Travel Time         |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Ratio: Variance to  | 1       | 2            | Not easy | High      |
| Average for Peak    |         |              |          |           |
| Trip Times          |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Annual Miles per    | 2       | 1            | Easy     | Low       |
| Truck               |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Border Crossing     | 3       | 2            | Not easy | Medium    |
| Times               |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Conditions on       | 2       | 2            | Not easy | High      |
| Intermodal          |         |              |          |           |
| Connectors          |         |              |          |           |
+---------------------+---------+--------------+----------+-----------+
| Customer            | 2       | 3            | D        | High      |
| Satisfaction        |         |              | ifficult |           |
+---------------------+---------+--------------+----------+-----------+

Based on these evaluations, the following indicators are recommended as
worthy of further development by FHWA:

Cost of highway freight per ton-mile

Cargo insurance rates

Point-to-point travel times on selected freight-significant highways

Hours of delay per 1,000 vehicle miles on selected freight-significant
highways

Crossing times at international borders

Condition of connectors between NHS and intermodal terminals

**Customer satisfaction**

No rigid scoring methodology was used for the selection of recommended
indicators. In general, the measures that were recommended are those
that ranked highest in terms of descriptive value and technical
appropriateness. Data availability and costs are important
considerations for FHWA as it considers the use of these measures.
However, this does not mean that measures with relatively high data
costs should not be pursued. Customer satisfaction, for example, would
require considerable effort to design a survey, obtain the cooperation
of private firms, and carry out the survey on an annual basis.
Nonetheless, it was recommended because of the high value of the
information it could provide to FHWA.

Further development, and use, of this set of measures will provide FHWA
with valid measures of the effectiveness of the highway system's
contribution to national productivity through the efficient movement of
domestic and international freight.

### Analysis of Individual Indicators

***Cost of Highway Freight per Ton-Mile***

##### Descriptive Value  {#descriptive-value .unnumbered}

This indicator is readily understood as an indicator of freight
performance. Some clarification, however, may be required that this is a
measure of freight shipper cost, rather than a measure of carrier cost
or full social cost.

##### Technical Appropriateness {#technical-appropriateness .unnumbered}

Cost of highway freight per ton-mile is technically appropriate as an
indicator of freight performance. However, it is important to recognize
that the cost of freight haulage by truck is affected by many factors,
among which the performance of the highway system is but one. Cost of
highway freight also reflects drivers' wages and benefits, vehicle
depreciation, fuel cost, tax and insurance charges, and fees paid for
road and roadside facilities. As a result, this measure reflects freight
performance, but not solely in relation to the highway system. It also
only reflects costs, not the quality of service.

##### Data {#data .unnumbered}

Data are available for cost of highway freight per ton-mile from the
Financial and Operating Statistics (F&OS) maintained by the American
Trucking Associations (ATA). The total cost measure can be taken
directly from the F&OS. One of the primary strengths of this measure is
that data on costs and ton-miles can be taken from the same source,
which ensures that the data are comparable.

##### Scores {#scores .unnumbered}

  ---------------------------------------------- ------------------------
  Descriptive value                              3

  Technical appropriateness                      3

  Data availability                              Easy

  Data cost                                      Low
  ---------------------------------------------- ------------------------

***Fuel Consumption of Heavy Trucks per Ton-Mile***

##### Descriptive Value  {#descriptive-value-1 .unnumbered}

This measure is not easy to grasp as an indicator of freight
performance. Although the measure itself is comprehensible, the link
between fuel consumption and freight productivity is not readily
apparent to the public.

##### Technical Appropriateness {#technical-appropriateness-1 .unnumbered}

If the interest is in the impact of the highway system on truck costs,
fuel consumption per ton-mile is technically appropriate because it
strips out the effects of drivers' wages and fuel prices, both of which
affect cost and neither of which depends on highway performance. Fuel
consumption is affected, in part, by highway conditionsespecially
congestion. Fuel consumption per ton-mile is also, of course, affected
by changing technology of engines and fuels. Whether it would be
possible to find some effective way to normalize for changing technology
is an open question.

##### Data {#data-1 .unnumbered}

Fuel costs are available from the ATA's Financial and Operating
Statistics (F&OS). In order to extract fuel consumption, one would need
to develop an average fuel price (most likely for diesel fuel).
Alternatively, one could use data from FHWA's Highway Statistics on fuel
consumption by single-unit 2-axle 6-tire or more trucks. These data are
derived from state fuel tax records and may not be comparable to figures
on ton-miles (e.g., they may reflect impacts of improved tax compliance,
improved reporting methods, or other factors).

##### Scores {#scores-1 .unnumbered}

  ---------------------------------------------- ------------------------
  Descriptive value                              1

  Technical appropriateness                      2

  Data availability                              Easy

  Data cost                                      Low
  ---------------------------------------------- ------------------------

***Cargo Insurance Rates***

*Descriptive Value*

This indicator would require some explanation for a generalist, but the
explanation could readily be accomplished in a single paragraph.

##### Technical Appropriateness {#technical-appropriateness-2 .unnumbered}

Changes over time in cargo insurance rates will track very closely with
the value of loss-and-damage claims. From the point of view of shippers
and receivers, loss-and-damage is a significant aspect of the quality of
freight service. As a result, cargo insurance rates are appropriate as a
measure of one aspect of quality of service. Cargo insurance rates,
however, do not solely reflect the quality of the highway system; they
also reflect driver experience and loss and damage resulting from
pilferage and handling. Changing rates could also reflect changing cargo
values. Nonetheless, loss and damage is an important aspect of the
quality of freight service, and this measure merits further examination.

##### Data {#data-2 .unnumbered}

Data should not be a significant problem. Two potential sources have
been identified. One is the insurance companies themselves. They
routinely supply quotes for cargo insurance, and it is not proprietary
information. One viable approach would be to select a panel of a small
number of insurance companies and survey them once a year to get quotes.
Another source would be State insurance commissions. Insurance companies
regularly file their rates with the offices of the State commissions.
One could select a panel of States and arrange to obtain the data from
them on a regular basis.

##### [Scores]{.smallcaps} {#scores-2 .unnumbered}

  ---------------------------------------------- ------------------------
  Descriptive value                              2

  Technical appropriateness                      2

  Data availability                              Easy

  Data cost                                      Low
  ---------------------------------------------- ------------------------

***On-Time Performance for Highway-Freight Delivery***

##### Descriptive Value  {#descriptive-value-2 .unnumbered}

Descriptive value is high. It is clear that on-time performance means
performance in terms of meeting a stated goal for delivery time. The
definition of "on time," however, could present serious problems. The
very concept of being on time is different in different circumstances.
For some receivers, on time means delivery by a specified date and time.
Others demand delivery within a specific window of time, often specified
as a particular hour, e.g., between 10:00 AM and 11:00 AM.

##### Technical Appropriateness {#technical-appropriateness-3 .unnumbered}

This indicator reflects an aspect of the quality of service that is very
important to shippers and receivers. The definition of "on time" in a
systematic way that would work with data collection and manipulation
could present serious problems, however. While all the actors in the
freight business --- carriers, shippers, receivers, and others --- have
their own concepts of "on time" that is important for them, there is
probably significant variation in the details of their definitions.
Nonetheless, it is a very important measure of quality. It may well be
the case that this indicator may be better addressed within the
framework of the customer-satisfaction measure discussed below.

##### Data {#data-3 .unnumbered}

Many of the required types of data are proprietary. Obtaining it in any
systematic way would be difficult. It is also likely to be costly
because it would require the development of a survey of some sort. It is
fairly easy to gather anecdotal information by talking with third-party
marketers, logistics firms, and the like, but this is not the kind of
data that will support an official performance measure.

