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Incorporating Truck Analysis into the Highway Capacity Manual (2014)

Chapter: Section 3 - Truck Carrier and Shipper Perspectives

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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
×
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Suggested Citation:"Section 3 - Truck Carrier and Shipper Perspectives." National Academies of Sciences, Engineering, and Medicine. 2014. Incorporating Truck Analysis into the Highway Capacity Manual. Washington, DC: The National Academies Press. doi: 10.17226/22311.
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11 This section presents available information on the perspectives of truck carriers and shippers regarding their use of highway facilities to move goods. Understanding of commercial vehicle operations by planning agencies has often not moved in lockstep with the demands of the industry. A primary reason has been the misconception among private enterprise that participation in planning studies will require the sharing of proprietary information. A related reason has been the difficulty in recruiting freight establish- ments to participate in market assessment studies—for example, stated choice surveys—which precede planning and investment. A third reason has been the relatively poor quality of survey data often collected from the few commercial vehicle operators that do participate in the market research efforts. However, recent efforts in this arena are showing better results, in part because of the grow- ing sense among establishments that public–private partnerships can help provide solutions that improve business performance. This section summarizes key highlights from recent studies conducted by the research team across different parts of the country that highlight commercial vehicle decisionmaking. These research studies cover large metropolitan areas, such as New York, as well as the breadth and width of the country. The rest of this section is organized as follows: first, an overview of the background of commer- cial vehicle decisionmaking is presented. Second, the methodology and approach in determining shipper carrier decisionmaking is discussed. Finally, the key findings are synthesized specifically focusing on the impact of performance measures on commercial vehicle decisionmaking. 3.1 Background There have been several research studies on the value of time and preferences of freight ship- pers and motor vehicle carriers: • Smalkoski and Levinson used a stated-preference survey to develop a Tobit model to esti- mate value of time for shippers. The average time value was $48.72/hour, although the results showed considerable variation across respondents. The study recommended an upper bound of $185/hour (2011 dollars) on commercial vehicle time (Smalkoski and Levinson, 2005). • Small et al. conducted a stated-preference survey of carriers. They estimated that on average, carriers value travel time savings between $265 and $350 per hour and delay costs at $680/hour (2011 dollars) (Small et al., 1999). A contributing factor to these high estimates may be the types of commodities transported by carriers selected for interview. A number of these carriers transport types of commodities (e.g., agriculture, construction materials) for which the shipper may have to bear the costs of late shipments. S e c t i o n 3 Truck Carrier and Shipper Perspectives

12 incorporating truck Analysis into the Highway capacity Manual • Fowkes et al. conducted a stated-preference survey of shippers, haulers, and third-party logis- tics operators to estimate the value of time reliability for long-haul shipments; the average shipping distance for those surveyed was 280 km (174 miles). The results indicate valuations of $189/hour for delay time, $151/hour for arrival time spread, and $116/hour of schedule delay (2011 dollars)1 (Fowkes et al., 2004). • Shinghal and Fowkes conducted a stated-preference survey of shippers’ mode choice and showed that it was highly related to both travel time and reliability (Shinghal and Fowkes, 2002). From these studies and others, the following conclusions can be drawn: • The value of time for trucks is considerably higher than that for passenger vehicles. From that perspective, management and investment decisions on highway capacity and operations improvements need to place a higher valuation on effects on truck traffic. • Travel time reliability is a prime consideration for the trucking industry. It is typically valued much more highly than travel time, especially for high-value cargoes. The main focus of this study is to understand the key LOS variables that impact truck move- ment. However, isolating the impact of LOS variables on commercial vehicle movement is dif- ficult due to the nature of the decisionmaking involved: • First, commercial vehicle decisions such as routing and time-of-day are governed not just by LOS variables—which are of most interest to this study—but also are influenced by variables such as equipment availability, local governance laws, oversize and overweight permits, and driver travel and rest patterns. Further, the relative importance of these variables differs by establishment, making it very difficult to develop a generalized impact on behavior. • Second, unlike automobile movements in which all decisions are made by the driver, com- mercial vehicle movements are controlled by multiple decisionmakers including shippers, receivers, and carriers. Therefore, it is important to capture the perspective of all three stake- holder groups when inferring about the decisionmaking process. • Third, commercial vehicle movements are governed by economic decisions at an establish- ment level, and establishments are often secretive about the heuristic rules they employ since they are proprietary and central to their business. While detailed rule-making procedures are unlikely to be fully disclosed by establishments, our research has found that they are willing to share the decisionmaking process at an aggregate level. This section of the report presents summary findings describing the impact of performance measures on commercial vehicle decisionmaking using findings from shippers, receivers, and carriers. While these findings are not applicable to every truck movement, they provide a good framework for an in-depth assessment of decisionmaking. A variety of market assessment options including focus groups, executive interviews, and survey efforts (and literature reviews) were employed to engage in discussions with commercial vehicle operators in these studies. 3.2 Approach and Methodology As discussed earlier, findings from three different types of methodology are reported herein: focus groups, executive interviews, and survey efforts. Each of these techniques has been used to identify different aspects of the decisionmaking process as well as differences in use, audience, and findings. Participants are selected based on their relevance to the study, and databases such as InfoUSA establishment data serve as the sampling frames for each of the three methods. 1 Conversion to 2011 dollars based on an exchange rate of 1£ = $1.60 and an inflation rate of 1.84 between 2000 and 2011.

