Purpose

Over the past decade, artificial intelligence (AI) technologies have rapidly advanced organizational management, with many organizations adopting AI-based algorithms to enhance employee management efficiency. However, there remains a lack of sufficient empirical research on the specific impacts of these algorithmic management practices on employee behavior, particularly the potential negative effects. To address this gap, this study constructs a model based on the psychological ownership theory, aiming to investigate how algorithmic management affects employees’ knowledge hiding.

Design/methodology/approach

This study validates the model through a situational experiment and a multi-wave field study involving full-time employees in organizations implementing algorithmic management. Various analytical methods, including analysis of variance, regression analysis and path analysis, were used to systematically test the hypotheses.

Findings

The study reveals that algorithmic management exerts a positive indirect influence on knowledge hiding through the psychological ownership of personal knowledge. This effect is particularly pronounced when employees have lower organizational identification, highlighting the critical role of organizational culture in the effectiveness of technological applications.

Originality/value

This study is among the first empirical investigations to explore the relationship between algorithmic management and employee knowledge hiding from an individual perception perspective. By applying psychological ownership theory, it not only addresses the current theoretical gap regarding the negative effects of algorithmic management but also provides new theoretical and empirical support for the governance and prevention of knowledge hiding within organizations in the context of AI algorithm application. The study highlights the importance of considering employee psychology (i.e. psychological ownership of personal knowledge) and organizational culture (i.e. organizational identification) under algorithmic management. This understanding aids organizations in better managing knowledge risks while maximizing technological advantages and effectively designing organizational change strategies.

中文翻译：

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算法管理的阴暗面：调查算法管理如何以及何时与员工知识隐藏相关？

 目的

在过去十年中，人工智能 （AI） 技术迅速推动了组织管理的发展，许多组织采用基于 AI 的算法来提高员工管理效率。然而，关于这些算法管理实践对员工行为的具体影响，特别是潜在的负面影响，仍然缺乏足够的实证研究。为了解决这一差距，本研究基于心理所有权理论构建了一个模型，旨在探讨算法管理如何影响员工的知识隐藏。

设计/方法/方法

本研究通过情景实验和涉及实施算法管理的组织中全职员工的多波现场研究验证了该模型。使用各种分析方法，包括方差分析、回归分析和路径分析，来系统地检验假设。

 发现

研究表明，算法管理通过个人知识的心理所有权对隐藏的知识产生积极的间接影响。当员工的组织认同感较低时，这种影响尤其明显，凸显了组织文化在技术应用有效性中的关键作用。

 原创性/价值

这项研究是最早的实证调查之一，旨在探索算法管理与从个人感知角度隐藏的员工知识之间的关系。通过应用心理所有权理论，它不仅解决了当前关于算法管理负面影响的理论差距，而且为 AI 算法应用背景下组织内部隐藏知识的治理和预防提供了新的理论和实证支持。该研究强调了在算法管理下考虑员工心理（即个人知识的心理所有权）和组织文化（即组织认同）的重要性。这种理解有助于组织更好地管理知识风险，同时最大限度地发挥技术优势并有效地设计组织变革战略。