The Impact of Food Delivery Riders’ Perception of Fairness on Organizational Identification in the Digital Economy: Based on the Intermediary Perspective of Organizational Trust in the Context of Digital Technology

With the rapid rise in the gig economy driven by advancements in digital technology and financial technology, this study focuses on the work experiences and psychological perceptions of food delivery riders in platform-based employment. This study used a sample of food delivery riders from 19 cities in China (such as Shanghai, Beijing, Guangzhou, etc.) and multiple delivery platforms (such as Meituan, Ele.me) to collect data through a combination of online and offline questionnaires. The impact relationship between perceived fairness, organizational trust, and organizational identity of food delivery riders was examined through factor analysis, structural equation modeling, and mediation effect modeling. The results of the survey and statistical analysis indicate that fairness perception and its dimensions (distributive fairness, procedural fairness, and interactional fairness) significantly influence riders’ organizational identification, with organizational trust serving as a critical mediating factor. The integration of digital technology has substantially enhanced the operational efficiency of platform-based employment by enabling real-time tracking, transparent communication, and data-driven decision-making. Innovations in financial technology, such as digital payment systems and financial management tools, offer riders safer and more convenient compensation methods, thereby contributing to their financial stability and fostering trust in the platform. The establishment of trust alleviates the riders’ concerns regarding compensation stability and bolsters their optimistic attitudes toward accessing platform resources and meeting their needs. This study provides significant insights and recommendations for leveraging digital technology and financial technology to improve the relationship and operational efficiency between riders and platform enterprises.