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

Muhammad Faraz Mubarak,G. Jucevičius,R. Evans,M. Petraite,Masood Fathi

Published 2025 in SAGE Open

ABSTRACT

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. Plain Language Summary Understanding how Key Factors Work Together in Collaborative Innovation: A New Approach to Mapping Innovation Drivers Collaborative innovation is essential for companies to stay competitive, but understanding how the various factors that drive innovation interact is not well-explored. This study aims to fill that gap by identifying and analyzing the key factors behind collaborative innovation and how they influence each other. Through a review of existing research, 34 factors were identified, and experts from academia and industry helped select the most relevant ones for further study. The study used a technique called DEMATEL to map out how these factors are connected. The results show that factors like trust, innovation culture, and organizational learning are the most influential drivers of innovation. On the other hand, factors such as knowledge creation and technological learning are more like outcomes that result from these drivers. Other factors like market dynamics and governance play a balanced role, while innovation capabilities act as both drivers and outcomes, forming a central part of the innovation process. The study creates a visual map, called a Network Relationship Map (NRM), which shows how all these factors work together. This map serves as a guide for managing collaborative innovation, helping businesses and networks understand the connections between innovation drivers and outcomes. The findings offer valuable insights for companies looking to improve their innovation efforts. The study also suggests future research should explore how these relationships change over time and how new technologies impact collaborative innovation.

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