Developing multi-vehicle freight trip generation models quantifying the relationship between logistics outsourcing and insourcing decisions
Despite the advancements in the logistics choices, freight trip generation (FTG) studies in the past have made no distinctions between insourced and outsourced variants of trips and the associated selection of truck types. This paper addresses past research gap by treating FTG as a joint package decision and proposing a multivariate ordered response system that allows error correlations capturing the underlying interdependencies. Study findings reveal the presence of complementary and substitution effects between freight trip decisions, and the additional computation burden resulting from the simultaneous model estimation appears to be justified for improving the logistical foundations of FTG models.
Transportation Research Part E: Logistics and Transportation Review
Pani, A., Mishra, S., & Sahu, P. (2022). Developing multi-vehicle freight trip generation models quantifying the relationship between logistics outsourcing and insourcing decisions. Transportation Research Part E: Logistics and Transportation Review, 159 https://doi.org/10.1016/j.tre.2022.102632