Dandan Zhang: China’s factory workers go gig
Peking University professor profiles China's overlooked, rapidly increasing, poorly-insured day laborers in export-oriented manufacturing.
Dandan Zhang is a Professor in Economics (with tenure) and Deputy Dean (in research, internal and international cooperation) at the National School of Development (NSD), and Deputy Dean of the Institute of South-South Cooperation and Development, Peking University.
She famously put the youth unemployment rate in China at a staggering 46.5% maximum in July 2023, more than twice the official figure of 21.3%. Amid heightened attention then, the National Bureau of Statistics of China paused the release of youth joblessness data in August 2023 and resumed publishing in December 2023 after revising its methodology to exclude full-time students.
Another of Zhang’s studies, which shows a “very strong correlation” between left-behind childhood and criminality in adulthood, was also featured on The East is Read last June.
The following article centers on understanding the scale, characteristics, profile, and policy implications of gig work in China’s manufacturing industry, particularly in the 3C (computer, communication, and consumer electronics) sector. Driven by smart manufacturing technologies, the platform economy, household registration restrictions, and fluctuations in export demand, the rise of a gig-based employment model under China’s existing institutional framework is an inevitable trend, Zhang says, and it is still essential to balance this flexibility with workers’ rights.
The following article was originally published on Caixin and is also available on the official NSD WeChat blog. Professor Zhang did NOT review this translation before publication.
张丹丹：不可忽视的制造业零工经济趋势
Dandan Zhang: The Non-Negligible Trend of Gigification in Manufacturing
The demand for labour in the 3C (computer, communication, and consumer electronics) manufacturing industry has given rise to a new production model in export-oriented manufacturing—one with distinct Chinese characteristics, combining “high-tech + gig work.” Estimates suggest that the number of on-demand workers in the manufacturing sector is around 40 million, accounting for 31.12% of the industry’s total workforce.
Since the reform and opening up, driven by globalisation, China's manufacturing industry has occupied an irreplaceable position in the global industrial chain. By 2023, the added value of China's manufacturing industry has ranked first in the world for 14 consecutive years, accounting for nearly 30% of the global total. Notably, China is the world's largest manufacturer-exporter. In 2022, its total manufacturing exports reached $3.33 trillion—roughly one-fifth of the global total—far exceeding Germany’s $1.37 trillion and the United States’ $1.1 trillion. However, over the past decade, both the number of manufacturing workers and the sector’s share of China’s national economy have been on the decline.
As industrial upgrading and digital transformation accelerate, the cost of capital declines, skill requirements evolve, and human capital depreciation speeds up, the employment model in the manufacturing industry has undergone profound changes. With the skill level required for manufacturing workers continuously decreasing, the traditional long-term, stable employment model is gradually being replaced by short-term and gig workers, making “gig work” the primary form of labour in the sector.
Take Kunshan, Suzhou—the focus of my team’s research—as an example. Ranked first among China’s 100 most economically competitive counties, Kunshan is home to thousands of labour service and employment intermediary agencies, which supply workers daily to thousands of large-scale manufacturing enterprises in the region and its surrounding areas. During peak periods, tens of thousands of workers enter factories for employment each day. This highly efficient labour supply-demand matching mechanism plays a crucial role in meeting the workforce needs of Kunshan’s 3C manufacturing industry, giving rise to a new production model in export-oriented manufacturing—one with distinct Chinese characteristics, combining “high-tech + gig work.”
While the flexible labour model enhances the international competitiveness of China's export-oriented manufacturing industry, reduces labour costs for enterprises, and provides diverse employment options for individual workers, it also presents potential risks at both the individual and industry levels. In the ongoing push for “high-quality and sufficient employment,” there is an urgent need to closely monitor the evolving trends of the gig workforce and explore strategies to sustain the international competitiveness of export-oriented manufacturing in the era of gigification. This is an issue that policymakers cannot afford to ignore.
