Post-pandemic job market: an analysis of factors influencing university students’ willingness for flexible employment based on SEM-ANN-fsQCA - Quanling Cai; Weidong Chen; Mingxing Wang; Kaisheng Di (Humanities & Social Sciences Communications)
Abstract The COVID-19 pandemic has reshaped global work patterns, making flexible employment a critical issue. This study investigates how self-determination efficacy influences university students’ willingness to pursue flexible jobs in China. Using data from 1270 survey responses, we applied Partial Least Squares Structural Equation Modeling (PLS-SEM), Artificial Neural Networks (ANN), and Fuzzy-Set Qualitative Comparative Analysis (fsQCA). The results show that self-determination efficacy positively affects students’ willingness to pursue flexible employment directly and indirectly through mediating factors like work-life balance, job satisfaction, and perceived self-development. The ANN model reveals complex nonlinear relationships, indicating that the impact of self-determination efficacy on employment intention is not linear. Furthermore, fsQCA identifies multiple pathways under different conditions, highlighting the importance of self-determination efficacy in specific contexts. This research provides valuable insights for policymakers and higher education institutions on promoting flexible employment among students.