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AI awareness and employee boundary-spanning behavior: a nonlinear mechanism
1Department of Human Resource Management, School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, China.
Abstract:
Drawing on conservation of resources theory, this study develops a nonlinear model of the association between AI awareness (AIA) and employee boundary-spanning behavior (BSB). It examines the mediating role of AI job crafting (AIC) and the joint moderating roles of AI help-seeking behavior (AIHSB) and leader AI job crafting (LAIC). Using two-wave time-lagged matched survey data from 501 employees of accounting firms, this study finds that: (1) AIA has strict U-shaped relationships with both BSB and AIC; (2) AIC exhibits a level-dependent nonlinear mediating pattern in the relationship between AIA and BSB; (3) AIHSB significantly moderates the U-shaped relationship between AIA and AIC, while LAIC further moderates this moderating effect. The conditional indirect effect varies jointly with AIA and the two moderators. This study advances research on AIA from divergent linear effects to a level-dependent nonlinear transition. It identifies the boundary conditions jointly created by individual access to AI resources and leader role modeling. The findings inform how organizations can help employees adapt to AI-driven change.
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