부산대학교 도서관

Data-driven technologies can have a broad impact on innovation management. In the present digital era, it has become a complex and debatable topic that requires refinement from a research perspective. Along this line, this study aims to understand how digital orientation facilitates the adoption of digital technologies to improve innovation performance. Using organizational learning theory and dynamic capability theory within a situation–actor–process and learning–action–performance framework, the study systematically captures and analyses the complexities and interactions among the factors affecting data-driven innovation in a case organization. It also highlights contingent variables that influence the relationship between data-driven insights produced by digital technologies and innovation performance. After case analysis, the study develops propositions and offers a conceptual model. Practitioners can use findings to develop a digital orientation for facilitating technology adoption and innovation management.