Assessing regional transferability and updating of freight generation models to reduce sample size requirements in national freight data collection program

Abstract

This paper analyses the transferability of freight generation (FG) models to provide guidance on the direction of transfer, the degree of transfer, and how to determine the sample size required for new regions. A set of FG models are developed for four regions in India, i.e., Hyderabad, Jaipur, North Kerala, and Central Kerala. Models are assessed for naïve transferability across these regions to know the direction and degree of transfer. Using multidimensionality scaling, we identified new regions similar to the study regions based on geographical characteristics like population density, number of establishments, land value, road density, and seaport proximity. The identical regions are further grouped into four different clusters using the K-means clustering algorithm. In order to determine the sample size of a new region, the transferability results are interpolated to these geographically linked regions with the same demographics. This research is crucial for saving survey resources in terms of money and time. The policymakers and stakeholders can borrow the strategies already under implementation in a region with topographic similarity with the novel methodology proposed. Furthermore, industrialists can take the case study of the establishments in geographically similar regions in strategizing the resource and capacity allocation for efficient and responsive supply chain design.