Saving face: Leveraging artificial intelligence‐based negative feedback to enhance employee job performance

Jialiang Pei; Hongli Wang; Qiuping Peng; Shanshi Liu

doi:10.1002/hrm.22226

Saving face: Leveraging artificial intelligence‐based negative feedback to enhance employee job performance

Jialiang Pei¹; Hongli Wang¹; Qiuping Peng²; Shanshi Liu¹

¹ School of Business Administration South China University of Technology Guangzhou Guangdong Province China · ² College of Economics and Management South China Agricultural University Guangzhou Guangdong Province China

Human Resource Management 2024

AbstractNegative performance feedback is vital for stimulating employees to enhance their performance despite resulting in stress and adverse work outcomes. Fortunately, artificial intelligence (AI)‐enabled automated agents have gradually assumed certain functions led by human leaders, such as providing feedback. Drawing from regulatory focus theory, we propose that AI‐based feedback systems can serve as a “remediation” tool, effectively mitigating employees' apprehensions about receiving negative feedback. In two studies, we found that for employees who fear losing face, AI‐based negative feedback motivates promotion‐focused cognition—motivation to learn—representing a learning mechanism to promote job performance and impedes their prevention‐focused cognition—interpersonal rumination—reducing the depletion needed for job performance. These findings present novel perspectives on using AI in performance feedback.

DOI: 10.1002/hrm.22226
Volume: 63 (5)
Pages: 775-790
Language: en
Export: BibTeX
Sources: crossref