Enhancing Freight Logistics: A Discrete-Continuous Model Approach Using Public Data for Multimodal Mode Selection

Authors

  • Taleb Eissa*, Rodrigo Mesa-Arango a, Kamal Mamoua, Hussin A.M Yahia, Shaban Ismael Albrka Ali, Mohd Azizul Ladin, Ali Ahmed Mohammed

Keywords:

Freight movement, Commodity Flow Survey data (CFS 2012), U.S. Census Bureau, with (NAICS) and (SCTG) Standard Classification, Aggregate model, discrete-continuous model, Freight mode choice, Multimodal Freight Mode

Abstract

This study presents a macroscopic model for U.S. freight transportation, integrating mode choice and shipment size decisions. Utilizing 2012 Commodity Flow Survey and U.S. Census Bureau data, it employs a discrete-continuous econometric framework to address selectivity bias. The model aggregates commodities into classifications based on the North American Industry Classification System (NAICS) and the Standard Classification of Transported Goods (SCTG), providing a comprehensive description crucial for economically consistent freight mode selection. Numerical findings underscore the significance of commodity characteristics, NAICS, and geographic distribution in influencing joint decisions for nine modes of transportation, varying from a single mode to competition between two or more modes.

 

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Published

2023-12-30

How to Cite

Taleb Eissa*, Rodrigo Mesa-Arango a, Kamal Mamoua, Hussin A.M Yahia, Shaban Ismael Albrka Ali, Mohd Azizul Ladin, Ali Ahmed Mohammed. (2023). Enhancing Freight Logistics: A Discrete-Continuous Model Approach Using Public Data for Multimodal Mode Selection. SJIS-P, 35(3), 780–799. Retrieved from http://sjis.scandinavian-iris.org/index.php/sjis/article/view/766

Issue

Vol. 35 No. 3 (2023)

Section

Articles