Enis Elezi, University of Westminster

Knowledge-intensive organisations face mounting complexity from resource constraints, digitalisation, accountability demands, and geopolitical pressures. Existing research on these challenges remains fragmented across disciplinary silos and often lacks systemic understanding of how these institutions observe, interpret and respond to complexity.

This special issue integrates typically isolated scholarly conversations about leadership, governance, risk, knowledge and entrepreneurship within a cybernetic framework. It explores the interconnected processes of observation, communication, decision and learning that enable organisations to adapt and remain viable across sectors including universities, health systems, research institutes and public agencies.

Appel publié par Kybernetes. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Leadership and governance as systemic architectures of observation, decision and learning
• Enterprise-wide risk management, knowledge management and entrepreneurship as interconnected cybernetic processes
• Cross-sector analyses of universities, health systems, research institutes, public agencies and professional service firms as complex learning systems
• Reflexive and second-order perspectives on how organisations construct and revise their own governance arrangements
• Theory-as-method applications using cybernetics, systems thinking or complexity frameworks

Timeline

• January 26, 2026: Opening date for manuscripts submissions
• December 26, 2026: Closing date for manuscripts submission

Organizations face increasing complexity from shifting geopolitical, economic, and technological conditions, requiring strategic approaches to knowledge management for sustainability. The integration of knowledge management with AI offers potential benefits for problem-solving and decision-making, yet presents challenges that require responsible and ethical implementation. This special issue examines how organizations can leverage strategic knowledge management to balance the opportunities and risks of AI while maintaining sustainability across their operations.

The call seeks contributions exploring how organizations can effectively manage both human knowledge and AI-generated intelligent knowledge, addressing issues such as knowledge overload, loss, and duplication. It emphasizes the importance of codification and personalization strategies that align with organizational values and objectives. The special issue invites researchers to examine how sustainable strategic knowledge management enables organizations to adapt to rapidly changing environments while achieving economic, social, and environmental goals.

Appel publié par Journal of Strategy and Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Knowledge management processes and sustainability in organizations
• Human-AI synergy and responsible AI use in knowledge systems
• Strategic knowledge management for organizational decision-making and problem-solving
• Managing explicit and tacit knowledge in digital environments
• Knowledge codification and personalization approaches
• Addressing knowledge overload from AI, cloud computing, and big data
• Sustainable knowledge-based organizations and resource optimization
• AI's impact on critical knowledge management processes
• Ethical and mission-aligned strategic knowledge for financial, social, and ecological benefits
• Knowledge management in complex organizational environments and geopolitical uncertainty

Timeline

• January 8, 2026: Opening date for manuscripts submissions
• October 31, 2026: Closing date for manuscripts submission

This special issue explores the interconnection between social capital and knowledge management in organizations. Social capital—networks of relationships, trust, and shared norms—facilitates knowledge exchange and integration, enhancing intellectual capital development and organizational competitiveness across sectors including technology, finance, healthcare, and creative industries.

The call addresses critical research gaps including the lack of general theory explaining how social capital translates to intellectual capital across different contexts, inconsistent measurement approaches, and limited longitudinal studies. It seeks contributions examining how social capital functions as a mediating mechanism in digital environments, how it evolves over time, and how cultural and technological factors influence these dynamics.

The special issue invites empirical and theoretical research from academics and practitioners investigating social capital's role in knowledge creation, innovation outcomes, and competitive advantage, with particular attention to measurement frameworks, trust mechanisms, and organizational structures that enable effective knowledge management.

Appel publié par VINE Journal of Information and Knowledge Management Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does social capital translate into intellectual capital across different organizational contexts?
• In what ways does social capital act as a mediator of knowledge management in digital and dynamic environments?
• How can social capital in knowledge management be measured? To what extent do trust, networks, and norms function as distinct versus overlapping dimensions of social capital?
• How does social capital evolve over time, and what are its long-term effects on knowledge creation and sharing?
• How do individual employee networks aggregate to create firm-level intellectual capital?
• How is social capital value disclosed?
• How do national cultures influence the relationship between social capital and knowledge management?
• In what ways do organizational structures influence the effectiveness of social capital in enabling knowledge management?
• How do emerging technologies impact the development and role of social capital in knowledge management?
• What role does trust play in knowledge sharing and knowledge application processes?
• How can organizations foster trust to strengthen social capital in virtual and hybrid workplaces?
• How does social capital-driven knowledge management contribute to organizational innovation?
• What is the relationship between social capital, knowledge management, and competitive advantage in dynamic markets?

