AI Implementation and Business Model Innovation in Chinese SMEs: a Configurational Research Framework

Abstract

Artificial intelligence (AI) is increasingly regarded as a critical enabler of business model innovation (BMI) in small and medium-sized enterprises (SMEs). However, existing research predominantly examines the net effect of AI adoption on BMI, overlooking the complex interactions among technological, organizational, and environmental conditions. Drawing on the Technology–Organization–Environment (TOE) framework integrated with dynamic capabilities theory, this study develops a configurational research framework for investigating how AI implementation combines with organizational capabilities and environmental conditions to drive BMI in Chinese SMEs. The framework proposes four theoretically grounded pathways to high BMI: technology–organization synergy, environment-pulled innovation, market-driven AI integration, and capability-first substitution. These propositions demonstrate that AI implementation is neither necessary nor sufficient for BMI; its effectiveness depends on alignment with dynamic capabilities and environmental support. The framework contributes to the AI–BMI literature by advancing a configurational perspective and offers a foundation for future empirical investigation using fuzzy-set qualitative comparative analysis (fsQCA).