Aybars Tuncdogan, King's College London

Henk W. Volberda, University of Amsterdam

Ioana Stefan, Mälardalen University

While innovation creation has received substantial research attention, value capture from innovations remains critically important yet increasingly complex. Digital technologies, AI, data-driven business models, and globally distributed R&D networks have expanded innovation reach but also created new vulnerabilities through rapid copying, disruption, and security threats. Organizations must now navigate both traditional appropriability challenges in collaborative and open innovation contexts, and emerging information security risks that threaten R&D artifacts and intellectual assets.

This special issue brings together two typically separate research conversations: innovation appropriability mechanisms (patents, trade secrecy, licensing, complementary assets, ecosystem governance) and information security protection (technical defenses, organizational safeguards, insider threat management). The issue seeks to understand how firms organize to balance value creation with value capture while managing information security risks in an increasingly digital, data-driven, and open innovation landscape.

Appel publié par R and D Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Appropriability mechanisms for digital innovation, including appropriability regimes in platforms, ecosystems, and data-driven markets
• Hybrid protection strategies combining secrecy, security, and openness
• New forms of protection for new forms of competitive advantage (static vs dynamic)
• Profiting from innovation under platform dominance
• Governance of data, IP, and secrecy in university-industry collaborations and open science initiatives
• Governance and lifecycle strategies for protecting data, algorithms, AI models, etc.
• Risks of imitation, leakage, and exfiltration in digital/AI-driven innovation
• Strategies and mechanisms to protect data, algorithms, and AI models
• Protection strategies for innovations that move faster than the ability to protect them
• Value capture in Industry 4.0 and smart manufacturing innovations
• Organizational designs and routines for secure collaboration
• Institutional and regulatory conditions shaping innovation security and value capture
• Closing and opening innovation in the digital era
• Insider threats to R&D knowledge
• Security-by-design and privacy-by-design principles in R&D and innovation processes
• Effective zero-trust policies in R&D departments and innovation processes

Timeline

• Invalid DateTime: Paper development workshop
• February 1, 2027: Submission window opens
• April 30, 2027: Full manuscript submission deadline

Laura Amo, University at Buffalo, State University of New York

Richard Baskerville, Georgia State University

Rui Chen, Iowa State University

Matthew Hashim, University of Arizona

Yaojie (William) Li, University of New Orleans

Yuan Li, University of Tennessee at Knoxville

As artificial intelligence increasingly dominates both offensive and defensive cybersecurity, this special issue emphasizes the critical importance of maintaining human involvement in security systems and decisions. The issue addresses concerns about AI-driven threats such as sophisticated phishing attacks, deepfakes, and behavioral data exploitation, while acknowledging that defensive reliance on AI-based threat detection creates cognitive challenges for practitioners.

Human-in-the-loop (HITL) is presented as a design principle that ensures human participation in system training, decision-making, and error mitigation, recognizing that fully automated security systems may be restrictive or dangerous. The special issue calls for behavioral information security research that balances AI's growing role with sustained focus on human behavior, cognition, and motivation in secure systems, training, and technologies.

Appel publié par Information Systems Frontiers. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Neurosecurity (NeuroIS) investigations of information security behavior
• Behavioral analyses of design science treatments enhancing or balancing security and privacy tradeoffs
• The behavioral intersection of cybersecurity/privacy research and AI/ML advancements
• AI-enabled security awareness, training, nudging, and behavioral intervention systems
• Human-AI collaboration in security decision-making, compliance, monitoring, and response
• Behavioral security implications of generative AI, including phishing, social engineering, misinformation, insider threats, and user overreliance on AI tools
• Design science approaches to developing, evaluating, and theorizing intelligent security artifacts with behavioral implications
• Adaptive, personalized, and context-aware security interventions enabled by AI and analytics
• Theoretical extensions or reconceptualizations of established behavioral security theories in AI-mediated environments
• Security behaviors in pervasive and post-pandemic work environments, including remote work, hybrid work, IoT, cloud platforms, and platform ecosystems

Timeline

• January 15, 2027: Submission deadline
• May 15, 2027: Notification of first round reviews
• July 15, 2027: Revised manuscript due
• September 1, 2027: Notification of second round reviews
• October 15, 2027: Final version due
• January 30, 2028: Tentative publication date