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121 APPEN D I X E Modal Freight Performance Measures: State of Practice

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122 Mode-Specific Performance such information have involved stopping trucks and inter- Measures viewing drivers or giving them a questionnaire. Often such surveys were conducted only once a decade, or less frequently. At the national level, significant volumes of data are col- A need for improved truck freight performance data has lected to measure many aspects of freight system perfor- led to efforts to use existing commodity-flow data and to mance. Collecting freight-related data are all of the modal exploit emerging technologies. The Freight Analysis Frame- agencies of the U.S. Department of Transportation, including work (FAF), a FHWA-led initiative, analyzes commodity-flow the FHWA, the Federal Railroad Administration (FRA), the information to produce estimates of overall freight volumes, Federal Motor Carrier Safety Administration (FMCSA), the as well as estimated origins and destinations. An FAF guide- Maritime Administration (MARAD), the FAA, the National book2 describes several means by which capacity-related Highway Transportation Safety Administration (NHTSA), measures could be estimated, including: and the Surface Transportation Board (STB). The U.S. Army Corps of Engineers (USACE) collects performance data on Traffic volume, the national marine transportation system. The U.S. Envi- Capacity, ronmental Protection Agency (EPA) tracks and regulates Volume-to-capacity ratios, mobile emissions, including those of trucks, ships, railroads, Average speed, and aircraft. The U.S. Department of Commerce monitors Travel time, and imports, exports, and many categories of commercial output. Link delay. The complexities of using data from these different sources are discussed below in the data quality of this appendix. Efforts to use GPS data to improve truck-movement infor- mation began in 1999 with an investigation of the use of on- Highway Infrastructure Condition Measures board devices to monitor the trucking industry's use of road- ways.3 This research was limited, however, to the number of The Highway Performance Monitoring System provides participating drivers and companies, and by equipment costs. data that reflect the extent, condition, performance, use, To further research the idea of using wireless truck position and operating characteristics of the nation's highways. It was data to determine metrics related to demand for roadways, developed in 1978 as a national highway transportation sys- Short and Jones4 analyzed several million truck movements tem database and includes limited data on all public roads, across the U.S. interstate system. It was shown that a ranking more detailed data for a sample of the arterial and collector of demand for groupings of 3-mile segments (i.e., hundreds functional systems, and certain statewide summary informa- of segments falling across entire interstate corridors) could tion. The data are sample based and therefore do not provide be determined, thus identifying a potential complement to data regarding every highway link. Also, speed and reliability the FAF information described earlier. The research has pro- data are estimated, making the data unsuitable for examina- duced robust travel-time and travel-reliability information tion of individual links. on the Interstate Highway System (IHS) and has identified The National Bridge Inventory compiles bridge inspection major truck-freight bottlenecks.5 data on the nation's bridges as reported by the state and local Using this source, the following methods for producing governments. It reports conditions in terms of Functional freight performance measures have been developed: Obsolescence and Structural Deficiencies. The National Bridge Inventory is bridge specific. Use of Multiple Unique Truck Positions to Measure Speed: Using The Fatality Analysis Reporting System includes state- this method, truck position pairs for individual/unique vehicles by-state data on crashes by type, including those involving are matched, and a time/distance calculation is made to deter- trucks. mine average travel rates. The end results are calculations along broad corridors (e.g., Interstate 10 from Jacksonville, FL, to Santa Monica, CA). A database of such calculations is updated monthly Trucking Performance Measures and measures 27 U.S. interstate corridors. Measurements can focus on specific regions, times of day, and days of the week. Trucking-specific performance data in the public domain Measuring Border Crossing and Bottleneck Delay: Delay is mea- remain insufficient for many policy, investment, and opera- sured at border crossings and other points, such as highly con- tional decisions, according to some.1 State transportation gested bottlenecks, by measuring travel time across such points. Spot Speed Measures: Speeds can also be measured for specific agencies usually generate actual or estimated average daily urban areas and highway intersections that are highly congested. traffic volumes for trucks, but other important information, The end result includes measures such as average speed in a geo- such as truck origins and destinations, remains expensive and graphic location by hour of day, which identifies peak times of intrusive for them to collect. Traditional means for gathering freight congestion/delay.

