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dc.contributor.advisorMesa-Arango, Rodrigo
dc.contributor.authorEissa, Taleb Eissa Ali
dc.date.accessioned2019-11-05T15:17:37Z
dc.date.available2019-11-05T15:17:37Z
dc.date.created2019-05
dc.date.issued2019-05
dc.date.submittedMay 2019
dc.identifier.urihttp://hdl.handle.net/11141/2983
dc.descriptionThesis (Ph.D.) - Florida Institute of Technology, 2019en_US
dc.description.abstractMode choice is an important strategic decision for shippers to carry commodities efficiently. Freight mode-choice is an important activity to develop a successful freight transportation business in the private sector and to plan for economically consistent freight transportation infrastructures in the public sector. Freight activities result from the complex interactions between different economic agents, but these relationships are commonly relaxed to account for three major agents: shippers, carriers and receivers. Furthermore, the behavior of freight choice is commonly not concentrated in one agent, but rather is divided jointly over multiple individuals and firms in a logistics process, each component of which represents particular policies and specialists from different backgrounds. Shipper freight modal choice depends on freight demand, infrastructure, and the quality of service characteristics of alternative transportation modes. Moreover, freight logistics characteristics, like the attributes of the shipper, the attributes of the commodities to be transported, as well as the spatial attributes of shipments strongly influence freight mode selection. In the United States, due to the heterogeneity of firms, commodities, and issues of confidentiality and reliability of data, relatively little research has been done on modeling freight mode choice compared with the choice behavior associated with passenger travel. This dissertation explores several dimensions of the problem employing advanced econometrics analytical tools. These dimensions include: publicly available freight data 2012 Commodity Flow Survey (CFS) Public Use Microdata (PUM), behavioral attributes driving the selection of freight services, and novel industry-cluster concept. Analytical tools include: sophisticated discrete choice models; multinomial logit model with random parameters, and discrete-continuous econometric framework. The dissertation is organized as follows: Chapter 1 introduces the problem and related concepts. Chapter 2 studies the attributes driving the selection of freight services and propose an econometric model as well as novel industry-cluster concepts to understand the freight mode choice using aggregated data from Commodity Flow Survey. Chapter 3 proposes a discrete-continuous econometric model and a set of industry-type clusters are postulated to describe freight mode choice and tested with the 2012 Commodity Flow Survey. Chapter 4 proposes a choice set approximation for different shipments to demonstrate only the available freight modes for any shipment. Finally, Chapter 5 the outcomes of this research have shown that many of the shipments characteristics and logistics clusters affecting mode choice vary with the shipper and the industry. This research provides meaningful discussion and guidance to understand the complex process for freight transport selection at regional level. Likewise, the analytical results demonstrate the benefits and efficiencies of the proposed models, which are transportation modeling contributions.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.rightsCC BY-SA 4.0en_US
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/legalcodeen_US
dc.titleEffect of Industry Clusters and Commodity Flow Characteristics on the Selection of Freight Transportation Modes in the United States with Advanced Econometric Approachesen_US
dc.typeDissertationen_US
dc.date.updated2019-07-01T15:21:30Z
thesis.degree.nameDoctor of Philosophy in Civil Engineeringen_US
thesis.degree.levelDoctoralen_US
thesis.degree.disciplineCivil Engineeringen_US
thesis.degree.departmentMechanical and Civil Engineeringen_US
thesis.degree.grantorFlorida Institute of Technologyen_US
dc.type.materialtext


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