Understanding the processes through which employees effectively share knowledge beyond their immediate groups is an important research issue. However, while transactive memory systems (TMS)—mechanisms that facilitate the efficient utilization of expertise—have been extensively studied within groups, their mechanisms and implications beyond group boundaries remain underexplored. This study defines the concept of TMS operating beyond group boundaries as “TMS outside the group” and analyzes the factors influencing it. The findings reveal that the use of enterprise social media facilitates TMS outside the group, while the perception of centralization acts as an inhibitory factor. Furthermore, under conditions of high uncertainty, strong TMS within the group tends to suppress TMS outside the group. This study offers theoretical contributions by examining the characteristics of both within-group and outside-group TMS and expanding the scope of TMS theory.

The purpose of this study is to analyze the factors influencing user behavior in the adoption of generative AI within enterprises. In particular, this study investigated how employees’ anxiety toward generative AI in Japanese firms affects their usage behavior. To this end, the research employed the conceptual framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) and conducted statistical analysis of survey data using partial least squares structural equation modeling (PLS-SEM) . The results revealed that performance expectancy, effort expectancy, and social influence significantly affect employees’ behavioral intention toward generative AI, thereby promoting their actual usage behavior. Furthermore, the interaction between employees’ anxiety and performance expectancy was found to have a negative moderating effect on behavioral intention, while the interaction between employees’ age and facilitating conditions exhibited a negative moderating effect.