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123 The rate at which trucks move and thus the time it takes to category are the Florida Reliability Method, which measures travel given distances is a common indicator of issues such as travel time during the peak, On-Time Arrival measures, and the Misery Index, which measures the most-congested 20 percent of congestion and delay. Measuring such issues through the use travel periods. of travel-time and travel-rate information can produce the following types of metrics:6 FHWA8 offers two methods for measuring reliability. The first, shown in Figure E.1, is named the Travel Time Index, Travel time or difference in travel times (minutes or seconds) which compares peak period and free-flow travel conditions. Travel rate (travel time divided by travel distances) The second method is the Buffer Time Index, which Delay rate (minutes per mile) "expresses the amount of extra `buffer' time needed to be on- Total delay (person hours, vehicle hours) time 95 percent of the time (late one day per month)."9 Relative delay rate (delay rate divided by acceptable travel FHWA defines travel time reliability "as how much travel rate times vary over the course of time." Thus, when measuring Delay ratio (delay rate divided by actual travel rate) the reliability of truck movements, truck-specific informa- Miles of congested roadway tion can be analyzed to determine similar travel-time vari- Miles of congested travel ability (over a specific time period) for all or part of the Miles of congested roadway Miles of congested travel trucking industry. The calculation of reliability measures specifically for Reliability Reliability trucks is demonstrated as shown in Figure E.2.10 The buffer Reliability of truck movement, Reliability as movement, of truck the term implies, is an as the term time implies, is was "calculated an indicator for atravel of how likely across roadway entire corridors [e.g., will perform indicator of how likely a roadway will perform in a certain Interstate 10], for each of the 100-mile in a certain way during a given period of time. As would be expected, trucking companies often prefer segments of the cor- way during a given roadways period of that perform time. in a reliable As would ridor, and travel across every combination manner so that they can plan routes/deliveries and accurately estimate be expected, of each of the 100- trucking companiescosts. oftenSuch factors prefer can playthat roadways a role in meeting perform in delivery milewindows segmentsand scheduling required hours of service of a corridor." a reliable manner soand rest that periods. they can plan routes/deliveries and accurately estimate costs. Such factors can play a role in meet- Operational Three methods are commonly used for determining reliability of travel: Costs statistical range, buffer time ing delivery windows and scheduling required hours of ser- measures, and tardy trip indicators:7 vice and rest periods. Beyond speed, delay, and reliability, several performance Three methods are commonly Statistical Range: used This can be described for determining reli- as ameasures Travel Time Window, look at thePercent cost ofVariation, or A first measure is production. Variability ability of travel: statistical range, Index, buffer timeall measures, of which can be applied and to freight cost movement. per mile. The American Trucking Associations (ATA) tardy trip indicators:7 Buffer Measures: These can be considered as 2003 "timeMotor Carrier allowance," Annual and measuresReport 11 includelists the key elements of Buffer Time, Buffer Time Index, and Planning Time a cost-per-mile Index. calculation for trucking. This includes the fol- Statistical Range: This can be described as a Travel Time lowing in approximate order of magnitude: Tardy Trip Indicators: These indicators measure "the unreliability impacts using the amount of indow, Percent Variation, or Variability Index, all of which can W late trips." Included in this category are the Florida Reliability Method, which measures travel be applied to freight movement. time during theaspeak, On-Time Other Arrival measures, wages and the andIndex, Misery benefits which measures the Buffer Measures: These can be considered "time allowance," and measures include Buffer most-congested Time, Buffer Time 20Index, percent travel periods. Equipment rents and purchased transportation ofPlan- and ning Time Index. Driver wages FHWA8 offers two methods for measuring reliability. The first, shown in Figure E.1, is named the Travel Tardy Trip Indicators: These indicators measure "the unreli- Miscellaneous Time Index, which compares peak period and free-flow travel conditions. ability impacts using the amount of late trips." Included in this Fuel and fuel taxes Figure E.1. Travel Time Index Figure E.1. Travel Time Index. The second method is the Buffer Time Index, which "expresses the amount of extra `buffer' time needed Comment [JP1]: A to be on-time 95 percent of the time (late one day per month)." Cambridge Systematic have a citation with pa FHWA defines travel time reliability "as how much travel times vary over the course of time." Thus, when measuring the reliability of truck movements, truck-specific information can be analyzed to 3

