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When and why algorithmic control leads to app-based gig workers' deviant work behaviour in China: A mixed-methods study in the food delivery sector

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TELEMATICS AND INFORMATICS 2025年 99卷

作者： Chi, Ming Xu, Yongshun Yang, Yihao Hainan Univ Int Business Sch Haikou 570228 Peoples R China Hainan Univ Sch Civil Engn & Architecture Haikou 570228 Peoples R China Jilin Univ Sch Business & Management Changchun 130012 Peoples R China

algorithmic control (AC) aligns worker behaviour with organisational goals and has consequently become a central feature of the gig economy. Despite its success, the impact of AC on deviant work behaviours (DWB) among app-based gig workers (app-workers) remains unclear, as it can yield both positive and negative effects. To address these contradictory outcomes, this study draws on the transactional model of stress and coping, proposing that AC may be perceived as a hindrance, leading to DWB through organisational dehumanisation, or as a challenge, reducing DWB through job crafting. We also examine how technology readiness moderates workers' appraisals of AC. Employing a mixed-methods approach, the study combines quantitative data from 317 app-workers in China (Study 1) and qualitative insights from 28 app-workers in China (Study 2). The results of Study 1 reveal that AC has a direct negative impact on app-workers' DWB, and an indirect negative impact through job crafting. This indirect effect is stronger when technology readiness is higher. Conversely, AC also has a positive indirect impact on DWB via organisational dehumanisation, with this effect being stronger when technology readiness is lower. The qualitative findings from Study 2 provide deeper insights into these relationships. Overall, the results offer important theoretical and practical implications for understanding app-workers' psychological and behavioural responses to AC, suggesting ways to mitigate the negative effects of AC and improve its effectiveness in the gig economy.

关键词： App-based gig workers Gig economy algorithmic control Deviant work behaviour Organisational dehumanisation Job crafting Technology readiness

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Blessing or curse? The two-sided effects of algorithmic control on and ego-depletion and safety performance of gig workers

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COMPUTERS IN HUMAN BEHAVIOR 2025年 162卷

作者： Chen, Renee Rui Gao, Jianglian Chen, Xiayu Huang, Qiuhui Shenzhen Univ Coll Management Shenzhen Peoples R China Hefei Univ Technol Sch Management Hefei Anhui Peoples R China Key Lab Philosophy & Social Sci Cyberspace Behav & Hefei Anhui Peoples R China

The emergence of gig economy has facilitated the adoption of algorithm-based management systems, creating favorable conditions for gig workers. Nevertheless, it also brings various challenges and uncertainties, especially gig workers' safety performance, having become a prominent concern. Based on ego-depletion theory, we investigate the underlying mechanism through which platform algorithmic control influences on safety performance of gig workers. Based on two points of data from 314 gig workers in China, we found that the three dimensions of algorithmic control (viz., standardized guidance, tracking evaluation and behavioral constraint) have differential effects on safety performance. On one hand, algorithmic standardized guidance is negatively related to ego-depletion, which in turn improves safety performance. On the other hand, algorithmic tracking evaluation and behavioral constraint are positively related to ego-depletion, and consequently reducing safety performance. Furthermore, algorithmic transparency moderates the relationship between algorithmic standardized guidance, algorithmic tracking evaluation, and ego-depletion;self-efficacy moderates the relationship between algorithmic standardized guidance and ego-depletion;both trait mindfulness and leadership safety commitment moderate the relationship between ego-depletion and safety performance. This study offers valuable insights for platform enterprises to optimize the effectiveness of algorithmic control.

关键词： algorithmic control Standardized guidance Tracking evaluation Behavioral constraint Trait mindfulness Safety performance Ego-depletion theory Self-efficacy Leader safety commitment

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Dark sides of algorithmic control in app-based gig work: An objectification perspective

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JOURNAL OF BUSINESS RESEARCH 2025年 195卷

作者： Yang, Yihao Chi, Ming Bi, Xinhua Xu, Yongshun Jilin Univ Sch Business & Management Changchun 130012 Peoples R China Hainan Univ Int Business Sch Haikou 570228 Peoples R China Hainan Univ Sch Civil Engn & Architecture Haikou 570228 Peoples R China

App-based gig work (app-work) relies on algorithmic control (AC) to enhance operational efficiency and minimize costs. While flexible, app-work raises concerns regarding workers' well-being and performance. Applying the stressor-strain-outcome framework, this study examines the relationship between AC and app-workers' proactive customer service performance (PCSP) from an objectification perspective. AC can lead to organizational and self-objectification, diminishing workers' motivation to engage in proactive customer service. This study uses a mixed-methods approach, combining quantitative data from 300 (Study 1) and qualitative insights from 25 app-workers (Study 2). A negative relationship exists between AC and PCSP, mediated by organizational and self-objectification. Coworker support moderates the impact of AC on organizational and self-objectification. Study 2 identifies contextual factors that may influence the verified relationships, providing insights into the research phenomenon. This research contributes to understanding app-workers' psychological and behavioral responses to AC.

