A MULTI-THEORETICAL ANALYSIS OF AI-RELATED CAPABILITIES AND NON-FINANCIAL PERFORMANCE IN CHINESE E-COMMERCE SMES: EVIDENCE FROM SICHUAN PROVINCE

This study examines how five AI-related capability domains—AI technological advantage, AI organizational infrastructure, environmental pressure, AI innovation capability, and AI market responsiveness—shape the non-financial performance of e-commerce small and medium-sized enterprises (SMEs) in Sichuan Province, China. Integrating the Technology–Organization–Environment (TOE) framework with Dynamic Capabilities Theory, the study argues that structural readiness and adaptive capabilities jointly determine whether AI use translates into customer-facing and market-facing outcomes beyond financial metrics. We further propose government policy support as a contextual moderator capturing within-province heterogeneity in access to digital infrastructure, training, and innovation platforms. The paper develops a parsimonious hypothesis model, details construct operationalization, and specifies an empirical strategy using survey data and partial least squares structural equation modeling (PLS-SEM) with robustness checks via OLS regression and subgroup comparisons. Non-financial performance is operationalized through customer satisfaction, brand value and reputation, market adaptability, and platform visibility. The study contributes a capability-oriented account of inclusive, policy-sensitive digital transformation among resource-constrained inland SMEs and provides a results-reporting template aligned with Scopus-indexed journal expectations.