truck carrier and Shipper Perspectives 13 Trade organizations were a good source to identify and connect with the correct person within a company for participation in these efforts. It was felt that this kind of approach would lend credibility to the survey as well as prepare respondents for receiving the phone call, making them less likely to hang up. Reaching the right person in a company was a bigger issue with large firms than with small firms with a few employees. A “pre-warning letter” was also used to prepare respondents for the study. Letters were seen as a means to potentially help with the challenges of getting through front office gate keepers such as receptionists and administrative assistants. Recruiting new participants through contacts at participating firms—that is, snowball sampling—was suggested as a method to increase participation, although with the caveat that using such a method would have selection bias implications. The three methods used are described below: • Focus groups: Focus group discussions provide a social platform to engage multiple stake- holders in one discussion. However, they are limited to engaging participants within or close to the study area. Typical recruitment methodology is to send out e-mail invites or recruit via telephone. Typical sessions tend to last between 90 and 120 minutes and are conducted with the help of a moderator. This method has helped capture invaluable qualitative information regarding business operations from shippers, carriers, and receivers provided that the infor- mation steers clear of proprietary information. • Personal interviews: One-on-one telephone interviews supplement findings from the focus groups and allow the study team to speak with decisionmakers that operate out of far-off headquarters. They are a powerful means to engage individuals from a specific enterprise to respond to a variety of policy scenarios. The personal interview format works very well to minimize privacy or proprietary information concerns that establishments often have in participating in focus groups. • Surveys: Ultimately, most policy decisions must be supported by a quantitative framework that assesses the net impact of the decision. Surveys are either administered over the phone, via mail or, more recently over the web. Surveys allow study teams to capture information from a large number of establishments and are relatively lower cost than either personal interviews or focus groups. But, because there is limited interaction between surveyor and participant in a survey format, it is important to understand the most relevant decisionmaking variables, the appropri- ate terminology, and the behavioral aspects of establishments prior to engaging them in a survey. Hence, the qualitative efforts are utilized first to help streamline the survey approach. When cre- ating surveys, it was also critical to provide sufficient descriptions of alternatives so that survey participants could picture viable “real world” situations—for example, costs included a detailed description of all costs involved such as tolls and parking. In real life, large shippers often receive discounts over displayed rates, which must be captured for modeling purposes. Considering a “delivery window” (e.g., 1 to 3 days, 2 to 4 hours) was an acceptable way to incorporate travel time and on-time delivery factors and reflects how decisions are made by firms. An example project where these three methods were applied was in New York. For this proj- ect, which focused on evaluating alternative means of crossing the Hudson River, stakeholders were approached in 2010 using a comprehensive three-phase market research study. First, focus groups and then interviews were conducted with companies that move significant amounts of freight within the New York–New Jersey area (Komanduri, Musti, and Proussaloglou, 2012). Then, a customized stated-preference survey was administered to a broader group of partici- pants to quantify their route, mode, and time-of-day decisionmaking. Appendix C presents interview guides used for this study. • Focus groups were conducted in New York City; therefore, participants were recruited from a list of companies located within and likely to have freight shipments in the New York (Manhattan), Bronx, Kings (Brooklyn), Queens and Nassau counties. The qualification for

14 incorporating truck Analysis into the Highway capacity Manual inclusion included transportation of freight shipments across the Hudson River (the main focus of the study). A mix of industries, geographies, and short- and long-haul shippers par- ticipated in the focus groups. • For interviews, employees from five major logistics companies and three large retailers were recruited. All recruited individuals were knowledgeable shipping professionals who held key positions within the logistics arms of their organizations such as transportation managers, chief operating officers, and vice-presidents of supply chain and were based primarily in areas other than the New York–New Jersey region. The three large retailers interviewed include one of the largest drugstore chains, a leading discount warehouse club, and a major household goods retailer. These establishments reported shipping at least 50 million pounds of freight annually. The five freight logistics companies were all large national transportation firms that had a huge operational presence in the region. • A total of 854 establishments were recruited using telephone interviews to participate in a stated-preference survey. Criteria for selection included firms that moved cross-Hudson ship- ments, that moved packages of at least 200 pounds, and that use both truck and other modes as the focus of the study was to move trucks off existing crossings. In all cases, most respon- dents reported limited vehicle ownership and a reliance on trucking firms, logistics providers, and other support to meet their transportation needs. The actual mode and details of shipping was often left to these companies, as long as they fit the cost, timing, and other parameters required by the shippers and/or customers. Other studies have used similar types of forums and recruited participants in a similar man- ner. Differences include targeting long-distance shippers, focusing on particular industries, and/or identifying and approaching a wider industry base. However, focus group sizes still remain between 5 and 10 participants to improve the quality of discussion while the number of interviews conducted tends to remain small owing to difficulty in recruiting and retaining high-profile participants for an hour or so. Surveys were designed using either web-based or telephone-based approaches to target larger audiences. 3.3 Shipper Carrier Surveys As part of this study, a private-sector outreach task was conducted in order to identify the dependence on performance measures by the trucking industry (shipper/carrier/logistical con- sultants) when making shipping and routing decisions, as well as the industry perceptions of the quality of service provided by streets and highways for freight transportation. To accomplish this task, a survey was developed by the research team and distributed through a national organization for members of the trucking industry in order to receive a variety of per- spectives on these issues. This section discusses the methodology and details the results of this private-sector survey. This survey was also intended for later use in conjunction with a similar public-sector survey to inform the remainder of this study in the development of recommenda- tions for updating the HCM. 3.3.1 Survey Methodology Through previous survey research, the research team found that the attributes regarded as most important to freight decisionmaking were cost, reliability (on-time delivery), travel time, frequency/flexibility, delivery window, and damage prevention/security/equipment availability. For the purposes of this study, these attributes were grouped into three categories: cost, travel time, and reliability (a category including all of the factors described above, minus cost and travel time). This survey attempted to obtain detailed information about what aspects of these

