压力认知评价理论视角下算法控制对平台员工工作投入的影响

The Impact of Algorithmic Control on Work Engagement of Platform Workers from the Perspective of the Cognitive Appraisal Theory of Stress

摘要: 随着数字技术与零工经济的深度融合，算法控制已成为影响平台经济工作者工作模式的关键因素。本研究聚焦于网约车司机和外卖员，基于资源保存理论和压力认知评价理论实证考察了算法控制影响平台员工工作投入的作用机制及边界条件。基于220份来自平台工作者的问卷调查数据发现：算法控制正向影响工作投入，但该影响受员工挑战性或阻碍性认知评价的调节。挑战性认知评价能增强算法控制的积极影响，而阻碍性认知评价可能导致工作投入降低。本研究发现有助于学界辩证地认识算法控制这一新兴管理技术，为平台企业科学地应用算法系统，以及构建和谐劳动关系和保障劳动者合法权益提供实践启示。

Abstract: With the deep integration of digital technology and the gig economy, algorithmic control has become a key factor shaping the work patterns of platform workers. Focusing on ride‑hailing drivers and food delivery riders, this study empirically examines the mechanism and boundary conditions through which algorithmic control influences platform employees’ work engagement, based on Conservation of Resources Theory and Transactional Theory of Stress and Coping. Using survey data from 220 platform workers, the results show that algorithmic control positively predicts work engagement, yet this effect is moderated by employees’ cognitive appraisals of challenge or hindrance. Challenge appraisals strengthen the positive impact of algorithmic control, whereas hindrance appraisals may reduce work engagement. These findings contribute to a dialectical understanding of algorithmic control as an emerging management technology, and provide practical implications for platform enterprises to rationally apply algorithmic systems, build harmonious labor relations, and protect workers’ legitimate rights and interests.