IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v189y2025ics0148296325000220.html
   My bibliography  Save this article

Algorithmic control as a double-edged sword: Its relationship with service performance and work well-being

Author

Listed:
  • Liang, Bingqian
  • Wang, Yixin
  • Huo, Weiwei
  • Song, Mengli
  • Shi, Yi

Abstract

Despite the disruptive changes introduced by algorithmic control in app-work platforms, research on its effects on app workers’ service performance and work well-being remains fragmented and inconsistent. Firstly, due to the lack of an established scale for perceived algorithmic control, we develop and validate one based on three rational control mechanisms and the input-behavior/process-output framework in Study 1. This validated scale, encompassing instructive guidance, process monitoring, and evaluation feedback, lays the foundation for subsequent empirical investigation. In Study 2, we build upon the job demands-resources perspective to hypothesize that perceived algorithmic control leads to increased job embeddedness and work anxiety. These, in turn, are expected to have both beneficial and detrimental impacts on service performance and work well-being. The indirect effects are dependent on the level of pay satisfaction. Our model is supported by findings from a multisource, three-wave study involving 359 app workers. Implications of our findings are discussed.

Suggested Citation

  • Liang, Bingqian & Wang, Yixin & Huo, Weiwei & Song, Mengli & Shi, Yi, 2025. "Algorithmic control as a double-edged sword: Its relationship with service performance and work well-being," Journal of Business Research, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:jbrese:v:189:y:2025:i:c:s0148296325000220
    DOI: 10.1016/j.jbusres.2025.115199
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296325000220
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2025.115199?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Newman, David T. & Fast, Nathanael J. & Harmon, Derek J., 2020. "When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 160(C), pages 149-167.
    2. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    3. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
    4. Chen, Qian & Gong, Yeming & Lu, Yaobin & Tang, Jing, 2022. "Classifying and measuring the service quality of AI chatbot in frontline service," Journal of Business Research, Elsevier, vol. 145(C), pages 552-568.
    5. Jian Zhu & Bin Zhang & Hui Wang, 2024. "The double-edged sword effects of perceived algorithmic control on platform workers’ service performance," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    6. Meng Liu & Erik Brynjolfsson & Jason Dowlatabadi, 2021. "Do Digital Platforms Reduce Moral Hazard? The Case of Uber and Taxis," Management Science, INFORMS, vol. 67(8), pages 4665-4685, August.
    7. Cram, W. Alec & Wiener, Martin & Tarafdar, Monideepa & Benlian, Alexander, 2022. "Examining the Impact of Algorithmic Control on Uber Drivers’ Technostress," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130811, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Cram, Alec W. & Wiener, Martin & Tarafdar, Monideepa & Benlian, Alexander, 2020. "Algorithmic Controls and their Implications for Gig Worker Well-being and Behavior," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124127, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Zhang, Xi & Wei, Xin & Zhang, Te & Tan, Yahe & Xu, Dongming & Ordóñez de Pablos, Patricia, 2023. "How platform-based internet hospital innovation affects doctors’ active stress coping efforts: The conservation of resource theory perspective," Technovation, Elsevier, vol. 121(C).
    10. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    11. Mengzhe Liu & Yuanyuan Lan & Zhen Liu & Mingyue Liu & Yuhuan Xia, 2024. "Navigating the maze: the effects of algorithmic management on employee performance," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    12. Gerbing, David W & Anderson, James C, 1984. "On the Meaning of Within-Factor Correlated Measurement Errors," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(1), pages 572-580, June.
    13. Qian Chen & Yeming Gong & Yaobin Lu & Jing Tang, 2022. "Classifying and measuring the service quality of AI chatbot in frontline service," Post-Print hal-04325624, HAL.