The Scale of "Gig Workers" in the Manufacturing Industry
Based on field research and the latest literature, this article defines “gig workers” in the manufacturing industry as individuals working on production frontlines without formal labour contracts with their employers and without access to basic social security benefits. This group primarily falls into two categories: first, “on-demand workers,” who are employed under labour contracts with intermediary agencies; and second, regular gig workers, often referred to as “day labourers,” who lack formal labour or service contracts, do not receive basic social insurance, typically secure work on their own, and are paid daily.
The Labour Contract Law of the People's Republic of China explicitly states that “labour contract employment is the basic employment form for enterprises in China. On-demand employment is a supplementary form and may only be used for temporary, auxiliary, or replacement positions.” In 2014, the Ministry of Human Resources and Social Security issued the Provisional Regulations on On-Demand Labour, with Article 4 further specifying that “employers must strictly control the number of on-demand workers, which must not exceed 10% of their total workforce.”
Since the introduction of the Provisional Regulations on On-Demand Labour, official statistics have consistently reported that on-demand workers make up less than 10% of the workforce. For example, in 2021 and 2022, the proportion of on-demand employees in Suzhou’s enterprises was 7.92% and 4.81%, respectively. However, some survey data paints a different picture.
The 2022 China Development Report on Flexible Employment, based on a 2021 survey of over 200 manufacturing enterprises, estimated that flexible workers accounted for 14.73% of the total manufacturing workforce. Additionally, this study, using data from the China Employer-Employee Survey (CEES), calculated the proportion of on-demand workers in manufacturing across five provinces (Jiangsu, Guangdong, Sichuan, Jilin, and Hubei), 100 counties, and 1,940 manufacturing enterprises. The results showed that in 2017, on-demand workers made up nearly 20.20% of the manufacturing workforce, showing a clear upward trend from 2010 to 2017.
Between 2022 and 2024, my research team conducted field visits to nearly 30 manufacturing enterprises, 20 employment intermediaries, and 10 labour markets in Kunshan of Suzhou Province, as well as in Dongguan, Foshan, and Shenzhen of Guangdong Province. Based on the collected data, in the manufacturing clusters of the Yangtze River Delta and Pearl River Delta, on-demand workers made up an average of one-third of the workforce, rising to as much as two-thirds during peak seasons. In large manufacturing plants with over 10,000 workers, the proportion of on-demand workers can reach as high as 80%.
This suggests that due to the high mobility of on-demand workers, conventional statistical methods struggle to obtain accurate data on the scale of employment in manufacturing enterprises, leading to an underestimation of the actual figures.
Using data from China’s Fourth National Economic Census and the Seventh National Population Census, it is estimated that on-demand workers in the manufacturing industry number around 40 million, making up 31.12% of the sector’s total workforce.
Profile of the "Gig Workers" Group
To further analyse the gig worker market in China’s manufacturing industry and their employment characteristics, this study selected two unique data sets: data from an online manufacturing worker recruitment platform and a sample survey of the platform’s registered members.
Founded in 2017 in Kunshan, the manufacturing on-demand labour recruitment platform is currently the largest and only online recruitment platform for on-demand workers in China. It not only provides online matching services between manufacturing enterprises and on-demand workers but has also expanded its offline network to over 20 cities nationwide, serving more than 3 million registered members.
The platform’s data covers approximately 1,000 manufacturing enterprises, 700,000 active members, and over 2.5 million matching records between enterprises and workers, primarily focusing on high-tech industries such as electronics manufacturing in the Yangtze River Delta and Pearl River Delta regions. These two regions are the most concentrated hubs of China’s export-oriented manufacturing, serve as key global manufacturing bases, and account for about 10% of China’s total manufacturing employment.
According to the platform’s data, 89.2% of on-demand workers are concentrated in electronics manufacturing. In 2023, exports from this sector accounted for approximately 23% of China’s total manufacturing exports, highlighting the export-oriented nature of manufacturing in the Yangtze River Delta and Pearl River Delta. As a result, the platform’s data is highly representative and provides valuable insights into the industry distribution and employment characteristics of gig workers in China’s export-oriented manufacturing sector.
