负面绩效反馈下员工绩效改进动机的人机比较

doi:10.3724/SP.J.1041.2025.0298

摘要/Abstract

摘要：

负面绩效反馈对员工学习和绩效提升具有重要意义, 然而其往往难以被员工所接受。随着人工智能技术(artificial intelligence, AI)逐渐应用于组织情境中, 探索AI提供负面绩效反馈对员工行为及态度的影响成为重要议题。采用4个递进式实验探索了AI与人类管理者提供负面绩效反馈对个体绩效改进动机的差异化影响及机制。实验1~3采取经典的虚假反馈的策略, 发现相较于人类管理者, AI提供负面绩效反馈引发个体更高水平的绩效改进动机(实验1)。并且, 在客观任务中, AI (较人类管理者)提供负面绩效反馈引发个体更高水平的绩效改进动机; 而在主观任务中, 结果则相反(实验2)。此外, 个体对于负面绩效反馈的内部归因解释了上述关系发生的内在机制(实验3)。实验4则采用相对真实的负面绩效反馈情境, 重复了先前3个实验的研究发现。该研究对于组织为何以及何时应用AI提供负面绩效反馈提供了一定的启示。

关键词: 负面绩效反馈, 人工智能, 绩效改进动机, 内部归因, 任务类型

Abstract:

Given that negative performance feedback can evoke negative reactions from employees, delivering such feedback effectively has become a challenge for organizations. Driven by rapid innovations in science and technology, artificial intelligence (AI) is gradually being applied in organizational management. For instance, AI can monitor employees’ work behaviors in real time, diagnose and analyze the reasons for their poor performance, and provide them with suggestions for performance improvement. Based on attribution theory, this study examined the benefits that employees may gain when receiving negative performance feedback from AI than from human managers. This study also explored the moderating effect of task type (subjective vs. objective) as a boundary factor for the influence of feedback source on employees’ motivation to improve their performance. Previous research has shown that individuals often experience internal or external attribution after receiving negative performance feedback. Therefore, this study also proposed internal and external attributions as underlying mediating mechanisms.

To test the hypotheses, four experiments were conducted (N = 598) involving various kinds of performance feedback contexts in the workplace, including performance feedback for employees in call centers, training of new employees, employees in vocational ability competitions, and middle managers’ capacity of management. Two strategies were adopted to provide performance feedback for the participants. Specifically, experiments 1-3 used fake feedback to control the feedback content among the participants, while experiment 4 delivered relatively real negative feedback based on the participants’ actual performance to further test the results of experiments 1-3.

Experiment 1 involved 128 full-time employees and used a single-factor, two-level between-subjects design, and results showed that compared with those coming from human managers, negative performance feedback coming from AI led to a higher employee motivation to improve performance. Experiment 2 involved 160 employees and used a two-factor between-subjects design, and results highlighted the interactive effect of negative feedback source (human manager vs. AI) and task types on employees’ motivation to improve their performance. Specifically, in subjective tasks, negative performance feedback from human managers (relative to AI) resulted in a higher motivation to improve performance. However, the opposite case was observed in objective tasks. Experiment 3 involved 150 employees who received negative performance feedback through email, and results highlighted the mediating role of internal attributions in the relationship between negative feedback source and motivation to improve performance. Experiment 4 involved 160 employees and utilized relatively real negative performance feedback, and results were the same as those obtained in experiment 3.

This study offers four theoretical contributions. First, with the emergence of AI as a feedback source for organizations, results show that compared with feedback from human managers, negative performance feedback from AI led to a higher motivation among employees to improve their performance, thereby enriching traditional research on negative performance feedback. Second, task type can moderate the relationship between negative performance feedback source and employees’ motivation to improve performance, and this finding contributes to the expansion of the boundary effects of feedback source (AI or human managers). Third, this study generates insights into agile performance management in the digital intelligence era by demonstrating the advantages of AI in replacing human managers in delivering negative performance feedback. Fourth, this study underscores internal attribution as a potential mechanism, thus expanding the application of attribution theory in explaining individual motivation and behavior within the context of AI versus human managers in delivering negative performance feedback.

Key words: negative performance feedback, artificial intelligence, motivation to improve performance, internal and external attribution, task type

中图分类号:

B849: C93

王国轩, 龙立荣, 李绍龙, 孙芳, 望家晴, 黄世英子. (2025). 负面绩效反馈下员工绩效改进动机的人机比较. 心理学报, 57(2), 298-314.

WANG Guoxuan, LONG Lirong, LI Shaolong, SUN Fang, WANG Jiaqing, HUANG Shiyingzi. (2025). A comparative study on human or AI delivering negative performance feedback influencing employees’ motivation to improve performance. Acta Psychologica Sinica, 57(2), 298-314.

图/表 6

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指标设备类型	最大运行速度(马赫)	最大产量 (件/天)	最大负荷 (千克)	费用 (万元)	可靠性程度 (评估分值)	灵敏性程度 (评估分值)
A	2.0	1500	20000	5.5	5	9
B	2.5	2700	18000	6.5	3	5
C	1.8	2000	21000	4.5	7	7
D	2.2	1800	20000	5.0	5	5

指标设备类型	最大运行速度(马赫)	最大产量 (件/天)	最大负荷 (千克)	费用 (万元)	可靠性程度 (评估分值)	灵敏性程度 (评估分值)
A	2.0	1500	20000	5.5	5	9
B	2.5	2700	18000	6.5	3	5
C	1.8	2000	21000	4.5	7	7
D	2.2	1800	20000	5.0	5	5