truck carrier and Shipper Perspectives 15 three attributes were most important to shippers and carriers and what characteristics influence the three attributes. In particular, the survey probed respondents on how these characteristics relate to factors such as design and geometry, which are associated with road planning and other functions that utilize the HCM. Survey Instrument The purpose of developing this survey was to collect industry perspectives about the criti- cal performance measures that affect the trucking industry. These performance measures were based on and serve to expand the research previously conducted by the research team on truck- ing industry decisionmaking. It was determined that the most cost-effective method for reaching a wide audience was to utilize the NCHRP web-survey instrument (documented in Appendix C). Survey respondents were also given a chance to provide additional comments or clarifications after taking the survey. A total of 21 questions were included in the survey. All questions were marked as optional in order to reduce survey fatigue, to allow survey respondents to focus on questions that directly applied to their business, and to reduce the amount of noise through allowing respondents to skip questions. The questions were divided into seven sections, as follows: • Section 1: Context (six questions). This section asked respondents to provide information about their position in their company; mode choice decisions made by their company (includ- ing identifying factors influencing mode choice, e.g., distance, cost); average shipment distance (e.g., long- or short-haul); and the percentage of “just in time” shipments. These questions were developed with the intention of understanding the context in which the decisions regarding shipping and routing that are addressed in the remainder of the survey sections were developed. • Section 2: Truck-Based Shipping Decisions (four questions). This section asked respondents to provide information about how their company makes shipping decisions, who is respon- sible for making the routing decisions, and factors that affect routing decisions. This section also recorded information regarding respondents’ rating on the need for modifying guidelines to road design and geometry for different road types (e.g., freeways, interchanges). • Section 3: Overall Values—Cost, Travel Time, and Reliability (two questions). This section asked respondents to evaluate cost, travel time, and reliability and to rank changes in one attribute to improvements in the other two attributes. • Section 4: Cost (two questions). This section asked respondents to choose factors that affect transportation cost. • Section 5: Travel Time (two questions). This section asked respondents to choose factors used to determine the travel time of a route and to question them on their willingness to pay tolls in order to obtain travel time savings. • Section 6: Reliability (three questions). This section asked respondents to choose charac- teristics associated with a “reliable” or “unreliable” route. Respondents were also asked their willingness to pay tolls in order to obtain an increase in on-time performance. • Section 7: Follow-up (four questions). Respondents were allowed to record any additional thoughts regarding items of the survey they felt required explanation. They also provided contact information if they were willing to participate in follow-up data collection efforts. The full survey text is included in Appendix C, unpublished herein but available at www.TRB. org by searching for NCFRP Project 41. Approach There are some difficulties that often occur when attempting to recruit respondents for plan- ning studies and surveys. These difficulties include the common misconceptions within the indus- try that participation in these studies requires the sharing of proprietary information, a difficulty

16 incorporating truck Analysis into the Highway capacity Manual of recruiting freight establishments to participate in studies, and a lack of interest or time on the part of individuals in private enterprise in participating in these studies. Recent efforts are begin- ning to show better response to these types of outreach, in particular due to the growing sense among establishments that public–private partnerships can help provide solutions that improve business performance. Regardless, approaching industry for research purposes can be difficult. For this study, the research team reached out to a variety of shipping and carrier related industry associations for assistance in distributing the survey. The survey was also posted on a national trucking-related forum. However, due to various reasons, including unfamiliarity with the NCFRP research program and proprietary research involvement requirements, most organizations declined to participate in this effort. Exhibit 2 summarizes the results of efforts to reach out to various national and online trucking organizations. One organization, the Truckers Report Forum, was supportive of the survey and gave permis- sion for the research team to create a forum thread, which was verified and recommended by a site administrator. This verification and recommendation was crucial in presenting the survey as a legitimate (i.e., not “spam”) research effort. The website reported over 800 “views” for the posting during the time the survey was active. This forum was found to be particularly effective in reaching truck drivers and trucking fleet owners for the survey. In addition to the survey responses, 18 com- ments were posted in the Truckers Report Forum thread. Six of these comments are categorized as “feedback” and considered within the scope of the study. The remainder are either administrative or not within the scope of the study. The responses received are included in Appendix C. 3.3.2 Survey Analysis This section provides an overview of the online survey results. Responses were scrubbed and a total of 39 responses were analyzed. The summary statistics of survey responses for each question are included in Appendix C. Section 1: Context A majority of respondents identified themselves as drivers (80%), with the remainder identify- ing as dispatchers or logistics/shipping executives. Of the respondents, 90% reported that they worked for a carrier, with the remainder reporting working for an owner/operator or private fleet. In terms of mode utilization, 82% of respondents reported that they exclusively used the truck mode; 8% of respondents also used intermodal or rail. The majority of respondents (72%) reported using at least some long-haul shipments (>8 hours travel time); 30% of respondents had some shipments that were considered local (<2 hours travel time), while 64% reported some shipments as short-haul (2–8 hours travel time). Of the respondents, 28% indicated that greater than 50% of their shipments were time critical, or “just in time,” shipments. Organization Participated? (Yes/No) Reason Given The Truckers Report Online Forum - www.thetruckersreport.com Yes American Trucking Association (ATA)/American Transportation Research Institute (ATRI) – www.trucking.org No Declined due to proprietary research requirements America’s Independent Truckers’ Association (AITA) - www.aitaonline.com No Did not respond or declined (no reason given) Truckingboards Truck Driver Forums – www.truckingboards.com No Did not respond or declined (no reason given) Truckload Carriers Association – www.truckload.org No Did not respond or declined (no reason given) Exhibit 2. Summary of survey placement.

