Influence of robots’ leadership styles on the job performance of human subordinates in human–robot teams

Purpose With the development of artificial intelligence technology, robots are playing an increasingly significant role in teams or organizations, and humanrobot hybrid collaborative teams are expected to become an important component of future workplaces. As with human leaders, robot leaders exhibiting different leadership styles—specifically, transformational and transactional—may elicit varying responses from their human subordinates. The aim of this study was to investigate the effects of transactional and transformational robot leaders on the job satisfaction and job performance of human subordinates and to reveal the mediating role of trust in the robot leader. Design/methodology/approach The participants were randomly assigned to either a transformational or transactional leadership group. A participant, a fake participant played by an experimenter, and a transactional or transformational robot leader completed the task of selecting outstanding employees in a simulated workplace. The task lasted 15 min. Findings The participants reported greater trust in the robot leader, job satisfaction and job performance when interacting with transformational robot leaders than when interacting with transactional robot leaders. Practical implications The results are an important extension of human–robot team interaction theory and leadership theory, which can help to better clarify the interaction mechanism of human–robot teams and improve the human–robot collaboration environment and effectiveness by appropriately adjusting the robot leadership style. Moreover, the results provide a basis for improving human–robot team performance, employee efficiency and employee satisfaction, which is highly important for the construction and development of human–robot team organizations and the behavioral design of robots. Originality/value Robots’ leadership styles indirectly and significantly affect the job satisfaction and performance of human subordinates by affecting trust in the robot leader. Human subordinates’ job satisfaction positively and significantly affects their job performance.

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Publication Details

Journal
Leadership & Organization Development Journal
Published
2025-09-04
DOI
https://doi.org/10.1108/lodj-12-2023-0692
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

Influence of robots’ leadership styles on the job performance of human subordinates in human–robot teams

Na Chen, Xueyan Hu, Cheng-ling Wang, Jiajia Cao
Leadership & Organization Development Journal
AI in Service Interactions
article

Influence of robots’ leadership styles on the job performance of human subordinates in human–robot teams

Na Chen, Xueyan Hu, Cheng-ling Wang, Jiajia Cao
article en

Abstract

Purpose With the development of artificial intelligence technology, robots are playing an increasingly significant role in teams or organizations, and humanrobot hybrid collaborative teams are expected to become an important component of future workplaces. As with human leaders, robot leaders exhibiting different leadership styles—specifically, transformational and transactional—may elicit varying responses from their human subordinates. The aim of this study was to investigate the effects of transactional and transformational robot leaders on the job satisfaction and job performance of human subordinates and to reveal the mediating role of trust in the robot leader. Design/methodology/approach The participants were randomly assigned to either a transformational or transactional leadership group. A participant, a fake participant played by an experimenter, and a transactional or transformational robot leader completed the task of selecting outstanding employees in a simulated workplace. The task lasted 15 min. Findings The participants reported greater trust in the robot leader, job satisfaction and job performance when interacting with transformational robot leaders than when interacting with transactional robot leaders. Practical implications The results are an important extension of human–robot team interaction theory and leadership theory, which can help to better clarify the interaction mechanism of human–robot teams and improve the human–robot collaboration environment and effectiveness by appropriately adjusting the robot leadership style. Moreover, the results provide a basis for improving human–robot team performance, employee efficiency and employee satisfaction, which is highly important for the construction and development of human–robot team organizations and the behavioral design of robots. Originality/value Robots’ leadership styles indirectly and significantly affect the job satisfaction and performance of human subordinates by affecting trust in the robot leader. Human subordinates’ job satisfaction positively and significantly affects their job performance.

Leadership & Organization Development JournalVol. 46(6)
Beijing University of Chemical Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
AI in Service Interactions
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