Labor control and task autonomy under the sharing economy: a mixed-method study of drivers’ work

Abstract

This mixed-method study analyzes the labor process and labor supply of drivers on a Chinese mobile-travel platform. Different from the control of the traditional labor process, such platforms have a more-fragmented control of labor, which coexists with workers' task autonomy. Based on this assessment, we propose three core mechanisms by which platforms control the labor process and produce work consent: task autonomy, performance-related pay and motivation, and the star rating system. Under the influence of these three mechanisms, workers form both active consent to and passive acceptance of the platform and its rules. Moreover, we analyze data from a survey of 15,484 drivers to show that drivers' work consent could be transformed into overwork, although identity difference is at play in the transformation process.

The game of popularity: The earnings system and labor control in the live streaming industry

“…According to the earnings system of the platforms, with increasing popularity, contract live streamers are given the opportunity of a salary raise, but the evaluation system that is closely associated with the earnings system would also be adjusted, and the valid duration of live streaming and the definition of “valid” would change accordingly. This is similar to a “floating ceiling” ( fudong de tianhuaban ) (Lan, 1998; Xie, 1997). Indicators of popularity may increase with the progress of live streamers’ working performance; however, the number of followers required to consider a salary raise and the duration of a “valid” performance are all determined by the platform, without any definite system.…”

“…For example, the internet makes it more convenient for platforms to monitor and control the labor process of drivers for online car-hailing services (e.g., Uber) in real time: platforms incorporate customer ratings into the remuneration system to determine the level of remuneration based on their ranking; platforms use driver data to carefully design a fluctuated and tiered payment system based on the average output of the drivers, to guide the drivers to increase their working hours and climb the "ladder". Platforms exert more power over those full-time workers whose main source of income comes from the platform (Chen, 2018;Cockayne, 2016;Rosenblat and Stark, 2016;Wu and Li, 2018).…”

“…Although consumers are endowed with the power of evaluation and assessment and have established direct relationships with workers, the platforms still realize labor control behind the scenes. The platforms view the evaluation information, the audience data, as an important criterion for labor evaluation (Wu and Li, 2018;Zhao and Liu, 2018). However, the information and data are generally not public and transparent; rather, they are in the hands of the platforms, leaving huge space for manipulation by the platforms.…”

“…Following this path, Xie (1997) specifically analyzed the dominant ideological effect of the earnings system. He found that in the absence of an internal labor market and state intervention in labor reproduction, the piece-rate earnings system still makes workers in Taiwan “voluntarily obey”.…”

“…From Marx (2004) to Burawoy (1985, 2008) and Xie (1997, 2013), and on to the following scholars engaged in labor research, each has been paying more attention to the function of the earnings system in labor control in their studies on labor processes. The operation of the earnings system itself as well as workers’ feelings about the earnings system have the effect of “manufacturing consent”.…”