AI薪酬制定对求职者满意度的影响研究

Study on the Impact of AI-Based Compensation Design on Job Applicant Satisfaction

摘要: 随着人工智能(AI)技术在人力资源管理领域的不断应用，AI参与薪酬制定逐渐成为企业提升管理效率的重要方式。然而，算法决策的复杂性和不透明性也使求职者对其公平性产生关注。基于组织公平理论，以AI薪酬制定为研究情境，探讨内容设计合理性和过程设计透明性对求职者满意度的影响机制，并考察公平感知的中介作用以及市场薪酬水平的调节作用。通过问卷调查收集数据，共获得128份有效样本，运用Stata 17.0进行实证分析。研究结果表明：AI薪酬制定的内容设计合理性和过程设计透明性均能够显著提升求职者的公平感知；公平感知能够显著提高求职者满意度，并在内容设计合理性、过程设计透明性影响满意度的过程中发挥中介作用；市场薪酬水平对公平感知与满意度之间的关系具有显著调节效应。进一步分析发现，相较于内容设计合理性，过程设计透明性对求职者满意度的影响更为突出。研究表明，企业在推进AI薪酬管理实践过程中，应兼顾薪酬方案设计的合理性与决策过程的透明性，通过加强信息沟通和决策解释提升求职者的公平感知与满意度。研究结论可为企业优化AI薪酬管理实践提供参考。

Abstract: With the increasing application of artificial intelligence (AI) technology in human resource management, AI-involved compensation design has gradually become an important means for enterprises to improve management efficiency. However, the complexity and opacity of algorithmic decision-making have also raised job applicants’ concerns about its fairness. Based on organizational justice theory, this study takes AI-based compensation design as the research context to explore the mechanisms through which content design rationality and process design transparency affect job applicant satisfaction, while examining the mediating role of perceived fairness and the moderating role of market salary levels. Data were collected through questionnaire surveys, yielding 128 valid responses, and empirical analyses were conducted using Stata 17.0. The results indicate that both content design rationality and process design transparency of AI-based compensation significantly enhance job applicants’ perceived fairness; perceived fairness significantly improves job applicant satisfaction and mediates the effects of both content design rationality and process design transparency on satisfaction; market salary level significantly moderates the relationship between perceived fairness and satisfaction. Further analysis reveals that, compared with content design rationality, process design transparency exerts a more pronounced impact on job applicant satisfaction. The findings suggest that, in advancing AI-based compensation management practices, enterprises should balance the rationality of compensation scheme design with the transparency of decision-making processes, enhancing job applicants’ perceived fairness and satisfaction through improved information communication and decision explanation. These conclusions provide practical implications for enterprises seeking to optimize AI-based compensation management practices.