Digital Transformation and Venture Performance: How Entrepreneurial Orientation Moderates AI-Driven Business Model Innovation in Resource-Constrained Environments

Abstract

The acceleration of digital transformation has emerged as one of the main strategies that new and small businesses are using to leverage artificial intelligence (AI) for a competitive edge. But resource poor ventures struggle to find the financial buffer, skill set, data system, and organisational habits to move beyond the adoption and into the long-term business model innovation (BMI). Based on the dynamic capabilities theory, the resource-based view, and entrepreneurial orientation theory, this study constructs and tests a moderated-mediation model, where AI-enabled BMI positively affects the performance of a venture, and EO further strengthens this link, while resource constraints weaken the link between AI and BMI. The study uses partial least squares structural equation modeling (PLS-SEM) analysis based on the time-lagged survey data of 312 technology-enabled ventures in emerging and developed markets. The findings reveal that AI for BMI has a positive impact on financial performance, customer performance, and innovation performance. EO enhances performance returns to AI-driven BMI to a significant degree, while resource limitations reduce the return on investing in AI to new value-creation architectures. The findings are extensions of previous research on digital transformation because they reveal that to gain performance benefits, digital transformation is not a prerequisite; it is related to the strategic entrepreneurial posture of the ventures. Implications for practice are sequencing investments in AI around experimentation, data preparation, and business model redesign.