Journal of Information & Knowledge Management
Scope & Guideline
Advancing the Frontiers of Information Science
Introduction
Aims and Scopes
- Knowledge Management Strategies:
The journal investigates various strategies and frameworks for effective knowledge management in organizations, emphasizing the role of technology in facilitating knowledge creation, sharing, and retention. - Information Technology and Big Data:
A significant focus is on the integration of information technology and big data analytics in enhancing decision-making processes and operational efficiencies across sectors. - Interdisciplinary Approaches:
The journal encourages interdisciplinary research that combines insights from computer science, social sciences, and management studies to address complex challenges in knowledge management. - Innovative Applications and Case Studies:
It publishes case studies and applications of innovative technologies such as artificial intelligence, blockchain, and machine learning in knowledge management and information systems. - Collaborative Learning and Knowledge Sharing:
Research on collaborative learning environments and knowledge-sharing practices is a key area, exploring how social dynamics and technology influence collaboration among individuals and organizations.
Trending and Emerging
- Artificial Intelligence in Knowledge Management:
Research on the application of artificial intelligence (AI) technologies in knowledge management is gaining momentum, focusing on how AI can enhance knowledge discovery, sharing, and retention. - Blockchain Technology Applications:
The exploration of blockchain technology for secure knowledge sharing and data management is an emerging theme, indicating a growing interest in decentralized solutions for information integrity. - Impact of Digital Transformation:
Studies assessing the impact of digital transformation on organizational knowledge management practices are trending, reflecting the necessity for organizations to adapt in a rapidly changing digital landscape. - Data-Driven Decision Making:
There is an increasing emphasis on data-driven decision-making processes, highlighting the importance of big data analytics in shaping effective knowledge management strategies. - Sustainable Knowledge Management Practices:
Research is increasingly focusing on sustainability in knowledge management, exploring how organizations can integrate sustainable practices into their knowledge management frameworks.
Declining or Waning
- Traditional Knowledge Management Models:
There has been a noticeable reduction in papers focusing on traditional knowledge management models, as the field shifts towards more dynamic, technology-driven approaches. - Static Data Management Approaches:
Research centered on static data management techniques has declined, indicating a move towards more agile and adaptive data management practices in response to the evolving technological landscape. - Non-Digital Knowledge Sharing Practices:
Papers addressing non-digital or face-to-face knowledge sharing practices are becoming less prevalent, reflecting a broader trend towards digital transformation and remote collaboration. - Basic Information Retrieval Techniques:
The journal is seeing fewer studies on basic information retrieval techniques, as the focus shifts to more sophisticated methodologies involving machine learning and artificial intelligence. - Generic Applications of Knowledge Management:
There is a waning interest in generic applications of knowledge management without a specific technological or contextual focus, as scholars seek to explore more specialized and innovative applications.
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