Regulating the algorithm: platform economy workers in China

中国 随意的 国家(计算机科学) 互联网 业务 经济 经济 政治学 计算机科学 万维网 法学 算法
作者
Aidan Chau
出处
期刊:International union rights [The International Centre for Trade Union Rights ICTUR]
卷期号:29 (2): 19-21 被引量:1
标识
DOI:10.1353/iur.2022.0019
摘要

Regulating the algorithm:platform economy workers in China Aidan Chau (bio) China makes an interesting case study for the global challenges of the platform economy. China's technology giants, such as Tencent and Alibaba, set the stage for high volumes of online commerce, and in this environment, other tech giants have thrived, notably food delivery companies Ele.me and Meituan, and ride hailing company Didi Chuxing. Platform workers face low wages, lack of labour protections, and working conditions dictated by algorithms. The political and social environment prevents independent organising and large-scale protests, exacerbated by the Covid-19 pandemic. China has one official trade union, the All-China Federation of Trade Unions (ACFTU) that is beholden to the Party and state, but recent reform efforts have led the ACFTU to try to focus on better representing platform workers. Further, the state has cracked down on technology companies and introduced regulations that attempt to strengthen workers' rights. China's platform economy China has the world's largest platform economy. A 'platform' is a tool that connects businesses, consumers, and others in a way not possible before the rise of the internet. Many platforms began as small websites or start-ups that expanded rapidly and resulted in a new flexible and casual employment model. In China, this began in 2008 with the spread of mobile technology. By 2014, mobile internet users surpassed those of computer users, meaning that many citizens accessed the internet for the first time on mobile phones and were ripe for app-based transactions. To avoid the effects of the global recession, China's economy became domestically re-orientated in 2008. Food delivery and ride hailing platforms experienced a rush of capital starting in 2013. The two ride-hailing companies Kuaidi and Didi received investments from Alibaba and Tencent, respectively. The food delivery platform Ele.me received a US$25 million capital investment from Sequoia Capital, and its rival Meituan got a US$300 million investment in 2014. The capital injection allowed these companies to set up their operations in all major cities in China within a year. Other economic conditions primed the platform economy to receive the necessary labour. The relative decline of China's manufacturing sector in the last five years has allowed an influx of workers. The new platform economy advertised good pay and flexible working conditions, which was attractive to those who formerly worked in factories. Statistics released by the companies reveal 15–30 percent of workers for these companies have come from manufacturing. Algorithms, labour and market share The rise of the platform economy in China has been rife with competition. Starting in 2014, the food delivery and ride hailing companies engaged in price wars by subsidising costs for their customers to expand their market shares. This competition resulted in Didi Chuxing buying Kuaidi and Uber China, and Ele.me purchased the third largest takeaway company, Baidu Waimai, maintaining a duopoly with Meituan ever since. Platform companies also compete with each other by worsening labour conditions for workers. Huge amounts of capital have been invested to develop algorithms that manage the allocation of labour, matching supply with demand and determining route planning. China has the world's largest platform economy. The new sector advertised good pay and flexible working conditions, which was attractive to those who formerly worked in factories In the food delivery industry, algorithms shorten the delivery time by fine-tuning the areas that workers are allocated to. In a pilot test conducted in 2019, the average distance travelled by a rider dropped by 5 percent. The algorithms also guide riders through the process of taking and dispatching orders, reducing the time workers spend waiting, planning and delivering the meals. For example, riders are directed by a heat map displaying the regional distribution of delivery orders. Workers follow the delivery route planned by the system, which is designed to find the fastest path for multiple deliveries. The combined effects of these algorithms have halved the delivery time of an average order from 1 hour in 2015 to 30 minutes in 20181. In the ride hailing industry, algorithms reduce the total time it takes for drivers to pick up passengers. Rather than...

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