The government of one of China’s top technology hubs is dispatching officials to 100 local corporations, including e-commerce giant Alibaba Group Holding Ltd (阿里巴巴), the latest effort to exert greater influence over the nation’s massive private sector.
The city government in Hangzhou, Zhejiang Province, is assigning government affairs representatives to facilitate communication and expedite projects, it said on its Web site.
Chinese beverage giant Hangzhou Wahaha Group Co (杭州娃哈哈集團) and automaker Zhejiang Geely Holding Group Co (浙江吉利控股集團) are among the other companies based in the prosperous region that have been singled out, state media reports said.
The initiative is aimed at smoothing work flow between officials and China’s high-tech companies and manufacturers, the city government said.
However, the move could be perceived also as an effort to keep tabs on a non state-owned sector that is gaining clout as a prime driver of the world’s No. 2 economy.
Representatives of the nation’s public security system are already embedded within China’s largest Internet companies, responsible for crime prevention and stamping out false rumors.
Government agencies may also be heightening their monitoring of the vast private sector at a time the Chinese economy is decelerating — raising the prospect of destabilizing job cuts as enterprises try to protect bottom lines.
Alibaba is hosting its annual investors’ conference this week in Hangzhou against the backdrop of a worsening outlook for the country.
“They might be checking whether the [Chinese] Communist Party [CCP] units are working effectively within the companies,” said Paul Gillis, a professor at Peking University’s Guanghua School of Management.
“While China legitimized capitalism, the level of government influence was never intended to disappear. Occasionally private entrepreneurs forget about this and are reminded of it,” Gillis added.
Zhejiang is considered the cradle of modern Chinese private enterprise, home to a generation of self-made billionaires from Alibaba’s Jack Ma (馬雲) and Geely founder Li Shufu (李書福) to Wahaha’s Zong Qinghou (宗慶后).
The CCP accepted so-called “red capitalists” or private entrepreneurs into the party in 2001, allowing them to become part of the nation’s legislature a year later.
Still, the relationship between Beijing and well-known businesspeople remains sensitive.
The government has been seen to try and step up an official presence within non-state firms, by among other things mandating that private companies of scale set up and maintain a party branch.
It was not clear whether the 100 Zhejiang-based companies included foreign enterprises.
“We understand this initiative from the Hangzhou City Government aims to foster a better business environment in support of Hangzhou-based enterprises. The government representative will function as a bridge to the private sector and will not interfere with the company’s operations,” Alibaba said in a text statement.
Representatives for Wahaha and Geely did not immediately respond to requests for comment.
The Hangzhou initiative also underscores how the government is trying to arrest a slowdown in the economy brought on by the trade war, Kaiyuan Capital Ltd (開源資本) managing director Brock Silvers said.
He expects similar policies to soon follow for other manufacturing-intensive areas.
The government yesterday approved applications by Alphabet Inc’s Google to invest NT$27.08 billion (US$859.98 million) in Taiwan, the Ministry of Economic Affairs said in a statement. The Department of Investment Review approved two investments proposed by Google, with much of the funds to be used for data processing and electronic information supply services, as well as inventory procurement businesses in the semiconductor field, the ministry said. It marks the second consecutive year that Google has applied to increase its investment in Taiwan. Google plans to infuse NT$25.34 billion into Charter Investments Ltd (特許投資顧問) through its Singapore-based subsidiary Fructan Holdings Singapore Pte Ltd, and
Micron Technology Inc is a driving force pushing the US Congress to pass legislation that would put new export restrictions on equipment its Chinese competitors use to make their chips, according to people familiar with the matter. A US House of Representatives panel yesterday was to vote on the “MATCH Act,” a bill designed to close gaps in restrictions on chipmaking equipment. It would also pressure foreign companies that sell equipment to Chinese chipmaking facilities to align with export curbs on US companies like Lam Research Corp and Applied Materials Inc. The bill targets facilities operated by China’s ChangXin Memory Technologies Inc
Singapore-based ride-hailing and delivery giant Grab Holdings’ planned acquisition of Foodpanda’s Taiwan operations has yet to enter the formal review stage, as regulators await supplementary documents, the Fair Trade Commission (FTC) said yesterday. Acting FTC Chairman Chen Chih-min (陳志民) told the legislature’s Economics Committee that although Grab submitted its application on March 27, the case has not been officially accepted because required materials remain incomplete. Once the filing is finalized, the FTC would launch a formal probe into the deal, focusing on issues such as cross-shareholding and potential restrictions on market competition, Chen told lawmakers. Grab last month announced that it would acquire
SECOND-RATE: Models distilled from US products do not perform the same as the original and undo measures that ensure the systems are neutral, the US’ cable said The US Department of State has ordered a global push to bring attention to what it said are widespread efforts by Chinese companies, including artificial intelligence (AI) start-up DeepSeek (深度求索), to steal intellectual property from US AI labs, according to a diplomatic cable. The cable, dated Friday and sent to diplomatic and consular posts around the world, instructs diplomatic staff to speak to their foreign counterparts about “concerns over adversaries’ extraction and distillation of US AI models.” Distillation is the process of training smaller AI models using output from larger, more expensive ones to lower the costs of training a powerful new
RSS