Sun Ping (center) conducting a survey in Beijing Photo: PROVIDED TO CSST

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Recently, a short video titled “Female Researcher Infiltrates Food Delivery Industry for Eight Years, Leading Platforms to Adjust Algorithms” has brought Sun Ping, an associate research fellow from the Institute of Journalism and Communication Studies at the Chinese Academy of Social Sciences, back into the online spotlight. The last time she trended was on Sept. 8, 2020, following the release of a report titled “Delivery Riders, Stuck in the System.” These two viral pieces have highlighted her and her team’s eight-year investigations into the lives of delivery riders. 

Plight of delivery riders

Eight years ago, when Sun and her team began their research on delivery riders, the food delivery industry was already well established and deeply integrated into daily life, and its prevalence sparked their interest in conducting deeper research. In May 2017, the team began immersing themselves in the food delivery industry in major cities like Beijing, Shanghai, and Shenzhen. They employed various research methods, including interviews, field observations, questionnaire surveys, and even shadowing riders on their routes. As platforms expanded to third- and fourth-tier cities, their research scope broadened, gradually focusing on the differences between urban and rural riders.

According to incomplete statistics, over the past eight years, Sun and her team have traveled to 19 provinces across the country and interviewed over 400 delivery riders. This extensive and in-depth research provided them with a wealth of firsthand data on the profession, leading to a detailed analysis of its development. Among their findings, the most notable was their observation of “why delivery riders are trapped in systemic dilemmas.”

Through the analysis of extensive research data, Sun’s team identified algorithm-driven systems as the core factor behind delivery riders’ struggles. For example, in a typical scenario, the platform system might allocate an hour for a delivery. To avoid being late, most riders will aim to complete the delivery in 55 or 56 minutes. After collecting substantial back-end data, the platform’s algorithm might conclude that the delivery could be completed more quickly, leading to a reduction in the allotted time for the next delivery to 57 minutes.

 “This kind of time adjustment turns delivery into a sort of ‘breaking through barriers’ game,” Sun continued. The platform algorithms strive to enrich “game scenes” and expand “game space” through refining management categories and formulating rules so that riders are continuously acting like players advancing through levels, all the while being ranked by the platform algorithmically. While each platform has different ranking conventions, the core metric is the rider’s “delivery capacity.” Simply put, the more orders a rider delivers, and the longer they work, the higher their rank. For example, on the now-defunct Baidu delivery platform, riders were ranked on a seven-level scale from “ordinary rider” to “Godlike rider.” Correspondingly, the bonuses and points accumulation varied by rank. An “ordinary rider” might earn an extra 10 cents per order, while a “diamond rider” could earn 1 yuan per order. On other platforms, riders at different levels enjoy different “privileges,” with higher levels granting more benefits, such as priority order assignments or exemptions from penalties for late deliveries. This connection between “ranks” and “privileges” entices some young, adventurous riders to push themselves harder.

Sun’s investigations reveal that most delivery riders can advance to and stabilize at the “golden rider” or “black gold rider” levels within half a year, but further advancement becomes exceedingly difficult, requiring tremendous investments of energy and time. In addition to rider rankings, platforms periodically introduce various challenges, tournaments, and events, setting different challenge targets according to each rider’s capacity and promising corresponding rewards for successful completion. These measures serve to incentivize riders to deliver more orders.

Ways forward

Around Aug. 30 this year, the above-mentioned short video went viral on WeChat. The memory of the internet prompted many to revisit the widely popular September 2020 article, “Delivery Riders, Stuck in the System.” This report brought Sun’s research to public attention and highlighted the plight of delivery riders, leading to responses from food delivery platforms like Meituan. These companies subsequently eased some of the stringent time constraints imposed by their algorithms and placed greater emphasis on rider safety. Some platforms even encouraged algorithm engineers to experience delivery work first-hand, completing orders to validate the reasonableness of their algorithmic systems. In 2021, Meituan publicly disclosed its algorithm governing rider delivery times, allowing for societal oversight and bringing the ethics of algorithms and the rights and interests of platform workers to the public eye.

Sun and her team aspire to broaden their research by collecting more diverse samples to delineate the panorama of the delivery rider occupation, including issues such as occupational mobility, development, and labor protection. Regarding the timeline for completing the research, Sun noted that from an academic perspective, long-term, continuous study can lead to deeper insights and discoveries. As such, she intends to extend this research for at least 10 years to construct a macro information map. This map will fully illustrate the career of delivery riders and the trajectory and logic of platform economy development.

When discussing the “systemic dilemmas” she is most concerned with, Sun repeatedly emphasized the necessity of improving the basic protection system for platform gig workers. She suggested that relevant government agencies should take the lead, with active participation from food delivery platforms, to explore ways to ensure riders’ basic income and social security. Additionally, she advocated for greater transparency in the fees and marketing practices of gig employment platforms, especially when developing or adjusting policies that affect rider interests. She stressed that platforms should conduct risk assessments and provide public disclosures in these cases.

As for the future of the delivery rider occupation within the platform economy, Sun admitted, “Like many riders, I can’t predict it.” However, as an emerging economic phenomenon, gig economy—represented by delivery riders—is evolving rapidly alongside advancements in internet technology. The ongoing transformation constitutes an important reason why Sun and her team will continue their research in this field.

Edited by YANG LANLAN