##### [Scores]{.smallcaps} {#scores-3 .unnumbered}

  ---------------------------------------------- ------------------------
  Descriptive value                              3

  Technical appropriateness                      1

  Data availability                              Difficult

  Data cost                                      High
  ---------------------------------------------- ------------------------

***Point-to-Point Travel Times for Freight-Significant Highways***

***Hours of Delay per 1000 Vehicle-Miles on Freight-Significant
Highways***

***Hours of Incident-Based Delay on Freight-Significant Highways***

##### Descriptive Value  {#descriptive-value-3 .unnumbered}

These three indicators are grouped together because they are concerned
with measures of speed and delay on freight-significant highways. This
is an important class of measures. They all rank high in terms of
descriptive value. Terms like speed, delay, and travel time require
little explanation. The term "freight-significant highways" requires
some description, however.

##### Technical Appropriateness {#technical-appropriateness-4 .unnumbered}

All three of these measures are technically appropriate as indicators of
freight performance in relation to the highway system. The concept of
the freight-significant highway is intended to link highway performance
more closely with freight performance. Without the connection to
freight-significant highways they would be measures of overall
highway-system performance, but would not tell much about the
performance of the system as a freight carrier. If certain stretches of
the NHS can be identified, in some way, as road segments with particular
significance for freight carriage, then these speed and delay indicators
would have real value as freight performance-measures. Incident-based
delay is especially important for trucking firms as this is the
component of transit time that is most difficult to predict.

In both conceptual and data terms, the greatest challenge in developing
these measures would be the identification of the freight-significant
highways. FHWA would have to develop a method or standard for
designating such roads, e.g., a disproportionately high percentage of
combination trucks in the traffic mix or some special significance of a
corridor because of the high levels of freight movement in it.

##### Data {#data-4 .unnumbered}

Data from the Highway Performance Monitoring System (HPMS) may be used
to designate freight-significant highways. The HPMS contains data on
traffic volumes and the percent of vehicles that are combination trucks
in the vehicle mix. One could determine which HPMS segments have high
truck traffic flows and use these to designate freight-significant
highways.

Once the freight-significant highways are identified, the data issues
are straightforward for travel time and delay but actual gathering of
data would require on-site observations. For the stretches of highway
designated (which could be 50 miles or 500 miles), it would be necessary
to make arrangements for direct measurements, e.g., with license plate
readers. Data on incidents on the relevant segments would have to be
gathered on a systematic basis and matched with observed delay in some
fashion. All of these direct observations would require special
arrangements with State and local governments and significant resources
would likely be required.

##### Scores: Point-to-point travel times for freight-significant highways {#scores-point-to-point-travel-times-for-freight-significant-highways .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          2

  Technical appropriateness                  3

  Data availability                          Not easy

  Data cost                                  Medium to high
  ------------------------------------------ ----------------------------

#####  {#section .unnumbered}

##### Scores: Hours of delay per 1000 vehicle-miles on freight-significant highways {#scores-hours-of-delay-per-1000-vehicle-miles-on-freight-significant-highways .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          2

  Technical appropriateness                  3

  Data availability                          Not easy

  Data cost                                  Medium to high
  ------------------------------------------ ----------------------------

#####  {#section-1 .unnumbered}

##### Scores: Hours of incident-based delay on freight-significant highways {#scores-hours-of-incident-based-delay-on-freight-significant-highways .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          2

  Technical appropriateness                  3

  Data availability                          Not easy

  Data cost                                  High
  ------------------------------------------ ----------------------------

***Ratio of Peak-Period Travel Time to Off-Peak Travel Time at
Freight-Significant Nodes***

***Ratio of Variance to Average for Peak Period Trip Times at
Freight-Significant Nodes***

##### Descriptive Value  {#descriptive-value-4 .unnumbered}

These two indicators measure congestion and reliability of travel in
metropolitan areas of special importance to freight movement. The first
of these is intended to measure the relative severity of peak-period
congestion, the second to measure the predictability of travel times in
peak periods. The term "freight-significant node" refers to cities or
metropolitan areas that are designated as especially important nodes in
the national freight network. These measures do not score well in terms
of descriptive value. They are somewhat technical in character; the
notion of a freight-significant node might be difficult to explain to a
generalist audience. The terms "ratio of peak-period travel time to
off-peak travel time" and "ratio of variance to average for peak period
trip times" also are somewhat difficult to understand.

##### Technical Appropriateness {#technical-appropriateness-5 .unnumbered}

The notion of "freight-significant nodes" is parallel to that of
freight-significant highways. Data on peak-period conditions in all
large cities would have little focus on freight; hence the idea of
identifying certain cities as of special importance for freight
movement. Such an identification, however, appears more difficult for
cities than for highways. Clearly, some cities originate or receive more
freight than others, but that does not necessarily mean they are more
critical in terms of movement of freight on the national network. There
appear to be real conceptual difficulties in finding a simple,
unambiguous standard for designating some metropolitan areas as
freight-significant.

##### Data {#data-5 .unnumbered}

Data problems relating to identification of freight-significant nodes
are closely entwined with the conceptual problems, i.e., it is not clear
what data one would seek. Regarding the actual measures, ratio of peak
to off-peak travel time should be derivable from the HPMS data on
volumes and capacity based on assumptions about peaking patterns. It is
known that, at one time, Cambridge Systematics developed a set of
empirically derived relationships between AADT/capacity ratios and
percentage of AADT in the peak period. Estimating the variance of
peak-period travel times could not be done with data from the HPMS.
Collection of data on the variance of travel time would require
arrangements for on-site observations.

##### [Scores: Ratio of peak-period travel time to off-peak travel time at freight-significant nodes]{.smallcaps} {#scores-ratio-of-peak-period-travel-time-to-off-peak-travel-time-at-freight-significant-nodes .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          1

  Technical appropriateness                  2

  Data availability                          Not easy

  Data cost                                  Medium to high
  ------------------------------------------ ----------------------------

##### Scores: Ratio of variance to average for peak period trip times at freight-significant nodes {#scores-ratio-of-variance-to-average-for-peak-period-trip-times-at-freight-significant-nodes .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          1

  Technical appropriateness                  2

  Data availability                          Not easy

  Data cost                                  High
  ------------------------------------------ ----------------------------

***Annual Miles per Truck***

*Descriptive Value*

Annual miles per truck is a measure of equipment utilization. It gets a
middle score on descriptive value. The concept itself is very easy to
understand; however, a generalist audience would not immediately
perceive its significance in regard to productivity or performance of
freight.

##### Technical Appropriateness {#technical-appropriateness-6 .unnumbered}

Annual miles per truck is a measure of utilization of equipment. In that
sense, it is a measure of the productivity of the trucking industry. Its
only significance to the users of the highway-freight system, however,
is that higher levels of equipment utilization have a favorable effect
on cost. It is doubtful that it would add much information if there were
another indicator measuring total cost. While miles per truck would
reflect, in part, speed and congestion conditions, it would also reflect
changing abilities of carriers to manage their fleets (including the
sizes of their fleets), changing characteristics of the trucking market,
i.e., length of haul, and other factors.

##### Data {#data-6 .unnumbered}

The data are directly available from the F&OS.

##### [Scores]{.smallcaps} {#scores-4 .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          2

  Technical appropriateness                  1

  Data availability                          Easy

  Data cost                                  Low
  ------------------------------------------ ----------------------------

***Crossing Time at International Borders***

##### Descriptive Value  {#descriptive-value-5 .unnumbered}

This indicator scores high on descriptive value. This measure is easy to
conceptualize.

##### Technical Appropriateness {#technical-appropriateness-7 .unnumbered}

The strength of this indicator is that it is a direct measure of freight
performance at specific points of some importance. Its weakness is the
obverse of its strength; it measures performance regarding a small
proportion of total freight movement. International border crossings,
however, are a highly visible component of international trade and are
of importance to the nation in terms of international commerce. As a
result, it would be appropriate for FHWA to focus on international
border crossings as a measure of freight performance even though this
measure only addresses a small portion of total freight movement.

