Workflow
无力支付1.5万劳动仲裁款!百度前高级副总裁王劲创业失败,已失联

Core Viewpoint - Zhongzhixing Technology Co., Ltd. has been accepted for bankruptcy liquidation by the court due to its inability to pay a labor arbitration amount of 15,000 yuan, reflecting the company's financial distress and the broader downturn in autonomous driving investments [1][2][4]. Company Summary - Zhongzhixing was founded by Wang Jin, a former senior vice president at Baidu and a pioneer in the L4 autonomous driving sector [1][9]. - The company has a registered capital of 150 million yuan and was established in June 2018 [6][9]. - The company has faced multiple enforcement cases, with a total historical enforcement amount reaching 47.328 million yuan, indicating severe financial difficulties [4][6]. Financial Distress - The court's ruling for bankruptcy was based on Zhongzhixing's inability to fulfill multiple financial obligations, including a labor arbitration agreement [2][4]. - The company has been unable to pay off debts, leading to a series of enforcement actions against it, with significant amounts remaining unpaid [6][7]. Operational Issues - The company has ceased operations, with its website inaccessible and contact numbers disconnected, indicating a complete loss of operational capacity [5][6]. - All three of its branches in Beijing, Fuzhou, and Shenzhen have been deregistered, and its official WeChat account has not been updated since February of the previous year [5][6]. Industry Context - The autonomous driving sector is experiencing a significant investment downturn, with many companies, including Zhongzhixing, facing challenges in achieving commercial viability [11][12]. - The industry is shifting towards a more competitive landscape, with several companies either going bankrupt or restructuring, highlighting the difficulties in the current market environment [11][12]. - Zhongzhixing's chosen technology route, which focuses on vehicle-road collaboration, has proven difficult to commercialize compared to the more prevalent single-vehicle intelligence approach [11][12].