Additionally, this study supplemented the platform’s big data with personal information—such as marital status, childbearing, education background, employment history, willingness to participate in social insurance, and future expectations—through an online survey. Conducted in April 2024, the survey was designed based on active platform members and randomly sampled 15,000 participants aged 16 to 59 who had been active on the platform.
Survey data shows that the average age of members on the manufacturing on-demand platform is 26.4 years, with males making up about four-fifths of the total. The proportion of female members has been gradually rising, increasing from 14.25% in 2019 to 21.19% in 2023. Most members come from provinces such as Henan, Gansu, Shaanxi, Yunnan, Shanxi, and Guizhou, with 89.7% holding rural household registrations and an average age of 29.4 years. Among them, 79.3% are single, and 75.4% have no children.
In terms of education, 40.2% of members have at most a junior high school education, 22.8% hold a senior high school diploma, 22.4% have a higher vocational school education, and 14.6% have a junior college degree or higher. Overall, over the past five years, the average years of schooling for new gig workers on the platform has steadily increased from 10.7 to 11.3 years, with a notable rise in the last two years.
Among the employed sample, as of April 2024, 54.8% of members were working as gig workers—including on-demand workers paid by the hour, day labourers, and flexible employees—while nearly 40% had transitioned to fixed-term employment (39.3%), and a small portion were self-employed (4%). Among gig workers, on-demand workers accounted for 44.7%, while day labourers made up 5.9%.
From a social insurance perspective, 47.8% of the sample do not participate in any of the five basic types of social security in China—pension, medical insurance, unemployment insurance, work-related injury insurance, and maternity insurance—nor in the mandatory housing fund. Women, rural workers, and older workers are more likely to be uninsured. Gig workers make up 41.8% of the uninsured group, a significantly higher proportion than fixed-term employees (20.6%) and self-employed workers (2.86%) in the sample.
There are also notable differences in members’ willingness to pay for social insurance. Survey data shows that members are willing to contribute an average of 1,499.3 yuan [$207.1] per month, but willingness is highly polarised. Workers not currently enrolled in social insurance are far less willing to pay compared to those who are partially or fully insured, with an average difference of about 1,200 yuan [$165.8].
Currently, members earn an average monthly income of 5,444.8 yuan [$752.2], with an hourly wage of 24.0 yuan [$3.3] and an average workweek of 61.6 hours. At the time of the research, the majority of surveyed members were still employed in general equipment manufacturing (17.9%) and consumer electronics (14.8%), with general workers (52.2%) being the most common occupation. Additionally, 10.2% of gig workers have transitioned to the service industry, while 11.6% have moved up to roles as professional technicians, administrative staff, or supervisors.
Regarding future plans for marriage and childbearing, 74.1% of unmarried respondents intend to marry in the future. However, among unmarried workers under 50, only 54.0% believe they are likely to marry before reaching 50. On average, members expect to have 1.41 children. Among workers under 45 who do not yet have children, they believe they have a 56.4% chance to have children before turning 45.
Regarding expected living locations, 81.7% of members anticipate continuing to live in cities five years from now. Among them, 24.4% plan to settle in first-tier cities (such as Beijing, Shanghai, Guangzhou, and Shenzhen), 27.1% expect to live in provincial capitals, and 30.2% prefer other prefecture-level cities. This suggests that while most members envision an urban future, they are more inclined to choose non-first-tier cities as their long-term residence.
Regarding future employment plans, 72.7% of members hope to engage in relatively stable work (including fixed-term employment or self-employment) within the next five years—a proportion significantly higher than the current share of members in such stable jobs. However, 16.9% still expect to continue working as on-demand workers, 2.5% anticipate working as day labourers, and 3.7% indicated they would “lie flat” and not actively seek employment opportunities.
Further regression analysis found that education positively influences members’ current employment decisions but does not significantly increase the likelihood of stable employment or improve labour productivity. Moreover, on-demand workers and day labourers exhibit path dependence, meaning they are more likely to continue in similar work over the next five years. This suggests that gig workers with lower education levels are less likely to transition to fixed-term employment. Additionally, even highly educated gig workers, once caught in a “low-stability equilibrium,” may struggle to break free from this situation.
