Algorithmic Platform Management and Risk-Taking Behavior among Chinese Food Delivery Riders

1. Research Overview
This dataset explores how algorithmic platform management shapes food delivery riders’ risk-taking behavior (e.g., traffic violations). Based on Cognitive Appraisal (CAT) and Persistent Cognition Theories (PCT), we proposed a dual-path model: algorithmic management influences behavior via an "online" path (Perceived Algorithmic Control during work) and an "offline" path (post-work Work Rumination), with Self-Control Resource Depletion (risk factor) and Learning Agility (protective factor) as boundary conditions.
2. Key Findings
Data supports the dual-path model, revealing a double-edged sword effect:
Algorithmic management increases risk-taking via Perceived Algorithmic Control and Emotional Rumination, but reduces it via Problem-Solving Contemplation.
Riders’ risk-taking is "silent compliance," driven by both active reward pursuit and passive penalty avoidance.
Self-Control Resource Depletion amplifies Perceived Algorithmic Control’s negative impact; Learning Agility mitigates the effects of Perceived Algorithmic Control and Emotional Rumination.
3. Data Interpretation
Algorithmic management’s influence extends beyond work hours via offline cognition. Behavioral outcomes are co-determined by algorithmic pressure, individual cognitive resources, and adaptive capabilities. Enhancing rider safety requires algorithm optimization (e.g., flexible time buffers) and programs to boost Learning Agility.
4. Data Collection
Source: Two-wave matched questionnaire survey of food delivery riders (Meituan, Ele.me, etc.) in Changsha, China.
Timeframe: T1 (Apr-May 2024), T2 (3 weeks post-T1).
Sample: 320 valid matched responses (full-time/part-time riders).
Design: Multi-wave offline collection (via station managers, field visits) to reduce common method bias.
5. Data Usage
Variables: Constructs (APM, PAC, ER, PSC, RTB, etc.) measured with adapted 6-point Likert scales.
Application: Ideal for gig economy, algorithmic management, occupational safety, and work psychology research (verification, secondary analysis, methodological reference).