Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook (2016)

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9 This chapter describes the concepts necessary to characterize the freight transportation system and its relationships to the land use system and the study of FG/FTG/STG. The Freight System Characterizing the freight system is challenging because of its multifaceted and highly hetero- geneous nature. It is hard to think of any other component of the transportation system that is more varied. The agents in the freight system exhibit many fundamentally different behaviors and involve more interacting parties than any other component of the transportation system. More importantly, the system is pervasive in modern life yet rarely studied. Because of this com- plexity, the freight system is best described by defining the relevant dimensions that characterize it and discussing each of these dimensions in some detail. The multidimensional nature of the freight system poses a major challenge to simple land use classification systems because it may not be possible to characterize such complexities by a single metric. A formal characterization requires defining the interacting agents within the system, and the links between them. A direct consequence of modern economies is their reliance on complex logistics and freight systems. It is useful to envision the freight system as the physical manifestation of the economy as, in most cases, monetary transactions are accompanied by a commodity flow in the opposite direc- tion. In essence, freight activity is economic activity in motion. The first level of complexity is related to the many agents that influence the generation of freight. So to understand the generation of freight, one must have a basic understanding of the connections among various economic agents. To decompose the process and facilitate understanding, the concept of a production- consumption (PC) link is useful. A PC link represents the transaction that connects a producer of cargo with the next consumer (which could be the end user or an intermediate consumer who uses the cargo as an input to another PC link). Figure 1 presents a schematic of some of the possibilities, together with the corresponding trip origins and destinations. In essence, a typical supply chain comprises many PC links by which an economic agent produces/ships freight that other agents process/transform and store, and ultimately deliver to intermediate or end consumers. Obviously, if the agents are not collocated, transportation has to take place. This, in turn, is what produces the vehicle trips that transportation planners and engineers capture as trip origins (O) and trip destinations (D). In simple supply chains (e.g., a farmer who sells produce to the local market), the corresponding PC pattern is straightforward. In complex supply chains (e.g., in the automobile industry), there could be hundreds of PC links corresponding to the various stages of the production process. The multiplicity of possibilities is overwhelming. To understand freight demand, one must study the underlying supply chains that satisfy the needs of the PC links that make up a production and distribution process. This is because C h a p t e r 2 Key Concepts

10 Using Commodity Flow Survey Microdata and Other establishment Data to estimate the Generation of Freight, Freight trips, and Service trips the transportation flows generated as part of those PC links materialize into freight traffic (e.g., truck trips). The main focus of this research is on locations where the cargo is produced, transformed, stored, or consumed (i.e., the nodes in the transportation network). Understand- ing the underlying process that determines how much freight is produced or attracted for the key land use classes is the key objective of this research project. Consequently, the study of the FG and FTG must consider (1) production sites/shippers; (2) intermediate processing points, including storage; and (3) intermediate and end consumer sites. Important practical reasons exist to be comprehensive in the study of FTG. Although it is easy to identify generators of freight and truck trips such as production sites, warehouses, trucking companies, and ports, the role of consumer-oriented businesses (e.g., retail stores) as generators of truck trips is frequently overlooked. The need to study FTG by service and retail businesses has long been recognized as a key priority (Fischer and Han 2001), but the role of consumer- oriented businesses as generators of truck trips is frequently overlooked. Frequently—and par- ticularly in urban areas—small establishments produce, as a group, more truck trips than any single large generator. As an example, calculations made by the research team indicate that the 10,000 restaurants and bars in Manhattan, New York, produce more truck traffic than do the Port Authority of New York and New Jersey terminals combined. A number of agents participate in freight transportation: shippers, carriers, receivers, third- party logistics operators, freight forwarders, and warehouses/distribution centers, among others. The main agents are: • shippers: the agents that produce or ship freight; • carriers: the agents that provide transportation services to the shipper to carry cargo to their respective destinations; and • receivers: the destination agents that receive the cargo sent from the shipper, including inter- mediate and end consumers. As a consequence of the individual agents fulfilling their roles at each stage, no single agent is able to provide information that yields a complete picture of the functioning of the entire system. Assembling a coherent description of the whole requires assembling the information Production Transportation Processing, storage Consumption Shipper, producer Carrier Distribution centers, warehouses Intermediate consumer End consumer To another PC link O1 O2 O3 O5 D2 D3 D5 D4 The arrows represent transportation flows, O is a trip origin, D is a trip destination, and the numbers represent the distinct physical locations of the agents. Figure 1. Production-consumption (PC) link.

