Abstract
Road–rail container intermodal transportation is considered a solution to reduce the share of truck transportation in China. A modal shift from truck to intermodal alternatives requires a better understanding of freight mode choice behavior and improved estimations of the value of service attributes. This paper focuses on the effects of distance and reliability on the value of time (VOT). An adaptive experiment is conducted on potential customers of intermodal transportation in the Yangtze River Delta area, China. Multinomial logit (binary logit) and mixed logit models are estimated for eight specifications. The results show that shipper characteristics, commodity characteristics, and shipment characteristics significantly influence the mode choice behavior. Specifications with an interaction term between the logarithm of distance and transportation time perform better. The VOT of short-distance transportation is higher than that of long-distance transportation. The rate of VOT reduction decreases with increasing distance. In addition, incorporating the reliability variable in model specifications leads to a more homogeneous random parameter distribution of time and a lower VOT. This study helps intermodal operators to optimize product and design pricing strategies. Moreover, the proposed measures help to promote the modal shift from truck to road–rail container intermodal transportation.
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