关键词： algorithmic control Proactive customer service performance Organizational objectification Self-objectification Coworker support

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algorithmic control in app-work platforms: Exploring its curvilinear impact on work well-being

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EUROPEAN MANAGEMENT REVIEW 2025年第0期

作者： Huo, Weiwei Wang, Yixin Liang, Bingqian Song, Mengli Xie, Jiaying Shanghai Univ SILC Business Sch 99 Shangda Rd Shanghai 200444 Peoples R China

algorithmic control in app-work platforms has sparked widespread concerns regarding its impact on app workers' work well-being. Existing research has predominantly explored the economic and operational benefits yet largely ignored its effects on app workers' work well-being. This study investigates when and how algorithmic control promotes or inhibits app workers' well-being. Drawing on the job demands-resources model and the sociotechnical perspective of work design, we propose an inverted U-shaped relationship between algorithmic control and the work well-being of app workers. We find that this curvilinear relationship is further moderated by app-workers' multi-focus identification (i.e., organizational and occupational identification) and their perception of algorithmic fairness. A time-lagged study of 304 app workers supports the hypothesized model. Additionally, to address the lack of a validated measurement tool, we developed and validated a perceived algorithmic control scale based on three rational control mechanisms. Theoretical and practical implications are discussed.

关键词： algorithmic control algorithmic fairness occupational identification organizational identification work well-being

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algorithmic control and gig workers: a legitimacy perspective of Uber drivers

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EUROPEAN JOURNAL OF INFORMATION SYSTEMS 2023年第3期32卷 485-507页

作者： Wiener, Martin Cram, W. Benlian, Alexander Tech Univ Dresden Chair Business Informat Esp Business Engn Dresden Germany Univ Waterloo Sch Accounting & Finance Waterloo ON Canada Tech Univ Darmstadt Endowed Chair Informat Syst & E Serv Darmstadt Germany

Organisations increasingly rely on algorithms to exert automated managerial control over workers, referred to as algorithmic control (AC). The use of AC is already commonplace with platform-based work in the gig economy, where independent workers are paid for completing a given task (or "gig"). The combination of independent work alongside intensive managerial monitoring and guidance via AC raises questions about how gig workers perceive AC practices and judge their legitimacy, which could help explain critical worker behaviours such as turnover and non-compliance. Based on a three-dimensional conceptualisation of micro-level legitimacy tailored to the gig work context (autonomy, fairness, and privacy), we develop a research model that links workers' perceptions of two predominant forms of AC (gatekeeping and guiding) to their legitimacy judgements and behavioural reactions. Using survey data from 621 Uber drivers, we find empirical support for the central role of micro-level legitimacy judgements in mediating the relationships between gig workers' perceptions of different AC forms and their continuance intention and workaround use. Contrasting prior work, our study results show that workers do not perceive AC as a universally "bad thing" and that guiding AC is in fact positively related to micro-level legitimacy judgements. Theoretical and practical implications are discussed.

关键词： algorithmic control gatekeeping vs guiding micro-level legitimacy continuance intention workaround use platform-based gig work

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Examining the Impact of algorithmic control on Uber Drivers' Technostress

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JOURNAL OF MANAGEMENT INFORMATION SYSTEMS 2022年第2期39卷 426-453页

作者： Cram, W. Alec Wiener, Martin Tarafdar, Monideepa Benlian, Alexander Univ Waterloo Sch Accounting & Finance 200 Univ Ave West Waterloo ON N2L 3G1 Canada Tech Univ Dresden Dresden Germany Univ Massachusetts Isenberg Sch Management Amherst MA 01003 USA Tech Univ Darmstadt Darmstadt Germany

This study examines how the use of algorithmic control within gig economy platforms relates to the well-being and behavior of workers. Specifically, we explore how two different forms of algorithmic control-gatekeeping and guiding-correspond with (positive) challenge technostressors and (negative) threat technostressors experienced by Uber drivers. We also examine the moderating impact of algorithmic control transparency on these relationships, as well as the outcomes of technostressors in terms of continuance intentions and workaround use. Based on a survey of 621 U.S.-based Uber drivers, we find that gatekeeping and guiding algorithmic control positively relate to both challenge and threat technostressors. The study bridges the literature on control and technostress by conceptualizing algorithmic control as a condition that puts workers under stress. This stress is found to contribute to important behavioral consequences pertaining to both continuance intentions and workaround use. Findings from our work suggest that gig economy organizations can use algorithmic control to enhance challenge technostressors for their workers, thereby contributing to the cultivation of a more committed workforce. Furthermore, we find evidence disputing the assumption that algorithmic control transparency can mitigate the negative effects of threat technostressors.

关键词： algorithmic control Uber drivers technostress challenge technostressors threat technostressors algorithmic control transparency gig economy

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The Influence of algorithmic control on Gig Drivers' Coping Behavior in Ride-Hailing Platforms 23rd

The Influence of Algorithmic Control on Gig Drivers' Coping ...