truck carrier and Shipper Perspectives 17 When asked to rank issues of importance to their shipping mode choice, almost all choices were ranked as “very important” or “somewhat important” by a majority of respondents. The top choices that were ranked highest as “very important” were on-time performance, delivery time frame, cost of shipment, and damage to goods/security. Similarly, the majority of factors presented regarding route selection were ranked as “somewhat important” or “very important” by most respondents. The top factors ranked as “very important” to route decisionmaking were route congestion, travel time, roadway conditions, and delivery time frame. Section 2: Truck-Based Shipping Decisions Several questions were included in the survey to determine who at a particular company con- trols the routing decisions, with the intention of understanding the perspective of the decision- maker who chooses to use a particular route over another. In every case, respondents indicated that the driver was given some control over route selection. For almost half of respondents, the driver is the primary selector of the route, while a quarter indicated that the route is selected by a dispatcher, but the driver has the ability to modify the route if necessary. Respondents were asked which road types needed modifications to design/geometry and also were asked to rank each independently on a 1 to 5 scale from “no need” to a “pressing need.” The road conditions indicated as a “pressing need” include urban streets, intersections, urban freeways, and interchanges. Fewer than 10% of respondents indicated that roadway design/ geometry modifications were not needed on any particular road type. Respondents indicated that a range of factors influenced route selection decisions. Truck parking and traffic congestion were rated as “always being considered” by a third of respondents, while roadway grade and pavement quality were always considered by a quarter of respondents. Availability of truck lanes was the only choice “never” considered at a higher rate than “always” considered. Section 3: Overall Values—Cost, Travel Time, and Reliability When asked to decide between reduced cost, reduced travel time, or increased reliability, responses were close to evenly split: 26% preferred a 10% reduction in travel time, 23% preferred a 10% reduction in cost, and 18% preferred a 10% increase in reliability. When asked to make a tradeoff between two of these factors (e.g., increased reliability with a corresponding increase in cost or decreased travel time with a corresponding decrease in reliability), responses were split across the various permutations. The most common response (23%) indicated that respondents were unwilling or unable to make a tradeoff and would prefer that the three variables remain static. Section 4: Cost Many factors were viewed as adding to the “cost” of a truck route. The factors identified as affecting transportation costs were distance, travel time, time of day, delivery window, route congestion, and roadway conditions. Factors attributed to the “cost” of travel on a particular roadway were tolls, vehicle wear and tear, traffic congestion, and cost of delay. Other factors not included in the survey but identified by respondents include fuel prices and reload availability. Section 5: Travel Time Less than half of respondents indicated that their company took action to minimize or man- age travel time on a route. Factors that are adjusted to minimize or manage the travel time of a shipment include using the shortest distance route or adjusting the time of day/delivery window. Factors not included in the survey but added by respondents included avoiding city rush hours and taking the “fastest route.” When asked how much they might be willing to pay to decrease travel time by 10% (as a percentage of cost), 43% of respondents indicated “nothing,” while only 10% of respondents indicated that they would be willing to pay any amount.

18 incorporating truck Analysis into the Highway capacity Manual Section 6: Reliability Out of the three focus characteristics of cost, travel time, and reliability, the latter appears to be highly associated with road design and characteristics. The survey asked what characteristics would be attributable to a reliable route. The most common response was high quality road (e.g., level terrain, wide lanes and shoulders, good pavement), followed by few intersections or traffic stops, no known construction, and “route my company uses often.” Conversely, charac- teristics of an unreliable route rated by a high number of respondents include poor road quality, high traffic volume, traffic congestion (51%), multiple intersections or traffic stops, and con- struction. Lack of truck parking was also selected by more than one-third of respondents as a characteristic of an unreliable route, and the truck parking issue was also brought up in several respondents’ free response comments. Few respondents reported a willingness to pay to increase their reliability. Section 7: Follow-up Five respondents indicated that they would be willing to participate in a follow-up interview and provided phone and/or email contact information. Four of these respondents, and five additional respondents, included additional comments, a sample of which follows: • “As a 10-year driver through 48 states, I will say that our highway system is terrible. I-5 in CA is bad, I-70 through IN and OH is bad. Certain states leasing toll roads to companies is really bad. There is a huge lack of truck parking in many states. I route myself away from many states due to road conditions, so I don’t buy fuel or spend money in these states as a result.” • “I went to school for Civil Engineering/Land Survey—where do I begin other than the fact most designers have NO CLUE what it’s like to pilot an OTR truck down the road. I’d make every designer in the DOTs get a Class A CDL and have them all get some road experience.” • “We regularly route around toll roads. They are much too expensive and are usually poorly maintained. We pay more than enough in fuel taxes to eliminate toll roads completely.” • “On the unreliable delivery time, we haven’t had that problem. We allow flex time for unan- ticipated delays. We have good reliability and think we know within the company how best to improve it.” 3.3.3 Discussion Although the findings of this survey represent a limited sample of industry perspectives and do not represent a detailed cross section of road users, several themes do emerge that provide valuable information on the preferences and perceptions of the freight trucking industry. It is clear that many aspects of road design and geometry, as well as the issues of congestion and road conditions, play a role in the broader decisions made by the freight industry. Overall, this survey served as a confirmation that the issues of cost, travel time, and reliability are important and often interwoven concerns that influence business decisionmaking. The interplay between cost, travel time, and reliability is complex, and many of the underly- ing measures contribute to more than one of these issues. In particular, the distance traveled, road congestion and condition, and time of day/delivery window factors play a part in multiple issues. Findings show that respondents were able to make the connection between factors of road design and geometry and these issues of interest—for example, vehicle wear and tear and the cost of delay were both seen as contributing to the “cost” of choosing a road by 40% to 50% of respondents. Respondents were also able to identify factors that made a road “reliable” or “unreliable,” particularly road quality, traffic volume or congestion, and intersections/traffic stops. These factors in particular are influenced by the planning process and road design and, thus, represent candidates for truck-specific factors to be incorporated into the HCM.

truck carrier and Shipper Perspectives 19 When asked about the types of roads needing design/geometry guideline modifications to better serve trucks, findings show that overall the respondents believe that there is a high need for modifications on all road types. Two out of three respondents reported a need for modifica- tions to urban and non-urban freeways and other highway types, interchanges, urban streets, and intersections. This confirms the intention of this project—that there is a need to better incorporate truck considerations into the planning process. When asked about specific types of roadway/geometric factors influencing their route selection, truck parking, traffic congestion, and pavement quality received the highest number of responses, indicating that they were highly influential in route selection. Respondents were less concerned with the availability of truck lanes or the design of intersec- tions. These findings indicate that the respondents in the study appear to be aware of road and route geometry and characteristics and incorporate these into their planning and operations. Hence, it makes sense to have improved standards by incorporating variables that are currently missing in the HCM such as reliability, travel time, and transportation cost and to tie them to road design or geometry parameters that are used by road planners. Finally, although respondents were able to identify areas that they felt needed improvement, they were less willing to make a tradeoff between different factors of importance (i.e., cost and travel time). In the business world, many companies have likely already made these tradeoffs to find the business models that work best for their company. Hence, it is understandable that companies might be reluctant to pay more or reduce some aspects that are important to them even if it does provide a savings in another area. 3.4 Findings from Shipper Carrier Survey This section synthesizes the key findings from the different studies. They are organized under broad topical areas. Special emphasis is placed on the LOS variables that are most relevant to this study. 3.4.1 Decisionmakers Control over decisionmaking varies depending on the size of the establishment and the amount of freight the establishment moves annually, as well as the role of the establishment in the logistics supply chain: • In general, receivers and shippers that do not own their own fleet tend to control time-of-day for pick-up and delivery while leaving the routing decisions up to carriers. • However, small shippers and receivers that move a limited amount of freight each year have limited control over decisionmaking and are dependent on rules employed by transportation service providers. • In fact, depending on the nature of goods being delivered and the establishments being served, delivery windows varied from “a fixed time” to “over six hours.” • Receivers and shippers that manage their private fleet, on the other hand, control all aspects of decisionmaking and are involved in developing customized logistics chains. Many respondents commented that they had limited time during work hours to take a phone survey. Most commented they would be willing to give 10 minutes, although a few said they would only give 5 minutes. Hearing the name of an official organization early in the call made respon- dents pay more attention and prevented hang-ups. Some wished to hear answers to “what’s in it for me” type questions during the survey.

