Decision and Coordination of Cross-Border E-Commerce Supply Chain: Based on Four Modes of Cooperation

Yan, Wei; Zhou, Huijun; Li, Hui

doi:10.1155/2021/5561357

Cited by 15 publications

(11 citation statements)

References 15 publications

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“…Due to the explosive growth trend of CBEC, Yan W conducts research on the supply chain from the perspective of decision-making and coordination. He used the Shapley value method and the fullcooperative income incremental sharing mechanism to redistribute profits under different cooperation modes, in order to provide a scientific decision-making reference for domestic CBEC companies to rationally choose cooperative relations [7]. His research is very novel but lacks the support of theoretical data.…”

Section: Introductionmentioning

confidence: 99%

Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning

Guo

Zou

2022

Mobile Information Systems

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E-commerce and logistics are symbioses with each other, but cross-border e-commerce (CBEC) still cannot break away from cross-border logistics. With the progress of economic internationalization, economic and trade ties around the world have become closer and closer, and the level of international business exchanges has been improved. The rise of multinational e-commerce has also caused unprecedented difficulties to multinational logistics and supply chain management. The application of deep neural networks in various fields provides opportunities for cross-border e-commerce platforms to solve these problems. The existing logistics distribution model cannot keep up with the development of CBEC and has become a constraint and bottleneck for the development of CBEC. Therefore, this article introduces deep learning neural network to cross-border logistics and supply chain based on the analysis of the existing cross-border logistics model and supply chain model and the status quo of e-commerce development. It optimizes the existing cross-border logistics and supply chain network in order to break through the current bottleneck in the development of CBEC. This paper shows through research that introducing deep learning neural networks into CBEC logistics and supply chain can improve the efficiency of logistics and supply chain. Compared with the previous efficiency, the efficiency of network optimization can be increased to about 50%, reducing the cost of cross-border logistics and supply chain. The research in this article has great theoretical and guiding significance for the development of CBEC.

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Section: Introductionmentioning

confidence: 99%

Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning

Guo

Zou

2022

Mobile Information Systems

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“…Regarding material storage and distribution, especially for inventory control, which still needs to be optimised to minimise costs while maintaining high customer satisfaction, Yu, Hou & Li (2019) applies the basic ideas of the ant colony algorithm and fuzzy model to the supply chain inventory optimisation model. Yan, Zhou & Li (2021) pointed out that due to problems, such as explosive growth trends and high transportation costs in cross-border electronic commerce, it is urgent to study the supply chain from the perspectives of decision-making and coordination.…”

Section: Related Workmentioning

confidence: 99%

Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing

Dong¹,

Chen²,

Wang³

2023

PeerJ Computer Science

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The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server’s computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain’s comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing.

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“…However, it has yet to solve a series of problems such as high transportation costs and insufficient publicity in CE. Based on this, Yan et al used the Shapley value method and the full cooperation income incremental sharing mechanism to redistribute the profits under different cooperation modes [5]. Although this provides a scientific decision-making reference for CEE to reasonably choose a partnership, there are still some unresolved problems in the multiobjective optimization process of the supply chain.…”

Section: Related Workmentioning

confidence: 99%

The Export Operation Mode and Optimization Strategy of Crossborder e-Commerce Enterprises Integrating Data Mining Algorithms

Ji-ling

Zhang

2022

Wireless Communications and Mobile Computing

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With the advent of the crossborder e-commerce (CE) boom, more and more traditional enterprises have transformed into the field of crossborder e-commerce. It has become a new outlet for enterprises in the international trade environment, and at the same time, it has some problems in the utilization of resources and the maximization of benefits. In response to this problem, it is very important to optimize the export operation model of crossborder e-commerce enterprises (CEE). With the development of intelligent algorithms, research on the application of intelligent algorithms to the economic field has gradually been carried out. Its characteristics and advantages are of great significance to the optimization of CEE export operation mode. The purpose of this paper is to study the CEE export operation mode and optimization strategy based on data mining algorithm (DMA). Through the analysis and research of DMA, it can be applied to the optimization of CEE export operation mode to cope with the world trade in the new environment. This paper explains the basic theory of DMA and CEE export operation mode. Its effect is experimentally analyzed, and the relevant theoretical formulas are used to explain. The results show that the comprehensive trade quality index of the CEE export operation mode integrating DMA is higher, and the adaptability is stronger. Compared with the traditional operating model, the difference between the two indices is 3.175 index points. It has guiding significance in terms of CEE export operation mode and optimization strategy.

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Decision and Coordination of Cross-Border E-Commerce Supply Chain: Based on Four Modes of Cooperation

Cited by 15 publications

References 15 publications

Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning

Cross-Border E-Commerce Platform Logistics and Supply Chain Network Optimization Based on Deep Learning

Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing

The Export Operation Mode and Optimization Strategy of Crossborder e-Commerce Enterprises Integrating Data Mining Algorithms

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