Generative Artificial Intelligence Adoption in E-Commerce SMEs: A Technology–Organization–Environment Perspective on Innovation and Firm Performance

Abstract

Today, small and medium sized enterprises (SMEs) selling online are increasingly using Generative Artificial Intelligence (GenAI) tools such as large language models and image generators in their daily operations. However, few studies have focused on understanding factors that drive e-commerce SMEs to implement these tools and whether or not adoption is associated with greater innovation and firm performance. The study proposes and tests a model in which technological (relative advantage, compatibility, complexity), organizational (top management support, readiness of the organization, employee digital skills) and environmental (competitive pressure, customer expectations, regulatory and infrastructure support) factors influence the way GenAI is adopted, which ultimately results in higher innovation performance and firm performance. The data collected from the owner-managers and the senior staffs of e-commerce SMEs were analysed using partial least squares structural equation modelling (PLS-SEM) and the data were collected by using a structured questionnaire. The results presented illustrate the importance of relative advantage, top management support and readiness and competitive pressure in adoption, the strong relationship between adoption and innovation performance, and the partial mediation of the adoption-firm performance relationship. The study adds to the TOE theory by applying it to the context of generative AI and provides actionable advice for SME owners and policy makers.