20 incorporating truck Analysis into the Highway capacity Manual 3.4.2 Decisionmaking Variables Establishments evaluate several attributes when making freight decisions. In interviews con- ducted across our studies, respondents identified transportation costs, travel time and reliability as the top factors in making freight decisions. Other related issues such as local governance laws for delivery times and routing were also critical to decisionmaking. In some urban areas, toll and parking costs are also important inputs to decisionmaking. Focusing on shipments across the Hudson, respondents developed a list of attributes that were important in their consideration of transportation modes and services. Participants were asked to rank a list of transportation factors that are considered in mode choice based on their importance in the consideration process using a 10-point scale, with 10 being the most impor- tant and 1 being the least important. The three most important attributes were cost, reliability and delivery time, followed by security features and avoidance of shipment damage. In addi- tion, special needs of certain shipments were found to impact consideration of shipment mode. Results are summarized in Exhibit 3. Other decision factors include the ability to track the shipment from origin to destination. Tracking was important to most participants who move freight, although some placed more emphasis on this as a decision factor than others. Customer service was not immediately recog- nized as a key decision factor, although discussions revealed that it was important when selecting a transportation service provider. Firms with poor customer service records, particularly related to on-time reliability and/or damages, were often not selected to move shipments. Factor Ranking* Notes Cost 10 Ranked consistently across the board Reliability (On-Time Delivery) 10 Typically considered slightly less important than cost Travel Time 9 Related to On-Time Delivery. Customers are normally informed of a specific timeframe for delivery, developed by using total travel time and other factors. Frequency – Flexibility 9 Frequency and flexibility of shipment arrangements are a factor in mode choice Damage Prevention/Security Transportation Equipment Supply 9 Prevention of damage to goods and ensuring safe arrival were very important. Having the right equipment and personnel is seen as a necessary step. Payment Terms 6 Not regarded as important Special Handling Equipment Customer Service Technology Origin and Destination Restraints Low (<5) These were all rated as relatively less important. However, when problems develop in these areas, special equipment needs, customer service and technology capabilities, and work rule/time slot restrictions can become extremely important. Environmental Considerations Very Low (<3) Respondents whose companies were responsible for the disposal of environmentally sensitive materials rated this consideration as important. Generally, environmental issues, carbon footprints, etc., are not included in the transportation managers’ perspective. *10 is “most important” and 1 is “least important.” Exhibit 3. Attributes central to freight decisionmaking in New York and New Jersey.

truck carrier and Shipper Perspectives 21 Highway versus Non-Highway Modes of Transportation Several factors influence modal decisions: • The shipping needs of the business translated as the nature of the goods being moved has a critical impact on the modal selection. For instance, bulk goods such as coal are almost always shipped on rail irrespective of freeway performance. • Trip length also influences modal selection. For instance, shippers in New York reported that they would never choose rail for trips shorter than 400 miles. • The service provided by competing modes is a critical factor in modal determination. For instance, rail has a relatively higher mode share to a central location such as Chicago whereas New York City, which has poor freight rail service, has about 2% of rail mode share. • Interviewed establishments reported relying on rail for at least some long-haul shipments, pri- marily motivated by lower costs. In general, establishments identify rail as a low-cost, slow mode of transportation. Retailers reported making tradeoffs routinely while making modal decisions. • Some firms reported a strategy of avoiding congested routes at all costs. Approaches using alternate roadways or shipping goods by rail or air were preferred. Participants from larger establishments in focus groups across the country reported dealing directly with trucking firms for their shipment needs. A majority were less inclined to deal with shipment details (e.g., whether shipment went by rail) and were interested only in knowing that shipments arrived as scheduled in undamaged condition. A few respondents reported interest in knowing the specifics about all modes and carriers used. The concern was that an intermediate carrier might be a “Mom and Pop with no insurance” and, therefore, less reliable. The possibil- ity of damaged goods or late delivery with the introduction of rail or other modes was also the cause of some unease. Supply Chain Logistics Most large establishments utilize distribution centers, which operate as “hubs” between ven- dors and retail establishments. Respondents reported that operating these hubs improved trans- portation efficiency as vendors were able to ship goods destined for many stores via the same carrier. Distribution centers allowed retailers to operate using different shipping strategies: • The most commonly reported—“just in time” type shipping—allows goods to ship to the store at the last opportune moment. This type of shipping minimizes warehousing and stock- ing costs and increases their ability to conform to their customer’s needs; however, it does place a higher burden on the transportation system and demands higher reliability. • The second strategy—“managing shipments based on the predictability of lead time”—is sometimes used in which store-managers are expected to place orders at the appropriate time to supply their inventory needs. This type of shipping may incur inventory stocking fees, but allows for more flexibility in delivery and travel times. These supply chains are dependent, to a large extent, on the reliability of transportation ser- vices. In fact, several participants reported choosing slower options that were more reliable than the fastest service. Carriers typically break down a long-haul trip into a series of smaller legs depending on the location of their distribution centers. Typically, a trip from New York to California may be bro- ken down into three legs with stops at two intermediate distribution/consolidation centers. At each of these distribution centers, carriers consolidate or break down their loads depending on the final destination and number of trucks available to make the trip. Should enough trucks be not available at any one or more of these intermediate stages, carriers may choose to move goods on rail to maintain efficiency and meet the travel time requirements for the goods being shipped.

