Accounting for Heterogeneity of Travel Time Reliability Valuation in Shippers' Freight Mode Choice. Issue 7 (July 2022)

• Record Type: Journal Article
• Authors: Jian, Wenliang; Xie, Xinyu; Zhu, Lichao; Gao, Liangpeng
• Is Part Of: Transportation research record. Volume 2676:Issue 7(2022)
• Page Start: 212
• Page End: 221
• Publication Date: 2022-07
• Subjects: preference heterogeneity -- value of reliability -- interaction effects -- hinterland leg transportation; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981221077996
• Languages: English
• ISSNs: 0361-1981

Abstract

Designing efficient strategies to adjust freight transportation mode structure requires in-depth understanding of shippers' mode choice behavior. This paper presents an empirical study to investigate preference heterogeneity in value of reliability (VOR) for hinterland leg transportation mode choice. A stated preference survey using a D-efficient design approach is carried out in the corridor from Yiwu to the port of Ningbo to collect data on shippers' behavior. Two model specifications including the Base Model and the Heterogeneous Model are developed to analyze these data. Mixed logit is applied to estimate the parameters of models. The estimation results of the base model reveal significant preference heterogeneity in shippers' VOR. We then calculate the mean and variation of overall VOR. In addition, the potential factors leading to heterogeneity in VOR are identified. Results imply that commodity characteristics including shipment size, value, and weight could partially explain the shippers' heterogeneity in VOR. Based on these factors, eight sub-groups of container shippers are obtained, and the mode shares of railway under different levels of railway reliability are estimated for each sub-group. Results show that improvement in the level of reliability is important to increase the mode share of rail, especially in the sub-group where shipments are light and of high value. The findings of this paper can be used for demand forecasting and transportation policy making.