Ilan Alon, Ariel University

Marcin Wątorek, Cracow University of Technology

Aušrinė Šilenskytė, University of Vaasa

Ziaul Haque Munim, University of South-Eastern Norway

Organizations increasingly manage distributed decision-making and systemic complexity through blockchain technologies that function as operating systems by embedding governance mechanisms into digital infrastructures. These systems are being advanced with artificial intelligence to monitor and shape behavior. Despite blockchain-based operating systems being adopted in platforms, supply chains, and decentralized autonomous organizations, their implications for organizational administration, governance, and control remain poorly understood.

This special issue invites research that advances administrative and organizational understanding of blockchain-based operating systems with AI-enabled complexity. The call welcomes theoretically grounded, methodologically rigorous contributions including empirical studies and theory-building papers that offer clear organizational insights and engage meaningfully with blockchain and AI as organizational infrastructures.

Appel publié par Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Blockchain as an organizational operating system and potential of AI advancements in it
• Public, private, and hybrid organizations adopting blockchain OS with AI advancements
• Integration of AI on Blockchain OS in crowdsourcing platforms, crypto exchanges, fintech firms, energy management, and transport services etc.
• Organizational decision-making in blockchain-based and AI enabled systems
• AI's role in administrative functions embedded in smart contracts and protocols
• Token-based incentives as administrative and managerial mechanisms
• Strategic control and accountability in decentralized platforms with AI-enabled advancements
• AI integration in governance, coordination, and control without centralized authority (DAOs)
• Complexity, emergence, and adaptation in blockchain-based and AI enabled organizations
• Organizational legitimacy, regulation, and institutional alignment in AI and blockchain OS integrations
• Ethical, responsible, and sustainable administration of blockchain systems, especially those advanced with AI

Timeline

• November 15, 2026: Submission Deadline

Olga Battaïa, Kedge Business School

Yasser Dessouky, San Jose State University

Reza Zanjirani Farahani, Paris School of Business

Masood Fathi, University of Skövde

Madjid Tavana, La Salle University

This special issue investigates how collaborative intelligence—combining human expertise, artificial intelligence, and distributed problem-solving—can advance operations research to address modern decision-making challenges. Traditional OR methods struggle with the dynamic and interconnected nature of contemporary problems, from logistics to emergency response. The collection seeks contributions that demonstrate how human-AI collaboration can enhance decision-making, boost system resilience, and optimize complex operational environments.

The call invites theoretical, computational, and applied research on human-AI collaboration in OR models, optimization and game-theoretic approaches for multi-agent systems, adaptive and decentralized frameworks, and data-driven learning-based optimization. Submissions should demonstrate both theoretical rigor and practical relevance, with innovative methodologies and real-world applications that advance collaborative intelligence in operations research.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Designing OR models that facilitate seamless interaction and information exchange between human decision-makers and AI agents
• The framework for integrating human judgment, preferences, and ethical considerations into AI-driven decision-making
• Techniques for visualizing and interpreting AI outputs to enhance human understanding and trust
• Novel optimization algorithms and game-theoretic frameworks for coordinating and optimizing decisions in multi-agent environments
• Models addressing diverse objectives, capabilities, and interactions among multiple agents
• Approaches to managing conflicts, uncertainties, and strategic behaviors in multi-agent decision-making
• OR frameworks capable of dynamically adapting to real-time changes and uncertainties
• Decentralized optimization algorithms and control strategies for distributed systems
• Online learning and adaptive control techniques to improve system responsiveness and resilience
• Leveraging machine learning and data analytics to extract insights and patterns for OR applications
• Learning-based optimization algorithms that improve performance through data feedback
• Predictive analytics and simulation techniques for enhanced decision-making and risk management

Timeline

• December 31, 2026: Submission deadline