Twenty years after the introduction of the Open Innovation (OI) paradigm, it is time to “go beyond the hype and get down to business” (Chesbrough, 2019). OI has long been defined as the paradigm assuming that “firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology” (Chesbrough, 2003). An underlying premise is that OI creates shared value through mutually advantageous relationships, wherein all partners benefit in terms of both value creation and appropriation (Chesbrough et al., 2018).

However, after two decades of extensive research, the time has come to explore how OI is actually organized, managed, and measured in practice. What does openness mean for today’s R&D functions? How do firms and institutions embed openness into their processes, empower their people, and assess performance outcomes? How can OI be implemented and scaled within organizations facing digital transformation, sustainability transitions, and geopolitical uncertainty?

This track calls for contributions that delve into the real-world dynamics of OI in R&D and innovation management. We invite both early and senior researchers to deepen our understanding of how openness is translated into managerial routines, collaborative architectures, and performance systems. By doing so, this track directly connects to the Special Issue of R&D Management — “Open Innovation in R&D: Processes, People, and Performance” — which examines how OI reshapes R&D processes, human capabilities, and performance evaluation systems.

We particularly welcome phenomenon-based and practice-oriented studies that explore how organizations and ecosystems design, govern, and evaluate OI initiatives across industries and institutional settings. Topics of interest include, but are not limited to:

Processes
• Strategic and organizational mechanisms for implementing OI in R&D.
• Emerging models such as venture building, venture clienting, and start-up studios.
• Governance, orchestration, and coordination of open R&D collaborations.
• Tools and platforms for technology foresight, roadmapping, and knowledge integration.

People
• The microfoundations of OI capabilities and boundary-spanning roles.
• Leadership, culture, and incentive systems fostering openness in R&D.
• Skills, mindsets, and learning mechanisms enabling effective collaboration.
• The role of digitalization and AI in shaping collaboration and creativity.

Performance
• Metrics and evaluation systems for assessing OI impact at project, portfolio, and ecosystem levels.
• Methods to capture learning, speed, partner contributions, and network value creation.
• Integrative frameworks linking performance measurement with strategic decision-making.