管理评论

管理评论 ›› 2025, Vol. 37 ›› Issue (2): 175-186.

• 组织行为与人力资源管理 • 上一篇    

感知算法控制对零工工作者工作投入的“双刃剑”效应研究

罗瑾琏1, 张超1, 赵陈芳2, 钟竞1   

  1. 1. 同济大学经济与管理学院, 上海 200092;
    2. 西南财经大学工商管理学院, 成都 611130
  • 收稿日期:2023-01-31 发布日期:2025-03-06
  • 作者简介:罗瑾琏，同济大学经济与管理学院教授，博士生导师，博士；张超（通讯作者），同济大学经济与管理学院博士研究生；赵陈芳，西南财经大学工商管理学院讲师，博士；钟竞，同济大学经济与管理学院副教授，博士。
  • 基金资助:
    国家自然科学基金面上项目（72372118；72372115；72072128）。

The Double-edged Effect of Perceived Algorithmic Control on Work Engagement of Gig Workers

Luo Jinlian1, Zhang Chao1, Zhao Chenfang2, Zhong Jing1   

  1. 1. School of Economics and Management, Tongji University, Shanghai 200092;
    2. School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130
  • Received:2023-01-31 Published:2025-03-06

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摘要： 基于资源保存理论和社会认同理论，构建了感知算法控制对零工工作者工作投入的作用机制模型。通过对采集于外卖骑手、网约车司机和即时配送员的385份有效实证数据进行分析检验，探究了感知算法控制对零工工作者工作投入的“双刃剑”效应。研究结果表明：感知算法控制对零工工作者工作投入具有“双刃剑”效应，感知算法控制一方面可能通过提升零工工作者的角色清晰而实现工作投入的提升;另一方面,可能通过引发零工工作者工作自主性的丧失而导致其工作投入的下降。进一步地，感知算法程序公平可能强化感知算法控制经由角色清晰影响零工工作者工作投入的提升路径，而缓冲感知算法控制经由工作自主性影响零工工作者工作投入的削弱路径，即感知算法程序公平越高，感知算法控制越能通过提高零工工作者角色清晰而促进其工作投入，而感知算法程序公平越低，感知算法控制越能通过降低零工工作者工作自主性而导致其工作投入的降低。

关键词: 感知算法控制, 工作投入, 角色清晰, 工作自主性, 感知算法程序公平

Abstract: Based on conservation of resources theory and social identity theory, this paper builds a model to explore the mechanism of how perceived algorithm control affects the level of gig workers’ work engagement. By analyzing and testing 385 valid empirical data collected from takeout riders, online ride-hailing drivers and instant delivery workers, this paper examines the “double-edged sword” effect of perceived algorithmic control on the work engagement of gig workers. The results indicate that perceived algorithmic control has a “double-edged sword” effect on the work engagement of gig workers, perceived algorithmic control may, on the one hand, improve the role clarity of gig workers and, on the other hand, lower work engagement by causing a loss of work autonomy. Furthermore, perceived algorithmic procedure fairness may also strengthen the ability of perceived algorithmic control to improve gig workers’ work engagement through role clarity and mitigate its ability to weaken their work engagement through job autonomy, i.e., the higher the perceived algorithmic procedure fairness is, the better able perceived algorithmic control is to facilitate gig workers’ work engagement by increasing their role clarity, while the lower the perceived algorithmic procedure fairness is, the more likely perceived algorithmic control is to dampen gig workers’ work engagement by diminishing their job autonomy.

Key words: perceived algorithmic control, work engagement, role clarity, job autonomy, perceived algorithm procedure fairness