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The calculation of reliability measures specifically for trucks is demonstrated as shown in Figure E.2. The buffer time was "calculated for travel across entire corridors [e.g., Interstate 10], for each of the 100- mile segments of the corridor, and travel across every combination of each of the 100-mile segments of a 124 corridor." Figure E.2. Buffer Index from Freight Performance Measures Initiative. Figure E.2. Buffer Index from Freight Performance Measures Initiative. Operational Costs Depreciation Cost per crash involving a nonfatal injury; and Beyond speed, delay, and reliability, several performance measures look at the cost of production. A first Insurance Cost per crash involving a fatality. measure is cost per mile. The American Trucking Associations (ATA) 2003 Motor Carrier Annual Outside maintenance 10 Report lists the key elements of a cost-per-mile calculation for trucking. This includes the following in Comment [JP2]: Author Tax and license check the endnote. It names approximate order of magnitude: Tires Economic Measures, Forecasting, and document document. as the source for t Other wages & benefits Other Private-Sector Trucking Performance Equipment rents & purchased transportation Measures Measurement of Safety Performance for Driver wages Trucks Miscellaneous Although much of the truck-specific economic forecast- Fuel & fuel taxes ing that is produced is related to growth in truck tonnage Truck safety measures Depreciation can be calculated in several ways. Insurance and other freight sectors, the trucking industry does follow ATA identifies the number of fatal crashes annually as a 12 the economic forecasts for a variety of non-freight industries, Outside maintenance safety measurement for the Taxentire industry and places the and license especially manufacturing. ATA's U.S. Freight Transportation measure into two categories: Tires Forecast tracks trends and forecasts in manufacturing, con- struction, agricultural commodities, mining, and non-oil Measurement Total Annual Large-Truck of Safety Performance Fatal Crashes for Trucks merchandise imports. Large-Truck Fatal Crash Truck Rate safety Per 100can measures Million VMT in several ways. ATA11 identifies the number of fatal crashes be calculated annually as a safety measurement for the entire industry and places the measure into two categories: Such statistics are typically sourced from reports such as Private-Sector Summary Total Annual Large-Truck Fatal Crashes the FMCSA Large Truck Crash Facts 2005, which develops Large-Truck Fatal Crash Rate Per 100 Million VMT Key private-sector performance measures are produced measures from data sources such as FARS, NHTSA's General Estimates System (GES), and FMCSA's Motor Carrier Manage- by ATA and listed in Trucking Trends. These measurements 4 ment Information System (MCMIS).13 FMCSA organizes crash include the following: statistics into four sections, which are described as follows: Commodity/ Commodity Flow Information: The statistics followed by the industry in this category focus mainly on how Number of crashes; freight is moved (i.e., percentage by truck, rail, air), as well as the Number of vehicles involved in crashes; value of and type of goods shipped. Number of people involved and resulting fatalities and in- Trucking Company Failures: The number of trucking com- juries; and pany failures that occur in a given time period is an indicator of industry performance. Trends in the number of failures can Number of drivers involved. help measure the impact of other forces on the trucking industry, such as high fuel prices or an economic slowdown. FMCSA addresses the cost of highway crashes that involve Tonnage Growth: ATA has a For-Hire Truck Tonnage Index medium and heavy trucks with estimates for the following that measures the decline or growth in freight hauled by the in- measures: dustry on an annual basis, as well as percent changes in the ton- nage index itself. Revenue Growth: For-Hire Trucking Revenue is also measured Cost of crashes involving longer combinations; as an index, as well as the percentage change in the index itself. Cost of straight truck crashes; Revenue per Mile and Revenue per Ton: Both revenue per mile Cost of "property damage only" crashes; and per ton of freight shipped are indexed on an annual basis.

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125 Trucking Producer Price Indices: The Producer Price Index ing origin and destination of cargo, types of commodities for segments of trucking are used to track the change in prices shipped, numbers of cars, tons and revenue, and length of for trucking services in general, and specifically for truckload haul. These data could be translated into various perfor- carriers, less-than-truckload carriers, local delivery, and long- distance trucking (as well as other segments). mance measures of rail volume, commodity shipment types, Other Financial and Operating Statistics: USDOT typi- or other measures.14 cally releases financial and operating data collected through Form M, which is a required reporting document for carriers with $3 million or more in annual revenue. These data and the Railroad Earnings performance measures derived from the data have not been re- leased by USDOT since 2003. The economic health of railroads is measurable from the earnings reports that the publicly traded and publicly regu- lated railroads must report. These reports track gross rev- Rail Performance Measures enues, net operating revenues, revenue ton-miles, and net The American Association of Railroads (AAR) has since income. In addition, the corporate annual reports required 1999 published performance measures for the Class I rail- by the Securities and Exchange Commission provide detailed roads. On its website (http://www.railroadpm.org/) it reports information on the economic performance of the railroads.15 weekly updates on train travel speeds, cars on line, and dwell times of Norfolk Southern, CSX, Union Pacific, BNSF, Kansas Railroad Statistics City Southern, and Canadian Pacific Railway. It notes that, despite using common methodology, one railroad's perfor- More than 1,500 categories of statistics are reported for mance metrics should not be compared to another's. It notes each of the Class I railroads in the Statistics of Class I Freight that performance can be affected by differences in network Railroads report. These data, required by STB, include uni- terrain, railroad design, the mix of traffic, the effect of pas- form reporting of income, expenses, investments in track, senger operations, and external factors such as weather and equipment investments, and depreciation by various catego- port operations. It also notes that each railroad's calculation ries. These data were last published in 2004.16 methodology of each measure also can vary. The performance measures allow train speeds to be mea- Cost of Capital sured by train type, such as intermodal, grain, coal, or double stack. It allows dwell times to be observed at major yards. It STB17 makes an annual calculation of whether the Class I also tracks cars on the system by the various types of cars such railroads have earned income that exceeds their cost of capi- as box, intermodal, or hopper cars. Historical performance tal, which for 2007 was determined to be 11.3 percent. For data are available for the past 53 weeks. 2008, it determined that the NS and Soo Line, or Canadian AAR reports that the railroads agreed over a series of Pacific, railroads earned more than their cost of capital. All years to consolidate their performance reporting for public other Class I railroads were found to be either revenue "ade- convenience. AAR states that it is unaware of the cost to the quate" or "inadequate." railroads of generating the measures because each railroad contributes its data from its internal reporting mechanisms. Rail Safety Data The Federal Railroad Administration Office of Safety Anal- Surface Transportation Board Data ysis18 website (http://safetydata.fra.dot.gov/officeofsafety/) STB requires voluminous reporting data from the U.S. rail- provides search and query tools to conduct analyses of rail- roads, much of which could be used to develop performance road crashes. The query tools link to federal crash databases measures at the national level. The data generally are aggre- that allow for analysis of crashes by railroads, state, crash gated from proprietary sources and are therefore not avail- types, and localities. Links to individual crash reports are able at a local or regional level. Some of the data sources are provided. described below. Aviation Performance Measures Waybill Data The air transportation industry has been measure- STB requires U.S. railroads to report sample waybill data, intensive for decades, with both private carriers and the FAA which is reported in a public form that has been purged of carefully evaluating key measures of reliability, safety, and proprietary information. It contains information regard- service. Annually, beginning in FY 2004, FAA developed an

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126 aggressive strategic plan to help manage and measure per- export, commodity trends, numbers of ships and containers formance. Its Flight Plan provides the framework to match involved, measures of trade, measures of employment in the resources with initiatives for long-term change. This report industry, and measures of the economics of waterborne ship- sets forth goals and the performance measures to assess prog- ping. It is useful to assess general trends in port volumes and ress in meeting them and is tightly aligned with the mission, activity (Table E.2). vision, goals, and performance measures outlined in the DOT Analogous to the highway mode, in which data exist for Strategic Plan. traffic volumes but not for highway performance to the same The Flight Plan highlights performance measures, and extent, there are little available data on port performance. conducts analysis on each measure to determine whether the Port volumes are measured, but information is not available data were complete and reliable enough to measure appropri- as to how ports have accommodated the growth in container ately. Within this report performance measures are grouped volume in past decades. in