Members with higher education levels have greater expectations for a stable life—they are more likely to seek fixed-term employment, obtain basic social insurance, and settle in urban areas. As they age, their intentions to marry and have children also increase. However, achieving these expectations presents considerable challenges. In the long run, higher-educated workers may experience a greater gap between their aspirations and reality compared to their lower-educated counterparts, leading them to make more extreme choices that resemble those of lower-educated workers.
Additionally, manufacturing gig workers in cities of different tiers exhibit significant differences in industry and job preferences. Those in first-tier cities show a stronger need for long-term planning and stability, yet due to constraints such as household registration restrictions and social security limitations, they struggle to enter the fixed-term employment pool, leading them to rely on gig work for livelihood. This finding further suggests that merely reforming employment practices cannot fundamentally change the current status of gig workers in the manufacturing industry.
What Drives the “Gigification” of Employment in Export-Oriented Manufacturing?
Why is “gig work” emerging as a trend in export-oriented manufacturing employment? This can be seen as a product of various converging factors, including the adoption of smart manufacturing technologies, the development of the platform economy, household registration restrictions limiting rural-to-urban mobility, and fluctuations in market demand for export products. These dynamics have led to the large-scale “gig” labour market in manufacturing hubs like the Yangtze River Delta and Pearl River Delta.
First, rapid advancements in smart manufacturing technologies have enhanced labour productivity and product yield, but they have also increased the substitution of skilled labour with machines. This has reduced the need for formal hires in skilled roles while driving demand for machine operators, leading to both “technological substitution” and “technological complementarity.”
“Technological substitution” refers to how automation improves production efficiency, lowers costs, and replaces routine tasks previously performed by medium-skilled workers. Meanwhile, low-skilled jobs involving non-routine manual tasks remain harder to automate, increasing demand for low-skilled workers.
“Technological complementarity” suggests that some low-skilled tasks work in tandem with automation technologies, meaning that instead of replacing low-skilled workers, technological advancements actually boost demand for these positions.
This polarisation effect, triggered by technological progress, is a widely observed economic phenomenon. The development of automation and other technologies leads to job growth in high-skilled and low-skilled positions, while medium-skilled jobs decline. This phenomenon has been confirmed in several studies. For example, Acemoglu and Autor (2011) found that between 1999 and 2007, technological advancements in the U.S. led to a polarisation in skill demand, with employment growth particularly concentrated in the lowest deciles of occupations.
Between 2010 and 2015, following the peak of China’s total labour force, wages for frontline manufacturing workers rose significantly, marking a gradual erosion of the country’s labour cost advantage. Meanwhile, advancements in automation technologies created a critical opportunity for the manufacturing sector to upgrade. The adoption of smart manufacturing technologies—such as industrial robots, artificial intelligence, big data, and the Internet of Things—not only boosted productivity and optimised costs but also accelerated the shift toward gig work in the labour market. In major manufacturing hubs like the Yangtze River Delta and Pearl River Delta, job openings were primarily for frontline roles in production, assembly, packaging, and inspection—positions that often required nothing more than familiarity with the 26 English letters, with no specific educational background or prior work experience needed.
Second, cyclical fluctuations in external demand and labour recruitment platforms’ ability to aggregate gig workers have enabled “seamless matching” between labour supply and demand. Technological advancements have fuelled the rapid growth of the platform economy, improving online information aggregation and enhancing labour market matching efficiency. For example, 周薪薪 Zhouxinxin, a recruitment platform for the manufacturing industry, integrates fragmented labour market intermediaries and uses big data to match workers with job openings, significantly boosting labour market efficiency.
Meanwhile, export-oriented manufacturing firms concentrated in the Yangtze River Delta and Pearl River Delta attract global orders, with their labor demand strongly shaped by seasonal fluctuations in international markets. These companies scale up hiring during peak seasons and downsize during off-peak periods, limiting the feasibility of fixed-term employment and making gig workers an ideal solution to meet seasonal labor needs.
