Multilayer network analysis of open innovation partnerships

Abstract

The success of open innovation (OI) partnerships depends on the careful management of diverse relational dynamics, including trust, knowledge-sharing, and problem-solving interactions. This study applies multilayer network analysis to examine the relational dynamics of three distinct OI partnerships in the food and agriculture sector. By analysing eight relationship layers, we examine how different types of interactions shape collaboration. The findings reveal that affect-based and cognition-based trust drive network cohesion and influence core-periphery community structures at different stages of innovation. Core communities, characterized by high multilayer participation and dense ties, rely on trust to enable complex, multi-dimensional interactions essential for ideation and execution. Peripheral communities, with less overlap in trust-related layers, play more transactional roles, emphasizing exploration and knowledge diversity. Tacit knowledge exchange is vital for addressing uncertainty, though it remains limited to specific relational contexts. These findings underscore the utility of multilayer network methods for understanding the intricate structures of OI partnerships and offer actionable strategies for fostering trust-based collaboration in innovation ecosystems.