Artificial intelligence will enhance the efficiency of cross-border e-commerce industry chain

2023-08-15

According to data recently released by the General Administration of Customs, in the first half of this year, China's cross-border e-commerce imports and exports amounted to 1.1 trillion yuan, a year-on-year increase of 16%. Among them, exports reached 821 billion yuan, an increase of 19.9%, while imports reached 276 billion yuan, an increase of 5.7%, maintaining a positive development momentum and effectively helping China's foreign trade to further stabilize its scale and structure. The further development of cross-border e-commerce industry has led to a significant increase in related enterprises this year. According to Tianyancha data, there are currently over 67000 cross-border e-commerce related enterprises in China, of which more than 8380 were newly registered in the first half of this year, an increase of 30% compared to the same period last year, with a significant increase. The general understanding of cross-border e-commerce by consumers is often that they purchase overseas goods through e-commerce platforms. However, in fact, the scope of cross-border e-commerce far exceeds this. Generally speaking, cross-border e-commerce refers to an international commercial activity where transaction entities belonging to different customs territories complete transactions, conduct electronic payment settlement through e-commerce platforms, and deliver goods through cross-border e-commerce logistics and remote warehousing, thus completing transactions. In other words, transactions between businesses through this model are also cross-border e-commerce, and it is a B2B model. Enterprises can display their products or services through various online platforms to build a global trade network. With the continuous development of e-commerce and the continuous expansion of the scope and scale of electronic payment settlement applications, cross-border e-commerce has become an important form of international trade. In fact, due to the reduction of partial information gap between the two parties in e-commerce platforms and the avoidance of market shortages, trading methods that rely on "information gap" or "market scarcity" are no longer effective, which will also affect the overall trading mode of international trade, shorten the time for information exchange, and turn "back to back" information into "face-to-face". The shortening of this time has a huge impact on the corresponding industry chain of the transaction itself, both upstream and downstream. It should be noted that a large number of cross-border e-commerce transactions will generate a large amount of data on e-commerce platforms and the enterprise ports of both parties. By analyzing this data through artificial intelligence, not only can transaction prices be better balanced, but also buyer demand will be effectively integrated and fed back to upstream production manufacturers as soon as possible. Similarly, the needs of transaction end consumers can also be effectively understood and evaluated. In the face of big data, through artificial intelligence analysis, the needs assessment of producers and consumers has also changed from "back to back" to "face-to-face". In the past, making information and demand "face to face" often required a lot of transaction experience, as well as human and material resources for market research and evaluation. Once artificial intelligence was used to empower cross-border e-commerce, these costs would be greatly reduced. More importantly, upstream manufacturers can use this data to adjust product design and production in a timely manner, intermediate trading parties can also adjust trading strategies in a timely manner, and downstream sales parties can also optimize sales methods and product layout in a timely manner. This progress will effectively improve the efficiency of the entire industry chain. At present, many enterprises have started to layout and provide technical support for cross-border e-commerce, including artificial intelligence, cloud computing, and other related technologies. Of course, can these technical support be effectively converted into economy

Edit:Hou Wenzhe    Responsible editor:WeiZe

Source:Worker Daily

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