the broad categories of Safety, Capacity, International In its Report to Congress on the Performance of Ports and the Leadership, and Organizational Excellence. Intermodal System20 MARAD noted that a lack of common Aviation Table E.1 provides Performance an overview of measures used Measures by FAA performance measures and the lack of a reporting process and highlights whether or not the performance measures have stymied its attempts to measure the efficiency of major The air transportation industry has been measure-intensive for decades, with both private carriers and the were met. U.S. ports. FAA carefully evaluating key measures of reliability, safety, It informed and service. Congress Annually, beginningthat it was unable to assess in FY congestion levels at ports or to assess 2004, FAA developed an aggressive strategic plan to help manage and measure performance. Its Flightthe performance of the Plan provides the framework to match resources with initiatives nation's for long-termsystem intermodal change.overall: This report sets Waterborne Freight forth goals and the performance measures to assess progress in meeting them and is tightly aligned with Performance Measures the mission, vision, goals, and performance measures outlined in the DOT Strategic Plan. The Flight Plan highlights performance measures, MARAD was unable to provide the requested comparison of MARAD produces an annual Statistical Snapshot 19 that and conducts analysis on each measure to determine the most congested ports in terms of operational efficiency due whether the data were complete and reliable enough to measure appropriately. Within this report provides nearly 20 categories of water-freight-related statis- to a lack of consistent national port efficiency data. Given the performance measures are grouped in the broad categories of Safety, Capacity, International Leadership, tics. The statisticsand address freight volumes, ports Organizational Excellence. of entry and diverse characteristics of U.S. ports, comparing port efficiency Table E.1 provides an overview of measures used by FAA and highlights whether or not the performance measures were met. Table TableE.1. FAAstatistics. E.1. FAA statistics. Table 10 Measure Actual Target Data Data Index Range 10S1 Commercial Air Carrier Fatality Rate (FAA) - - Green 10S2 General Aviation Fatal Accident Rate (FAA) 0.0 8.1 Green 10S2 General Aviation Fatal Accident Rate (FAA) 1.09 1.02 Red 10S3 Alaska Accident Rate (FAA) 2.55 1.70 Red 10S4 Runway Incursions (Category A and B) (FAA) 0.12 0.45 Green 10S6 Commercial Space Launch Accidents (FAA) 0 0 Green 10S7 Operational Errors (FAA) 3.24 2.05 Red 10S59 Safety Management System (FAA) 3 3 Green 10S105 Total Runway Incursions (FAA) 409 446 Green GREATER CAPACITY 10 (FAA) - - Green 10C1 Average Daily Airport Capacity (35 OEP Airports) (FAA) 101.354 102,648 Yellow 10C2 Airport Average Daily Capacity (7 Metro Areas) (FAA) 42.494 39,484 Green 10C3 Annual Service Volume (FAA) 3 3 Green 8

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127 Table E.1. Continued. Table 10 Measure Actual Target 10C4 Adjusted Operational Availability (FAA) 398.78 99.7 Green 10C5 NAS On-Time Arrivals (FAA) -99.78 88.00 Yellow 10C6 Noise Exposure (FAA) 089.69 3 Green 10C7 Aviation Fuel Efficiency (FAA) 3 3 Green INTERNATIONAL LEADERSHIP 10 (FAA) 3 - Green 10I2 CAST Safety Enhancements (FAA) 1- 4 Red 10I7 International Aviation Development Projects (FAA) 3 3 Green 10I23 NextGen Technology (FAA) 2 1 Green 10I40 Aviation Leaders (FAA) 1 1 Green ORGANIZATIONAL EXCELLENCE 10 (FAA) - - Green 10E2 Cost Control (FAA) 3 3 Green 10E3 Critical Acquisitions on Budget (FAA) 100 90 Green 10E4 Critical Acquisitions on Schedule (FAA) 96 90 Yellow 10E5 Information Security Program (FAA) 3 3 Green 10E6 Customer Satisfaction (FAA) 3 3 Green 10E61 OPM Hiring Standard (FAA) 3 3 Green 10E102 Reduce Workplace Injuries (FAA) 3 3 Green 10E104 Unqualified Audit Opinion (FAA) 2 3 Yellow 10E107 Grievance Processing Time (FAA) 3 3 Green 10E108 ATC Positions Workforce Plan (FAA) 15,812 15,639 Green 10E226 Continuity of Operations (FAA) 0 0 Green 10E231 Aviation Safety Positions Workforce Plan (FAA) 7 7,171 7,195 Green *STRATEGIC OBJECTIVES (FAA) 0 0 Green Source: FAA 2010 Performance Targets, http://www.faa.gov/about/plans_reports/performance/quarter_scorecard/media/ FY10%202nd%20Quarter%20Scorecard.pdf. 9 would require the creation of new methodologies and the collec- officials, port labor representatives, shippers, ship operators, tion of data that were not available for this report. and truckers, and it had to assess the infrastructure related to highways, rail, water, and the intermodal transfer points To generate its report for Congress on port performance, between the modes. MARAD formed four teams of researchers who interviewed The MARAD report noted a wide variety of issues--both officials and representatives at 23 major U.S. ports. It stressed operational and infrastructure related--that can influence that, to assess port operations, it needed to interview port efficient port operations:

