Impact Factor:4.8

DOI number:10.1016/j.ocecoaman.2022.106414

Journal:Ocean & Coastal Management

Funded by:国家自然科学基金面上项目（No.72071091）

Key Words:Hub location; Intermodal transportation; Government subsidy; Contest theory; Belt and road initiative

Abstract:Driven by globalization, the COVID-19 outbreak has severely impacted global transport and logistics systems. To better cope with this globalization crisis, the Belt and Road Initiative (BRI)—based on the concept of cooperation—is more important than ever in the post-pandemic era. Taking the BRI as the background, we design an intermodal hub-and-spoke network to provide reference for governments along BRI routes to improve their crossborder transportation system and promote economic recovery. In the context of the BRI, local governments at different nodes have incentives to subsidize hub construction and/or rail transportation to boost economic development. We consider co-opetition behavior among different levels of government caused by subsidies in this intermodal hub location problem, which we call the intermodal hub location problem based on government subsidies. We establish a two-stage mixed-integer programming model. In the first stage, local governments provide subsidies, then the central government decides the number and location of hubs. In the second stage, freight carriers choose the optimal route to transport the goods. To solve the model, we design an optimization method combining a population-based algorithm using contest theory. The results show that rail subsidies are positively correlated with construction subsidies but are not necessarily related to the choice of hubs. Compared with monomodal transportation, intermodal transportation can reduce costs more effectively when there are not too many hubs and the cost of different modes of transportation varies greatly. The influences of local government competition and hub construction investment on network design and government subsidies are further examined.

Indexed by:Journal paper

Discipline:Management Science

Document Type:J

Volume:231:

Page Number:106414

Number of Words:13443

ISSN No.:0964-5691

Translation or Not:no

Date of Publication:2023-01-01

Included Journals:SCI

Links to published journals:https://www.sciencedirect.com/science/article/pii/S0964569122003908