Abstract
This research aims to study application of support vector machine algorithm, artificial neural networks and five different types of decision trees in predicting mode choice of freight transportation. Performance of these models has been compared with log it model which is one the most prevalent statistical models in the field. Effect of factors such as cargo weight, distance, type and characteristics of commodity has been studied in process of modelling mode choice which is rail and road. In this regard, data gathered in the United States, is used and similarities and advantages of the models are described in details. Results indicated that cost-sensitive support vector machine is the best method in predicting shipment mode choice. After this method, stand C5 decision tree and artificial neural network. The most important variables in determining shipment mode choice of firms are respectively weight, great-circle distance between origin and destination, commodity type, compound impedance factor of rail and truck and containerized condition of the shipment to be moved.
Highlights
Transporting goods in road network causes multiple drawbacks
While in commuters mode choice it is dealt with people each having their own characteristics, in freight transportation it is dealt with firms each of them in one or more supply chains and their respected decisions are usually made joint, resulting in complex behaviour
Employing models able to examine non-linear relations between independent and dependent variables may be regarded as a suitable option in studying freight mode choice decisions
Summary
Transporting goods in road network causes multiple drawbacks. The most important disadvantages to be mentioned are safety reduction, increase in travel time, increased emissions and energy consumption and destruction of infrastructures (Wisetjindawat et al, 2015). Mode choice can be regarded as one of the most substantial decisions of each firm involved in a supply chain (Samimi et al, 2011). In studying behaviour of firms in field of freight mode choice there are much more complicity than mode choice of commuters. While in commuters mode choice it is dealt with people each having their own characteristics, in freight transportation it is dealt with firms each of them in one or more supply chains and their respected decisions are usually made joint, resulting in complex behaviour. Employing models able to examine non-linear relations between independent and dependent variables may be regarded as a suitable option in studying freight mode choice decisions
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