多重化和多任务化之间的契合如何塑造员工的自我领导力? 人工智能赋权任务处理的调节作用
Zhirui Zhou1, Shuting Xiang1, Qingxin Xie2
1School of International Business, Southwestern University of Finance and Economics, Chengdu, China.
Frontiers in artificial intelligence
|February 12, 2025
概括
当员工的多任务偏好与工作需求保持一致时,员工的自主领导力会勃发展,特别是在人工智能支持下. 多时间性和多任务性之间的一致性可以提高自我领导力,人工智能可以作为促进者或负担,具体取决于合适情况.
科学领域:
- 组织心理学 组织心理学
- 人与计算机的交互
- 工作场所的人工智能
背景情况:
- 人工智能集成需要了解员工自我领导动态.
- 多任务实践和人工智能支持相互作用,影响自我领导力.
- 个人工作偏好和任务需求之间的匹配对于组织的有效性至关重要.
研究的目的:
- 为了调查多任务和多重性之间的匹配如何影响员工的自我领导力与人工智能赋权.
- 检查工作中繁荣的调解作用和人工智能赋权任务处理的调节作用.
- 为实施人工智能工具和管理多任务的组织提供见解.
主要方法:
- 使用多项式回归,块变量分析和响应表面方法的两个时间滞后调查研究.
- 数据收集来自中国三家人工智能公司的204名员工,跨越多个时间点.
- 基于个人,任务和技术之间的合适 (FITT) 框架和JD-R理论模型.
主要成果:
- 多重性和多任务性之间的一致性显著预测了员工更大的自我领导力.
- 较高的一致度与更强的自我领导力相关; "高-低"不一致状态比"低-高"更有益.
- 人工智能赋权的任务处理调解了这种关系,为匹配的员工提供便利,为不匹配的员工提供负担.
结论:
- 将员工的工作偏好 (多重性) 与任务需求 (多任务) 结合起来,对于有效的AI集成和自我领导至关重要.
- 人工智能对自主领导力的影响取决于多重性-多任务性合适性,突出了对量身定制的实施策略的需求.
- 了解和优化这种适应可以提高组织效率和员工赋权在人工智能增强的工作场所.
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