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1 The movement of freight through the roadway system is a key source of unreliability in mod- ern supply chains. Automation and other technologies have made production and warehousing increasingly efficient and predictable, however delays on the roadâfor example, from severe weather or crashesâcan cause significant supply chain disruptions. Almost all supply chains are exposed to these risks, because they often involve one, if not multiple truck shipments. Most shippers account for uncertainty in truck shipments by adding slack in their supply chains and having alternatives ready in case delays are substantial. However, these contingencies take up resources and increase the costs of products. Trucking companies also introduce slack in their operations to deal with unreliability, from adding a buffer to delivery schedules to having trucks and drivers available to pick up after delayed shipments. This effectively decreases the productivity of their assets, ultimately forcing them to charge higher rates. Shippers and truck- ing companies that do not take precautions against unreliability face steep costs when they have to scramble in response to a delayed shipment. Even with all appropriate precautions, supply chains can still be disrupted if delays are large enough. The reliability of shipments has arguably become even more important in the past couple of decades, as shippers turn to just-in-time supply chains to manage inventories more efficiently. In these âpullâ supply chains, shipments need to be scheduled precisely so that they arrive exactly when needed, reducing the need for expensive inventories at multiple stages of the supply chain. The ability of companies to adopt these logistic strategies and seek efficiencies is constrained by unreliability in truck arrival times. This type of uncertainty represents a key limitation in the further optimization of supply chains. All this has led to a consensus in the research literature that reliability is the most important variable for most shippers and trucking companies. Kurri et al. (2000) found on the basis of their survey that âthe most important conclusion is that it is not the transport time that matters but rather the reliability of transport time.â Maier et al. (2002) concluded similarly that âreliability obviously is the most valuable performance characteristic in logistic managerâs evaluation of transportation services.â Through interviews of shippers, Bolis and Maggi (2003) also found that âthe most important qualities of transport and logistics services are reliability, followed by price, speed, and safety.â This conclusion is ubiquitous throughout the literature, even in studies that did not initially focus on reliability. 1.1 Public Sector Challenge Despite the importance of reliability in freight transportation, this variable has generally not been considered by planners in the evaluation of roadway projects. The freight benefits of projects have, therefore, been systematically underestimated, which has likely led to fewer investments C H A P T E R 1 Introduction
2 Estimating the Value of Truck Travel Time Reliability that improve freight transportation. The underfunding of freight projects ultimately reduces the efficiency of supply chains and decreases economic competitiveness. The main reason why reliability has typically not been considered in planning analyses is the lack of robust methodologies for quantifying and monetizing improvements in reliability. There have been no nationwide studies in the United States into how much shippers and trucking companies value reliability, and, more fundamentally, there does not exist a consensus in the literature for how reliability should be measured or modeled. The most recent guidance on benefitâcost analysis published by the U.S. Department of Trans- portation (2018) states that the department âdoes not have a specific recommended methodology for valuing reliability benefits in BCA [benefitâcost analysis],â even though âimprovements in reliability [are] highly valued by transportation system users, particularly for freight movement.â In contrast, this guide provides detailed methodologies for quantifying the benefits of many other factors, from travel time savings to reductions of emissions of different pollutants. It is critical that planners have clear methodologies for quantifying the importance of reliability relative to all these other factors. Otherwise, the status quo will continue to disadvantage freight in regional and national planning efforts. 1.2 Value of Reliability The importance of reliability to freight users and the broader economy is often represented by the value of reliability (VOR). This parameter is defined as the rate at which the costs of ship- pers and trucking companies increase as unreliability on the road increases. The VOR considers both the opportunity costs of adding slack to supply chains and the direct costs when delays overcome the slack and lead to disruptions. The VOR attempts to summarize all these costs into a single figure that represents the average marginal impact of unreliability on freight users. If a shipper makes a recurring shipment that faces half a unit of unreliability (however mea- sured) and has a VOR of $100, then the shipper would face on average $50 of unreliability costs per shipment. This does not imply that every shipment incurs exactly $50 of unreliability costs, but instead, that over 100 shipments, the total costs of unreliability are likely to be $5,000. This calculation considers implicitly the likelihood of delays (corresponding to half a unit of roadway unreliability) and their costs. In this example, the shipper would be equally well-off if there was a way for it to pay $50 per shipment to have full certainty that all shipments arrive on time. From this perspective, it is easy to see that the VOR represents the burden of roadway unreli- ability on the economy. Planners need robust estimates of this parameter to consider reliability in existing planning processes. 