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題名 Human-robot collaboration: A multilevel and integrated leadership framework
作者 侯宗佑
Tsai, Chou-Yu;Marshall, Jason D.;Choudhury, Anwesha;Serban, Andra;Hou, YoYo Tsung-Yu;Jung, Malte F.;Dionne, Shelley D.;Yammarino, Francis J.
貢獻者 傳播學院
關鍵詞 Human-robot interaction; Human-robot collaboration; Robots as leaders and followers; Robots as partners; Levels of analysis
日期 2022-02
上傳時間 6-Jul-2026 10:16:42 (UTC+8)
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.
關聯 The Leadership Quarterly, Vol.33, No.1, Article:101594
資料類型 article
article
DOI https://doi.org/10.1016/j.leaqua.2021.101594
dc.contributor 傳播學院
dc.creator (作者) 侯宗佑
dc.creator (作者) Tsai, Chou-Yu;Marshall, Jason D.;Choudhury, Anwesha;Serban, Andra;Hou, YoYo Tsung-Yu;Jung, Malte F.;Dionne, Shelley D.;Yammarino, Francis J.
dc.date (日期) 2022-02
dc.date.accessioned 6-Jul-2026 10:16:42 (UTC+8)-
dc.date.available 6-Jul-2026 10:16:42 (UTC+8)-
dc.date.issued (上傳時間) 6-Jul-2026 10:16:42 (UTC+8)-
dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=183157-
dc.description.abstract (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.
dc.format.extent 108 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) The Leadership Quarterly, Vol.33, No.1, Article:101594
dc.subject (關鍵詞) Human-robot interaction; Human-robot collaboration; Robots as leaders and followers; Robots as partners; Levels of analysis
dc.title (題名) Human-robot collaboration: A multilevel and integrated leadership framework
dc.type (資料類型) article
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.leaqua.2021.101594
dc.doi.uri (DOI) https://doi.org/10.1016/j.leaqua.2021.101594