@Article{jpa.2025.067238,
AUTHOR = {Yungui Guo, Xuan Fan},
TITLE = {Leaders’ artificial intelligence symbolization behavior and enterprise digital transformation: Mediation by employees’ attitude towards digital transformation, and moderation of learning orientation},
JOURNAL = {Journal of Psychology in Africa},
VOLUME = {35},
YEAR = {2025},
NUMBER = {6},
PAGES = {791--796},
URL = {http://www.techscience.com/jpa/v35n6/65157},
ISSN = {1815-5626},
ABSTRACT = {This study examined the moderating role of employees’ learning orientation on the relationship between leaders’ artificial intelligence symbolization behavior (LAISB), employees’ attitude towards digital transformation (ATDT), and enterprise digital transformation. The sample consisted of 261 employees from five enterprises in China (female = 34.5%; primary industry includes the internet and transportation; mean age = 42.51 years, SD = 8.63 years; bachelor’s degree or above = 72.8%). The results of structural equation modeling and simple slope test indicated that LAISB predicted higher enterprise digital transformation, with ATDT partial mediation. Furthermore, employees’ learning orientation weakened the relationship between LAISB and ATDT, as well as the indirect effect of LAISB on enterprise digital transformation through ATDT. This study contributes to social cognitive theory and the digital transformation literature by integrating leaders behavior, employee attitudes, and individual differences into a coherent framework explaining digital transformation mechanisms. The findings imply that enterprises should prioritize leadership training in AI symbolism to facilitate successful digital transformation.},
DOI = {10.32604/jpa.2025.067238}
}