Timeline

• April 1, 2026: Opening date for manuscript submissions
• October 31, 2026: Closing date for manuscript submissions

Anna Yström, Linköping University

Susanne Ollila, Chalmers University of Technology

Paul Carlile, Boston University

Deborah Roberts, University of York

This special issue examines spaces for innovation—such as living labs, maker spaces, and virtual environments—as crucial elements for stimulating innovation and enabling co-creation. While the role of physical spaces in fostering innovation has long been established, contemporary innovation involves multiple interrelated spatial modalities: physical, virtual, cognitive, and social. The special issue aims to advance interdisciplinary innovation management theory and practice by investigating how these diverse spaces are designed, experienced, and orchestrated to stimulate innovation.

The special issue addresses significant gaps in understanding how spatial configurations shape innovation in collaborative contexts. Key concerns include how different spatial modalities interact to drive innovation, the role of AI and technological systems in reshaping innovation spaces, the challenges of integrating knowledge across organizational and disciplinary boundaries, and how managers can orchestrate inclusive and ethical innovation environments. Additionally, the call seeks methodological advancements to capture the dynamic and evolving nature of spaces across their multiple dimensions.

Appel publié par Journal of Product Innovation Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Dynamics of Stimulating Innovation Across Spatial Modalities - how different modalities of space (physical, digital, cognitive, and social) stimulate innovation, both intentionally and serendipitously, and how these modalities interact over time
• AI-Augmented Spaces and Their Role in Stimulating Innovation - how AI-augmentation reshapes spaces for innovation and their management, including impacts on creativity, decision-making, collaboration, power relations, and ethical considerations
• Knowledge Integration and Boundary-Spanning in and across Spaces for Innovation - how spaces enable or constrain knowledge integration and boundary-spanning across organizational, disciplinary, and cultural divides
• Orchestrating Spaces for Innovation: Inclusion, Power, and Governance - how orchestration forms and practices shape spaces for innovation with attention to fairness, transparency, inclusion, and the dark sides of innovation spaces
• Methodological Advancements for Studying Spaces Across Modalities and Over Time - methodological approaches to capture the dynamic, multi-modal nature of spaces for innovation as they evolve, including mixed methods, ethnography, spatial and network analysis, and AI-driven tools

Timeline

• Invalid DateTime: Expected publication
• April 30, 2026: Proposal deadline for paper development workshop (optional)
• May 11, 2026: Decisions on proposal for paper development workshop
• June 8, 2026: Online information session with Q&A followed by paper development workshop (optional)
• September 30, 2026: Full paper submission window opens
• November 30, 2026: Full paper submission window closes
• February 28, 2027: First round decisions
• June 30, 2027: First round revision due
• November 30, 2027: Second round decisions
• February 28, 2028: Second revisions due
• June 30, 2028: Final editorial decisions

Associate editors

• Gerda Gemser, University of Melbourne

This special issue invites submissions that explore the intersection of data-driven innovation, sustainable product development, and knowledge management. We seek research that examines how organizations can leverage data analytics, big data, machine learning, and knowledge management systems to drive innovation in sustainable product development. The focus is on understanding how data can be collected, analyzed, interpreted, and managed to support decision-making processes that lead to more sustainable products and services.

Appel publié par Journal of Engineering and Technology Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Application of data analytics and big data techniques in sustainable product development
• Knowledge management systems for supporting data-driven innovation in sustainability contexts
• Integration of lifecycle assessment (LCA) data with knowledge management platforms
• Machine learning and AI applications for identifying sustainable product innovations
• Data governance frameworks for managing sustainability-related information
• Organizational learning and knowledge sharing in sustainable innovation processes
• Digital transformation enabling sustainable product development
• Real-world case studies of data-driven sustainable product innovation
• Challenges and barriers to implementing data-driven approaches in sustainability
• Tools and technologies for collecting, analyzing, and leveraging sustainability data

Timeline

• October 15, 2026: Submission deadline

Appel publié par Journal of Innovation & Knowledge. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• September 30, 2026: Submission deadline

Appel publié par Journal of Innovation & Knowledge. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• December 31, 2029: Submission deadline

Guillermo Antonio Dávila, Universidad de Lima

Susanne Durst, Bangkok University

Organizations in resource-constrained and institutionally weak contexts face significant challenges in maintaining competitiveness and innovation amid political uncertainty and technological change. This special issue addresses the underexamined role of knowledge management in enabling these organizations—including SMEs, NGOs, and entities in developing regions—to overcome financial constraints, limited technological access, and skilled workforce shortages.