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23rd Wuhan International Conference on E-business (WHICEB)

作者： Li, Yize Tang, Jian Li, Xuefeng Zhou, Xinxue Cent Univ Finance & Econ Sch Informat Beijing Peoples R China Guangxi Univ Sch Business Nanning Peoples R China

ISBN: (纸本)9783031603266;9783031603242

The use of algorithmic control is commonplace in gig economy platforms. Algorithms may direct, evaluate, or discipline gig workers to enforce their compliance, or conversely, trigger their reactance. This paper explores the impact of algorithmic control on ride-hailing drivers' coping behavior. Based on the legitimacy process model, we develop a research model that links perceived algorithmic control to gig drivers' compliance and workaround behaviors. Using survey data from 197 ride-hailing drivers, we find that perceived algorithmic control positively affects fairness and privacy judgment. Fairness judgment has a positive impact on compliance behavior, and privacy judgment has a negative impact on workaround behavior. The paper discusses theoretical and practical implications.

关键词： Gig Economy algorithmic control Ride-hailing Platforms Mixed Research Method

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Resisting algorithmic control: Understanding the rise and variety of platform worker mobilisations

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NEW TECHNOLOGY WORK AND EMPLOYMENT 2023年第1期38卷 125-144页

作者： Cini, Lorenzo Univ Coll Dublin Michael Smurfit Grad Business Sch Dublin Ireland

Algorithms are seen as effective for managing workers. Literature focuses mainly on the functioning and impact of algorithmic control on workers' experiences and conditions. The ways in which platform workers have organised collectively to regain control have received far less scholarly attention. This paper addresses this gap by making sense of the mobilisation dynamics of two platform-work categories: crowdwork (Amazon Mechanical Turk) and work on-demand (food-delivery couriers). These are salient mobilisation cases, as these workers have resisted algorithmic control by adopting specific organising modes, action repertoires and collective solidarities. By analysing a combination of extant literature and policy reports concerning each category of mobilisation forms at a global level over 5 years, the study elucidates why and how these workers were able to act without the involvement of traditional trade unions by showing that specific supportive communities and political activism traditions were crucial in the rise and variety of mobilisation.

关键词： algorithmic control Amazon Mechanical Turk food-delivery couriers political activist tradition supportive community worker mobilisations

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Who is pulling the strings in the platform economy? Accounting for the dark and unexpected sides of algorithmic control

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ORGANIZATION 2023年第1期30卷 140-167页

作者： Pignot, Edouard Leonard de Vinci Pole Univ Paris France

This paper aims to address the dark side perspective on digital control and surveillance by emphasizing the affective grip of ideological control, namely the process that silently ensures the subjugation of digital labour, and which keeps the 'unexpectedness' of algorithmic practices at bay: that is, the propensity of users to contest digital prescriptions. In particular, the theoretical contribution of this paper is to combine Labour Process with psychoanalytically-informed, post-structuralist theory, in order to connect to, and further our understanding of, how and why digital workers assent to, or oppose, the interpellations of algorithmic ideology at work. To illustrate the operation of affective control in the Platform Economy, the emblematic example of ride-hailing platforms, such as Uber, and their algorithmic management, is revisited. Thus, the empirical section describes the way drivers are glued to the algorithm (e.g. for one more fare, or for the next surge pricing) in a way that prevents them, although not always, from considering genuine resistance to management. Finally, the paper discusses the central place of ideological fantasy and cynical enjoyment in the Platform Economy, as well as the ethical implications of the study.

关键词： algorithmic control cynicism digital interpellation ethics ideological fantasy platform economy post-structuralism Uber unexpectedness

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Strategies for communicating and mitigating algorithmic control on delivery platforms

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CONVERGENCE-THE INTERNATIONAL JOURNAL OF RESEARCH INTO NEW MEDIA TECHNOLOGIES 2024年第5期30卷 1685-1709页

作者： Tuomi, Aarni Jianu, Brana Hua, Maizi Roelofsen, Maartje Ascencao, Mario Passos Haaga Helia Univ Appl Sci Pajuniityntie 11 Helsinki 00320 Finland Univ Surrey Surrey England Univ Oslo Oslo Norway Wageningen Univ Wageningen Netherlands

Delivery platforms use algorithmic control mechanisms to control couriers' work. Despite studies looking at how algorithmic control manifests on different delivery platforms, there is a dearth of research exploring how delivery platforms communicate their approaches to algorithmic control, what kinds of strategies delivery workers adopt to mitigate algorithmic control, and to what extent information regarding such 'algoactivistic approaches' is shared among communities of delivery couriers who in many cases are in direct competition with one another. To that end, two studies are conducted. Study 1 analyses five publicly listed delivery companies' annual reports (n = 14), highlighting a lack of transparency on how the platforms' algorithms function. In Study 2, a netnographic approach is used to conduct interviews (n = 12) and a qualitative analysis of delivery workers' online discussion forum posts (n = 830) on the discussion forum Reddit. Four approaches to mitigating algorithmic control are found, and the way these are shared among couriers is considered.

关键词： Algoactivism algorithmic control communication delivery platform collaborative competition annual report netnography

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