Structural commodity generation model that uses public data

Fatemeh Ranaiefar, Joseph Ying Jun Chow, Daniel Rodriguez-Roman, Pedro Camargo, Stephen Ritchie

Research output: Contribution to journalArticle

Abstract

Freight forecasting models are data intensive and require many explanatory variables to be accurate. One problem, particularly in the United States, is that public data sources are mostly at highly aggregate geographic levels but models with more disaggregate geographic levels are required for regional freight transportation planning. A second problem is that supply chain effects are often ignored or modeled with economic input-output models that lack explanatory power. This study addressed these challenges with a structural equation modeling approach that was not confined to a specific spatial structure, as spatial regression models would have been, and allowed correlations between commodities. A model for structural commodity generation that was based on freight analysis framework was specified, estimated, and shown to provide a better fit to the data than did independent regression models for each commodity. Three features of the model are discussed: indirect effects, supply chain elasticity, and intrazonal supply-demand interactions. A goal programming method was used with imputed data to validate the geographic scalability of the model.

Original languageEnglish (US)
Pages (from-to)73-83
Number of pages11
JournalTransportation Research Record
Issue number2378
DOIs
StatePublished - Dec 1 2013

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Supply chains
Freight transportation
Scalability
Elasticity
Planning
Economics

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

Cite this

Structural commodity generation model that uses public data. / Ranaiefar, Fatemeh; Chow, Joseph Ying Jun; Rodriguez-Roman, Daniel; Camargo, Pedro; Ritchie, Stephen.

In: Transportation Research Record, No. 2378, 01.12.2013, p. 73-83.

Research output: Contribution to journalArticle

Ranaiefar, F, Chow, JYJ, Rodriguez-Roman, D, Camargo, P & Ritchie, S 2013, 'Structural commodity generation model that uses public data', Transportation Research Record, no. 2378, pp. 73-83. https://doi.org/10.3141/2378-08
Ranaiefar, Fatemeh ; Chow, Joseph Ying Jun ; Rodriguez-Roman, Daniel ; Camargo, Pedro ; Ritchie, Stephen. / Structural commodity generation model that uses public data. In: Transportation Research Record. 2013 ; No. 2378. pp. 73-83.
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