To adopt artificial intelligence (AI) technology or not has become crucial for e-commerce SMEs seeking to enhance their marketing capabilities and competitive advantages in the increasingly digitalized business arena. This study aims to elucidate how organizational and individual determinants converge to influence AI adoption within e-commerce SMEs, and subsequently, how this adoption process orchestrates multi-dimensional marketing agility.
Integrating technology acceptance model (TAM) and dynamic capabilities theory (DCT), we developed a multi-level framework examining the relationships between adoption antecedents, usage behavior and strategic outcomes. Using data collected from 317 marketing managers in Chinese e-commerce SMEs, we leveraged a dual-stage analytical approach, combining PLS-SEM (partial least squares structural equation modeling) and artificial neural networks (ANN) analysis, to test our theoretical framework and reveal linear and non-linear relationships that may be obscured by traditional methods. Marketing agility was operationalized as a second-order construct comprising four dimensions and all measurement scales were adapted from established literature.
The results reveal that technology readiness and organizational support play dominant roles in shaping AI adoption intentions, while the impact of perceived usefulness and ease of use is relatively smaller. Furthermore, AI integration is demonstrated to be critical driver for our marketing agility construct. This study demonstrates the joint influencing mechanism of organizational and individual factors, providing empirical evidence to engage with the micro-foundations debates within the theoretical framework of dynamic capabilities. In practice, it provides an actionable roadmap for SMEs to transform AI potential into tangible marketing capabilities.
Upon the investigation, our contribution lies in empirically testing how individual psychological acceptance scales into organizational strategic agility, providing a non-linear and micro-foundational perspective that best reconciles TAM and DCT for the AI-driven marketing landscape of SMEs. Unlike traditional adoption models that focus solely on the “if” and “when” questions of technology use, this study reveals the “how” roadmap of strategic transformation.
