Discrete Choice Model of Agricultural Shipper's Mode Choice

Abstract

Abstract This article presents disaggregate mode choice model for shippers of agricultural freight. We have used disaggregated revealed preference (RP) data of grain movement from elevators to develop the model. The utility function includes attributes of the modes, attributes of the shippers, and interaction between the two. We initially estimate the mode choice probability assuming the random component of the utility function to have logit distribution. Price agreement between shippers and carriers, variation of railcars availability, and variation of equipment ownership annul the assumptions of the logit model. To overcome this problem we introduced heteroscedastic extreme value model, probit model and mixed-logit model. Based on estimated McFadden's likelihood ratio, it is observed that probit model is the best fit. We estimated demand elasticity to assess the sensitivity of mode choice probability to changes in cost of shipment, elevator capacity and quantity of shipment. To validate the model's prediction accuracy we estimated hit ratio of the forecast mode choice for individual shipment; the result was satisfactory.