关键词: 零工工作者, 顾客不当行为, 算法管理, 压力应对, 人工智能干预

Abstract: With the widespread application of algorithmic management in the gig economy, the labor process of gig workers has become increasingly embedded in digital contexts shaped by platform rules and customer evaluations. Consequently, the impact of customer mistreatment on workers' psychology and behavior has become increasingly prominent. However, existing research primarily examines gig workers' stress and behavioral consequences through the lens of algorithmic control, leaving a systemic gap in understanding the mechanisms by which algorithms reshape work contexts by empowering customers.Drawing upon cognitive appraisal theory, this study constructs an integrated analytical framework to address the challenges gig workers face when coping with customer misbehavior in algorithmic contexts. It systematically responds to three progressive research questions: First, it analyzes how algorithmic management reshapes the manifestations of customer misbehavior and develops a measurement scale tailored to the gig context, providing a foundation for subsequent analyses of cognitive appraisal and coping mechanisms. Second, from a perspective of long-term stress accumulation, it examines the impact of customer misbehavior on gig workers' job burnout, employability, and turnover intentions. This section reveals the mediating roles of deep acting and surface acting, while investigating the moderating effects of personal, platform, and social resources as boundary conditions. Third, the study proposes a research design for AI-mediated responsive forgiveness interventions, exploring potential pathways to facilitate cognitive adjustment and emotional recovery for gig workers to buffer the negative impacts of customer mistreatment.This research not only deepens the application of customer misbehavior and stress-coping theories within emerging business models but also provides significant theoretical insights and empirical evidence for "human-centered" platform governance and the technological empowerment of laborers.

Key words: Gig workers, Customer mistreatment, Algorithmic management, Stress coping, Artificial intelligence intervention