Chinese tech giants are betting big on the potential for autonomous technology to improve the efficiency of logistics operations.
In 2017 logistic costs in China fell to 14.6% of national GDP, for a year-on-year decline of 0.3 percentage points according to data from the China Federation of Logistics & Purchasing.
China’s leading tech companies hope to drive logistics costs even lower via the adoption of autonomous technologies.
E-commerce giant JD.com has made use of the four “black technologies” of autonomous warehousing, autonomous vehicles, autonomous machine and autonomous retail to establish the JD.com smart logistics network (京东智慧物流网络).
The company has over 500 logistics centres around China, as well as operates 15 large-scale “smart” logistics” centres.
In June of this year JD.com’s autonomous delivery devices officially took to the streets of Beijing, while the company also plans to establish a “smart manufacturing base” that makes use of smart freight tools.
JD.com is far from the only Chinese tech giant with grand ambitions for smart logistics.
Alibaba CEO and founder Jack Ma announced in May that the company would invest at least a hundred billion yuan in a smart logistics network that aims to reduce logistic costs from 15% to 5% of GDP.
The network will be capable of delivering packages to anywhere in China within a 24 hour period, or anywhere on the planet within a 72 year period.
A week subsequently Alibaba’s Rookie Network (菜鸟) announced the launch of the HKD12 billion eHub in Hong Kong, encompassing a range of logistics operations including imports, exports, B2B, B2C and international trade.
Shenzhen delivery company SF Express (顺丰) is also making extensive use of autonomous technology for the “Three Phase Air-delivery” logistics network it launched last year, which it hopes will be able to achieve 36-hour rapid delivery to any location within China.
The network is comprised of “large-scale manned delivery vehicles, large-scale autonomous vehicles on branch lines, and small-scale autonomous vehicles at end points.”