Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina

Tapia, Rodrigo Javier; de Jong, Gerard; Larranaga, Ana M.; Bettella Cybis, Helena B.

doi:10.1007/s11067-021-09531-y

Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina

Title

Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina

Author

Tapia, Rodrigo Javier (TU Delft Transport and Planning; Universidade Federal do Rio Grande do Sul)
de Jong, Gerard (University of Leeds)
Larranaga, Ana M. (Universidade Federal do Rio Grande do Sul)
Bettella Cybis, Helena B. (Universidade Federal do Rio Grande do Sul)

Date

2021

Abstract

There are some examples where freight choices may be of a multiple discrete nature, especially the ones at more tactical levels of planning. Nevertheless, this has not been investigated in the literature, although several discrete-continuous models for mode/vehicle type and shipment size choice have been developed in freight transport. In this work, we propose that the decision of port and mode of the grain consolidators in Argentina is of a discrete-continuous nature, where they can choose more than one alternative and how much of their production to send by each mode. The Multiple Discrete Extreme Value Model (MDCEV) framework was applied to a stated preference data set with a response variable that allowed this multiple-discreteness. To our knowledge, this is the only application of the MDCEV in regional freight context. Free alongside ship price, freight transport cost, lead-time and travel time were included in the utility function and observed and random heterogeneity was captured by the interaction with the consolidator’s characteristics and random coefficients. In addition, different discrete choice models were used to compare the forecasting performance, willingness to pay measures and structure of the utility function against.

Subject

Freight modelling
Multiple Discrete Extreme Value Model
Willingness to pay

To reference this document use:

http://resolver.tudelft.nl/uuid:cfbe9b9c-4dff-43f3-a562-adad70b6f568

DOI

https://doi.org/10.1007/s11067-021-09531-y

ISSN

1566-113X

Source

Networks and Spatial Economics: a journal of infrastructure modeling and computation, 21 (3), 581-608

Part of collection

Institutional Repository