22 incorporating truck Analysis into the Highway capacity Manual Long-Term Contracts Retailers reported using a bidding process to determine the most efficient way to ship goods across the country. The carriers are made aware of the shipping strategy of the company and are expected to price their bids accordingly. For instance, a “just in time” shipment may need to be delivered in a relatively short timeframe while the general replenishment of an in-stock item running low may have a delivery window of a few days. Depending on the volume of goods shipped, they are often provided large discounts over the “spot rate” provided to smaller shippers. “Spot rate” roughly translates to the highest possible shipping rate between an origin- destination pair. Retailers reported paying close attention to both on-time delivery and damages. While not stated explicitly, it is understood in the commercial movement circles that these fac- tors play a role in identifying the most competitive bidder. Typically, goods were classified into four categories based on volume—parcel, less than truck- load, full truckload, and intermodal load. Some retailers reported selecting different carriers for different volumes of goods being shipped. Logistics firms reported tailoring their shipping choices to meet the requirements of their client. In several cases, the clients often made modal decisions for goods movement. This is more apparent among larger clients who ship enough volume to justify making modal decisions for the logistics firms. Establishments reported that in many cases, customers would specify a shipping preference. This was more common when customers had an existing shipping contract or had negotiated a lower cost rate with a specific carrier than the manufacturer could quote. Transportation man- agers usually welcome this because they are unlikely to be held responsible for any transporta- tion related incidents. In instances where the manufacturer has a better rate for shipping than the customer, their routes are selected. In these cases, the transportation manager informs the customer, who, in turn, makes the final carrier selection. A similar consideration process occurs with regards to suppliers. Depending on the materials being shipped, the manufacturer may stipulate shipping requirements, but, in many cases, the supplier makes the shipping decision. Routing Decisions Several carriers reported making detailed route maps for their drivers and tracking the move- ment of trucks along the way. Drivers were instructed to contact their dispatch officer if they anticipated having to deviate more than 5 miles from their assigned route. Routing decisions for most large firms were made using custom route optimization software products. Routing decisions vary depending on the length of the trip. Local deliveries are often carried out on congested, local arterials whereas long-haul deliveries are almost always made using freeways and major roadways. A study in Los Angeles found the following with regard to routing decisions: • More than three-quarters (77%) of companies used a routing system that was either manual or a combination of a manual system and an automated system. Twenty-one percent of the firms indicated that routing was handled by the drivers, and this was more prevalent among firms with 25 or more trucks, whereas 29% said that drivers handled routing, compared with 18% for firms with fewer than 25 trucks. • Of the companies surveyed, 38% reported that they relied, at least in part, on Automatic Vehicle Location (AVL) systems or Global Positioning Systems (GPS) or technologies for fleet management. More than one-half of the firms (54%) with a fleet size greater than 25 used such a system, compared with just under one-third (32%) of firms with smaller fleet sizes that employed AVL/GPS as a fleet management tool. • Information sources with direct impacts on time had the highest overall value to respondents. On a 5-point scale where 1 is least valuable and 5 is most valuable, knowledge about queue lengths at the Port of Los Angeles and Long Beach scored the highest at 4.03. Real-time route informa- tion between origin and destinations also had a high value to respondents, with a mean rating

truck carrier and Shipper Perspectives 23 of 3.83. Travel times along freeway segments and information about the location of bottlenecks with travel time through the obstructed area received similar ratings at 3.74 and 3.70, respectively. • Of the drivers surveyed, 90% used information to change routes as appropriate, either in- route (47%) or before leaving (43%). However, only 11% used it to change pick-up/delivery times or to accept or decline assignments. This suggests that there is limited flexibility in drivers’ ability to determine when they are on the road. • Knowing the fastest routes, the location and delay time associated with bottlenecks, and times to travel different freeway segments were all assessed as top value information. • The key improvements desired by drivers included better freeway traffic information and information that was easier to use, more accurate, and delivered faster. Each of these improve- ments was rated as useful or very useful by at least 90% of drivers, suggesting that there is a strong desire to see better delivery of accurate and actionable information. Key Routes and Governance Laws Evidence gathered from the research suggests that truckers prefer using Interstates and major roads for the majority of trips. These roadways are preferred for their limited stops, sufficient clearance and for providing reasonably fast service between origins and destinations. However, research from a project in Los Angeles indicated that the use of surface streets for goods move- ment also depended on the length of the overall trip. For instance, for trips where the average trip distance was less than 50 miles, 80% of the trips involved use of a surface street, compared with only 55% of trips longer than 50 miles. On a related note, truckers are precluded from using certain roadways based on local gover- nance laws. For instance, in New York City, several parkways preclude commercial vehicles from operating on them. Such laws have an impact on routing, and operators are forced to choose less optimal routes for travel between an origin-destination pair. Oversize/Overweight Truck Movements In addition to the typical LOS attributes considered by most truckers, oversize/overweight (OSOW) trucks must focus on additional factors when selecting which roads to travel. Often, OSOW vehicles must submit specific routings when applying for a permit. Both the trucking company and the permit-issuing agency have concerns specific to or more enhanced for OSOW trucks. In many cases, the lowest cost or more direct route may not be available due to infrastructure or classifica- tion restrictions. Some of the most common factors for OSOW trucks are summarized in Exhibit 4. 3.5 A Model to Quantify Quality-of-Service Perceptions Numerous studies of freight transport economics and the shippers’ decisionmaking process show that the choice to ship via truck and the choice to ship via a specific motor vehicle carrier hinge on cost, time, and reliability. Virtually all other factors, such as pavement quality, and safety, can be captured via a combination of cost, time, and reliability. For instance, pavement quality and collisions affect a carrier’s operating costs (through higher insurance rates, lower reliability, and more frequent tire replacements), which translate into higher fees charged to shippers and less assurance of making the delivery on time. It is critical to understand the relative importance placed on each of these measures so that they can be appropriately weighed and fed into a truck LOS calculation. Therefore, researchers have worked towards quantifying the rela- tionship between travel time, distance, reliability, and shipment costs in freight decisionmaking. The research team developed a series of choice models that aim to capture this very relation- ship in a New York and New Jersey study. Key findings include that shippers, receivers, and carriers contribute equally to freight decisionmaking; cost, travel time, and on-time reliability affect decisions; and respondents value their participation in surveys at $100 per hour and prefer