##### Data {#data-7 .unnumbered}

Existing information on border crossing time is not tracked
consistently. It should be possible, however, to arrange for observation
of time in queues at selected crossings on the Mexican and Canadian
borders.

##### [Scores]{.smallcaps} {#scores-5 .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          3

  Technical appropriateness                  2

  Data availability                          Not easy

  Data cost                                  Medium
  ------------------------------------------ ----------------------------

***Performance on Connectors between the NHS and Intermodal Freight
Terminals***

##### Descriptive Value  {#descriptive-value-6 .unnumbered}

This indicator receives a middle score for descriptive value. Its
meaning and importance are fairly easy to grasp. Conditions,
particularly congestion and pavement condition, on the links between the
intermodal terminals and the main highways are important parts of the
system for carrying intermodal freight. A generalist audience may not
immediately understand how connectors are defined or how conditions are
measures (e.g., pavement quality measures, levels of service).

##### Technical Appropriateness {#technical-appropriateness-8 .unnumbered}

This indicator is a measure of the condition of roadway connectors. As a
result, it is not a direct measure of freight performance but rather a
measure of conditions that affect freight performance. Connectors are of
particular importance to intermodal freight movement, so it makes sense
to focus on these links.

##### Data {#data-8 .unnumbered}

[D]{.smallcaps}ata are a problem for this indicator. Regarding
congestion, intermodal connectors are tagged as such in the HPMS, so
there are some data on congestion. But there has been no systematic
effort to establish a sample of connectors. Those in the HPMS are there
by happenstance. They would constitute a small sample and, more
importantly, a badly designed one or, rather, one that has not been
designed at all. This could be rectified by asking the States to add a
substantial fraction of the 600-odd connectors to the HPMS. A
willingness to cooperate on the part of a large number of States would
be necessary and, almost certainly, resources to assist the States with
the effort would be required. Regarding pavement condition, data for all
connectors are in the HPMS, but there are doubts about the quality of
these data. A similar effort with the States would be necessary to make
sure of good pavement-condition data.

##### [Scores]{.smallcaps} {#scores-6 .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          2

  Technical appropriateness                  2

  Data availability                          Not easy

  Data cost                                  High
  ------------------------------------------ ----------------------------

***[C]{.smallcaps}ustomer Satisfaction***

##### Descriptive Value  {#descriptive-value-7 .unnumbered}

Customer satisfaction is an easy concept to grasp. However, it is a
somewhat "fuzzy" term that could be interpreted differently by different
audiences.

##### Technical Appropriateness {#technical-appropriateness-9 .unnumbered}

Customer satisfaction is a very appropriate measure of the performance
of highway and intermodal freight. This indicator could be defined in
many ways, however. It would, perhaps, be most useful if it were to be
based on a survey designed to identify how shippers, receivers, and
carriers view the performance of highway-freight movement (e.g., on-time
performance) and the performance of the highway system in supporting
freight movement. Views of carriers should be useful on the latter
point.

##### Data {#data-9 .unnumbered}

Data collection would involve issues associated with proprietary
information from businesses and the expense of designing a survey and
implementing it. Firms would need to be convinced that their anonymity
would be protected. Design of the survey would be a major undertaking
and one requiring, and meriting, substantial resources.

##### [Scores]{.smallcaps} {#scores-7 .unnumbered}

  ------------------------------------------ ----------------------------
  Descriptive value                          2

  Technical appropriateness                  3

  Data availability                          Difficult

  Data cost                                  High
  ------------------------------------------ ----------------------------

#  {#section-2 .unnumbered}

#  {#section-3 .unnumbered}

#  {#section-4 .unnumbered}

#  {#section-5 .unnumbered}

#  {#section-6 .unnumbered}

#  {#section-7 .unnumbered}

#   {#section-8 .unnumbered}

# Appendix A: Evaluations of Individual Studies {#appendix-a-evaluations-of-individual-studies .unnumbered}

This section provides a summary and evaluation of each study that was
examined. For each effort, we systematically document relevant
information about the effort (sponsors, report authors, participants,
date), summarize the relevant findings as they pertain to measures of
freight productivity performance, and assess the findings. Our focus in
evaluating each study is on the strength of conclusions and the
applicability of recommendations to FHWA.

Efforts have been divided into three categories:

-   *U.S. DOT efforts:* efforts sponsored by the Federal Highway
    Administration or other parts of the U.S. Department of
    Transportation;

-   *State and local efforts:* initiatives undertaken by State DOTs,
    metropolitan planning organizations, or local transportation
    agencies, typically as part of a transportation plan; and

-   *Academic efforts:* studies undertaken at universities or other
    institutions, typically with a focus on theoretical aspects of
    measuring freight productivity

## U.S. DOT Efforts

#### REPORT: *Examination of Transportation Industry Productivity Measures. Searching for Solutions (No. 8): An Examination of Transportation Industry Productivity Measures*, Summary of Proceedings: Highway-Related Transportation Industry Productivity Measures Symposium held in Arlington, Virginia on November 19-20, 1992.  {#report-examination-of-transportation-industry-productivity-measures.-searching-for-solutions-no.-8-an-examination-of-transportation-industry-productivity-measures-summary-of-proceedings-highway-related-transportation-industry-productivity-measures-symposium-held-in-arlington-virginia-on-november-19-20-1992. .unnumbered}

SPONSORS: U.S. Department of Transportation, Federal Highway
Administration (FHWA)

**AUTHORS:** FHWA

**PARTICIPANTS:** Approximately 80 participants from the U.S. Department
of Transportation (FHWA, Federal Railroad Administration, Federal
Transit Administration, Federal Aviation Administration, Office of the
Secretary, Volpe National Transportation Systems Center), other federal
government agencies (Bureau of Labor Statistics, U.S. Department of
Commerce, Army Corps of Engineers, Oak Ridge National Laboratory,
Interstate Commerce Commission), the Virginia Department of
Transportation, trade associations, transportation industry
representatives, consultants, and academia.

**DATE:** Symposium held on November 19-20, 1992. Report published July
1993.

**SUMMARY:**

The symposium focused on issues in measuring transportation industry
productivity and, in particular, the difficulty of measuring
productivity in the motor carrier industry. It provided an opportunity
for participants to discuss technical issues and users' needs related to
transportation productivity measures, with a focus on the transportation
industry's economic performance. The overall focus was productivity of
transportation industries (including the trucking industry), not the
performance of the highway system or of FHWA relative to freight
productivity. It was noted, however, that transportation infrastructure
investment has an effect on transportation productivity, which in turn
can be a big contributor to the bottom line of U.S. industry and the
economy.

The panelists generally agreed on the difficulties in measuring
transportation industry performance. Randall Eberts, Assistant Vice
President and Economist of the Cleveland Federal Reserve Bank maintained
that several levels of economic performance must be considered in
linking public capital infrastructure with overall economic
productivity: 1) performance of the transportation facility (e.g.,
efficiency, condition); 2) performance of the transportation industry as
a whole (e.g., how elements work together to provide productive
service); and 3) aggregation from the local economy to the international
economic picture.

Traditional industry measures of physical productivity and performance,
such as route-miles, number of terminals, and percentage of empty
vehicle-miles, were identified, as well as labor productivity and
multifactor productivity measures (e.g., output per unit of combined
labor, capital, and intermediate outputs). Firm-level measures were also
identified, such as dock productivity, pickup and delivery productivity,
freight bills handled per hour, and average load factors.

Difficulties in measuring productivity in the motor carrier industry
were noted. In particular, Paul Roberts, President of Transmode
Consultants, noted that the measure of productivity is complicated
because of difficulties in measuring inputs and outputs, as well as the
different outlooks of economists and engineers (e.g., economists measure
productivity in dollars, while engineers use physical measures). Some of
the presentations suggested that traditional measures in terms of
ton-miles carried are deficient because they fail to account for the
quality of service provided; that is, more ton-miles carried per unit of
labor appears to be a productivity improvement, but it does not capture
improvements in reliability and on-time delivery.

