Bui Huy Nhuong, Dinh Duc Truong, Bui Huy Quang, Duong Duc Tam
This study aims to examine the factors influencing and moderating the level of supply chain digitalization (SCD) in SMEs in Vietnam, within the context of increasing global competition and market pressures. The study integrates three theoretical frameworks: the Technology-Organization-Environment (TOE) framework, Institutional Theory (IT), and Dynamic Capability Theory (DCT) to construct an empirical model. A quantitative approach is employed, utilizing a survey of 412 export SMEs to collect data. Structural Equation Modeling (SEM) is applied to analyze both direct and moderating relationships between 13 factors and SCD. Additionally, an SCD index is developed to measure SCD levels. Response Surface Plot Analysis (RSPA) is used to visualize the nonlinear interactions among Technology (T), Organization (O), Environment (E) factors, and Dynamic Capabilities (DC) in shaping SCD. The study identifies ten key factors directly influencing SCD, with three main factors, customer and partner pressure, financial capability, and innovation and learning capability, emerging as the most critical drivers. The research also reveals that DC moderate the relationships between TOE factors and SCD, indicating that the impact of technological, organizational, and environmental factors is strengthened or weakened depending on a firm’s DC. For businesses, it is recommended to enhance technological infrastructure, foster organizational readiness, and invest in digital technologies to improve supply chain digitalization. For policymakers, it is essential to provide financial incentives, regulatory support, and training programs to assist SMEs in improving their digital capabilities and ensuring inclusive digital transformation across sectors. This study contributes to understanding the factors influencing SCD by integrating theoretical frameworks such as TOE, IT, and DCT. The development of the SCD index and the application of RSPA offer a novel approach to analyzing the nonlinear relationships among key factors, providing valuable insights for both businesses and policymakers to promote effective digital supply chain management (SCM). JEL Classification: O33, D22, F23.