摘要：在数字化工作场所，员工-AI协作流畅性已经成为改进员工工作效果的重要因素。然而，既有研究尚未厘清员工-AI协作流畅性的概念，其结构和测量也尚不清晰，致使现阶段实证研究滞后。为此，本研究采用定性和定量相结合的方法以探究员工-AI协作流畅性的内涵及维度结构。首先，通过半结构化深度访谈获取样本数据，并基于扎根理论进行三阶段编码，归纳出员工-AI协作流畅性的核心范畴与结构维度。其次，依据编码结果开发测量量表，按照探索性因子分析和验证性因子分析程序，对量表的信度与效度进行检验。最后，采用问卷法收集样本数据，并根据资源保存理论进行了新开发量表的后效研究。研究结果表明：(1)员工-AI协作流畅性是一个包含可理解性(含透明度和可解释性)、可预测性(含意图预测和行为预测)、适应性(含自我调整和自我学习)、连续性(含跨平台衔接和记忆延续)和同步性(含实时协同和即时性)五个维度的多层次构念。(2)本文所开发的包含五个维度18个题项的测量量表具有良好的信效度。(3)对新开发量表的预测效度检验结果显示，员工-AI协作流畅性显著正向影响员工的身体健康和心理健康。本研究结论拓展并丰富了员工-AI协作流畅性的理论框架和概念内涵，为员工-AI协作流畅性的实证研究提供了有效的测量工具。此外，结论表明企业不仅应在技术层面重视人机协作流畅性的系统性优化，还应在管理层面建立常态化的协作流畅性评估机制，以进一步优化协作效果。

Abstract: In digital workplace, employee-AI collaboration fluency has become a critical factor in enhancing employee work effectiveness. However, existing research has yet to clarify the core connotations of employee-AI collaboration fluency, and its structural dimensions and measurement remain ambiguous, leading to a lag in empirical studies. To address this gap, this study first constructs a five-dimensional model of employee-AI collaboration fluency based on grounded theory, encompassing comprehensibility, predictability, adaptability, continuity, and synchronicity. Second, following exploratory factor analysis and confirmatory factor analysis procedures, we develop a validated scale to measure employee-AI collaboration fluency. Finally, drawing on the Conservation of Resources theory, this study conducts a consequential validation study demonstrating that employee-AI collaboration fluency significantly and positively impacts employees' physical and mental health. These findings expand and enrich the theoretical framework and conceptual boundaries of employee-AI collaboration fluency, provide an empirical measurement tool for future research, and offer practical insights for organizations to optimize employee-AI collaboration and safeguard employee health.