Bahar Norris, Senior Economist at the U.S. DOT Volpe Center noted that
changes in price are not the same as changes in productivity and made a
distinction between "performance" measures and "productivity" measures.
For example, she suggested that price reductions that occurred in the
1980s were the result not of productivity factors but of declines in
fuel prices and a reduction in excess profits due to increased
competition. Norris also noted that single factor productivity measures,
such as those considering only a change in labor units, are deficient
because they fail to consider all factors in production. According to
Thomas Corsi, Professor of Transportation, Business, and Public Policy
at the University of Maryland, multifactor productivity measures are
also suspect because they are highly sensitive to the specific inputs
and outputs selected and to the weights given to each measure.

Instead of multifactor productivity measures, the motor carrier industry
tends to use three indicators:

> Annual miles per truck
>
> Average load per truck
>
> Average length of haul

Other potential measures of highway freight transportation productivity
identified by participants were:

> Ratio of inventory to monthly sales of manufactured goods (reflects
> speed and reliability)
>
> Route-miles of less-than-truckload (LTL) carriers
>
> Tons, or number of shipments, per terminal - a measure of terminal
> performance
>
> Percentage of empty vehicle-miles

Questions raised by the panelists included:

-   How should transportation productivity be defined and measured
    across and within different transportation modes

-   How can methods of acquiring data be developed to include all
    transportation activity?

-   To what extent are transportation productivity measures related to
    service quality measures?

-   What role should customer satisfaction and private-sector
    performance have in productivity measurements?

-   

Several ways to improve transportation productivity were also
identified: increasing connectivity (adding new links in the highway
network to decrease mileage and travel time), increasing service levels
on existing links (making improvements to reduce time, fuel, and other
inputs), improving the efficiency of operations (e.g., by increasing
vehicle utilization, reducing empty miles), and reducing the costs of
primary inputs (e.g., reduce costs of labor, equipment, and facilities).

PERFORMANCE MEASURES PRESENTED:

In the final breakout sessions, the following transportation
productivity measures were suggested:

> Empty/loaded ratio for truck moves
>
> Annual miles per truck
>
> Average length of haul by vehicle
>
> Energy consumption per ton-mile
>
> Labor cost per ton-mile

The measures judged most appropriate for public policy evaluation were
empty vs. loaded miles, average length of haul, and energy consumption
per ton-mile.

**ASSESSMENT:**

This symposium provides a good overview of issues associated with
measuring freight productivity. This effort, however, focused on
performance of the transportation industry with generally little
relation to the performance of the highway system. As a result, some of
the measures identified in the symposium are not strong measures of
freight performance as it relates to the highway system. For example,
measures such as average load per truck and percent of empty vehicle
miles have more to do with logistics and efficiency of schedules than
the condition of the transportation system.

Other performance measures suggested at the symposium relate indirectly
to highway condition and capacity. For example, energy consumption per
ton-mile would be affected by highway quality (as well as other factors
like the size of trucks). The condition of the highway system would also
have some effect on annual miles per truck and labor cost, since both
could be affected by speed.

REPORT: *The Productivity Effects of Truck Size and Weight Policies*

SPONSORS: U.S. Department of Transportation, Federal Highway
Administration (FHWA)

**AUTHORS:** David Middendorf and Michael Bronzini, Oak Ridge National
Laboratory

**PARTICIPANTS:** N/A

**DATE:** November 1994

**SUMMARY:**

The report is concerned with the effect on transportation productivity
of allowing longer and/or heavier trucks. Productivity is measured in
terms of transportation costs plus logistics costs, with transit time,
inventory levels, etc., included in the latter category. It is not
concerned with the performance of the highway system as such.

**PERFORMANCE MEASURES PRESENTED:**

As noted, the study used transportation cost, to the shipper, plus
logistics costs, for analyzing the effects of various policy options.

**ASSESSMENT:**

These are sensible measures of freight-service performance from the
point of view of shippers. The problem is linking these measures
specifically to the highway system. The report notes that there are
major problems in securing data on logistics costs, because firms do not
want to divulge such information for fear it will reach their
competitors.

REPORT: *The Use of Intermodal Performance Measures by State Departments
of Transportation*

SPONSORS: U.S. Department of Transportation

**AUTHORS:** Czerniak; R., S. Gaiser; and D. Gerard; Department of
Geography, New Mexico State University

**PARTICIPANTS:** N/A

**DATE:** June 1996

**SUMMARY:**

The report identifies intermodal performance measures by State
departments of transportation. The Intermodal Surface Transportation
Efficiency Act of 1991 (ISTEA) mandated that all States implement a
performance-based planning process aided by an Intermodal Management
System (IMS). States were mandated to develop work plans and inventories
of intermodal facilities, to establish performance measures, and to
collect data. Although these requirements were subsequently dropped,
many states continued with the development and implementation of such
systems.

This study identifies intermodal performance measures for freight and
passenger movement, categorized by their relationship to a set of goals.
The authors found 15 States that had developed performance measures of
this type for their intermodal management systems. The report discusses
the role of performance measures in the transportation planning process.

**PERFORMANCE MEASURES PRESENTED:**

Intermodal freight performance measures are classified by six goals as
shown below.

Goal 1: Accessibility of intermodal facilities

-   Level of service

-   Conditions of a transportation route

-   Bridge restrictions (e.g., weight restrictions)

-   Queuing of vehicles

-   Turning radius into facility

-   Deficiencies of the facility (e.g., number of structures lacking
    21\' vertical clearance)

Goal 2. Availability of intermodal facilities

-   Volume-to-capacity ratios

-   Railroad track capacity

-   Storage capacity

Goal 3: Cost and Economic Efficiency

-   Cost per ton-mile by mode

-   Revenue ton-miles

-   Expenditures (e.g., for freight rail, to retire deficiencies)

Goal 4: Safe Intermodal Choices

-   Number of accidents

-   Cost of accidents

-   Number of fatalities

Goal 5: Connectivity between modes or intermodal connectivity ease of
connection

-   Number of intermodal facilities

-   Delay of trucks at facilities

-   Travel times

Goal 6: Time

-   Total transfer time

-   Freight transfer time between modes

-   Average travel time

**ASSESSMENT:**

The narrow focus of this study on intermodal facilities limits its
usefulness to FHWA. It is not directly concerned with overall highway
system performance in moving freight. Goals 1 and 2, accessibility and
availability of intermodal facilities, are more appropriate for a state
than FHWA in examining freight performance. A number of the measures are
also "internal" measures dealing with the operation of an intermodal
facility. Other indicators are really measures of activity, such as the
number of vehicles accessing a facility or number of revenue ton-miles
carried.

Goals 3 to 6 have somewhat more relevance for evaluation of freight
performance as it relates to the highway system. However, again, many of
these indicators focus on internal facility measures or general activity
measures at facilities. Under Goal 3, the cost per ton-mile measure is
potentially useful as a national performance measure, but some of the
other cost measures are not. For example, while "expenditures to retire
deficiencies" does have an impact on freight, it is not a measure of
performance. Increased highway spending does not necessarily mean an
improvement in freight performance; it could mean inefficient allocation
of resources.

REPORT: *Workshop on Productivity Performance Indicators: Report of
Proceedings.*

SPONSORS: U.S. Department of Transportation, Federal Highway
Administration (FHWA)

**AUTHORS:** Hickling Lewis Brod, Inc.

**PARTICIPANTS:** Various economists and policy analysts from FHWA, the
Bureau of Transportation Statistics (BTS), the Volpe Transportation
Center, the Congressional Budget Office, freight/logistics companies,
and consulting firms.

**DATE:** May 15, 1998

**SUMMARY:**

This report summarizes proceedings of a workshop sponsored by the FHWA
Office of Policy Development on March 12, 1998 to review and suggest
appropriate indicators for the "productivity" element of the agency's
Performance Plan. An advisory panel identified 21 potential productivity
indicators and ranked these based on conceptual suitability,
measurability, and communicative value of the proposed indicators.