Besides shifts in the export market, fluctuations in the domestic market also drive seasonal variations in labor demand. During shopping festivals like “618” and “Singles' Day,” consumption peaks compel manufacturers to hire large numbers of temporary workers to manage the spike in orders.
Third, the urban-rural divide in the household registration system encourages migrant workers to pursue short-term employment in cities, making them more inclined toward jobs that offer “higher wages, lower social insurance contributions.” This makes gig work—where pay is higher per unit of labour—more attractive to migrant workers.
Additionally, implementing the Labour Contract Law in 2008 strengthened worker protections and increased labor costs for businesses. In response, many companies turned to on-demand labor and outsourcing to reduce employment expenses. By hiring on-demand workers managed by third-party agencies, businesses can avoid the costs associated with layoffs, allowing them to flexibly adjust their workforce size and mitigate labor cost risks.
Furthermore, short-term factors have also intensified the trend of gigification in recent years. The impact of the COVID-19 pandemic and international geopolitical tensions has put manufacturing companies reliant on foreign orders under dual pressure—domestic economic slowdowns and rising uncertainty in global markets. As domestic manufacturers faced declining orders and reduced hiring, labour market uncertainty further drove up demand for gig workers.
In 2013, China’s Labour Contract Law was revised again, and the Provisional Regulations on On-Demand Labour explicitly stipulated that “employers must strictly control the number of on-demand workers, which must not exceed 10% of their total workforce.” However, demand for flexible labor remains high, and the effectiveness of policy adjustments is constrained by the economic environment and businesses’ production needs.
The following chart shows that the labor price index for manufacturing on-demand workers fluctuates in line with employment trends, with no signs of rising wages since 2022. Additionally, by the end of 2023, the platform’s membership had dropped to half of what it was in the same period of 2021, while the average labor price decreased by about 10%. This suggests that industry demand is dominant in shaping labor recruitment trends.
Promoting the Sustainable Growth of “Gig Workers”
By 2021, China’s flexible workforce had reached 200 million, accounting for 43% of urban employment. The platform economy, by bridging supply and demand, has created job opportunities for flexible workers, offering them greater autonomy and flexibility. At the same time, it acts as a “reservoir” to ease urban employment pressures.
However, most flexible workers do not sign formal labour contracts with platforms, have low social security coverage, and face inadequate labour rights protection. This issue has become a key concern in social governance and a critical topic in discussions on achieving “high-quality and sufficient employment.” While flexible employment in service industries, such as food delivery, express delivery, and ride-hailing, has drawn significant attention, gig work in manufacturing remains largely overlooked.
Manufacturing gig work is characterised by its vast scale, and its labour productivity directly affects China’s position in the global manufacturing landscape. In particular, the human capital of manufacturing gig workers plays a crucial role in shaping productivity.
In the era of smart manufacturing and flexible labour models, the growing specialization of tasks presents risks of skill monotony and deskilling for workers performing repetitive micro-tasks on production lines, making it more difficult for them to accumulate human capital.
Looking ahead, as smart manufacturing advances and industrial upgrades continue, the scale of gig work is expected to expand. Therefore, guiding the career development of gig workers, optimising social security systems, and reducing urban living costs for migrant workers will be crucial for ensuring the sustainable development of the manufacturing labour market. These efforts will also be a key step toward helping low-income groups achieve “common prosperity.”
Additionally, it is essential to create a dignified and sustainable earning environment for migrant workers, enhance their income resilience during non-working hours, reduce living costs, and improve their labour market competitiveness through diverse and flexible education and retraining opportunities.
In summary, the gig work model in manufacturing is driven by industrial clustering, market demand fluctuations, and policy environments. Its flexibility plays a crucial role in global supply chain adjustments and corporate production. Under China’s current institutional framework, gig work is an inevitable trend, but balancing this flexibility with worker rights is still essential.
Policies should go beyond simply integrating gig workers into traditional social insurance systems and instead develop more flexible, tailored social security schemes that ensure both income flexibility and basic protections for gig workers. Meanwhile, at the micro level, enterprises and HR managers must adapt to evolving work patterns and transform organizational management models to meet new development needs.
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