    14. Thor Berger & Carl Benedikt Frey & Guy Levin & Santosh Rao Danda, 2019. "Uber happy? Work and well-being in the 'Gig Economy'," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(99), pages 429-477.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Choi, Sunhwa & Yi, Youjae & Zhao, Xiaohong, 2024. "The human touch vs. AI efficiency: How perceived status, effort, and loyalty shape consumer satisfaction with preferential treatment," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    2. Wang, Siqi & Lim, Weng Marc & Cheah, Jun-Hwa & Lim, Xin-Jean, 2025. "Working with robots: Trends and future directions," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
    3. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Javed Ali, 2024. "Thematic Evolution of Service Quality (2011-2023): Insights for Future Research Directions ," GATR Journals jmmr341, Global Academy of Training and Research (GATR) Enterprise.
    5. Peng, Leiqing & Luo, Mengting & Guo, Yulang, 2023. "Deposit AI as the “invisible hand†to make the resale easier: A moderated mediation model," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    6. Michael Hennessy & Amy Bleakley & Martin Fishbein, 2012. "Measurement Models for Reasoned Action Theory," The ANNALS of the American Academy of Political and Social Science, , vol. 640(1), pages 42-57, March.
    7. Junwei Zheng & Guangdong Wu, 2018. "Work-Family Conflict, Perceived Organizational Support and Professional Commitment: A Mediation Mechanism for Chinese Project Professionals," IJERPH, MDPI, vol. 15(2), pages 1-23, February.
    8. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    9. Pinochet, Luis Hernan Contreras & de Gois, Fernanda Silva & Pardim, Vanessa Itacaramby & Onusic, Luciana Massaro, 2024. "Experimental study on the effect of adopting humanized and non-humanized chatbots on the factors measure the intensity of the user's perceived trust in the Yellow September campaign," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    10. Keding, Christoph & Meissner, Philip, 2021. "Managerial overreliance on AI-augmented decision-making processes: How the use of AI-based advisory systems shapes choice behavior in R&D investment decisions," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    11. González-Gómez, Helena V. & Hudson, Sarah, 2024. "Employee frustration with information systems: Appraisals and resources," European Management Journal, Elsevier, vol. 42(3), pages 425-436.
    12. Hannah, Sean T. & Avolio, Bruce J. & Walumbwa, Fred O. & Chan, Adrian, 2012. "Leader Self and Means Efficacy: A multi-component approach," Organizational Behavior and Human Decision Processes, Elsevier, vol. 118(2), pages 143-161.
    13. Ahn, Suhyoung & Park, JungKun & Ye, Sangbeak, 2025. "How AI enhances employee service innovation in retail: Social exchange theory perspectives and the impact of AI adaptability," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).
    14. Kim Shin Young & Sang-Gun Lee & Ga Youn Hong, 2024. "User satisfaction with the service quality of ChatGPT," Service Business, Springer;Pan-Pacific Business Association, vol. 18(3), pages 417-431, December.
    15. Mütterlein, Joschka & Kunz, Reinhard E. & Baier, Daniel, 2019. "Effects of lead-usership on the acceptance of media innovations: A mobile augmented reality case," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 113-124.
    16. Zhang, Yan & Han, Yu-Lan, 2019. "Paradoxical leader behavior in long-term corporate development: Antecedents and consequences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 155(C), pages 42-54.
    17. Juquelier, Antoine & Poncin, Ingrid & Hazée, Simon, 2025. "Empathic chatbots: A double-edged sword in customer experiences," Journal of Business Research, Elsevier, vol. 188(C).
    18. Chen, Qian & Jing, Yufan & Gong, Yeming & Tan, Jie, 2025. "Will users fall in love with ChatGPT? a perspective from the triangular theory of love," Journal of Business Research, Elsevier, vol. 186(C).
    19. Won, Jongho & Lee, Daeho & Lee, Junmin, 2023. "Understanding experiences of food-delivery-platform workers under algorithmic management using topic modeling," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    20. Sonal Ahuja & Vaibhav Sharma & Simarjeet Singh, 2025. "Is fintech chatbot adoption a far-off aspiration? Establishing adoption model using ISM-MICMAC approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 413-437, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:189:y:2025:i:c:s0148296325000220. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.