摘要：随着社会步入数智经济时代，员工与组织间雇佣关系发生了巨大转变，如何构建和谐可持续的员工关系成为组织亟待解决的关键问题，因而与数字、智能、算法相结合的员工关系管理——数智型员工关系管理逐渐受到学界与业界的广泛关注。基于此，本研究旨在科学界定数智型员工关系管理的概念内涵与维度结构，开发相应测量工具，同时基于工作要求-资源模型和社会信息加工理论，探究数智型员工关系管理对员工算法公民行为的工作繁荣机制，同时考察数据向善的边界条件作用。针对315份多时点有效样本的实证研究发现：(1)数智型员工关系管理对算法公民行为有显著正向影响；(2)工作繁荣在数智型员工关系管理与算法公民行为间有显著中介作用；(3)数据向善正向调节数智型员工关系管理对工作繁荣的直接作用及其通过工作繁荣对算法公民行为的间接作用，数据向善水平越高，其直接与间接作用越强。本研究为数智经济时代企业员工关系管理改善提供理论依据与决策借鉴。

Abstract: As society enters the era of digital intelligent economy, the employment relationship between employees and organizations has undergone significant changes. How to build a harmonious and sustainable employee relationship has become a key issue that organizations urgently need to solve. Therefore, employee relationship management, which combines digital, intelligent, and algorithmic methods, has gradually received widespread attention from academia and the industry. Based on this, this study scientifically aims to define the conceptual connotation and dimensional structure of digital intelligent employee relationship management, develop corresponding measurement tools, and explore thriving at work mechanism of digital intelligent employee relationship management on employee algorithmic citizenship behavior according to the work requirement resource model and social information processing theory. At the same time, it examines the boundary condition effect of data for goodness. An empirical study of 315 valid samples from multiple-time points found the follows. Firstly, digital intelligent employee relationship management has a positive impact on algorithmic citizenship behavior. Secondly, thriving at work has a significant partial mediating effect between digital intelligent employee relationship management and algorithmic citizenship behavior. Thirdly, data for goodness positively regulates the direct impact of digital intelligent employee relationship management on thriving at work and its indirect impact on algorithmic citizenship behavior through thriving at work. The higher the level of data for goodness, the stronger its direct and indirect effects. This study provides theoretical basis and decision-making reference for improving employee relationship management in enterprises during the era of digital intelligent economy.