Impact of generative AI and green process innovation on sustainable supply chain performance in Saudi Arabian industrial SMEs

Abstract Saudi-based manufacturing companies are under pressure to improve operational efficiency and environmental sustainability. This paper examines the associations between generative artificial intelligence (GAI) and sustainable supply chain performance (SSCP) in Saudi small and medium-sized enterprises (SMEs), with green process innovation (GPI) as the mediating variable and technological competence (TC) as the moderating variable. A quantitative methodology was applied, with data gathered through a survey of 347 senior managers from 50 manufacturing companies that actively used GAI. Data analysis was conducted using partial least squares structural equation modeling (PLS-SEM). The findings indicate that GAI is significantly associated with SSCP, both directly and indirectly, through its positive relationship with GPI. Moreover, TC shows a direct positive relationship with SSCP but moderates the association between GAI and SSCP negatively, suggesting it may be difficult to integrate at high levels of capability. The results are added to the literature on sustainable manufacturing because they outline the delicate positions of AI-based innovation and technological readiness. The study reiterates that achieving successful digital transformation towards sustainability requires adopting GAI and strategically aligning it with existing organizational capabilities.