A comparative study on human or AI delivering negative performance feedback influencing employees’ motivation to improve performance

doi:10.3724/SP.J.1041.2025.0298

Abstract

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

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.

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