**PERFORMANCE MEASURES PRESENTED:**

The top ten indicators in terms of overall merit as judged by the panel
members (and ranking, in scale 1-4) were:

-   cost of highway freight per ton-mile (3.9)

-   hours of delay per 1000 vehicles processed at border crossings (3.4)

-   ratio of variance to average minutes per trip in peak periods in
    major metro areas (3.3)

-   hours of delay per 1000 vehicle-miles (3.1)

-   hours spent waiting at toll plazas per 1000 vehicle-miles (2.9)

-   hours spent waiting at weigh stations per 1000 ton-mile (2.9)

-   contribution of investment to GDP growth (2.6)

-   net present value of improvements (2.4)

-   average minutes per trip in peak period in major metro areas (2.3)

-   total public and private costs of travel (2.3)

Based on the judgement of the consultants, the report recommends six
indicators as meriting further investigation as candidates for inclusion
in FHWA's Performance Plan:

-   cost of highway freight per ton-mile

-   contribution of investment in highways to GDP growth

-   net present value (or current year benefit-cost ratio) of highway
    improvements

-   average minutes per trip in peak period in major metro areas

-   ratio of variance to average minutes per trip in peak periods in
    major metro areas

-   total public and private costs of travel

**ASSESSMENT:**

This effort identified a number of potentially useful indicators of the
impact of the highway system on productivity. The effort is not focused
specifically on freight but more broadly on measures that can be used to
gauge FHWA's progress in attaining its productivity-related strategic
goal, "Continuously improve the economic efficiency of the Nation's
transportation system to enhance America's position in the global
economy." Each potential indicator is described and issues such as data
availability and applicability are discussed at a basic level.

The authors do not explain why their recommendations of six indicators
that merit further investigation do not match with the top six
indicators identified by the panel. The authors appear, however, to have
selected indicators that broadly address the economic impacts of highway
investments. They did not include measures that only address specific
aspects of travel, such as hours of delay at border crossings, toll
plazas, or weigh stations. Indicators that focus on these aspects of
travel have more of a direct connection with freight traffic but
presumably were considered too narrow as national indicators.

Some of the measures recommended by the authors do not address freight
specifically, but focus on the overall economic costs and benefits of
highway investments. For example, net present value (or current year
benefit-cost ratio) of highway improvements accounts for benefits such
as travel time savings, accident cost savings, and vehicle operating
cost savings. While these cost savings clearly have positive
implications for productivity, benefits accrue to both freight and
personal travel, with a large portion of the benefits of most highway
projects coming from personal travel time savings. As a result, net
present value (or current year benefit-cost ratio) of highway
improvements is not a measure of freight productivity but rather a
measure of the total economic efficiency of highway investment.

"Total public and private costs of travel" appears to be a weak measure,
even though it was recommended by authors as worth further consideration
(in contrast, the panel ranked this measure relatively low). This
measure is difficult to understand conceptually, is difficult to use to
track progress over time, and has problems of data availability. The
concept behind this measure is that the optimal transportation system
minimizes total "costs" when one accounts for total public and private
costs. In a standard benefit-cost analysis framework, an increase is
costs is not necessarily bad if it is more than offset by an increase in
benefits (e.g., travel time and vehicle operating cost savings may more
than offset the cost of an infrastructure investment). Under this
measure, however, beneficial project impacts are viewed as a reduction
in cost (e.g., a reduction in travel time costs) rather than as a
benefit. In order to use this measure, one must account for all public
and private sector transportation costs. This would be fine in a static
system. However, in a growing economy, one sees not just changes in
travel time costs, operating costs, and infrastructure construction and
maintenance, but also changes in the amount of travel. The benefits of
new travel are not addressed in this framework since the focus is solely
on costs. The measure also has a negative focus.

REPORT: *The Role of the National Highway System Connectors: Industry
Context and Issues*

SPONSORS: U.S. Department of Transportation, Federal Highway
Administration (FHWA)

**AUTHORS:** A. Strauss-Wieder, Inc., KPMG Peat Marwick LLP, Louis
Berger and Associates, Parsons Brinkerhoff

**PARTICIPANTS:** N/A

**DATE:** February 1999

**SUMMARY:**

The primary purpose of the report is not the development of performance
measures. Its focus is on intermodal connectors and what can be done to
improve them. A National Highway System (NHS) connector is a public road
leading to a major intermodal terminal; this includes passenger as well
as freight facilities.

**PERFORMANCE MEASURES PRESENTED:**

The report mentions five "qualities" of freight service that are
important to shipping firms:

1.  Reliability - consistently ensuring that goods are delivered on the
    specified date at the specified time in the specified amount in the
    specified condition

2.  Transit time - meeting arrival times (time definite service)

3.  Efficiency - optimally using transportation equipment to minimize
    costs

4.  Cost - obtaining the lowest possible cost for moving goods
    (regardless of the number of modes involved)

5.  Damage minimization

The report emphasizes that the focus is on these characteristics rather
than on individual modes and routes. Intermodal connectors and allow
transportation providers to use the best of each mode and increasingly
play an essential role in ensuring the reliability, transit time,
efficiency, and cost sought by shippers.

**ASSESSMENT:**

These are perfectly rational measures in terms of what is important to
freight customers. It is not completely clear why a customer would care
about a carrier's equipment utilization other than through its effect on
cost, but cost is already listed as one of the measures. Conceptually,
these are all good measures of the quality or cost of freight service.
Specific indicators would need to be developed to measure these
characteristics (e.g., measures of reliability, such as percent on-time
arrivals or average variability in point-to-point travel times).

## State and Local Efforts

REPORT: *Regional Freight Mobility Action Packages*

SPONSORS: Regional Freight Mobility Roundtable, Puget Sound Regional
Council

**AUTHORS:** Harvey Consultants, Inc., Transmode Consultants, Inc.,
Ellen Kret Porter

PARTICIPANTS: Regional Freight Mobility Roundtable includes shippers,
carriers, and third-party interests in the Puget Sound region. The
Roundtable is concerned with freight movement by highway, rail, ship,
and air. The Puget Sound Regional Council is the MPO for the Seattle
area.

**DATE:** September 6, 1994

**SUMMARY:**

The purpose of the report and an ensuing meeting of the Regional Freight
Mobility Roundtable was to develop a package of freight actions for
inclusion in the Metropolitan Transportation Plan prepared by the MPO
(Puget Sound Regional Council). The plan includes highway improvements
but does not have an exclusive highway focus. The performance measures
were developed as a by-product of the package of freight actions.
Performance measures were not the focus of the effort.

**PERFORMANCE MEASURES PRESENTED:**

1.  Transit time (and order-cycle time)

2.  Transportation and logistics costs

3.  Schedule reliability

4.  Safety

**ASSESSMENT:**

Transit time is straightforward, especially if read as transit time for
highway-freight movements. Transportation costs and reliability are also
important, but more specificity would have been useful. The fourth
measure, safety, is less a measure than a goal. Something like number of
truck crashes might be more useful. The report, however, appears to be
concerned with overall transportation safety in this case, not reduction
of accidents linked to freight movements.

It should be noted that a later report, the *1998 Progress Report* of
the Puget Sound Regional Council, a follow-up to the 1995 Metropolitan
Transportation Plan, made no reference to these performance measures.
There is a reference to a requirement for good data, but the context is
not clear.

REPORT: *Intermodal Performance Measures for the Bay Area Transportation
System*

SPONSORS: Metropolitan Transportation Council (San Francisco MPO)

AUTHORS: David W. Jones

**PARTICIPANTS:** N/A

**DATE:** June 20, 1995

**SUMMARY:**

This report addresses multi-modal performance measures designed to track
effectiveness and efficiency of the San Francisco Bay Area's
transportation system. The focus is on measures of mobility that are
user-oriented and multi-modal. The report includes four case studies of
the Bay Area's transportation system, one of which addresses goods
movement.

