A Derived Demand Function for Freight Transportation

Friedlaender, Ann F.; Spady, Richard H.

doi:10.2307/1927111

Cited by 76 publications

(38 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Oum reported relatively high Allen elasticities of substitution (σ) between railroads and trucks for transporting the output of these manufacturing industries, declaring, "the two modes are intrinsically highly substitutable in moving most commodities, but less so for lumber." (p. 476) He found much larger cross-price elasticities than Friedlaender and Spady (1980) found. On the other hand, Oum's own-price elasticities were smaller than Friedlaender and Spady's (1980) and were generally less than or equal to one.…”

mentioning

confidence: 77%

“…Friedlaender and Spady (1980) estimated transportation share equations derived from the cost functions of a sample of manufacturing industries using data from the Census of Transportation and calculated factor demand elasticities for railroad and trucking transportation services from these equations. It turned out that the less-than-truckload general freight segment dominated the trucking data from the Census of Transportation.…”

Section: Demand Functions-trucking and Railroadsmentioning

confidence: 99%

See 1 more Smart Citation

Publications information

1978

IEE-IERE Proc. India UK

View full text Add to dashboard Cite

mentioning

confidence: 77%

Section: Demand Functions-trucking and Railroadsmentioning

confidence: 99%

Publications information

1978

IEE-IERE Proc. India UK

View full text Add to dashboard Cite

“…Clark et al (2005)] An additional measure of elasticity, the cross-price elasticity, is used to estimate which of two interchangeable modes will be substituted for the other when there is a price increase in one of the modes, as follows: a cross-price elasticity greater than zero indicates that the two modes are substitutes and there is a potential for mode shift; an elasticity of zero indicates that there is no relationship; and an elasticity less than zero indicates that the modes complement each other and there is a potential for mode shift. Figure 4.2 presents the cross-price elasticities between rail and truck from studies reviewed in the Navigation Economic Technologies Program report (Oum 1989;Friedlaender and Spady 1980;Winston 1981;Abdelwahab 1998). There is some variation, but most commodities and modes are fairly inelastic, supporting the idea that, in many cases, mode shift potential is small based on price changes alone.…”

Section: Prices and Modal Shiftsmentioning

confidence: 95%

Transportation Energy Futures Series: Freight Transportation Modal Shares: Scenarios for a Low-Carbon Future

Brogan¹,

Aeppli²,

Beagan³

et al. 2013

View full text Add to dashboard Cite

This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a U.S. Department of Energy (DOE)-sponsored multi-agency project initiated to identify underexplored strategies for abating greenhouse gases (GHG) and reducing petroleum dependence related to transportation. The project was designed to consolidate existing transportation energy knowledge, advance analytic capacity-building, and uncover opportunities for sound strategic action.Transportation currently accounts for 71% of total U.S. petroleum use and 33% of the nation's total carbon emissions. The TEF project explores how combining multiple strategies could reduce GHG emissions and petroleum use by 80%. Researchers examined four key areas -lightduty vehicles, non-light-duty vehicles, fuels, and transportation demand -in the context of the marketplace, consumer behavior, industry capabilities, technology and the energy and transportation infrastructure. The TEF reports support DOE long-term planning. The reports provide analysis to inform decisions about transportation energy research investments, as well as the role of advanced transportation energy technologies and systems in the development of new physical, strategic, and policy alternatives.In addition to the DOE and its Office of Energy Efficiency and Renewable Energy, TEF benefitted from the collaboration of experts from the National Renewable Energy Laboratory and Argonne National Laboratory, along with steering committee members from the Environmental Protection Agency, the Department of Transportation, academic institutions and industry associations. More detail on the project, as well as the full series of reports, can be found at http://www.eere.energy.gov/analysis/transportationenergyfutures. .................................................................................................................... ........................................................................................... 70 References ............................................................................................................................ EXECUTIVE SUMMARYFreight transportation modes-truck, rail, water, air, and pipeline-each serve a distinct share of the freight transportation market. A variety of factors influence the modes chosen by shippers, carriers, and others involved in freight supply chains. Analytical methods can be used to project future modal shares, and federal policy actions could influence future freight mode choices. This report considers how these topics have been addressed in existing literature and offers insights on federal policy decisions with the potential to prompt mode choices that reduce energy use and greenhouse gas emissions. Options for Moving 18.5 Billion Tons of FreightTruck, rail, water, air, and pipeline services provide a spectrum of competitive and complementary freight transportation options, with each mode offering advantages and disadvantages in terms of price, speed, reliability, accessibility, visibility, secu...

show abstract

“…We used research methods from life-cycle analysis, transportation economics, and local food case-study literature in formulating and conducting the survey (Friedlaender & Spady, 1980;Hummels, 2007;King, Hand, & DiGiacomo, 2013;Moneta, 1959;Mundler & Rumpus, 2012;Wang et al, 2000). For life-cycle analysis accounting, the research unit of interest should be clearly defined (Rebitzer et al, 2004).…”

Section: Local Farmer Surveymentioning

confidence: 99%

Locational Advantage and the Impact of Scale: Comparing Local and Conventional Fruit and Vegetable Transportation Efficiencies

Grigsby

Hellwinckel

2016

J. Agric. Food Syst. Community Dev.

View full text Add to dashboard Cite

Some have suggested that in order for local foods to reach broader consumer segments and become price-competitive with foods sold in mainstream market channels, local farmers need to scale up their production and distribution operations to match the efficiencies of the conventional food system. In this study, we take a first step in evaluating how scaling up production and distribution could make locally produced foods more competitive with the conventional food system. We compare the transportation efficiencies of the conventional and local fruit and vegetable transportation networks in Knoxville, Tennessee, and determine the Knoxville-area food system's competitive transportation zones, defined as the region in which local farmers' shorter travel distances to market give them a locational advantage in transportation over their long distance, conventional food supply chain competitors. We analyze the extent to which local farmers' scales of production and distribution affect their transportation efficiencies, and we investigate factors that could improve their competitiveness with conventional distribution networks. We find that farms located within 25 miles (40 km) of the downtown market tended to deliver their produce to market at least as efficiently as conventionally distributed foods from California. More distant farms needed to scale up their production and distribution operations to remain within the competitive transportation zones. Investigating travel distance thresholds could provide policy-makers with useful information in planning land use and infrastructure investment projects for local food systems and in a *

show abstract

A Derived Demand Function for Freight Transportation

Cited by 76 publications

References 11 publications

Publications information

Publications information

Transportation Energy Futures Series: Freight Transportation Modal Shares: Scenarios for a Low-Carbon Future

Locational Advantage and the Impact of Scale: Comparing Local and Conventional Fruit and Vegetable Transportation Efficiencies

Contact Info

Product

Resources

About