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Not all algorithmic controls are equal: the double-edged impact of algorithmic control dimensions on mental health and risky riding behavior among food delivery riders
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  • Published: 11 March 2026

Not all algorithmic controls are equal: the double-edged impact of algorithmic control dimensions on mental health and risky riding behavior among food delivery riders

  • Jinnan Wu1,
  • Wenqian Yang1,
  • Juan Qi1 &
  • …
  • Wenpei Zhang1 

Humanities and Social Sciences Communications , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Business and management
  • Health humanities
  • Psychology
  • Science, technology and society

Abstract

Online labor platforms rely on big data-driven algorithms to implement precise, immediate, and fine-grained control over the labor service process of food delivery riders, called algorithmic control. While algorithmic control enhances the overall efficiency of platform-based organizations, it also exerts multiple psychological and behavioral impacts on food delivery riders, though the underlying mechanisms remain unclear. This study subdivided the three dimensions of perceived algorithmic control (i.e., tracking evaluation, behavioral constraint, and standardized guidance), and considered work pressure as a mediator based on the Job Demands-Resources (JD-R) model, in order to explore whether and how perceived algorithmic control affects the mental health and risky riding behavior of food delivery riders. The study also investigates the moderating role of perceived autonomy. Data from 466 Chinese food delivery riders were analyzed using a structural equation model and bootstrapping procedure. The results showed that both perceived algorithmic tracking evaluation and behavioral constraint impaired riders’ mental health and promoted risky riding behavior through work pressure, while perceived algorithmic standardized guidance improved their mental health and reduced risky riding behavior through work pressure. Perceived autonomy mitigates the negative effects of algorithmic tracking evaluation and enhances the positive effects of algorithmic standardized guidance, but it amplifies the negative effects of algorithmic behavioral constraint. These findings provide a clear explanation for understanding the “double-edged sword” effect of perceived algorithmic control on the food delivery riders’ psychology and behavior, which not only enriches the research on algorithmic control in the context of the gig economy, but also sheds light on the managerial practices of platform-based organizations to improve their algorithmic systems and enhance the sustainable development of gig workers.

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Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to a confidentiality agreement with the company conducting the surveys. However, data will be made available on reasonable request from the corresponding author.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (No. 72172002, 72304002), the University Excellent Research Innovation Team Foundation of Anhui Province (No. 2023AH010018), the University Outstanding Youth Foundation of Anhui Province (No. 2022AH030040), and the Philosophy and Social Sciences Planned Project of Anhui Province (No. AHSKQ2021D16).

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Authors and Affiliations

  1. School of Business, Anhui University of Technology, Ma’anshan, China

    Jinnan Wu, Wenqian Yang, Juan Qi & Wenpei Zhang

Authors
  1. Jinnan Wu
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  2. Wenqian Yang
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  3. Juan Qi
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  4. Wenpei Zhang
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Contributions

Conceptualization, WY and JW; methodology, WY; formal analysis, WY and JQ; writing - original draft preparation, WZ, WY, and JW; writing - review and editing, WZ and JW; visualization, WY; supervision, JW; and funding acquisition, JW and WZ. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Wenpei Zhang.

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Competing interests

The authors declare no competing interests.

Ethical approval

This study was ethically reviewed and approved by the Institutional Review Board of the School of Business, Anhui University of Technology (Research Ethics Committee Number: SB-AHUT-REC-2023-04-HS01) in April 2023. The review process ensured that all research procedures adhered to institutional guidelines, the principles outlined in the 1964 Helsinki Declaration and its subsequent amendments, as well as comparable ethical standards.

Informed consent

Participants in the survey conducted in July 2025 have electronically signed informed consent forms. The electronic survey included a detailed information section outlining the research objectives, data processing methods, and participants’ rights. Respondents were required to actively confirm their understanding of the aforementioned information and express their willingness to participate by checking the consent box in the electronic questionnaire. This method ensured that respondents had the opportunity to review all relevant details before granting consent. It was explicitly stated that all data collected through the survey would remain anonymous.

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Supplementary materials (download DOCX )

Dataset

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Wu, J., Yang, W., Qi, J. et al. Not all algorithmic controls are equal: the double-edged impact of algorithmic control dimensions on mental health and risky riding behavior among food delivery riders. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-06909-6

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  • Received: 20 September 2024

  • Accepted: 26 February 2026

  • Published: 11 March 2026

  • DOI: https://doi.org/10.1057/s41599-026-06909-6

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