The goods movement case study discusses effectiveness of freight
movement in the context of United Parcel Service (UPS), a
package-express company and Consolidated Freightways (CF), a major
less-than-truckload (LTL) operator. Both types of operation use large
trucks (plus airplanes and rail intermodal in the case of UPS) for the
line haul and smaller vehicles for delivery. It notes that both
companies are 24-hour operations, which enable them to schedule
line-haul movements during hours when congestion is minimal and the
highway system is operating most reliably. The report notes that because
most trucking companies have optimized their operations to avoid freeway
congestion during peak commute hours, the highway system's day to day
reliability is the performance attribute most important for shippers and
carriers. It also suggests that relatively narrow peak periods are an
important highway-system attribute for freight.

**PERFORMANCE MEASURES PRESENTED:**

While the report does not explicitly put forward performance measures,
the two attributes mentioned above, reliability and narrow peaks, are
certainly important for freight productivity and could be used to
develop performance measures.

**ASSESSMENT:**

This study provides a good discussion of highway-system characteristics
that are important for the effectiveness and efficiency of urban goods
movement.

**REPORT:** *Report to Statewide Model Task Force on Freight Modeling
and Forecasting Techniques*

SPONSORS: State of Florida

**AUTHORS:** Draft prepared by Florida Department of Transportation

#### PARTICIPANTS: N/A {#participants-na .unnumbered}

**DATE:** February 1998

**SUMMARY:**

This report was requested by the Stateside Model Task Force to provide
an overview of freight planning and modeling processes in Florida and
around the nation. It reports on the Florida's Intermodal Management
System (IMS) Pilot Project, which was designed to address ISTEA
mandates. A highlight of Florida's IMS Pilot was the development of
performance measures designed for intermodal system evaluations.

**PERFORMANCE MEASURES PRESENTED:**

The following possible measures were put forward:

-   cost per ton-mile by mode

-   revenue per ton-mile by mode

-   maintenance cost of connector links

-   insurance cost (for freight)

-   direct and indirect jobs created

-   change in fuel consumption per ton-mile

**ASSESSMENT:**

Although the focus of this work was intermodal, most of these would be
useful for overall highway-freight purposes. The exception is jobs
created; aside from the difficulty of measuring this indicator, it is
not a valid measure of freight performance or economic efficiency.
Insurance cost is a proxy for loss and damage, which is an important
aspect of the quality of freight movement. As a result, insurance cost
could be used as a performance measure.

REPORT: *CommunityLink 21: 1998 Regional Transportation Plan*

SPONSORS: Southern California Association of Governments

**AUTHORS:** N/A

**PARTICIPANTS:** N/A

**DATE:** April 16, 1998

**SUMMARY:**

SCAG's 20-year transportation plan includes goals, objectives, and
policies for Southern California. It offers performance indicators to
compare a 2020 baseline with the 2020 plan. The discussion is not
focused specifically on freight, but addresses topics of general
highway-performance, two of which relate to freight movement: mobility
and reliability.

**PERFORMANCE MEASURES PRESENTED:**

-   Mobility: PM peak highway speed; percent of PM peak travel in delay

-   Reliability: percent of on-time arrivals

**ASSESSMENT:**

The mobility measures are basic measures of highway-system performance
that are reflective of general highway traffic (primarily personal
travel). They are relevant to freight-movement performance, but, as
offered here, are quite general. To be more focused on freight
performance, the measures may need to be more specific to freight
movement, such as PM peak highway speed on highway routes of particular
importance to freight or on roads with a relatively high portion of
truck traffic. The reliability measure is freight-specific but is
difficult to develop as an indicator because of data availability
problems.

**REPORT:** *1998 California Transportation Plan: Statewide Goods
Movement Strategy*

SPONSORS: California Department of Transportation (Caltrans)

AUTHORS: California Department of Transportation (Caltrans)

**PARTICIPANTS:** Caltrans received input from a California
Transportation Plan Policy Advisory Committee (PAC) and Statewide
Intermodal Goods Movement Advisory Committee (SIGMAC). These committees
were composed of stakeholders from local governments, metropolitan
planning organizations (MPOs), ports, railroads, shippers, FHWA,
consultants, and other stakeholders.

**DATE:** August 1998

**SUMMARY:**

The Statewide Goods Movement Strategy was developed as part of the
overall transportation plan in a conscious decision to make improvement
of freight movement an explicit component of the overall plan. The
document is a strategic policy and action blueprint that identifies
strategic policies, goals, and objectives. Further, the report
identifies development of freight performance measures as a long-term
action item in the strategy. Some performance measures are offered,
although their development is not the main focus of this initial effort.

**PERFORMANCE MEASURES PRESENTED:**

1.  Hours of incident-based delay.

2.  Hours of recurrent delay.

3.  Lane-miles of high-level highway requiring rehabilitation.

4.  Crossing time for trucks at Mexican border.

5.  Crossing time for trucks at the state's domestic borders.

**ASSESSMENT:**

The first three are standard highway-performance measures. They reflect
highway conditions, which certainly have a bearing on freight travel.
However, they are not specific to freight or focused particularly on
freight productivity. They address issues related to travel time,
reliability, and safety. The last two are certainly truck-specific and
probably important. However, they focus only on border crossings, and
are not reflective of performance of the highway system as a whole. Only
a portion of freight traffic crosses state or international borders.
These measures are useful as facility-specific types of measures that
could be used to compare and track progress among border crossings, but
are somewhat less useful as a national measure of freight performance.

REPORT: *Goods Movement Issue Paper*

SPONSORS: East-West Gateway Coordinating Council (St. Louis region MPO)

AUTHORS: East-West Gateway Coordinating Council, with input from freight
stakeholders

**PARTICIPANTS:** N/A

**DATE:** August 1998

**SUMMARY:**

The goods movement issue paper was developed in conjunction with the
long-range transportation plan for the St. Louis region, called
"Transportation Redefined." Efficient movement of goods is one of seven
focus areas established in the plan to guide strategic problem solving.
As background, the issue paper highlights the importance of goods
movement efficiency, identifies and describes the region's multi-modal
and intermodal freight system and facilities, and describes commodity
flows. It also provides the overarching vision and goals for freight
movement in the region, including 22 objectives and 23 investment
projects. The final section of the White Paper is focused on performance
measures. It provides a brief background on performance measures, those
considered, and the proposed performance measures for the region. Rather
than selecting a few specific data measures, the paper presents a hybrid
of measures for major categories of issues.

**PERFORMANCE MEASURES PRESENTED:**

1.  Connectivity/Congestion measures:

-   Average speed on the regional roadway network.

-   Truck counts at several key locations on the region's Priority Goods
    Movement Network (PGMN).

2.  Reliability measure: Level-of-service below C on PGMN roadways.

3.  Intermodal measures:

-   Tons of air freight departing Lambert-St. Louis International
    Airport

-   Tons of cargo transported through the port

-   Number of intermodal lifts that occur yearly at the local intermodal
    facilities

4.  Safety measures:

-   Number of at-grade railroad crossings in the Region/or on the PGMN.

-   Number of overpasses in the Region (or on the PGMN) that have
    vertical clearance restrictions.

-   Number of weight restricted bridges in the Region (or on the PGMN).

-   Intersections with inadequate turning radii for 53\' trailers in the
    Region (or on the PGMN).

-   High accident locations on the PGMN as well as total number of
    accidents (to detect trends).

-   Ramp geometry where site distance to poor or sharp turns are
    required.

-   Pavement life remaining on PGMN routes.

5.  Economic / Environmental measures:

-   Value of the freight that is moved from, to and within the region to
    develop an overall (Direct, indirect and induced) economic impact.

-   Number of people employed in five (5) or so major economic sectors
    in the St. Louis Region such as transportation, distribution, and
    manufacturing.

