Navigating Interdependencies In Collaborative Innovation: A Data-Driven Dematel Framework

Collaborative innovation is vital for organisational competitiveness, yet the literature still offers an incomplete picture of how its numerous drivers interact. This study advances that understanding by consolidating 34 factors from a content-centric review of recent research and distilling them to eight core variables: market dynamics, knowledge creation and acquisition, technological learning, trust, innovation culture, organisational learning, innovation capabilities and governance. We engage a ten-member panel of academics and industry experts and employ the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method - an innovative multi-criteria decision-making approach - to quantify the causal structure among these factors. The resulting network relationship map shows that trust, innovation culture and organisational learning form the principal engine of collaborative innovation, exerting the strongest net positive influence on the system. Knowledge creation and technological learning surface mainly as outcomes of this relational engine, while market dynamics and governance assume balanced, context-sensitive positions. Innovation capability emerges as a hinge factor, receiving almost as much influence as it delivers, thereby converting relational gains into competitive advantage. By integrating DEMATEL with network visualisation, the study provides one of the first data-driven blueprints for managing the dynamics of collaborative and open innovation. The reference model guides managers in prioritising actions—cultivating trust, fostering an experimentation-friendly culture, institutionalising learning routines and aligning governance with environmental turbulence - across both firm and network levels. Future research should examine the temporal evolution of these interactions and explore how emerging technologies such as AI, digital twins and blockchain further reshape collaborative innovation ecosystems.