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

George Boak, York St John University

Wooyong Eom, Keimyung University

Sanghyeok Park, Gyeongsang National University

Christine Abbott, Centre for Action Learning

This special issue invites contributions exploring action learning across Asia. While previous journal issues have featured individual papers on action learning in various Asian countries, this collection seeks to expand representation to underrepresented regions throughout the continent.

The editors are particularly interested in how cultural contexts shape action learning approaches. Submissions should examine whether distinctive characteristics emerge in action learning design and facilitation across different cultural settings, and how cultural factors influence both the aims and processes of action learning.

The issue welcomes empirical studies, conceptual papers, and practitioner accounts that contribute to understanding action learning theory and practice in Asian contexts. Authors are encouraged to consult with editors before submitting full papers.

Appel publié par Action Learning: Research and Practice. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Action learning practices and theory in Asian countries including South Korea, China, Japan, the Philippines, Thailand, Singapore, Taiwan, Turkey, Nepal, India and Pakistan
• Cultural influences on action learning design, aims and processes
• Distinctive characteristics of action learning facilitation in different cultural environments
• Empirical and conceptual explorations of action learning
• Practitioner accounts and personal experiences of action learning

Timeline

• October 1, 2026: Manuscript deadline

Yu Kang Yang Trevor, Nanyang Technological University

Brian D. Blume, University of Michigan

Jason L. Huang, Michigan State University

Kenneth G. Brown, University of Iowa

Work-related learning is essential for organizational competitiveness, yet remains disconnected from human resource management scholarship. While learning research focuses on individual processes, HRM emphasizes organizational systems, creating a gap in understanding how learning can be strategically integrated into HR practices. This special issue aims to bridge that divide by examining learning processes across different levels and work contexts, positioning learning as a strategic mechanism central to HRM.

The special issue welcomes research on formal, informal, incidental, and self-directed learning in traditional, hybrid, and digital environments. Submissions should integrate learning with HR systems and strategy, adopt multilevel perspectives, address contemporary challenges such as artificial intelligence and hybrid work, and demonstrate practical relevance for organizations. Both empirical and theoretical contributions from diverse methodological approaches are invited, provided they maintain focus on HRM.

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

Potential topics

• Integrative approaches to learning systems and how HR systems can integrate formal, informal, and self-directed learning into coherent architectures aligned with business strategy
• Mechanisms linking learning and development initiatives to workforce agility, innovation, and firm performance
• Compositional and compilational processes linking learning across individual, team, and organizational levels
• Longitudinal and multilevel research designs tracing learning episodes across different levels of analysis
• Multidimensional learning criteria incorporating cognitive, skill-based, and affective outcomes
• Learning ROI evaluation through both immediate performance metrics and long-term indicators of adaptability, resilience, and innovation
• How organizations create, sustain, and transfer learning cultures through HR practices
• HR system characteristics facilitating or hindering learning transfer at individual and team levels
• Organizational learning climates and psychological safety influencing skill transfer
• Formal training, leadership development, and on-the-job learning effectiveness and long-term transfer
• Adaptive and AI-driven learning systems tailoring training content
• Sequencing of learning events affecting transfer outcomes
• Social learning interventions such as peer mentoring and communities of practice
• Proactivity, self-regulation, and learning motivation affecting continuous learning and career adaptability
• Exploration-exploitation tradeoffs during work-related learning
• Employee management of tradeoffs between work, nonwork, and recovery when allocating resources to self-directed learning
• Motivational processes sustaining self-directed learning in fast-changing environments
• Meta-cognitive awareness of learning strategies, habits, and biases
• HRM practices fostering sustained self-regulated learning cycles
• Relationships and interactions between formal, informal, and self-directed learning
• Emotions, personality traits, and workplace context shaping informal learning processes
• How digital technologies influence the experience, design, and delivery of learning opportunities
• Knowledge, skills, and abilities especially valuable in AI-mediated work settings such as data literacy and human-AI collaboration
• AI in predictive and generative algorithms, microlearning, and learning management systems affecting learning and organizational outcomes
• Co-learning experiences with AI systems such as chatbots and virtual coaches
• Trust, dependence, and resistance emerging when AI guides or assesses learning
• Contextual factors interacting with technologies to influence learning effectiveness
• Digital collaboration platforms fostering or fragmenting knowledge sharing and informal learning
• Obstacles and challenges faced by persons with disabilities, mid-career switchers, elderly workers, and non-standard employees in learning
• HR systems and public policy democratizing learning access and ensuring equitable capability development
• Employment status, industry type, and job level determining learning opportunities and outcomes
• Learning opportunities and self-assessment for vulnerable and non-affiliated workers such as gig and informal economy workers
• Equitable access to formal and informal learning for workers in small and medium enterprises or platform-based employment
• Learning technologies amplifying or reducing disparities in learning outcomes
• HR policies and public-private partnerships supporting continuous learning for displaced, older, or low-skilled workers
• Cognitive, motivational, and affective processes shaping engagement in work-related learning under conditions of high workload and continuous change
• Fluctuations in attentional control, working-memory capacity, and cognitive load influencing knowledge acquisition and transfer
• Job design features facilitating or undermining sustained cognitive engagement in learning
• Affective states such as curiosity, anxiety, and psychological safety influencing learning persistence and adaptability
• Insights from cognitive and neurocognitive research informing the design of high-quality jobs and HR systems supporting learning and psychological sustainability

Timeline

• January 31, 2027: Submission deadline

Maarten Renkema, University of Twente

Laura Lamers, University of Twente

Christoph Lutz, BI Norwegian Business School

Anna B. Holm, Aarhus University

Organizations are rapidly adopting AI technologies, but this creates significant challenges including algorithmic bias and opacity. AI literacy—the knowledge, skills, and attitudes enabling individuals to engage effectively and critically with AI—has become essential for competitive survival and is now mandated by the EU's AI Act. However, research on AI literacy remains focused primarily on educational contexts and individual learners, leaving organizational and HRM perspectives largely unexplored.

This special issue seeks to advance theoretical understanding of AI literacy as an organizational phenomenon rather than merely an individual competency. The editors invite contributions that move beyond both naive enthusiasm and dismissive skepticism, instead adopting critically engaged perspectives grounded in empirical evidence. Contributions should examine AI literacy across multiple organizational levels—individual, team, and organizational—and explore how HRM can facilitate its development and implications for HR functions and practices.

Appel publié par The International Journal of Human Resource Management. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Implications of AI literacy for core HRM functions including recruitment, selection, learning and development, performance management, and employee well-being
• Organizational AI literacy: design, implementation, and governance of HRM activities
• Emergence mechanisms through which individual AI literacy becomes collective organizational capability
• Relationship between organizational AI literacy and adjacent constructs such as organizational AI readiness
• Competition for AI talent and inequality implications
• Team design and composition to enable and develop AI literacy
• HRM and HRD practices supporting AI-literate teams including workforce planning, staffing, job design, and training
• Levels and combinations of AI literacy needed across different teams and roles
• Manifestation of AI literacy in everyday work practices
• Technical, ethical and practical dimensions of AI literacy in AI-mediated recruitment
• AI literacy's influence on employees' AI overreliance and fairness perceptions
• AI literacy of HR professionals and its influence on adoption of AI tools

Timeline

• Invalid DateTime: Special issue completion
• September 1, 2026: Special Issue announced
• February 1, 2027: Submission window opens
• April 30, 2027: Submission deadline
• July 1, 2027: Decision on first submissions

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