24 incorporating truck Analysis into the Highway capacity Manual to be recruited over the phone for short surveys. These findings are in line with earlier studies on freight decisionmaking such as those performed by Danielis et al. (2005): • Respondents were shown two truck route variations and were asked to make tradeoffs based on on-time reliability, travel times, and transportation costs. Through a binomial logit model, reliability emerged as an important factor, and high reliability routes (>90%) were preferred over medium reliability (85% to 90%) and low (<85%) reliability routes. • As expected, higher transportation costs and travel times negatively impact route choice (Danielis et al., 2005). Interestingly, both of these variables were found to impact behavior differently for different commodities. In fact, establishments reported varying sensitivities to cost based on the commodity being shipped, the distance of travel, and the time taken to travel between origin and destination. • There was a non-linear sensitivity to cost—that is, for moves with higher transportation costs, respondents were less sensitive to a dollar increase (decrease) in cost when compared with moves with lower transportation costs. Similarly, long-haul movers were less sensitive to unit increases in travel time when compared with short-haul movers. These results suggest that long, expensive shippers are less interested in unit savings in cost and time. This is a critical observation which suggests that shippers making long trips must be presented with larger travel time (or cost) savings to influence behavior to the same extent as short trips. Factor Description Truckers’ Responses Roadway Classification Interstates, U.S. highways, and state highways are generally built to withstand heavier loadings and higher traffic volumes than other roads. Truck routes must be designed to avoid any roads not accessible to trucks and often utilize truck routes and/or highways when possible. Mileage Minimize impacts from OSOW vehicles on public safety and infrastructure by encouraging or requiring agencies to use the shortest routes that are possible using roads built to handle OSOW traffic (e.g., Interstates). When selecting a route, may utilize strategies such as “ramping,” which allow trucks to exit and then re-enter a facility in order to avoid a particular bridge or obstruction, instead of following a longer route avoiding the facility with the obstruction all together. Local Permits States can provide permits for state and federal roads. Municipalities can require additional permits for locally owned or maintained roads. Need to balance permitting time, cost, and requirements of a local route versus a longer bypass route. Corridor Routes Some states have designated corridors or “preferred routes” for OSOW traffic. Preferred routes can reduce effort required to plan a route and receive a permit, but may not be the shortest possible route. Other Restrictions Routes that would normally be acceptable for OSOW traffic can be restricted or banned for reasons including time-of-day, and political, seasonal, and construction- related reasons. Certain routes or urban areas have time restrictions. Depending on the move schedule, carriers will use this as a factor in selecting a route. If there is a delay on a route that will force them to stop travel, they will avoid the route. Bridge Limitations Heavier loads are requested or required to not cross restricted bridges and infrastructure. If a crossing is required, trucks may be required to wait for a particular time window, obtain pilot cars, or follow other restrictions, increasing time and cost. If possible, carriers will often avoid bridges and facilities that have additional restrictions. Intersection Limitations Some intersections, including roundabouts and traffic circles, are not designed for OSOW trucks. Routes must avoid these intersections. Generally more applicable to larger loads. Inspection Stations Fixed or mobile sites where state or federal personnel conduct safety, permitting, weight, and other inspections of vehicles. Trucks may avoid roads with inspection stations in order to save travel time and/or avoid inspection. Exhibit 4. Impact of local laws on oversize-overweight truck routing decisions.

truck carrier and Shipper Perspectives 25 The calculated values of time varied from as low as $5.00/hr for long-haul movers shipping bulk commodities such as coal to as high as $170/hr for short-haul moves transporting high-end consumer electronic goods. Equation 1 presents the binary route preference utility model fitted to the New York/New Jersey panel survey. This model captures the sensitivity of decisionmaking for alternative truck routes. The estimated parameter values are presented in Exhibit 5. Exhibit 6 presents the values of time suggested by the choice model. 0, 900 1 0, 12 2 0, 25 Equation 1 U LR MR A SC CS Max SC CT ETT TS Max ETT TS Max ETT G G ( ) ( ) ( )= + + ∗ + ∗ − + ∗ + ∗ − + ∗ − where U = expected utility of shipping route; LR = dual value variable; = -0.758 if shipment is expected to be on-time with less than 85% probability, = 0 otherwise; Exhibit 5. Route preference choice model. Coefficient Description Value T-Stat On-Time Reliability Low Reliability (<85% on-time) –0.758 –4.4 Medium Reliability (85-90% on-time) –0.275 –1.4 Shipment Cost Cost Agricultural Goods –0.0108 –4.4 Cost Metal and Mining Goods –0.0095 –5 Cost Construction Goods –0.0086 –7 Cost Chemical Goods –0.0092 –6 Cost Wood and Paper Goods –0.0109 –5.6 Cost Electronics Goods –0.0099 –5.2 Cost Transportation and Utility Goods –0.0060 –4.1 Cost Wholesale and Retail Goods –0.0068 –7 Cost Spline (Applied if Cost > $900) 0.0053 5.7 Travel Time Time (hr) –0.320 –5.6 Time Spline 1 (Applied if TT > 12 hr) Agricultural Goods 0.237 3.6 Time Spline 1 (Applied if TT > 12 hr) Metal and Mining Goods 0.173 3.1 Time Spline 1 (Applied if TT > 12 hr) Construction Goods 0.166 3.2 Time Spline 1 (Applied if TT > 12 hr) Chemical Goods 0.146 2.4 Time Spline 1 (Applied if TT > 12 hr) Wood and Paper Goods 0.156 2.8 Time Spline 1 (Applied if TT > 12 hr) Electronics Goods 0.135 1.7 Time Spline 1 (Applied if TT > 12 hr) Transportation and Utility Goods 0.205 3.8 Time Spline 1 (Applied if TT > 12 hr) Wholesale and Retail Goods 0.174 3.6 Time Spline 2 (Applied if Travel Time >= 25 hours) 0.109 2.6 Pseudo R2 (0) 0.415 Pseudo R2 (c) 0.324 Number of Observations 716 Notes: • Student’s “t” statistics greater than 2.0 or less than -2.0 generally indicate that the value of the coefficient is significantly different from 0 at the 95% confidence level. • Pseudo R2(0), the correlation coefficient, indicates the quality of fit compared with a constant 0 value. A value of 1.0 is exceptionally good, a value of 0.0 is exceptionally poor. • Pseudo R2(c) indicates the quality of fit compared with a constant mean value of the data. • A spline is a variable that takes on a specific constant value only for a specific range of another variable.

