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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2016. Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/24602.
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Page 132
Page 133
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2016. Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/24602.
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Page 133

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.

132 Bureau of Transportation Statistics (2008). “Commodity Flow Survey: Detailed Description.” Retrieved March 7, 2007, from http://www.bts.gov/programs/commodity_flow_survey/detailed_description/index.html. Cambridge Systematics, Inc. (1996). Quick Response Freight Manual. Final Report of the Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Cambridge Systematics, Inc. (2007). Quick Response Freight Manual II. Final Report of the Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. FHWA-HOP-08-010 EDL No. 14396. Clark & Chase Research, Inc. (2008). “2008 National Congestion Impact Survey (08003).” Survey prepared for the Reason Foundation. Fischer, M. J., and M. Han (2001). NCHRP Synthesis 298: Truck Trip Generation Data: A Synthesis of Highway Practice. Transportation Research Board of the National Academies, Washington, D.C. Fowler, J. (2001). The Commodity Flow Survey and Hazardous Materials Safety Data: Perspectives on Use, Content, and Needs for the Future. Presented at the 80th Annual Meeting of the Transportation Research Board, Washington, D.C. Hartgen, D. T., G. M. Fields, A. L. Layzell, and E. San Jose (2014). “Employer Views on Traffic Congestion,” Policy Brief 115 (February 2014). Available from: http://reason.org/files/employer_views_traffic_congestion.pdf. Holguín-Veras, J., M. Jaller, L. Destro, X. Ban, C. Lawson, and H. S. Levinson (2011). Freight Generation, Freight Trip Generation, and Perils of Using Constant Trip Rates. Transportation Research Record: Journal of the Transportation Research Board, No. 2224, Vol. 1, Transportation Research Board of the National Academies, pp. 68–81. Holguín-Veras, J., M. Jaller, I. Sánchez-Díaz, J. Wojtowicz, S. Campbell, H. Levinson, C. Lawson, E. L. Powers, and L. Tavasszy (2012). NCHRP Report 739/NCFRP Report 19: Freight Trip Generation and Land Use. Transporta- tion Research Board of the National Academies, Washington, D.C. Available from http://onlinepubs.trb.org/ onlinepubs/nchrp/nchrp_rpt_739.pdf. Holguín-Veras, J., I. Sánchez-Díaz, C. Lawson, M. Jaller, S. Campbell, H. S. Levinson, and H. S. Shin (2013a). Transferability of Freight Trip Generation Models. Transportation Research Record: Journal of the Transportation Research Board, No. 2379, Transportation Research Board of the National Academies, Washington, D.C., pp. 1–8. Available from: http://dx.doi.org/10.3141/2379-01. Holguín-Veras, J., M. A. Silas, J. Polimeni, and B. Cruz (2007). An Investigation on the Effectiveness of Joint Receiver-Carrier Policies to Increase Truck Traffic in the Off-Peak Hours: Part I: The Behaviors of Receivers. Networks and Spatial Economics 7(3), pp. 277–295. doi: 10.1007/s11067-006-9002-7. Holguín-Veras, J., J. M. Wojtowicz, C. Wang, M. Jaller, X. J. Ban, F. Aros-Vera, S. Campbell, X. Yang, I. Sánchez-Díaz, J. Amaya, C. González-Calderón, R. Marquis, S. D. Hodge, T. Maguire, M. Marsico, S. Zhang, S. Rothbard, K. Ozbay, E. F. Morgul, S. Iyer, K. Xie, and E. E. Ozguven (2013b). Integrative Freight Demand Management in the New York City Metropolitan Area: Implementation Phase. Final Report submitted to U.S. Department of Transportation. Available from http://cite.rpi.edu/news/16-off-hour-delivery. Institute of Transportation Engineers (ITE) (2004). Trip Generation Handbook: An ITE Recommended Practice. Washington, D.C. Institute of Transportation Engineers (2008). Trip Generation: An ITE Informational Report. Washington, D.C. Institute of Transportation Engineers (2012). Trip Generation Manual. Washington, D.C. Lawson, C., Holguín-Veras, J., I. Sanchez-Diaz, M. Jaller, S. Campbell, and E. Powers (2012). Estimation of Freight Trip Generation Based on Land Uses. Proceedings of the 91st Annual Meeting of the Transportation Research Board, Washington, D.C. Sánchez-Díaz, I., J. Holguín-Veras, and X. Wang (2014). An Exploratory Analysis of Spatial Effects on Freight Trip Attraction. Transportation: 1–20. Available from: http://dx.doi.org/10.1007/s11116-014-9570-1. References

References 133 Tomer, A., and J. Kane (2014). Mapping Freight: The Highly Concentrated Nature of Goods Trade in the United States. Available from: http://www.brookings.edu/research/reports2/2014/11/06-mapping-freight-tomer- kane?utm_campaign=Metropolitan+Policy+Program&utm_source=hs_email&utm_medium=email&utm_ content=14841696&_hsenc=p2ANqtz—FGwrqD-S2D1W-Z4m-6ob9vWojaPg0ojevf76OfSk69yZHZ- prB6kPijXheAXhE59nI_CCr2uZw3TUIKkrXEZlAp-oPg&_hsmi=14841696. U.S. Census Bureau (2013). “Zip Code Business Patterns.” Database. Information retrieved February 17, 2014, from http://www.census.gov/epcd/www/zbp_base.html.

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Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook Get This Book
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TRB's National Cooperative Freight Research Program (NCFRP) Research Report 37: Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook provides policy makers with improved establishment-level models that estimate the Freight Trip Generation (FTG), the number of vehicle trips produced and attracted at a given establishment; the Freight Production (FP), the amount of cargo produced by the establishment; and the Service Trip Attraction (STA), and the number of vehicle trips that arrive at the establishment to perform a service activity. These models, estimated with the best data available, provide tools to assess the various facets of the overall Freight and Service Activity (FSA) that takes place in urban and metropolitan areas. The models will allow transportation practitioners to conduct sound curb-management, properly size loading and unloading areas, support traffic impact analyses, and improve transportation planning and management efforts.

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