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related statistics. The statistics address freight volumes, ports of entry and export, commodity trends, numbers of ships and containers involved, measures of trade, measures of employment in the industry, and measures of the economics of waterborne shipping. It is useful to assess general trends in port 128 volumes and activity (Table E.2). Table E.2. Port volumes. Table E.2.Port volumes. Port 2003 2004 2005 2006 2007 2008 % Change 2003-08 LA/LB 47.8 53.6 57.1 66.5 69.7 69.8 46 New York 22.1 23.6 26.8 27.8 29.9 31.9 44.3 Savannah 10.5 11.6 13.6 14.5 17.1 18.7 78.1 Houston 15.9 14.6 15.3 16.3 17.6 18.4 15.7 Seattle/Tacoma 12.6 14.5 18.3 17.6 18.9 17.9 42.1 Norfolk 10.2 10.1 10.9 11.9 12.3 12.9 26.5 S. Francisco 8.4 9.6 10.9 11.4 11.7 11.8 40.5 Charleston 9.9 10.8 12.1 11.2 11.3 10.9 10.1 Miami 7.7 8.5 9.7 9.3 8.8 8.3 7.8 N. Orleans 4.1 5.0 4.6 5.5 6.0 5.7 39.0 Top 5 109.0 117.8 131.0 142.7 153.2 156.7 43.8 Top 10 149.2 161.8 179.1 192.2 203.2 206.2 38.2 Total 174.0 187.6 205.8 220.6 231.6 235.1 35.1 Source: US Bureau of Census, Foreign Trade Division www.census.gov/foreign-trade Analogous toSource: the highway mode, US Bureau in which of Census, data Foreign exist Trade for traffic Division, volumes but not for highway performance www.census.gov/foreign-trade. to the same extent, there are little available data on port performance. Port volumes are measured, but information is not available as to how ports have accommodated the growth in container volume in past decades. The greatest concerns for both commercial operations and methodologies for measuring port efficiency. The literature re- military deployments were the surge in cargo flows into the viewed supported MARAD's finding that there is no widespread ports, the adequacy of cargo staging areas in the ports, port agreement on an approach to measuring the efficiency of a port rail infrastructure, and communications. Additional issues that as a link in the logistics chain. A 2004 article in10 Maritime Policy & dominated commercial operations were landside access to ports, Management states: "Measures of port efficiency or performance highway signage, channel and port dredging, increasing cargo indicators use a diverse range of techniques for assessment and volumes, financing, and intermodal connectivity. Two additional analysis, but although many analytical tools and instruments major concerns specific to military deployments were training exist, a problem arises when one tries to apply them to a range and coordination among ports and shippers. of ports and terminals. Ports are very dissimilar and even within While there were a wide variety of themes in response to a single port the current or potential activities can be broad in MARAD's questions, there was much agreement on the most ur- scope and nature, so that the choice of an appropriate tool of gent congestion and infrastructure issues facing the MTS [Mari- analysis is difficult. Organizational dissimilarity constitutes a se- time Transportation System]. About half the ports cited specific rious limitation to enquiry, not only concerning what to measure reasons for congestion that cause infrastructure overload. One but also how to measure. Furthermore, the concept of efficiency is fourth of the ports described their infrastructure impediments vague and proves difficult to apply in a typical port organization as "severe." The responses mirror the concerns raised in recent extending across production, trading and service industries.21 DOT, Government Accountability Office (GAO), and non-gov- ernment studies on MTS issues. MARAD listed the following considerations that influence MARAD advised Congress that, although a variety of a port's efficiency and could skew an attempt to make com- potential port efficiency performance measures could be parisons between ports: adopted, few of the potential measures had universal accep- tance because of the large diversity in port operations: Type of cargoes handled by the port (specialization); Location of port relative to shippers' markets (regional In preparing this report, MARAD reviewed articles and stud- demand); ies from the academic and scientific communities that set forth Price of port services relative to shippers' alternative ports;

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129 Waterside access limitations; Its Strategic Plan includes a cascading series of outcomes, Carrier investment in port infrastructure; strategies, key performance indicators, and performance Quality of port services; measures. The performance measures are included in the Business realignment to increase purchasing power; and agency budget documents and link expenditures with effec- Availability of national government subsidies. tiveness. Two examples are the number of out-of-service ships that are dismantled in an environmentally sustainable MARAD noted "Factors That Affect Port Efficiency": way and the number of communities MARAD engages to enlist their help in improving the Maritime System. The Labor efficiency (cargo moved per unit of labor); MARAD measures evaluate internal agency performance Land use efficiency (cargo storage per unit of land); and not the performance of ports, intermodal links, or Waterside access limitations; actual shipments. Capacity of port