Inventory Theory and Freight Transport Modelling

Combes, François

doi:10.1016/b978-0-12-410400-6.00005-7

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…The resulting lack of flexibility comes at a cost for carriers, in a way which can imply an increase in the fixed costs of dispatching a shipment (the need to take margins to arrive on time, the greater costs of being early or late, the lack of possibility to carry more shipments together). Lastly, transshipments are associated with the consolidation of small shipments and cross-docking operations, in order to reduce the fixed costs of transporting shipments (Combes and Tavasszy, 2016). As a consequence, the Multi_trips variable should be associated with smaller shipments, which is empirically confirmed.…”

Section: Discrete Shipment Size Modelmentioning

confidence: 74%

“…Some authors consider shipment size as a continuous variable (Sakai et al, 2020;Koning et al, 2018;Abate and de Jong, 2014;Combes, 2009;Holguín-Veras, 2002;Abdelwahab and Sargious, 1992), others as discrete (Keya et al, 2019;Abate et al, 2019;Piendl et al, 2017;Pourabdollahi et al, 2013;Windisch et al, 2010;de Jong and Ben-Akiva, 2007). Some articles assume shipment size is unaffected by mode choice (Sakai et al, 2020;Kawamura et al, 2010;Wisetjindawat et al, 2005) or conditional on it (mode-specific influences are included as binary indicators (Combes, 2012)), whereas others account for the interdependencies between decisions, either implicitly or explicitly (Keya et al, 2019;Abate et al, 2019;Irannezhad et al, 2017;Combes and Tavasszy, 2016;Abate and de Jong, 2014;Pourabdollahi et al, 2013). Some authors opt for an empirical approach where all potentially relevant explanatory variables are tested (Keya et al, 2019;Pourabdollahi et al, 2013;Windisch et al, 2010;Holguín-Veras, 2002); as opposed to others who start from a microeconomic analytical model -typically the TLC framework -to derive a structural form which is then empirically tested (Sakai et al, 2020;Abate et al, 2019;Koning et al, 2018;Combes and Tavasszy, 2016;Abate and de Jong, 2014;Liedtke, 2012;de Jong and Ben-Akiva, 2007).…”

Section: The Choice Of Shipment Sizementioning

confidence: 99%

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Building latent segments of goods to improve shipment size modelling: Confirmatory evidence from France

Piendl

Koning

Combes

et al. 2022

European Journal of Transport and Infrastructure Research

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Freight transport demand models are generally based on administrative commodity type segmentation which are usually not tailored to behavioral freight transport demand modelling. Recent literature has explored new approaches to segment freight transport demand, notably based on latent class analysis, with promising results. In particular, empirical evidence from road freight transport modelling in Germany hints at the importance of conditioning and handling constraints as a sound basis for segmentation. However, this literature is currently sparse and based on small samples. Before it can be accepted that conditioning should be integrated in the state-of-the-art doctrine of freight data collection and model specification, more evidence is required. The objective of this article is to contribute to the issue. Using detailed data on shipments transported in France, a model of choice of shipment size with latent classes is estimated. The choice of shipment size is modelled as a process of total logistic cost minimization. Latent class analysis leverages the wide range of variables available in the dataset, to provide five categories of shipments which are both contrasted, internally homogenous, and directly usable to update freight collection protocols. The groups are: "‘standard temperature-controlled food products"’, "‘special transports"’, "‘bulk cargo"’, "‘miscellaneous standard cargo in bags"’, "‘palletised standard cargo"’. This segmentation is highly consistent with the empirical evidence from Germany and also leads to better estimates of shipment size choices than administrative segmentation. As a conclusion, the finding that conditioning and handling information is essential to understanding and modelling freight transport can be regarded as more robust.

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Section: Discrete Shipment Size Modelmentioning

confidence: 74%

Section: The Choice Of Shipment Sizementioning

confidence: 99%

Building latent segments of goods to improve shipment size modelling: Confirmatory evidence from France

Piendl

Koning

Combes

et al. 2022

European Journal of Transport and Infrastructure Research

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“…A non-exhaustive list, representative of the various methods tested, is McFadden et al (1985), Abdelwahab and Sargious (1992), Holguin-Veras (2002), or Pourhabdollahi (2013). For a more complete review and discussion, see Combes (2014). For the same reason, freight transport models have not incorporated inventory theoretic concepts, with the exception of De Jong and Ben-Akiva (2007).…”

Section: Introductionmentioning

confidence: 99%

Inventory theory, mode choice and network structure in freight transport

Combes¹,

Tavasszy

2016

European Journal of Transport and Infrastructure Research

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In passenger transport, hub-and-spoke networks allow the transportation of small passenger flows with competitive frequencies, in a way that direct line networks cannot. Equivalently, in freight transport, it can be expected that small shipper-receiver flows of high added value commodities transit through hub and spoke networks, while larger shipper-receiver flows of less expensive commodities are transported directly, without transhipment. The objective of this paper is first to present an analytical model, based on inventory theory, explaining how for a given commodity flow, the organisation of freight transport operations is closely related to the characteristics of the shipper-receiver relationship; second to assess empirically this model. Special emphasis is put on the number of transhipments in the transport operation, as an indication of organisation of the transport operations. The theoretical model is a simplified microeconomic model, built on principles of inventory theory. The empirical assessment of this model is based on the French shipment survey ECHO, which provides both the details of the transport operation and of the shipper-receiver relationships. With this database, we first provide a straightforward, graphical verification of the prediction of the theoretical model; secondly, we estimate it econometrically.

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