Mobile Platforms as the Alleged Culprit for Work–Life Imbalance: A Data-Driven Method Using Co-Occurrence Network and Explainable AI Framework

The digital transformation of organizations has propelled the widespread adoption of mobile platforms. Extended availability and prolonged engagement with platform-mediated work have blurred boundaries, making it increasingly difficult for individuals to balance work and life. Criticism of mobile platforms has intensified, precluding digital transformation towards a sustainable future. This study examines the complex relationship between mobile platforms and work–life imbalance using a comprehensive data-driven methodology. We employed a co-occurrence network technique to extract relevant features based on previous findings. Subsequently, we applied an explainable AI framework to analyze the nonlinear relationships underlying technology-induced work–life imbalance and to detect behavior patterns. Our results indicate that there is a threshold for the beneficial effects of availability demands on integration behavior. Beyond this tolerance range, no further positive increase can be observed. For organizations aiming to either constrain or foster employees’ integration behavior, our findings provide tailored strategies to meet different needs. By extending the application of advanced machine learning algorithms to predict integration behaviors, this study offers nuanced insights that counter the alleged issue of technology-induced imbalance. This, in turn, promotes the sustainable success of digital transformation initiatives. This study has significant theoretical and practical implications for organizational digital transformation.