Knowledge management has demonstrated capacity to enhance innovation, strengthen organizational resilience, and foster learning even under severe resource limitations. While empirical evidence from emerging economies supports these benefits, research remains concentrated on stable, well-developed environments, leaving underrepresented contexts insufficiently studied despite their numerical significance and potential for theoretical contribution.

Appel publié par Knowledge Management Research & Practice. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• KM as an enabler of organizational performance under conditions of resource scarcity
• Knowledge risk management as crucial function in environments characterized by internal and external constraints
• KM in underrepresented organisational settings, including SMEs, family businesses, informal organisations, low-technology firms, social organisations or geographically isolated regions
• Organisational learning processes in contexts characterised by institutional and resource constraints
• The role of KM in strengthening organisational resilience during internal and external crises and disruptions
• Necessary conditions and bottlenecks for organizational development empowered by KM
• The interplay between artificial intelligence and KM in overcoming organisational and institutional constraints
• The role of institutional ecosystems and inter-organisational networks in enhancing the effectiveness of KM
• Novel methodological approaches for studying KM in constrained and underrepresented contexts

Timeline

• March 15, 2027: Manuscript deadline

Asha Thomas, Wrocław University of Science and Technology

Moreno Frau, Corvinus University of Budapest

Dominyka Venciūtė, ISM University of Management and Economics

Across contemporary organizations, advances in artificial intelligence (AI) are transforming AI from a discrete technological resource into a systemic organizational capability that actively shapes decision-making, business model innovation, and competitive advantage. Traditionally, AI interfaces have largely been reactive, responding to human prompts and predefined inputs. The emergence of Agentic Artificial Intelligence represents a fundamental shift, as agentic systems are designed to operate with increasing autonomy, enabling goal-driven planning, workflow orchestration, coordination across systems, and machine-initiated action with limited human intervention.

Appel publié par Journal of Enterprise Information Management. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does Agentic AI enable new forms of value creation, capture, and measurement in organizations? Under what conditions can agentic systems also lead to value co-destruction or unintended negative outcomes due to misaligned autonomy, resource integration, or decision logic?
• How do organizations design governance, accountability, trust, and regulatory compliance mechanisms for Agentic AI systems operating with increasing autonomy? What challenges arise when human oversight is limited or distributed across functions?
• How do ethical considerations, responsibility, and moral agency evolve when AI systems act as semi-autonomous organizational actors rather than decision-support tools?
• How does Agentic AI reshape business process redesign, orchestration, and automation across organizational functions such as marketing, human resource management, operations, finance, and customer engagement?
• In what ways is artificial intelligence becoming normalized within organizational and marketing practice, shifting from experimental adoption to routinized, AI-embedded decision-making and workflows?
• How does Agentic AI influence workforce transformation, the future of work, and human resource management practices, including recruitment, performance evaluation, learning, and employee autonomy?
• How does the adoption of Agentic AI differ across organizational contexts, such as small and medium-sized enterprises versus large corporations, and what factors shape successful implementation and impact?
• How do emotional, relational, and interactional dynamics shape human–AI engagement in Agentic AI–driven sales, marketing, and customer experience contexts?
• How can human–AI collaboration and human-in-the-loop design be sustained when AI systems increasingly initiate actions, coordinate tasks, and learn autonomously?
• How do multi-agent systems, coordination mechanisms, and organizational architectures evolve as multiple human and artificial agents interact within complex socio-technical environments?
• How can existing theories of agency, organizational learning, and socio-technical systems be extended or reconfigured to explain machine agency and autonomous action in Agentic AI–enabled organizations?
• How does Agentic AI transform knowledge management, organizational learning, and decision support by enabling systems that not only retrieve and integrate knowledge but also reason, adapt, and act upon it?

Timeline

• March 1, 2026: Opening date for manuscript submissions
• September 30, 2026: Closing date for manuscript submissions