Junfeng Cheng, Shankar Chelliah
HRMARS - Purpose: This study critically examines how the Job Demands-Resources (JD-R) model explains innovative job performance (IJP) within the context of digital intelligent transformation. It aims to identify the generative mechanisms through which job demands and resources influence IJP and to clarify the mediating and moderating roles of job crafting and person-job fit (PJ fit). Design/methodology/approach: Drawing upon a systematic and critical review of 162 SSCI-indexed studies published between 2020 and 2025, this research synthesises findings using the dual-pathway logic of the JD-R model. Thematic coding and evaluative comparison were employed to ensure analytical coherence. Findings: (1) job demands exhibit a double-edged sword effect, constraining or stimulating innovation depending on employees' cognitive appraisals. (2) job resources, particularly digital literacy, digital leadership, and PJ fit, serve as primary drivers of IJP through motivational enhancement. (3) promotion and prevention-focused job crafting function as critical mediating pathways linking antecedents and outcomes. Research limitations/implications: The review is limited by language and time-frame constraints, suggesting future research employ meta-analytic and longitudinal methods to examine causal mechanisms across diverse contexts. Practical implications: The findings guide organisations in enhancing innovation by developing digital competencies, fostering empowering leadership, and optimising PJ fit. Originality/value: This study extends the JD-R model to innovation research, elucidating its dual-pathway mechanisms and boundary conditions within technology-intensive environments.