To enhance the quality and efficiency of information processing and decision-making, automation based on artificial intelligence and machine learning has increasingly been used to support managerial tasks and duties. In contrast to classical applications of automation (e.g., within production or aviation), little is known about how the implementation of automation for management changes managerial work. In a work design frame, this study investigates how different versions of automated decision support systems for personnel selection as a specific management task affect decision task performance, time to reach a decision, reactions to the task (e.g., enjoyment), and self-efficacy in personnel selection. In a laboratory experiment, participants (N = 122) were randomly assigned to three groups and performed five rounds of a personnel selection task. The first group received a ranking of the applicants by an automated support system before participants processed applicant information (support-before-processing group), the second group received a ranking after they processed applicant information (support-after-processing group), and the third group received no ranking (no-support group). Results showed that satisfaction with the decision was higher for the support-after-processing group. Furthermore, participants in this group showed a steeper increase in self-efficacy in personnel selection compared to the other groups. This study combines human factors, management, and industrial/organizational psychology literature and goes beyond discussions concerning effectiveness and efficiency in the emerging area of automation in management in an attempt to stimulate research on potential effects of automation on managers’ job satisfaction and well-being at work.

为了提高信息处理和决策的质量和效率，基于人工智能和机器学习的自动化越来越多地用于支持管理任务和职责。与自动化的经典应用（例如，在生产或航空领域）相比，人们对管理自动化的实施如何改变管理工作知之甚少。在工作设计框架中，本研究调查了不同版本的自动决策支持系统如何将人员选择作为一项特定的管理任务影响决策任务绩效、做出决定的时间、对任务的反应（例如，享受）和自我效能在人员选拔上。在实验室实验中，参与者（N = 122) 被随机分配到三组并执行五轮人员选拔任务。第一组在参与者处理申请人信息之前通过自动支持系统对申请人进行排名（处理前支持组），第二组在之后获得排名他们处理了申请人信息（支持后处理组），第三组没有排名（无支持组）。结果表明，处理后支持组对决策的满意度更高。此外，与其他组相比，该组的参与者在人员选择方面的自我效能感显着提高。本研究结合了人为因素、管理和工业/组织心理学文献，并超越了关于新兴管理自动化领域有效性和效率的讨论，试图激发对自动化对管理者工作满意度和幸福感的潜在影响的研究在上班。