The Impact Mechanisms of Virtual Meeting Interruptions on Employee Engagement and Voice - Baesd on A Hybrid Framework: Combine SEM and Machine Learning
Year: 2025
Type: conference-paper
Abstract: When contrasted with traditional face-to-face meetings, virtual meetings are more prone to being interrupted by external distractions or unplanned interactions. It has been demonstrated that such interruptions have a negative impact on the efficacy of virtual cooperation. Considering the growing prevalence of virtual meetings, it is both theoretically significant and practically relevant to examine how interruptions influence employee engagement voice. This study takes the perspective of interruptions under virtual meetings scenarios and proposes a model illustrating the virtual meeting interruptions mechanism. As for methodology, it utilizes the random forest model along with SHAP to explain the findings. This hybrid approach integrates the SHAP model with machine learning algorithms to identify linear and nonlinear patterns.
Authors: Junzhu Wang, Jiafei Jin, Jialiang Xu, Nan Zhang
Institution: Harbin Institute of Technology
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4412887537