Key Concepts 11 provided by the composite parts (i.e., the different agents, who may be aware only of those aspects that concern their operation). Table 1 summarizes information with which each agent is typically familiar. Table 1 shows that producers and shippers of cargo are typically aware of the characteristics of the cargo that they receive and/or ship out; however, they do not know much about what happens once the freight vehicles leave their facilities. Carriers know the details of their operations— including the loaded and empty trips produced. Quite frequently, however, carriers are not aware of the attributes of the cargo they transport. Carriers also know to whom they deliver, though they do not necessarily know who else is delivering to a particular customer. The consumers of the cargo (i.e., the receivers), know the details of the cargo they receive/ship out, though they do not always know how many vehicle trips have been generated because many of them only observe the number of deliveries (a truck trip could be used to make multiple deliveries). Transportation agencies have an idea about truck traffic in the network and land use patterns; however, in most cases, they know very little about the freight flows in their jurisdictions. In summary, of the agents involved in freight, none has sufficient information to fully describe what happens in the system as a whole. This situation has important implications for data collection efforts, as most surveys rely on the information gathered from the participants in the freight activity. The fundamental challenge is how to assemble that information into a com- prehensive FG picture that is relatively accurate, practical, and conceptually correct. From the standpoint of FG and FTG, there should be no doubt that the consumers and producers of the cargo are the agents that are able to provide the most complete view because they have the details of the cargo they receive and/or ship out, as well as the corresponding delivery frequencies and shipment sizes. This implies that establishment data—and the models estimated with them— are the most accurate. Freight Generation Shippers/ Producers Carriers Distribution Centers/ Warehouses Consumers of Cargo (Receivers) Transportation Agencies Amount of cargo Yes (1) Yes (1) Yes (1) Yes (2) No Number of loaded vehicle trips Yes (1) Yes (1) Yes (1) Not always At key links (No distinction between loaded and empty) Number of empty vehicle trips No Yes (1) No No Number, frequency of deliveries Yes (1) Yes (1) Yes (1) Yes (2) No Commodity type Yes (1) Not always Yes (1) Yes (2) Only at some ports of entry Shipment size Yes (1) Yes (1) Yes (1) Yes (2) No Cargo value Yes (1) Not always Not always Yes (2) Only at some ports of entry Land use patterns Yes (1) Yes (1) Yes (1) Yes (1) All (1) Only of the cargo that they handle. (2) For all the cargo they receive. Source: Holguín-Veras et al. (2012). Table 1. Partial views of the freight system.

12 Using Commodity Flow Survey Microdata and Other establishment Data to estimate the Generation of Freight, Freight trips, and Service trips Relationship Between the Freight System and Land Use This section discusses the interconnected relationship between freight activity and land use, building on both empirical evidence and theory. On the one hand, land use patterns can impact FG/FTG/STG patterns, as the different activities generate different amounts of freight-related trips. Conversely, the freight system also can have a significant impact on land use, and this typically occurs with large developments such as distribution centers, terminals, ports, and intermodal centers, which not only influence the freight flows, but also the geographic patterns of land use surrounding them. The lack of consensus among professionals with respect to a definition for the term “land use” blurs the connections between freight and “land use.” Although some evidence exists of the application of the Land-Based Classification Standards (LBCS) for freight, the comprehensiveness of the dimensions (e.g., activity, function, structural characteristics, site development character, and ownership) would be very useful for understanding the relationships between the freight system and land use. For example, in studies that use the ITE Trip Generation Manual land use classifications (i.e., primarily structure-based or site descriptors), it should be possible to map these classifications to the LBCS Structure categories, whereas studies using employment codes (e.g., SIC or NAICS) could be mapped to the LBCS Function categories, and those using land use planning designations could be mapped to the LBCS Activity categories. Each dimension could have a different impact on FG or FTG, making it essential to reclassify various studies’ outcomes. In describing the connections between the freight system and land use, it is important to distinguish between two separate aspects: (1) how land use at the establishment level influences FTG, and (2) how freight activity and land use interact with each other at the system level. These effects are shown in Figure 2. Although both aspects are important, given that the main emphasis of this project is the impact of land use on FTG, the freight/land use connections are not discussed here. Determining how land use impacts FG/FTG/STG requires resolving and reconciling the difference of opinions between economic/logistic and transportation literature. The economic/ logistic literature suggests that FTG is determined by the FG (in itself the output of an economic process), along with a host of interactions concerning shipment size and total logistics costs. Interestingly, this body of literature barely mentions land use as a factor. The reason seems to Inputs (cargo) Freight trip generation Notation: Output (Freight generation) Establishment: * Economic activity * Size: - Employment - Area, etc. * Land use class * Other attributes Carrier: Based on shipments from the establish- ment and others, decides on: * Vehicle type *Delivery frequency (Freight Generation) (Freight Trip Generation) Surrounding Land Use System: * Spatial distribution of activities * Externalities (posi- tives and negatives) Main focus of NCFRP Project 25(01) Figure 2. Schematic of connections between freight and land use.

Key Concepts 13 be that, in most cases, land use is a constraint to the production process, not an input. From the economic/logistic point of view, the input factors that determine FG and FTG include labor, capital, and other intermediate inputs to the process. In essence, the larger the employment or the capital, the larger the FG (while other factors, as discussed, determine the impact on FTG). In contrast, the research conducted by the NCFRP Project 25(01) team stresses the importance of separately studying FG as well as FTG. The analyses described in this guidebook indicate that business establishments attract and produce cargo (i.e., FG) that translates into freight vehicle trips (i.e., FTG). The amount and nature of the incoming and outgoing FG depends on the type of business, and its size. In contrast, the FTG depends on the corresponding shipment sizes and the ability of the carriers to consolidate their shipments (e.g., with the shipments of other establishments). Other factors, such as storage capacity constraints, inventory and transporta- tion costs, and so forth play a key role in determining shipment sizes, delivery frequencies, and the amount of inventory. In addition to FG and FTG, STG at the establishments also is important to consider. The travel of technicians that is associated with the services they provide results from the specialization and interconnectedness of modern economies, in which businesses increasingly rely on other businesses for the provision of key services. This focus suggests that an establishment’s land use is, at best, a proxy for the underlying economic activity being conducted. However, in the absence of detailed information about an establishment’s economic characteristics, assuming that FTG depends on general characteristics of land use may just be a pragmatic solution. The weakness of this decision is that various land use classes group together economic sectors with fundamentally different FTG patterns. In essence, the adequacy of land use attributes as explanatory variables depends on how well the land use class matches the FTG patterns of the industry segments that have been included. In cases for which there is a good match, land use is likely to be a good predictor. In contrast, if a land use class groups disparate economic activities, it is unlikely to be a good explanatory variable.