-   Amount of warehouse space available in the St. Louis region and
    Current Occupancy Rate of the warehouse space.

-   Number of projects and dollars expended on the PGMN.

**ASSESSMENT:**

Although most of these measures relate directly to freight travel, they
do not focus directly on productivity. Many of the measures are
indicators of freight transport activity, but none are real indicators
of how productive or efficient freight transport is.

REPORT: *Act 51 White Paper -- State Trunklines: Performance Measures*

SPONSORS: Michigan Department of Transportation

**AUTHORS:** Act 51 Transportation Funding Study Committee

**PARTICIPANTS:** N/A

#### DATE: 1999 {#date-1999 .unnumbered}

**SUMMARY:**

This White Paper summarizes Michigan DOT's strategic objectives and
highway performance measures as identified in the Michigan DOT's FY 2000
budget. There was not a specific focus on freight movement.

**PERFORMANCE MEASURES PRESENTED:**

-   Increase the percent of miles of state trunklines with surface
    condition classified as good

-   Increase the number of trunkline bridges rated as good

-   Reduce the percent of state trunklines experiencing congested
    traffic flow

-   Reduce the rate of fatal accidents

#### ASSESSMENT: {#assessment .unnumbered}

These are general highway-system measures. They have some relevance to
freight movement, as do all general measures of highway performance, but
they lack a freight focus.

REPORT: *Transportation System Performance Measures: Applicability of
Indicators to Goods Movement*

SPONSORS: California Department of Transportation (Caltrans)

**AUTHORS:** Booz-Allen & Hamilton

**PARTICIPANTS:** Received input from Caltrans staff, including the team
that developed the freight module of the California Transportation Plan
(CTP) and the System Measures Working Group

**DATE:** June 30, 1999

**SUMMARY:**

This report addresses the applicability of performance indicators to
goods movement as part of the Performance Measurement initiative of
Caltrans. It concludes that it is feasible for the State and regional
partners to apply performance measures that relate to freight movement.
Based on an evaluation of outcomes from the State's Transportation
System Performance Measures report, the authors select six outcomes as
applicable to goods movement: mobility/accessibility, reliability,
economic well-being, environmental quality, safety and security, and
equity.

**PERFORMANCE MEASURES PRESENTED:**

Of the "outcomes" and indicators identified from the State report, the
following are most directly related to freight performance and
productivity:

+----------------------------+-----------------------------------------+
| **Outcome**                | **Indicator**                           |
+----------------------------+-----------------------------------------+
| Mobility/Accessibility     | Travel time                             |
+----------------------------+-----------------------------------------+
|                            | Delay (lost time)                       |
+----------------------------+-----------------------------------------+
|                            | Accessibility to intermodal facilities  |
+----------------------------+-----------------------------------------+
| Reliability                | Standard deviation of travel time       |
+----------------------------+-----------------------------------------+
| Safety and Security        | Safety rates                            |
|                            |                                         |
|                            | \- Accident rate                        |
|                            |                                         |
|                            | \- Fatality rate                        |
+----------------------------+-----------------------------------------+
| Economic Well-Being        | Final demand (the value of all          |
|                            | transportation-related goods and        |
|                            | services delivered to the final         |
|                            | customer) generated by transportation   |
|                            | projects                                |
+----------------------------+-----------------------------------------+

**ASSESSMENT:**

These indicators all have some relationship to the productivity of
freight movements, with the mobility/accessibility and reliability
measures most directly useful. Other outcome goals identified as
relevant to goods movement --- environmental quality and equity --- do
not really address the issue of productivity.

Safety is critical to the trucking industry for reasons of liability,
industry reputation, potential revenue loss and productivity. The
industry pays close attention to trends involving accidents, with
particular emphasis on specific safety risks such as rail grade
crossings and the potential operational disruptions associated with
accidents and lack of alternate routes. According to this report, truck
safety data are fairly difficult to access. In any case, the number of
fatalities, which are probably the most accessible data, relate less to
freight productivity than to concerns about loss of life and medical
injuries.

The mobility/accessibility and reliability indicators are standard
measures of highway-system performance. Reliability is one of the most
important outcomes for shippers. Poor accessibility to many delivery
locations exacerbates truckers' reliance on the highways to travel just
in time for delivery at the point of destination. Travel time and delay
information is also of interest to shippers for scheduling, routing,
equipment utilization, shift assignment, and overtime management
reasons. However, using the same travel time and delay figures
experienced by commuters as a measure of that experienced by truck
drivers may not be an accurate assessment.

Accessibility to intermodal facilities is the most freight-focused of
these measures.

The last indicator, final demand for the value of transportation-related
goods and services delivered to final customers, can be applied to goods
movement by measuring one of the following final demand generated by
transportation improvement projects. This measure is actually quite
difficult to develop. Although there are several sources of information
on total economic activity, these data do not relate to highway
improvement projects, and so are simply measures of total economic
activity. Total economic activity, in turn, is affected by such factors
as macroeconomic cycles, industry trends, and tax policies. Data are
also available on how much transportation services contribute to Gross
Domestic Product (GDP), but it is not clear whether more spending on
transportation services means that freight transport is more productive
or not. According to the Booz-Allen & Hamilton report, input-output
models, like the REMI regional economic model, could be used to measure
final demand in response to transportation projects. Use of such as
model is probably most applicable at a regional level for forecasting
rather than monitoring performance.

REPORT: *Freight Moves the Oregon Economy*

SPONSORS: Oregon Department of Transportation

#### AUTHORS: Oregon Department of Transportation {#authors-oregon-department-of-transportation .unnumbered}

**PARTICIPANTS:** N/A

**DATE:** July 1999

SUMMARY:

This report identifies several types of performance measures developed
in various Oregon transportation plans or similar efforts. The
particular planning efforts examined were: Oregon's Intermodal
Management System (IMS); the 1999 Oregon Highway plan; and the Oregon
Commercial Vehicle Safety Plan. Each of these produced some performance
measures.

**PERFORMANCE MEASURES PRESENTED:**

[Oregon IMS:]{.underline}

> For connector roads and highways:

-   Volume-to-capacity ratios (average weekday PM V/C ratio,
    intersection average weekday PM peak hour V/C ratio)

-   Pavement condition

-   Accident rates

-   Annual hours of truck delay

> For intermodal terminals:

-   Annual throughput as a percentage of capacity

-   Number of hours daily when service is available

-   Number of hours waiting in line outside the terminal gate

[1999 Oregon Highway Plan:]{.underline}

> For the Highway Plan policy addressing the State highway freight
> system:

-   Percent of freight-system lane miles that meet State highway
    mobility standards during the peak hour or peak two hours peak
    period; and

-   Number and percent of accidents on the designated State Highway
    Freight System involving trucks

> For the Highway Plan policy addressing travel alternatives:

-   Percentage of identified obstacles to freight movement that are
    eliminated through action of the State or the State in partnership
    with others

-   Percentage (or number) of intermodal connectors improved.

[Oregon Commercial Vehicle Safety Plan:]{.underline}

-   Reduce sleep/fatigue-related truck crashes

-   Reduce truck crashes related to speed, following too closely, unsafe
    lane change, and unsafe turns

-   Decrease mechanical out-of-service percentage for intrastate
    carriers

**ASSESSMENT:**

This study is considerably above the average. A number of the measures
presented are not only relevant to highway freight but specific to
trucks. Annual hours of truck delay is a good example, but it also
raises a question about data. The idea of designating a freight system
is a good one; the test would be whether roads that carry a
disproportionate share of freight or are key links in the freight
network were actually selected. If it is simply the high-level roads,
then measures based on it are still general highway measures. Percentage
of obstacles to freight movement removed would be good in principle.
There is an obvious problem of definition and counting; what is an
obstacle and how do you establish the base number of obstacles? An
appealing feature of this measure is that it actually ties back to
actions of the State.

REPORT: *Freight Performance Measures: A Yardstick for Minnesota's
Transportation System*, Preliminary Draft, subject to review and
approval.

