Freight Mode Choice

2021 ◽  
pp. 231-235
Author(s):  
Hyun Chan Kim ◽  
Alan Nicholson
Keyword(s):  
Mode Choice ◽  
Freight Mode Choice

scholarly journals A Comparison between Different Data Mining Algorithms in Freight Mode Choice

2017 ◽  
Vol 14 (2) ◽  
pp. 204-216
Author(s):  
Amir Samimi ◽  
Hesamoddin Razi-Ardakani ◽  
Amir Nohekhan
Keyword(s):  
Data Mining ◽  
Mode Choice ◽  
Data Mining Algorithms ◽  
Freight Mode Choice ◽  
Mining Algorithms

A behavioral analysis of freight mode choice decisions

2011 ◽  
Vol 34 (8) ◽  
pp. 857-869 ◽  
Author(s):  
Amir Samimi ◽  
Kazuya Kawamura ◽  
Abolfazl Mohammadian
Keyword(s):  
Mode Choice ◽  
Behavioral Analysis ◽  
Freight Mode Choice

An inter‐Urban freight mode choice model

1983 ◽  
Vol 8 (1) ◽  
pp. 61-80 ◽  
Author(s):  
W. Young ◽  
A. J. Richardson ◽  
K. W. Ogden ◽  
A. L. Rattray
Keyword(s):  
Choice Model ◽  
Mode Choice ◽  
Urban Freight ◽  
Mode Choice Model ◽  
Freight Mode Choice

scholarly journals Freight shipper’s mode choice preference for sustainable inland transportation

2021 ◽  
Vol 916 (1) ◽  
pp. 012004
Author(s):  
N Firdausiyah ◽  
D P Chrisdiani
Keyword(s):  
Stated Preference ◽  
Mode Choice ◽  
Discrete Choice Models ◽  
Choice Preference ◽  
Goods Movement ◽  
Binary Logit ◽  
Shipping Cost ◽  
The Common ◽  
Freight Mode Choice ◽  
The Cost

Abstract Modelling of transport mode choice preferencehas beencurrently regarded essential to identify the preference of transport agents towards a transport policy. This research proposes a model of the freight mode choice preference by using Stated Preference Methods for the data collection from industrial freight shippers in Gresik, Indonesia. This research examines how truck as an existing mode and rail as a sustainable mode alternative compete for goods movement. As the common feature of discrete choice models, the Binary Logit was utilized to analyze the data. The sensitivity of mode preferences was investigated by changing the shipping cost and hauling time. The results indicated that the respondents were sensitive to haul time and shipping cost. When the shipping cost and hauling time was similar, the probability of choosing a truck was 77%. However, the industrial freight shippers changed the preference when the truck’s shipping cost and haul time was higher than that in the train. The train had a 65% choosing probability when the cost difference was IDR 500,000 lower and the hauling time difference was two days faster than the truck. This study assisted the policymakers to correctly design the variables of shipping cost and hauling time for the future sustainable inland transportation based on freight shipper’s preferences.

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