Linking Digital Orientation and Data-Driven Innovations: A SAP-LAP Linkage Framework and Research Propositions

• Published in: IEEE transactions on engineering management Vol. 71; pp. 1346 - 1358
• Main Authors: Mishra, Ruchi, Singh, Rajesh Kr, Papadopoulos, Thanos
• Format: Journal Article
• Language: English
• Published: New York IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; Big Data; Data models; Data-driven innovation; digital orientation; Digital systems; digital technologies; Digital technology; dynamic capability; Innovation management; Innovations; Internet of Things; Interviews; Learning systems; Learning theory; Manufacturing; Organizational learning; Orientation; Technological change; Uncertainty
• ISSN: 0018-9391; 1558-0040
• DOI: 10.1109/TEM.2022.3153588

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.