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随着人工智能技术的飞速发展,平台算法逐步取代了传统组织中的管理者职能,突出表现为运用数字技术精确捕捉零工工作者的劳动信息,实现对劳动过程的约束、指导与评估。然而,现有研究关于感知算法控制如何通过具体的心理机制和工作行为调整而影响零工工作者工作绩效还不系统。本研究基于工作要求-资源模型,以350名网约车司机为研究对象,发现:（1）感知算法控制可以促进零工工作者积极开展工作重塑,提高绩效表现;（2）感知算法控制也会造成零工工作者的情绪耗竭,抑制工作绩效;（3）工作不安全感既会强化感知算法控制对工作重塑的正向影响,也会强化其对情绪耗竭的正向影响,并以“双刃剑”的形式调节感知算法控制分别通过工作重塑和情绪耗竭对工作绩效的正向和负向间接影响。这些发现丰富了算法控制领域的实证研究,有助于提高对这一新兴管理实践的全面影响的理解,也为零工平台如何在数字化转型背景下有效管理员工、促进员工心理健康与提升工作绩效提供理论依据和实践指导。
Abstract：With the rapid development of artificial intelligence technology, platform algorithms have gradually replaced the function of managers in traditional organizations, which is typically demonstrated by the use of digital technology to accurately capture the labor information of gig workers and to constrain, guide, and evaluate the labor process. However, existing research on how perceived algorithmic control affects gig workers' job performance through specific psychological mechanisms and work behavior adjustments is not yet systematic. Based on the Job Demands-Resources model, this study, targeting 350 online car-hailing drivers, found that:(1) Perceived algorithmic control can promote gig workers to actively engage in job crafting, thereby enhancing their performance;(2) Perceived algorithmic control can also cause emotional exhaustion among gig workers, inhibiting job performance;(3) Job insecurity not only strengthens the positive impact of perceived algorithmic control on job crafting but also strengthens its positive impact on emotional exhaustion, thereby moderating the positive and negative indirect effects of perceived algorithmic control on job performance through job crafting and emotional exhaustion, respectively, in a "double-edged sword" pattern. These findings enrich empirical research in the field of algorithmic control, contribute to a better understanding of the comprehensive impact of this emerging management practice, and provide a theoretical basis and practical guidance for how gig platforms can effectively manage workers, promote their mental health, and enhance job performance in the context of digital transformation.
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基本信息:
DOI：10.16471/j.cnki.11-2822/c.2025.12.006
中图分类号:TP18;F272.92
引用信息:
[1]汪鑫,陈丽莉,张惠琴.感知算法控制对零工工作者工作绩效的双刃剑影响及其工作不安全感的调节作用:基于JD-R模型的视角[J].中国人力资源开发,2025,42(12):83-96.DOI:10.16471/j.cnki.11-2822/c.2025.12.006.
基金信息:
成都市软科学项目（2025-RK00-00158-ZF）; 四川省教育规划重点项目（SCJG25B013）
2025-12-15
2025-12-15