26 incorporating truck Analysis into the Highway capacity Manual MR = dual value variable, = -0.275 if shipment is expected to be on-time with between 85% and 90% probability, = 0 otherwise; AG = shipping cost parameter for good type “g” values as shown in Exhibit 5; SC = shipment cost ($) (note: average shipment size in survey was 2,000 lbs); CS = cost spline constant of 0.0053 added for shipments over $900 in cost; CT = -0.320, the expected shipping time parameter; ETT = the expected shipping time (hr); TS1G = Time Spline 1, an additive constant for good type “g” that is applied only if the expected shipping time exceeds 12 hours; values as shown in Exhibit 5; and TS2 = Time Spline 2, an additive constant value of 0.109 that is applied only if expected ship- ping times are 25 hr or greater. The route choice models clearly indicate that a single value of time often used in demand mod- els to describe freight movement is an extreme simplification. This research suggests that values of time vary by distance, shipment cost, and commodity. Further, results suggest that shippers who move high-value commodity goods over short distances are more likely to embrace policy options such as congestion pricing in return for improved travel times than are others. The model also reveals that short-haul shippers would choose highway alternatives that could generate a 1-hr savings in travel time for a toll of up to $30 over current toll rates in the New York region. However, most long- and short-haul shippers are likely to switch to less congested and circuitous routes that take 1 to 2 hr longer if a new $60 toll were imposed on the most congested and direct routes. While unlikely, a variable toll by commodity could be enforced to impact congestion and freight behavior at a finer level. It is important to note that the model highlights findings from a highly customized study conducted in New York. The findings from that study should by no means be applied without properly understanding the context of that study. We merely present the model to highlight the point that decisionmaking is affected by multiple factors such as cost, travel time, and reliability. Sensitivity to a host of other qualitative factors such as establishment location, customer prefer- ences, and urgency, while not explicitly captured by the model, are captured by the constant: • The route preference model helps compute the probability of choosing a particular route. For instance, if a shipper is faced with the task of shipping a commodity from Point A to Point B and has two potential routes available, the route preference model may be used to calculate Value of Time (per hr) *Cost<$90 0 Time>24 hr Cost<$900 12<T<24 hr Cost<$900 Time<=12 hr Cost>=$900 Time>24 hr Cost>=$900 12<T<24 hr Cost>=$900 Time<= 12 hr Agricultural — $7.69 $29.63 — $15.09 $58.18 Metal and Mining — $15.47 $33.68 $9.05 $35.00 $76.19 Construction $5.23 $17.91 $37.21 $13.64 $46.67 $96.97 Chemical $7.07 $18.91 $34.78 $16.67 $44.62 $82.05 Wood and Paper $5.05 $15.05 $29.36 $9.82 $29.29 $57.14 Electronic $7.68 $18.69 $32.32 $16.52 $40.22 $69.57 Transportation and Utility (TU) — $19.17 $53.33 $8.57 $164.29 — Wholesale and Retail $5.44 $21.47 $47.06 $24.67 $97.33 — *Cost is shipment cost. Exhibit 6. Values of time suggested by the choice model.

Truck Carrier and Shipper Perspectives 27 the probabilities of each route being selected based on measurable characteristics such as transportation costs, travel times, and reliability of the routes. • The negative coefficients on travel time in the model suggest that if a particular route has a higher travel time, then that route has a lower utility and is more likely not to be chosen for the shipment. • A time spline is a variable that indicates the impact of a variable after a specific range on the utility of a choice is slightly different. For example, in Exhibit 7, the solid line indicates the negative directionality of cost, and the dashed line lowers the negative effect and creates a kink in the utility at cost $900. • The t-stat (Student’s t test) is a test to measure the statistical significance of the estimated coefficients. A t-stat value greater than 1.96 for positive coefficients and less than -1.96 for negative coefficients indicates that the value of the coefficient is significantly different from 0 at the 95% confidence level (thus, rejecting the null hypothesis). 3.6 Conclusions on Carrier and Shipper Perceptions The interviews and survey of shippers and carriers indicate that freight decisionmaking is complex and often varies by establishment. In addition, the criticality of travel time and on- time delivery varies by a factor of 10 depending on the cost of the material being hauled and the distance hauled (travel time). Lower valued goods hauled for longer distances (or times) have the lowest value of time. Therefore, it is very difficult to develop one unique set of criteria that fit all establishments. However, it is possible to develop a general assessment of criteria that fit most establishments using detailed marketing research approaches. In general, travel time, cost and reliability (on-time performance) are the key determinants of route selection. Local laws, long term contracts between shippers and receivers, the type of goods being shipped, transportation costs and travel times, and logistics supply chains all impact the relative importance of these attributes in decisionmaking of shippers, receivers, and carriers. In conclusion, the three most critical highway-related factors affecting motor vehicle carrier and shipper perceptions of the quality of service provided by the highway facilities on a given route are: the shipment time (travel time), the probability of on-time arrival (reliability), and the transport cost for the shipment. Exhibit 7. Example of cost spline effect on utility curve.

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TRB’s National Cooperative Freight Research Program (NCFRP) Report 31: Incorporating Truck Analysis into the Highway Capacity Manual presents capacity and level-of-service techniques to improve transportation agencies’ abilities to plan, design, manage, and operate streets and highways to serve trucks. The techniques also assist agencies’ ability to evaluate the effects of trucks on other modes of transportation.

These techniques are being incorporated into the Highway Capacity Manual, but will be useful to planners and designers working on projects with significant truck traffic.

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