road and rail connections; Its more extensive lists of key performance indicators do Inland transportation availability; and relate to many aspects of national concern regarding ship- Cargo handling capability. ping performance and security. However, it notes they are not quantitative, nor do they have a measurement system related It went on to say that the diversity of factors prevents the to them. They are of a more qualitative nature. They include general measurement of port efficiency. It quoted Cullinane22 issues such as increased outreach to public and private sec- as saying that there is even a lack of standard terminology tors, increased private investment in the Maritime System between ports as to how define measures, with different ports and adoption of best practices in managing port facilities to using different terminology to describe similar functions. It maximize throughput. quoted Robinson23 as saying that port efficiency measures "will always have a national tendency to be terminal specific." Inland Waterways It quoted De Monie24 as saying that the following factors impede measurement of port efficiency: USACE's Navigation Economics Technology Program26 produces a suite of analytic tools for the Corps to evaluate The sheer number of parameters involved; possible investments in the inland waterways system. It has The lack of up-to-date, factual, and reliable data, collected produced a report, An Overview of the U.S. Inland Waterway in an accepted manner and available for dissemination; System, that provides baseline information on the domestic The absence of generally agreed and acceptable definitions; inland system. It includes statistics on the size and charac- The profound influence of local factors on the data ob- teristics of the waterways, locks, ports, and commodity flows tained; and on the system. The data are extensive but static and are not The divergent interpretation given by various interests to subject to regular updates. The Corps also produces a web- identical results. site with significant amounts of performance data regard- ing waterborne commerce and the conditions of locks and dams27 (Figure E.3). MARAD Strategic Plan and Performance RITA produces in its Key Transportation Indicators monthly Measures report a moving average of delay on the inland waterway MARAD has a strategic plan with embedded performance system.28 measures for the years 20082015.25 Its measures support its five basic strategic goals, which are: Time Series Analysis of U.S. Inland Waterways Trade Improve maritime policies and programs to enrich and se- cure the nation. BTS29 publishes monthly trend data on the shipment of Expand reliable private and public investment funding commodities on U.S. inland waterways. Aggregate data are mechanisms to support the growth of the Marine Trans- normalized to adjust for seasonal variations but do not pro- portation System. vide granularity as to types of commodities shipped, or by Revitalize the partnerships between the Maritime Admin- origins and destinations. istration and the Marine Transportation System's private and public stakeholders. European Union Transport Policy for 2010 Enhance the U.S. intermodal transportation system. Maximize the potential of each employee to achieve the The European Union has not adopted freight performance agency's mission. measures per se but it has adopted firm goals that arise from

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RITA produces in its Key Transportation Indicators monthly report a moving average of delay on the inland waterway system.26 130 Figure Figure E.3. Inland E.3. Inland waterway waterway volumes. volumes. its freight-transport Time Series policies. Analysis The EU exampleof U.S. Inland represents a Waterways Trade continues to grow, particularly in the former Eastern Bloc clear case of performance goals selected specifically to achieve members, which are rapidly developing. Between 1995 and a formal, official transportation policy.30 Its 2001 White Paper 2004, highway freight grew 35 percent compared 13 to 6 percent proposed approximately 60 measures to develop a transport for rail freight.31 system capable of shifting the balance between modes by A recent European research program conducted for the reducing the growth in truck freight, revitalizing rail trans- Dutch Ministry of Transport, Public Works and Water Man- port, encouraging in-land and short sea shipping, and con- agement has shown that the EU so far has not succeeded in trolling the rate of growth in air travel. achieving its passenger mode-shift goals and has had only In a 2006 assessment of the 2010 White Paper goals, the EU partial success on its freight goals. The Dutch study proposed noted mixed progress. Highway freight still carried 44 percent a renewed emphasis on pricing to discourage highway travel of freight tonnage, compared to 8 percent for rail and 4 per- and increase travel on rail and water modes. It also proposed cent for inland waterways. For passengers, 79 percent of travel the acceleration of biofuels and hydrogen to achieve air qual- was on roads, compared to 6 percent for rail and 5 percent for ity and greenhouse gas emissions goals that have not