Examining the Impacts of Highway Proximity on Freight Flow Patterns of Establishments

Abstract

Highway proximity is essential to the economic growth of establishments and productivity of freight operations. The present study is motivated by the discernible gap in knowledge about the potential impacts of highway proximity on freight flow patterns of establishments. This knowledge gap impedes accurately estimating the potential benefits associated with infrastructure investments, especially related to freight-specific facility planning in developing countries. This paper investigates highway proximity impacts on freight establishments’ travel and shipment patterns using a comparative experiment approach. A total of 17 explanatory variables reflecting the freight flow pattern of an establishment have been considered. Proximity impact is evaluated by comparing the means of these explanatory variables among establishments closer to the highway, termed the “Influence” group, and those farther from the highway, defined as the “Control” group. Spatial and kernel analyses are carried out to determine the cut-off distance for demarcating samples into Influence and Control groups. The propensity score matching technique is subsequently used to create matched samples for a one-to-one comparison between the Influence group and Control group establishments. Results suggest that the Influence group typically consists of older establishments with larger business areas, generates many small-sized trips, and is associated with lower tonnage generation, expenditure, and shipment size than the Control group. The study findings are expected to have important implications on the infrastructure investment decision process and planning of freight operations.

A Model Assembly Approach of Planning Urban–Rural Transportation Network: A Case Study of Jiangxia District, Wuhan, China

“…In the production spaces, it is necessary to coordinate the relationship between transportation and industrial development, ensure interregional interaction, transportation of goods, industrial and agricultural production, etc. and configure transportation facilities around industrial production, so as to improve the transportation capacity of urban and rural industries [39][40][41][42]. In the ecological spaces, natural factors such as geological topography and water system distribution affect the distribution of transportation networks.…”

Examining the Effects of Local Sample Sizes on Spatial Transferability of Freight Production Models

“…The literature outlines various explanatory variables used in FG/FTG models. These variables include site area ( 9 ), building area ( 10 ), gross floor area ( 3 , 11 ), age in business ( 12 ), parking space ( 13 ), employment ( 6 , 14 ), commodity type ( 15 ), and industry segment ( 14 , 16 ). These models were developed using several mathematical models, and ordinary least squares (OLS) regression was often used.…”