Assessing regional transferability and updating of freight generation models to reduce sample size requirements in national freight data collection program
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, the authors 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.
- Record URL:
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
-
Supplemental Notes:
- © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
-
Authors:
- Balla, Bhavani Shankar
- Sahu, Prasanta K
-
0000-0002-4309-5631
- Publication Date: 2023-9
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 103780
-
Serial:
- Transportation Research Part A: Policy and Practice
- Volume: 175
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0965-8564
- Serial URL: http://www.sciencedirect.com/science/journal/09658564
Subject/Index Terms
- TRT Terms: Cluster analysis; Data collection; Freight transportation; Policy making; Supply chain management; Transfers
- Geographic Terms: India
- Subject Areas: Data and Information Technology; Economics; Freight Transportation; Policy;
Filing Info
- Accession Number: 01902817
- Record Type: Publication
- Files: TRIS
- Created Date: Dec 20 2023 3:43PM