AI Adoption Intensity and SME Innovation: A Configurational Perspective Based on Organizational Readiness and Learning Capability
DOI:
https://doi.org/10.63808/iod.v2i4.400Keywords:
AI adoption intensity, SMEs, Innovation performance, Organizational readiness, Organizational learning capabilityAbstract
This paper explores the configurations through which AI adoption intensity acts as a catalyst for innovation performance in SMEs. Based on configurational theory, a theoretical framework integrating AI adoption intensity, organizational readiness (IT infrastructure readiness, resource readiness, and culture readiness) and organizational learning capabilities (knowledge acquisition capability, knowledge integration and application capability) is developed. The findings of the fuzzy-set qualitative comparative analysis based on survey data collected from 196 SMEs in China indicate that none of the individual conditions is a necessary condition for achieving high levels of innovation performance. Three sufficient configurations are identified with a solution consistency score of 0.847 and a coverage score of 0.631. AI adoption intensity serves as a central condition in two configurations and a peripheral condition in one configuration, suggesting that its configurational role is context-dependent rather than uniform.
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