Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
8 It is crucial to effectively incorporate freight considerations into transportation planning and policymaking because the freight system is an essential part of a vibrant economy, a determinant of quality of life, and a key component of efforts to combat global warming and climate change. In essence, the freight transportation system is important because of both its positive and nega- tive contributions to modern life. On the positive side, an efficient freight system is necessary for economic competitiveness and to realize the full potential of economic globalization. On the negative side, freightâlike the rest of the transportation sectorâproduces significant amounts of negative externalities that, in turn, generate community opposition. Transportation agencies and metropolitan planning organizations (MPOs) are therefore under pressure to balance the conflicting objectives of those involved in and impacted by freight activity. These considerations acquire greater significance given the major economic trends shaping the twenty-first century. These trends suggest that the freight system will have to cover a larger geographic area, be more responsive to user needs and expectations, cooperate in national security efforts, reduce the impacts of truck traffic, and do all of this in a context in which providing additional freight infrastructure capacity will become more difficult and expensive. Essentially, the freight trans- portation system will have to do more with less. This challenge is compounded by the complexity of freight activity and the lack of appropri- ate freight models currently affecting all facets of demand modeling: generation, distribution, mode choice, and traffic assignment. There is a great need to enhance the quantitative aspects of freight demand modeling, which is the rationale for NCFRP Project 44. The ultimate goal is to ensure that freight models (1) have solid behavioral foundations, (2) are multimodal, and (3) are able to include feedback effects from changes in policy variables (Hedges 1971). In the area of freight mode choice policy, there is a particularly woeful lack of research and data on the impacts of policy-induced freight modal shifts. The last freight mode choice research efforts at the national level were conducted more than 25 years ago (McFadden et al. 1986b, Abdelwahab and Sargious 1991). A better understanding of the variables influencing freight mode choice would enable more accurate demand forecasts, better quantification of the impacts of freight activity, and more effective policies. Although small efforts have been conducted to collect mode choice data, their small sample size and reliance on Internet-based questionnaires leads to concerns about selectivity-bias and data quality. The main goal of NCFRP Project 44 was âto develop a handbook for public practitioners that describes the factors shippers and carriers consider when choosing freight modes and provides an analytical methodology for public practitioners to quantify the probability and outcomes of policy-induced modal shifts. . . .â The team accomplished this goal by means of an arduous multi-prong research effort that is described in this report. The following presents the report structure along with brief descriptions of the remaining chapters. C H A P T E R 1 Introduction
Introduction 9 Part A: Overview of Freight Mode Choice and Influencing Factors includes Chapters 2 and 3: â¢ Chapter 2 presents in-depth analyses of the historical patterns of freight mode shares. â¢ Chapter 3 provides a technical identification of the influencing factors at the market (macro) level, and at the shipper (micro) level that shape freight mode choice decisions. Part B: Freight Mode Choice Modeling includes Chapters 4 and 5: â¢ Chapter 4 provides an in-depth technical review of the potential modeling methodologies, both econometric and supply-chain-based, that could be used to develop freight mode choice models. â¢ Chapter 5 presents a critical evaluation of the advantages and disadvantages of the various methodologies and a description of how the most appropriate ones were selected for NCFRP Project 44. Part C: Model Estimation includes Chapters 6 through 8: â¢ Chapter 6 describes the process of gathering the 4.5 million records in the confidential Com- modity Flow Survey (CFS) microdata file and merging them with the even larger Longitudinal Business Database (LBD), as well as the process of preparing custom-made datasets with the modal attributes (i.e., door-to-door travel time, referred to in this report as âtransit timeâ; freight rates; and three different versions of generalized costs) and merging them to prepare the master dataset for estimation of the freight mode choice models. â¢ Chapter 7 describes the modeling formulations of four sets of market-share models esti- mated (transit times and freight rates and the three versions of generalized costs) and twelve sets of shipment-level models estimated (transit times and freight rates; the three versions of generalized costs; and three different weighting schemes to ensure that the models replicated the market shares in the CFS microdata, the domestic market shares embedded in the Freight Analysis Framework [FAF], and the total cargo handled in the country, both domestic and imports and exports) at the level of two digits in the North America Industrial Classification System. â¢ Chapter 8 presents the models selected from more than 1,000 models estimated by the team and analyzed to identify the ones that met the conditions of being conceptually valid and statistically significant. Part D: Case Studies and Numerical Experiments includes Chapters 9 and 10: â¢ Chapter 9 presents six case studies of freight mode policy efforts in the United States. â¢ Chapter 10 details numerical experiments using hypothetical examples inspired by the Crescent and Heartland Corridors that were conducted to gain insight on the ability of the models to produce sound estimates of the impacts of hypothetical policies. This arduous effortâwhich required more than 100 person-trips to one of the Census Bureauâs secured Research Data Centers (RDCs) to use the confidential CFS microdata and the LBDârepresents the largest and most comprehensive freight mode choice research effort in the United States and the world and is the first one that has used the confidential CFS microdata.