Influence of robot leaders’ conflict management styles on work performance
Ning Chen & Mengwei Chen
Abstract
Purpose This study aims to investigate the impact of robot leaders’ conflict management styles on work performance, focusing on the mediating roles of leader evaluation and dyadic emotional climate. It aims to explore how cooperative versus competitive conflict management styles influence outcomes and whether leader type (robot vs human) moderates these effects. Design/methodology/approach A 2 (conflict management style: cooperative, competitive) × 2 (leader type: robot leader, human leader) experimental design was used. A total of 72 participants were recruited to complete the “Lunar Survival Task” in collaboration with either a robot or human leader. Findings Teams led by leaders with a cooperative conflict management style demonstrated superior performance compared to those with a competitive style. Leader evaluation and dyadic emotional climate were found to mediate the relationship between conflict management style and work performance, with evidence of a chain mediation effect. In addition, leader type moderated the effects of conflict management style on leader evaluation and dyadic emotional climate, highlighting distinct dynamics in human–robot collaboration. Originality/value To the best of the authors’ knowledge, this study is among the first to examine the role of robot leaders’ conflict management styles in work performance, emphasizing the importance of cooperative approaches in human–robot interaction. It provides novel insights into the mediating mechanisms of leader evaluation and dyadic emotional climate, as well as the moderating role of leader type. The findings offer theoretical support and practical guidance for optimizing human–robot collaboration in team settings.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.