1.3 Research Objective The objective of this research was to estimate the VOR for trucking under different circum- stances and provide guidance for how to use these estimates to answer common freight planning questions. To this end, the Reliability Valuation Framework was developed to provide trans- portation professionals and planners practical guidance on how to assess roadway performance from the perspective of freight users. This included recommendations for how to measure and model reliability in ways that are compatible with VOR estimates, existing planning processes, and available data sources. These methodologies allow VOR estimates to be used to evaluate roadway projects, identify truck bottlenecks, and assess system performance. While the main objective of this research was to provide clear and tractable guidance for plan- ners and analysts, theoretical issues in network modeling, statistical modeling, and survey design
Introduction 3 are also described to convey the strengths and weaknesses of the framework and facilitate future research in this area. This study is the second phase of a research effort sponsored by the National Cooperative Highway Research Program (NCHRP). The first phase, summarized in NCHRP Report 824 (Hirschman et al. 2016), focused on learning how shippers and trucking companies think about unreliability and respond to mitigate its negative impacts on their operations. This study used interviews and a survey to better understand the perspective of freight users and provide a win- dow into how the sector deals with unreliability. The conclusions of that study informed the assumptions adopted in the present study, so that the Reliability Valuation Framework reflects the realities of trucking in the U.S. 1.4 Target Audience The primary audience of this research is state and local transportation agencies that are seek- ing to better incorporate freight reliability in their planning processes. This study provides esti- mates of the truck VOR that are applicable in a wide range of conditions and then describes in the Reliability Valuation Framework how to use these values. This practical guidance is pre- sented alongside theoretical discussions of how the VOR is estimated and how it can be used, so that researchers and analysts can develop their own valuation frameworks that work best in local conditions. This could include conducting targeted surveys and estimating VOR parameters for specific circumstances. 1.5 Report Organization The remainder of this report is organized as follows: â¢ Chapter 2: Background provides an overview of how the literature has conceptualized the causes, impacts, and costs of unreliability and the responses to it. This chapter also provides an overview of how previous research studies have estimated the VOR and concludes that a stated-preference survey was likely to provide the best results for this project. â¢ Chapter 3: Stated-Preference Survey describes how the survey was structured and admin- istered. This chapter also briefly provides summary statistics for the 1,142 respondents who completed the survey. â¢ Chapter 4: Modeling first presents an analytical model for representing how motor carriers and shippers are affected by reliability and then uses the insights learned from this model to estimate statistical models that best capture the respondentâs trade-offs in the stated- preference data. This chapter also recommends several VOR and value of time (VOT) values for use in planning analyses. â¢ Chapter 5: Reliability Valuation Framework provides practical guidance on how to use VOR and VOT estimates to answer common freight planning questions. Emphasis is placed on methodologies that could be easily implemented by state and local transportation agencies using publicly available data. â¢ Chapter 6: Case Study demonstrates how to use the Reliability Valuation Framework to identify truck bottlenecks on a corridor of I-35 in Austin, Texas, and then estimate the benefits to users of improving capacity at a particularly congested segment. â¢ Chapter 7: Conclusions provides an overview of the key findings of the study and presents lessons learned in surveying and modeling that can be used in future estimations of VOR. â¢ Appendix A: Stated-Preference Survey Design reviews the literature on how to design stated- preference surveys, particularly for estimating VOR, and goes into greater detail on the ratio- nale behind several of the design choices made for the survey used in this study. â¢ Appendix B: Survey Responses describes in detail the characteristics of the respondents who completed the survey and provides some descriptive statistics of their responses.