Work

A Model Typology Approach for Improving Spatial Transferability of Freight Demand Estimates: Case Study of Geographically Dissimilar Regions in India

Year: 2025

Type: article

Abstract: Spatial transferability of freight demand models is a practice that is needed to enable the use of formerly developed models in estimating the freight demand of another region. This practice is particularly crucial for planning agencies in densely populated countries like India, needing more resources for comprehensive freight data collection. There are studies on the transferability of freight demand models. However, the transferability of non-parametric freight demand models has yet to be investigated. It is necessary to understand whether the extent of transferability of non-parametric models is greater than that of parametric models so that planning agencies can adopt more reliable modelling approaches/typologies. This paper investigates the spatial transferability of freight production models using parametric (ordinary least squares regression and robust regression) and non-parametric (multiple classification analysis and support vector regression) modelling approaches. The transferability assessment results show that the non-parametric models are more transferable than non-parametric models.

Source: Transportation research procedia

DOI: 10.1016/j.trpro.2025.06.049

Authors: Bhavani Shankar Balla, Prasanta K. Sahu, Agnivesh Pani

Institutions: Roma Tre University, Birla Institute of Technology and Science, Pilani, Indian Institute of Technology BHU

Language: English

Topic: Urban and Freight Transport Logistics

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Birla Institute of Technology and Science, Pilani