Business Model Innovation and Sustainable Entrepreneurship: Component-Level Evidence from Multi-Treatment Double/Debiased Machine Learning

Sustainable entrepreneurship depends on a firm’s ability to turn opportunities into durable systems of value creation, value proposition, and value capture. Prior studies link business model innovation (BMI) to firm performance, but the evidence is largely correlational and treats BMI as a single aggregate construct, leaving it unclear which component most directly converts business model change into sustainable innovation outcomes. Using firm-level data on 2798 Korean firms from the 2022 Entrepreneurship Survey, this study adopts a progressive empirical design that moves from ordinary least squares (OLS) to Double/Debiased Machine Learning (DML), and from aggregate BMI to a multi-treatment specification of its three components. The findings indicate that aggregate BMI shows a positive baseline association with innovation performance. When the three components are modeled jointly, value proposition emerges as the most consistently and strongly associated component of sales-based innovation performance, whereas value creation and value capture display weaker and more conditional patterns. The value proposition association is stronger in B2C firms. This study advances sustainable entrepreneurship research by identifying customer-facing value articulation as the BMI component most consistently associated with sustained innovation performance under observable-confounder adjustment.