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Discrete choice model for air-cargo mode selection

Subhro Mitra (Division of Urban and Professional Studies, University of North Texas at Dallas, Dallas, Texas, USA)
Steven M. Leon (Department of Marketing, University of Central Florida, Orlando, Florida, USA)

The International Journal of Logistics Management

ISSN: 0957-4093

Article publication date: 4 November 2014




The purpose of this paper is to develop a better understanding of the factors that influence a shipper's decision to choose air cargo as a mode of shipment.


A disaggregate multinomial discrete choice model is developed using freight shipment survey data to identify critical factors influencing air cargo mode choice. Disaggregate revealed preference data is obtained from surveying 347 manufacturers, freight forwarders, and other third-party service providers.


The empirical model developed in this research shows that the rate of shipment, time of transit, cost-per-pound shipped, quantity shipped, perishability and delay rate of the mode are significant factors that influence mode choice.

Research limitations/implications

The discrete choice model developed can be improved by taking into account logistics costs not considered in this research. Perhaps more in-depth surveys of the shippers and freight forwarders are needed. Additionally, improving the mode choice model by including stated preference data and subsequently incorporating service quality latent variables would be beneficial.

Practical implications

Identifying the sensitivity of the shippers to various factors influencing mode selection enables transportation planners make better demand forecast for each mode of transportation.


This paper extends previous mode choice studies by analyzing mode selection between air cargo and other modes. Better forecasting is achieved by replacing the logit model with probit, heteroscedastic extreme value and mixed logit models.



Mitra, S. and M. Leon, S. (2014), "Discrete choice model for air-cargo mode selection", The International Journal of Logistics Management, Vol. 25 No. 3, pp. 656-672.



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Copyright © 2014, Emerald Group Publishing Limited

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