SPONSORS: Minnesota Department of Transportation

**AUTHORS:** Mark Berndt and Mark Larson, Minnesota Department of
Transportation

**PARTICIPANTS:** Minnesota Freight Advisory Committee (MFAC) MFAC is
made of shippers and carriers that advise MINNDOT on freight issues. To
a large extent, the report reflects MFAC recommendations.

**DATE:** August 25, 1999

**SUMMARY:**

This is an effort with the explicit goal of developing freight
performance measures for a transportation system and largely for the
highway system. It is not the result of a concentrated study, rather the
result of a one-day meeting at which MFAC members devoted themselves to
discussing and proposing performance measures.

**PERFORMANCE MEASURES PRESENTED:**

The report presents a number of indicators, classified, in part,
according to availability of data.

[Performance measures with data available:]{.underline}

1.  Freeway travel time, by route and time of day

2.  Average speed on freeways, by route and time of day

3.  Congestion ranking of freeways, by route

4.  Relative congestion levels of major metropolitan areas

5.  Benefits to heavy trucks from major improvement projects

6.  Dollar cost of crashes (apparently heavy-truck crashes, but not
    obvious) and crash cost comparisons by mode.

7.  Number of "design impediments" to freight traffic (e.g., grade
    crossings, truck-restricted roads, deficient bridges)

[Performance measures that require data to be developed:]{.underline}

1.  City-to-city travel time for major highway routes

2.  Point-to-point transit time for shippers

3.  Transit time to major regional, national, and global markets

4.  Number of "design impediments" to access to terminals (truck, rail,
    air, and water)

5.  Crash rate per ton-mile by mode

[Other indicators:]{.underline}

1.  Minnesota's transportation investment and spending as a percent of
    gross state product (GSP).

2.  Shipment cost per mile (by ton or value), by mode and by major
    commodity groups

**ASSESSMENT:**

Many of these are potentially useful. Information on speed and transit
times by route and by city pair would be especially helpful if routes
and city pairs that have special significance for freight movement could
be identified. Transportation spending as a percent of GSP is an odd
one; it is difficult to see how that measures performance. Shipment cost
per mile makes sense. Design impediments would be useful, but, again, it
would be helpful to tie these to routes that are important for freight.
A design impediment on a road rarely used by heavy trucks would seem to
have little relevance. Crash rate per ton-mile seems useful. Dollar cost
of heavy-truck crashes seems to be more about *consequences* of moving
freight than about *effectiveness* in moving freight. Dollar costs of
deaths and injuries and property damage is appropriate for measuring
overall highway performance; for freight purposes, it might be useful to
focus in more narrowly, e.g., on loss-and-damage costs.

##  Academic Studies 

REPORT: *Demand-based Transportation Planning, Policy, and Performance*,
an unpublished paper under journal review

SPONSORS: N/A

**AUTHORS:** Edward A. Morash, Graduate School of Management, Michigan
State University

**PARTICIPANTS:** N/A

**DATE:** undated (1999)

**SUMMARY:**

The paper is largely concerned with the notion that public policy should
be based, in part, on the effective functioning of the supply chain; put
another way, that good private-sector logistics should be a goal of
public policy. Development of performance measures is not the main
purpose of the work.

**PERFORMANCE MEASURES PRESENTED:**

The performance measures offered are related to the private-sector
supply chain.

1.  Transportation cost (including loss and damage and costs of service
    failures)

2.  Productivity of transportation labor and equipment

3.  Asset management (inventory levels)

4.  Customer service (e.g., on-time delivery)

5.  Logistical quality (e.g., damage frequency)

**ASSESSMENT:**

These are legitimate measures of effectiveness in supply-chain
management, and the author is right to point out that public policy can
affect these measures. The difficulty would come in trying to isolate
the effects of highway-system performance on these indicators. That
would not be easy to do.

# Appendix B: Individuals Contacted {#appendix-b-individuals-contacted .unnumbered}

## Federal Government {#federal-government .unnumbered}

Russ Capelle, Bureau of Transportation Statistics, 202-366-5685

Arthur Jacoby, Federal Highway Administration,

James March, Federal Highway Administration, 202-366-9237

Beth Pinkston, Congressional Budget Office, 202-226-2940

Barbara Fraumeni, Bureau of Economic Analysis, 202-606-9603

## State and Local Government {#state-and-local-government .unnumbered}

Dan Casshin, Office of Policy Planning, Florida DOT, 850-488-8006

Mark Berndt, Section Director, Freight Policy and Programs, Minnesota
DOT, 651-296-1676

Matt Garrett, Leader of Freight Group, Oregon DOT, 503-986-4214

Jahangir Kashkooli, Senior Transportation Planner, California DOT,
916-653-2575

Doug McLeod, Florida DOT, 850-488-4640

## Academia and Industry {#academia-and-industry .unnumbered}

Michael Belzer, University of Michigan Trucking Industry Program,
734-647-9474

Tina Casgar, Intermodal Association of North America, 301-982-3400

Bob Czerniak, New Mexico State University, 505-646-3509 (or -2815),
<rczernia@nmsu.edu>

Edward Morash, Department of Marketing and Logistics, Michigan State
University, 517-353-6381

Lance Newman, Cambridge Systematics, 617-354-0167

## Other {#other .unnumbered}

Antii Talvitie, World Bank, 202-473-7017

Burkhard Horn, independent consultant based in Paris (exchanged e-mails)

Table of Contents

Executive Summary i

1 Introduction [1](#introduction)

1.1 Background and Purpose [1](#background-and-purpose)

1.2 Report Organization [2](#report-organization)

2 Overview of Indicators Identified in Previous Research
[3](#overview-of-indicators-identified-in-previous-research)

2.1 Focus of Past Research and Policy Efforts
[3](#focus-of-past-research-and-policy-efforts)

2.2 Indicators Identified [3](#indicators-identified)

2.2.1 Travel Time Measures [4](#travel-time-measures)

2.2.2 Reliability Measures [5](#reliability-measures)

2.2.3 Cost Measures [7](#cost-measures)

2.2.4 Safety or Damage Measures [8](#safety-or-damage-measures)

2.2.5 Highway Condition Measures [9](#highway-condition-measures)

2.2.6 Economic Impact Measures [10](#economic-impact-measures)

2.2.7 Transportation Industry Productivity Measures
[11](#transportation-industry-productivity-measures)

3 Recommendations [13](#recommendations)

3.1 Initial Screening [13](#initial-screening)

3.1.1 Potentially Valuable (First-Tier) Indicators
[14](#potentially-valuable-first-tier-indicators)

3.1.2 Second-Tier Indicators [15](#second-tier-indicators)

3.1.3 Corridor or Facility Measures [16](#corridor-or-facility-measures)

3.1.4 Not-Useful Measures [16](#not-useful-measures)

3.2 Evaluation of First-Tier Indicators
[18](#evaluation-of-first-tier-indicators)

3.2.1 Criteria Used [18](#criteria-used)

3.2.2 Findings [19](#findings)

3.2.3 Analysis of Individual Indicators
[20](#analysis-of-individual-indicators)

Appendix A: Evaluations of Individual Studies
[29](#appendix-a-evaluations-of-individual-studies)

3.3 U.S. DOT Efforts [29](#u.s.-dot-efforts)

3.4 State and Local Efforts [39](#state-and-local-efforts)

3.5 Academic Studies [53](#academic-studies)

Appendix B: Individuals Contacted
[54](#appendix-b-individuals-contacted)

[^1]: Notable examples are the studies: Nadiri, M. Ishaq and Theofanis
    Mamuneas. "Contributions of Highway Capital to Industry and National
    Productivity Growth." September 1996, Final Report. Prepared for
    FHWA. Nadiri, M. Ishaq. "Contribution of Highway Capital to Output
    and Productivity Growth in the U.S. Economy and Industries." August
    1998. Prepared for FHWA.