Empirical Shipment Size Model for Urban Freight and its Implications

Abstract

Modeling shipment size for intra-city shipments is a subject that has not been sufficiently addressed in past research, despite its growing importance in disaggregate freight modeling. While past research on shipment size estimation mainly focuses on inter-city shipments, intra-city shipments differ from them in various aspects. In filling this research gap, this study estimates shipment size models using the records of intra-city shipments, identifying the effects of factors and heterogeneity on the shipment size selection mechanism. The estimated coefficients are also compared against their theoretical values derived from a conceptual economic order quantity model. The estimated empirical models highlight the characteristics of intra-city shipments and indicate the importance of both receiver function and commodity type, and also vehicle operation type, in capturing the nuances of the selection mechanism among intra-city shipments.

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

“…Overall, there are many options to model shipment size in the empirical literature. 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 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).…”

“…Apart from the variation in shipment sizes originating in the trade-off between transport costs and inventory costs, heterogeneity comes alongside various logistics aspects like handling requirements, packaging or storage conditions (called logistical requirements hereinafter). Some articles approximate their impacts with information about the shipper and/or the receiver (Sakai et al, 2020;Pourabdollahi et al, 2013;Holguín-Veras, 2002), or about the transported commodity itself (Sakai et al, 2020;Abate et al, 2019;Keya et al, 2019;Koning et al, 2018;Abate and de Jong, 2014;de Jong and Ben-Akiva, 2007).…”