Work–family conflict and motivation: the mediating role of perceived visionary leadership and insights from explainable machine learning

Introduction Drawing on Conservation of Resources (COR) and Self-Determination Theory (SDT), this study examines the relationships among work–family conflict (WFC), perceived visionary leadership (VL), employee age, and motivation, focusing on the mediating role of perceived VL and the direct and moderating role of employee age. Methods Using survey data from 232 employees across various sectors, we employed a hybrid explanatory–predictive quantitative framework combining Partial Least Squares Structural Equation Modeling (PLS-SEM) with six supervised machine learning (ML) algorithms (Ridge, Lasso, Random Forest, XGBoost, LightGBM, and CatBoost) and explainable ML techniques. Model generalizability was further assessed using repeated and nested cross-validation. Results PLS-SEM indicated that WFC was not directly associated with employee motivation, whereas a statistically significant indirect association emerged through perceived VL. Age was associated with motivation and moderated the relationship between WFC and motivation. The predictive analyses provided complementary rather than confirmatory evidence. Within the LightGBM explainability analyses, perceived VL emerged as the most influential predictor, while WFC and age also contributed to prediction. The explanatory and predictive analyses showed partial convergence, particularly regarding the prominence of perceived VL, while also revealing a nonlinear predictive pattern for WFC. Discussion The findings highlight the relevance of leadership and age to the WFC –motivation relationship and demonstrate how explanatory and predictive approaches can provide complementary insights into organizational behavior without being treated as mutually validating analytical frameworks.