TY - JOUR
T1 - Integrated data collection and modeling with freight origin–destination synthesis
T2 - Application to Bangladesh
AU - Holguín-Veras, José
AU - Kalahasthi, Lokesh Kumar
AU - Ismael, Abdelrahman
AU - Yushimito, Wilfredo F.
AU - Herrera-Dappe, Matías
AU - Hoque, Md Shamsul
N1 - Publisher Copyright:
© 2025
PY - 2025/6
Y1 - 2025/6
N2 - This paper reports the research conducted on developing and implementing a national freight demand model for Bangladesh based on Integrated Data Collection and Modeling with Freight Origin-Destination Synthesis (IDCM-FODS). The approach developed in this paper seeks to minimize the cost and time spent on model development by exploiting the power of clever data collection and modeling without sacrificing the quality of the work. The approach has two major components: (1) Integrated Data Collection and Modeling (IDCM), intended to estimate the freight generation (both production and attraction) and freight trips, using a targeted survey sample of commercial establishments to estimate econometric models that are then applied to national statistics to estimate freight generation and freight trip generation; (2) Analyze freight generation across various economic metrics and (3) Freight Origin-Destination Synthesis (FODS) models, both generic commodity and multi-commodities, to infer freight flows and calibrate a freight distribution model, and a vehicle-trip model (considering both loaded and empty trips) that minimizes the errors between the modeled and observed traffic in the network. The paper discusses background information about Bangladesh, the data used in the research effort, the process to conduct the survey and estimation of the econometric freight generation models, the use of these models to obtain freight generation estimates countrywide, the FODS models obtained, and the chief conclusions of the overall effort. This research demonstrates the potential of IDCM-FODS methods to develop freight models in environments with limited data availability.
AB - This paper reports the research conducted on developing and implementing a national freight demand model for Bangladesh based on Integrated Data Collection and Modeling with Freight Origin-Destination Synthesis (IDCM-FODS). The approach developed in this paper seeks to minimize the cost and time spent on model development by exploiting the power of clever data collection and modeling without sacrificing the quality of the work. The approach has two major components: (1) Integrated Data Collection and Modeling (IDCM), intended to estimate the freight generation (both production and attraction) and freight trips, using a targeted survey sample of commercial establishments to estimate econometric models that are then applied to national statistics to estimate freight generation and freight trip generation; (2) Analyze freight generation across various economic metrics and (3) Freight Origin-Destination Synthesis (FODS) models, both generic commodity and multi-commodities, to infer freight flows and calibrate a freight distribution model, and a vehicle-trip model (considering both loaded and empty trips) that minimizes the errors between the modeled and observed traffic in the network. The paper discusses background information about Bangladesh, the data used in the research effort, the process to conduct the survey and estimation of the econometric freight generation models, the use of these models to obtain freight generation estimates countrywide, the FODS models obtained, and the chief conclusions of the overall effort. This research demonstrates the potential of IDCM-FODS methods to develop freight models in environments with limited data availability.
KW - Bangladesh freight study
KW - Freight (trip) generation
KW - Freight demand modeling
KW - Freight origin–destination synthesis
UR - https://www.scopus.com/pages/publications/105003964744
U2 - 10.1016/j.cstp.2025.101456
DO - 10.1016/j.cstp.2025.101456
M3 - Article
AN - SCOPUS:105003964744
SN - 2213-624X
VL - 20
JO - Case Studies on Transport Policy
JF - Case Studies on Transport Policy
M1 - 101456
ER -