Human-robot collaboration: A multilevel and integrated leadership framework

概念化 机器人 知识管理 纪律 工程伦理学 滞后 管理科学 社会学 计算机科学 工程类 人工智能 社会科学 医学 病理
作者
Chou‐Yu Tsai,Jason Marshall,Anwesha Choudhury,Andra Serban,Yoyo Tsung-Yu Hou,Malte Jung,Shelley D. Dionne,Francis J. Yammarino
出处
期刊:Leadership Quarterly [Elsevier BV]
卷期号:33 (1): 101594-101594 被引量:60
标识
DOI:10.1016/j.leaqua.2021.101594
摘要

In an era of rapid advances in artificial intelligence, the deployment of robots in organizations is accelerating. Further, robotic capabilities are expanding to serve a broader range of leadership behaviors related to task accomplishment and relationship support. Despite the increasing use of robots in various roles across different industries, research on human-robot collaboration in the workplace is lagging behind. As such, the current research aims to provide a state-of-the-science review and directions for future work in this underdeveloped area. Drawing on current leadership paradigms, we review human-robot collaboration studies from four academic disciplines with a history of publishing such work (i.e., management, economics, psychology, engineering) and propose that the research trajectory of human-robot collaboration parallels the evolution of leadership research paradigms (i.e., leader centric, relational view, and follower centric). Given that leadership is an inherently multilevel phenomenon, we apply a levels-of-analysis framework to integrate and synthesize human-robot collaboration studies from cross-disciplinary research areas. Based on our findings, we offer suggestions for future research in terms of conceptualization, theory building and testing, practical implications, and ethical considerations.
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