Development of freight trip generation model using observed and unobserved information of supply chain characteristics for a sustainable urban transformation

Abstract

Supply Chain Characteristics (SCC) drive the city logistics to control the economic activities that support urban life and transformation. The dynamics of freight trip activity and SCC in city logistics are less understood by city planners, disrupting the prediction of urban Freight Trip Generation (FTG) models. To develop robust urban FTG models, the present study introduces the concept of estimating the freight trip activity using observed and unobserved (subjective) information of SCC for sustainable urban transport movement. Traditionally, the objective variable excludes the unobserved information of SCC while developing the FTG model; this gap can be addressed by incorporating subjective variables to measure both observed and unobserved information of SCC. A unique framework was designed by a combination of objective and subjective variables through Exploratory Factor Analysis (EFA) and Structural Equation Modelling (SEM) to estimate the freight trip activity. An Establishment Based Freight Survey (EBFS) collected from an Indian smart city (1793 samples) comprising various SCC was used to test the developed framework. Deployed EFA can identify the subjective variables using latent constructs to explain the observed and unobserved information in the SCC. Then, sequential execution of SEM with hypothesis path structure for estimating the freight trip activity. The direct, indirect, and total effects of the FTG model revealed added advantage of causal inter-relationship of urban freight trip activity and SCC between intermediate and pure receiver establishment. The developed FTG models using observed and unobserved information of SCC predicted freight trip activity with an accuracy of 57% for intermediate and 63% for pure receiver establishment. The effect of SSC on freight trip activity aids in creating sustainable urban freight transportation that could be an agile, responsive, and flexible adaptive system for the global market demand.