Marta F. Arroyabe, Carlos F.A. Arranz
This study examines how environmental sustainability, social sustainability, and artificial intelligence (AI) interact to foster social innovation in small and medium-sized enterprises (SMEs). Drawing on Resource-Based Theory (RBT) and Institutional Theory, it explores how internal resources, and external pressures jointly shape social innovation outcomes. Using a large dataset of more than 12,000 European SMEs, the study investigates the individual and combined effects of these practices. The findings reveal differential impacts among the three drivers. Social sustainability emerges as the most significant predictor of social innovation, highlighting its central role in generating social value and promoting equity and inclusion. Environmental sustainability also exerts a positive influence, contributing to the development of innovations that address both ecological and social challenges. In contrast, AI plays a more indirect role by enhancing efficiency, resource optimisation, and the implementation of sustainability strategies. Theoretically, the study advances understanding of social innovation in SMEs by integrating internal (RBT) and external (institutional theory) perspectives. It shows that innovation arises from the alignment of firm capabilities with institutional expectations. Practically, it offers guidance for SMEs and policymakers on how to integrate AI and sustainability to improve competitiveness while contributing to societal well-being.