Factors in the sea ports-of-entry and road ports-of-entry cross-border logistics route choice

Li, Shengchao; Cao, Xiaoshu; He, Yongquan

doi:10.1016/j.jtrangeo.2020.102689

Cited by 7 publications

(3 citation statements)

References 24 publications

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“…The study conducted by S. Li et al focuses on analyzing the geography factors and international trade in China, Myanmar, and Vietnam using the conditional logit model to analyze the relevant factor related to the geography. The results show that the scale of freight, duration, transportation charge, distance, quality of infrastructures, geographical location, and characteristics of the shippers and POEs influence and propose new policies [23]. While some authors (S. Hanaoka, 2021), propose to identify the factors for crossing borders between the land corridor and maritime border which influence trade by using the Tobit model to analyze the factors, the results of this study showed that distance and infrastructure quality are the most important factors [24].…”

Section: Literature Reviewsmentioning

confidence: 99%

Analysis of the Efficiency of Transport Infrastructure Connectivity and Trade

Netirith

2022

Sustainability

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Analyzing the efficiency of transport infrastructure connectivity and trade in the Regional Comprehensive Economic Partnership (RCEP) is very important for regional integration for international trade in the RCEP. This study aims to significantly measure the efficiency of the connectivity of infrastructure in the RCEP for improving the performance of infrastructure connection and suggest the way to improve the connection of infrastructure. Therefore, the input and output variables of infrastructure connectivity have been inserted to achieve this objective. The inputs are: the number of ports, rail range, and road networks, the number of land borders, the number of maritime borders, number of cross border points, railway linkage with other countries, number of ports connected with railways, and the number of ports connected with road base on the “intermodal and multimodal concept”. On the other hand, the output factors most related to trade and economics are GDP, transport, import, and export volume. The paper applied DEA (Data Envelopment Analysis) model by using DEAP software to analyze the data. The result reveals that the efficiency of infrastructures connectivity and international trade in 10 countries were efficient and 5 countries were inefficient. The research study presents ways of development to improve the connectivity by investing in the basic infrastructures, such as increasing the logistics connection points and driving forward for international trade in the RCEP.

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Section: Literature Reviewsmentioning

confidence: 99%

Analysis of the Efficiency of Transport Infrastructure Connectivity and Trade

Netirith

2022

Sustainability

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“…They determined that shippers were more inclined to select maritime shipping because of the high value of fixed utility. Li et al [25] analyzed the influence of geographical factors on the land ports-of-entry (POEs) and sea POEs cross-border logistics routes choice in China, Myanmar, and Vietnam by using the conditional logit model. The results show that there are significant differences in the characteristics and their influencing factors, which are reflected in the scale of freight, distance, duration, transport expense, infrastructure quality, geographical location, and characteristics of the shippers and POEs.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying Factors for Selecting Land over Maritime in Inter-Regional Cross-Border Transport

et al. 2021

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Several cross-border land corridor projects have been implemented worldwide, because land transport is a vital alternative to international maritime transport in inter-regional transport. Maritime transport generally costs less than land transport, but it is much slower. Nonetheless, land transport can be more appropriate than maritime under certain situations. This study aims to identify factors that can help select between these two modes in long-distance inter-regional cross-border transport; to this end, a Tobit model is employed to estimate the dependent variable, i.e., the land ratio of origin–destination pairs between countries and/or areas. Eight variables are identified as significant: distance, export of manufacturing commodity, landlocked country/area, neighboring country/area, country risk, infrastructure level, port-access time, and maritime transport frequency. We also find that geographical conditions, country relationship, and regulations are barriers for selecting land transport. However, cross-border land corridors contribute to the increase of land ratio.

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“…Reddy, K. N., et al studied the design problem of a multi-facility green RL network by combining the carbon footprint and the choice of vehicles, which contributed to the optimization of solutions to logistics problems [18]. Li, S. and other scholars took China-Myanmar-Vietnam international trade as the research object, combined with geospatial characteristics, analyzed how cross-border logistics routes are affected by geographic factors, and then explored the influence of geographic factors of land and sea transportation on cross-border logistics routes based on the conditional logit model, also explored the influence mechanism of land and sea logistics, based on the enterprise's land and sea logistics, and explored the influence mechanism of land and sea logistics, based on the enterprise's land and sea logistics [19]. Naseem, M. H. and other scholars analyzed and listed the barriers of supply chain logistics, proposed a method based on fuzzy hierarchical analysis to compare and determine the weights of the barriers, and used the fuzzy ranking method with the similarity to the ideal solution to make a final ranking of the solutions of reverse logistics so that the logistics personnel and experts can solve the problems according to their priorities [20].…”

Section: Introductionmentioning

confidence: 99%

Optimisation of cross-border e-commerce logistics model innovation path in the era of digital technology

Wei

2024

Applied Mathematics and Nonlinear Sciences

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Currently, cross-border e-commerce logistics is lagging behind the development of infrastructure imperfections and other issues, so the realization of e-commerce logistics model innovation is a top priority. This paper firstly analyzes the innovation path of cross-border e-commerce logistics mode to shorten the logistics cost and improve the development efficiency of cross-border logistics chain by supply chain, logistics system, packaging, and localization. Secondly, it establishes a logistics operation demand forecasting model based on principal component analysis and radial basis function and introduces the composite system synergy model to measure the logistics matching ability and calculate the cross-border e-commerce logistics matching ability. Finally, quantitative analysis is carried out on three aspects of cross-border e-commerce logistics operations: demand, matching ability, and service effect. The results show that: the application of a cross-border e-commerce logistics model innovation path reduces the potential risk of cross-border express clearance, and the average timeliness of returned express shipment, goods arrival to delivery, product tariff tax rate across the border, and the complaint rate are reduced by 45, 0.5, 0.28, and 0.65 in 2019-2023. Meanwhile, the customer satisfaction is increased from 0.8416 to 0.9641. The cross-border e-commerce logistics model innovation path is proposed to meet the actual needs of social development.

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Factors in the sea ports-of-entry and road ports-of-entry cross-border logistics route choice

Cited by 7 publications

References 24 publications

Analysis of the Efficiency of Transport Infrastructure Connectivity and Trade

Analysis of the Efficiency of Transport Infrastructure Connectivity and Trade

Identifying Factors for Selecting Land over Maritime in Inter-Regional Cross-Border Transport

Optimisation of cross-border e-commerce logistics model innovation path in the era of digital technology

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