TY - GEN
T1 - Leadership in the Digital Age
T2 - 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024
AU - Ling, Xiao
AU - Lo, Ying Tuan
AU - Wu, Tong
AU - Thoo, Ai Chin
AU - He, Tong
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Leadership-team models are prevalent in various enterprises, and studies have demonstrated that leadership styles can significantly impact team members, thereby affecting team performance. In the field of organizational dynamics, the pivotal role of leadership in shaping the work environment, culture, vocational education, and ultimately employee performance cannot be overstated. The China Workforce Insight Report (2020) reaffirms the direct impact of leadership style on job performance, revealing that more than 65% of employees attribute their job performance directly to leadership style. This conceptual paper explores the influence of leadership style on job performance, specifically focusing on the mediating role of AI-enhanced training programs. By examining how AI-enhanced training influences the relationship between leadership behaviors and organizational outcomes, this study aims to elucidate the mechanisms through which leadership can drive performance improvements in the context of advanced technological interventions. The paper aims to explore theoretical mechanisms through which leadership can drive performance improvements in the context of advanced technological interventions.
AB - Leadership-team models are prevalent in various enterprises, and studies have demonstrated that leadership styles can significantly impact team members, thereby affecting team performance. In the field of organizational dynamics, the pivotal role of leadership in shaping the work environment, culture, vocational education, and ultimately employee performance cannot be overstated. The China Workforce Insight Report (2020) reaffirms the direct impact of leadership style on job performance, revealing that more than 65% of employees attribute their job performance directly to leadership style. This conceptual paper explores the influence of leadership style on job performance, specifically focusing on the mediating role of AI-enhanced training programs. By examining how AI-enhanced training influences the relationship between leadership behaviors and organizational outcomes, this study aims to elucidate the mechanisms through which leadership can drive performance improvements in the context of advanced technological interventions. The paper aims to explore theoretical mechanisms through which leadership can drive performance improvements in the context of advanced technological interventions.
KW - AI-enhanced Training
KW - Job Performance
KW - Leadership Styles
UR - http://www.scopus.com/inward/record.url?scp=105002725988&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-3949-6_14
DO - 10.1007/978-981-96-3949-6_14
M3 - Conference Proceeding
AN - SCOPUS:105002725988
SN - 9789819639489
T3 - Lecture Notes in Networks and Systems
SP - 191
EP - 197
BT - Selected Proceedings from the 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024 - Advances in Intelligent Manufacturing and Robotics
A2 - Chen, Wei
A2 - Ping Tan, Andrew Huey
A2 - Luo, Yang
A2 - Huang, Long
A2 - Zhu, Yuyi
A2 - PP Abdul Majeed, Anwar
A2 - Zhang, Fan
A2 - Yan, Yuyao
A2 - Liu, Chenguang
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 22 August 2024 through 23 August 2024
ER -