been air. The number of cars trebled between 1970 and 2000 and achieved so far by the mode-shift strategy.32 Endnotes 7 Lomax, Tim, David Schrank, Shawn Turner, and Richard Margiotta. Selecting Travel Reliability Measures, FHWA, http://tti.tamu.edu/docu- 1 Beagan, Daniel, M. Fischer, and A. Kappam, Quick Response Freight Manual ments/474360-1.pdf, 2003. II, prepared for USDOT, FHWA, Office of Freight Management and Opera- 8FHWA. Traffic Congestion and Reliability: Linking Solutions to Problems. Pre- tions, Washington, D.C., 2007. pared by Cambridge Systematics with the Texas Transportation Institute for 2 Fekpe, Edward, M. Alam, T. Foody, and D. Gopalakrishna. Freight Analysis FHWA Office of Operations, 2004. Framework Highway Capacity Analysis: Methodology Report, prepared for 9FHWA, Traffic Congestion and Reliability: Linking Solutions to Problems, USDOT Office of Freight Management and Operations, Washington, D.C., Cambridge Systematics and Texas Transportation Institute for FHWA Office 2002. of Operations, 2004. 3Battelle. Heavy-Duty Truck Activity Data Collection and Analysis Using Global 10 Jones, Crystal, Daniel Murray, and Jeffrey Short. Measurement of Travel Time Positioning Systems, prepared for USDOT, FHWA, Office of Highway Infor- in Freight-Significant Corridors: Phase Two, presented at 12th Annual World mation Management, Washington, D.C., 1999. Congress on ITS, San Francisco, CA, November 610, 2005. 4 Short, Jeffrey, and C. Jones, Utilization of Wireless Truck Position Data to De- 11ATA. Motor Carrier Annual Report, Arlington, VA, 2003. termine Demand for Highways. 10th International Conference on the Appli- 12ATA. American Trucking Trends 2007-2008, Arlington, VA, 2008. cation of Advanced Technologies in Transportation, Athens, Greece, 2008. 13FMCSA. Large Truck Crash Facts 2005. Washington, D.C., 2007. 5 Mallet, William, C. Jones, J. Sedor, and J. Short. Freight Performance Measu- 14 STB. Waybill data, http://www.stb.dot.gov/stb/industry/econ_waybill.html rement: Travel Time in Freight Significant Corridors (FHWA-HOP-07-071), (accessed Sept. 30, 2008). Office of Freight Management and Operations, FHWA, U.S. DOT, Decem- 15 STB Decision Ex Parte No. 552 (Sub-No.12) Railroad Revenue Ade- ber 2006. quacy--2007 Determination, Decided: September 24, 2008. http://www. 6 Turner, Shawn, T. Lomax, and H. Levinson. "Measuring and Estimating stb.dot.gov/decisions/ReadingRoom.nsf/UNID/07DBA8356B2F41F685257 Congestion Using Travel Time-Based Procedures," Transportation Research 4D00047B59E/$file/39363.pdf. Record 1564, Transportation Research Board, National Research Council, Washington, D.C., 1996, pp. 1119.

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131 16STB, Statistics of Class I Freight Railroads, http://www.stb.dot.gov/econdata. 25MARAD. Strategic Plan for Fiscal Years 20032008, 2008. nsf/66a333195e0491c885256e82005ad319?OpenView (accessed Sept. 30, 26 USACE, Navigation Economic Technologies Program. An Overview of the 2008). U.S. Inland Waterway System, IWR Report 05-NETS-R-12, 2005. 17 STB Decision Ex Parte No. 552 (Sub-No.12) Railroad Revenue Ade- 27 U.S. Army Corps of Engineers, "Publications from the Navigation Data quacy--2007 Determination, Decided: March 24, 2010. http://www.stb.dot. Center," http://www.ndc.iwr.usace.army.mil/publications.htm (accessed gov/decisions/ReadingRoom.nsf/UNID/07DBA8356B2F41F6852574D0004 May 24, 2010). 7B59E/$file/39363.pdf. 28RITA. Key Transportation Indicators, April 2010. https://www.bts.gov/pu- 18 FRA Office of Safety Analysis, http://safetydata.fra.dot.gov/officeofsafety/ blications/key_transportation_indicators/april_2010/index.html (accessed (accessed March 24, 2010). May 24, 2010). 19MARAD. U.S. Water Transportation Statistical Snapshot, 2008. 29BTS. A Time Series Analysis of U.S. Inland Waterways Trade, 2008, https:// 20MARAD, Report to Congress on the Performance of Ports and the Intermodal www.bts.gov/publications/transportation_indicators/december_2002/Spe- System, June 2005. cial/html/A_Time_Series_Analysis_of_US_Inland_Waterways_Trade.html 21 MARAD, Report to Congress on the Performance of Ports and the Intermo- (accessed Sept. 29, 2008). dal System, June 2005, p. 7. 30 European Union. "White Paper: European Transport Policy for 2010: A Time 22 Wang, T.-.F., D.-W. Song, and K. P. B. Cullinane. The Applicability of Data En- to Decide," 2001. velopment Analysis to Efficiency Measurement of Container Ports, presented at 31 European Union, "Keep Europe Moving Sustainable Mobility for Our Conti- the International Association of Maritime Economists, Panama Conference, nent (Mid-term review of the European Commission's 2001 transport White November 2002, p. 6. Paper)," 2006, p. 10. 23 Robinson, D. Measurements of Port Productivity and Container Terminal De- 32 J. Annema, "Effectiveness of the EU White paper: `European Transport Policy sign: A Cargo Systems Report, IIR Publications, London, 1999. for 2010' 2005 for the Dutch Ministry of Transport, Public Works and Water 24 De Monie, G. Measuring and Evaluating Port Performance and Productivity, Management. Monograph No. 6, UNCTAD Monographs on Port Management, UN Con- ference on Trade and Development, Geneva, Switzerland, 1987.