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MiF3 method: Modeling intermodal fluidity freight flows

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  • Cedillo-Campos, Miguel Gastón
  • Lizarraga-Lizarraga, Giovanni
  • Martner-Peyrelongue, Carlos Daniel

Abstract

Modern industrial systems have developed advanced supply systems going from just-in-time to just-in-sequence deliveries based on intermodal freight transport solutions. However, the increase of product variety, and multiple interfaces needed to deliver products have exposed them to vulnerability of variability. Thus, information on how fluid an intermodal freight transport solution is, becomes critical to private decision makers for knowing if supply chains are achieving their goals. Additionally, it is significant to public decision makers in determining if and where enhancements in infrastructure and/or in policy and regulations might improve economic development. Therefore, as a result of detailed analysis of the processes involved from a systems approach, this paper contributes to the body of knowledge by proposing a mathematical framework to model and forecast supply chain fluidity when using any intermodal freight transport combination. Its spatial and temporal flexibility lets expand the analysis to handle a wide range of intermodal paths. The proposed method contributes to demonstrate the key connection between improvements in supply chain performance and enhanced economic development. As a conclusion key issues for improving fluidity of intermodal freight flows are discussed, and future research is presented.

Suggested Citation

  • Cedillo-Campos, Miguel Gastón & Lizarraga-Lizarraga, Giovanni & Martner-Peyrelongue, Carlos Daniel, 2017. "MiF3 method: Modeling intermodal fluidity freight flows," Research in Transportation Economics, Elsevier, vol. 61(C), pages 15-24.
    • Handle: RePEc:eee:retrec:v:61:y:2017:i:c:p:15-24
    DOI: 10.1016/j.retrec.2017.01.001
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    References listed on IDEAS

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    1. Jesus Gonzalez-Feliu, 2013. "Multi-stage LTL transport systems in supply chain management," Post-Print halshs-00796714, HAL.
    2. repec:hal:wpaper:halshs-00796714 is not listed on IDEAS
    3. Bueno-Solano, Alfredo & Cedillo-Campos, Miguel Gastón, 2014. "Dynamic impact on global supply chains performance of disruptions propagation produced by terrorist acts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 1-12.
    4. Dullaert, Wout & Zamparini, Luca, 2013. "The impact of lead time reliability in freight transport: A logistics assessment of transport economics findings," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 190-200.
    5. Thun, Jörn-Henrik & Hoenig, Daniel, 2011. "An empirical analysis of supply chain risk management in the German automotive industry," International Journal of Production Economics, Elsevier, vol. 131(1), pages 242-249, May.
    6. Vilko, Jyri P.P. & Hallikas, Jukka M., 2012. "Risk assessment in multimodal supply chains," International Journal of Production Economics, Elsevier, vol. 140(2), pages 586-595.
    7. Pfohl, Hans-Christian & Köhler, Holger & Thomas, David, 2010. "State of the art in supply chain risk management research. Empirical and conceptual findings and a roadmap for the implementation in practice," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 41981, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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    Cited by:

    1. Ngui Min Fui Tom, 2019. "Strategy to Build a Transshipment Port as a Catalyst to Achieving Critical Mass for Sabah’s Economic Growth," International Business Research, Canadian Center of Science and Education, vol. 12(7), pages 141-166, July.
    2. Cedillo-Campos, Miguel Gastón & Pérez-González, Carlos Mario & Piña-Barcena, Jared & Moreno-Quintero, Eric, 2019. "Measurement of travel time reliability of road transportation using GPS data: A freight fluidity approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 240-288.

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