ECKM Call for Papers

• Academic Papers
• Case Studies
• Work in-Progress Papers
• PhD Papers
• Masters Papers
• Posters and Presentations
• Non- Academic or Practitioner Contributions
  

Aims and Scope 

The primary aim of ECKM is to foster a deeper understanding of knowledge management processes, practices, and technologies, and to explore their impact on organizational effectiveness and innovation. The conference seeks to bridge the gap between theory and practice by encouraging the exchange of ideas between academics and practitioners. It also aims to promote interdisciplinary collaboration by bringing together experts from various fields such as business, information technology, education, and public administration. 

ECKM’s scope is broad, encompassing all aspects of knowledge management, from the creation and sharing of knowledge within organizations to the role of technology in enabling KM processes. The conference addresses both the strategic and operational dimensions of knowledge management, emphasizing its importance in enhancing organizational learning, innovation, and competitive advantage. 

Topics Covered 

ECKM covers a wide range of topics related to knowledge management, reflecting the evolving nature of the field and its application in different contexts. The call for papers asked for contributions that considered the following topics. In addition, the committee welcomed papers on a number of specialist mini-tracks which can be seen at the end of this list. 

Knowledge Creation and Sharing

• Tacit and Explicit Knowledge 
• Knowledge Sharing Practices. 

Knowledge Management Systems and Technologies 

• KM Tools and Platforms 
• Artificial Intelligence and KM 
• Big Data and Knowledge Analytics. 

Organizational Learning and Innovation

• Learning Organizations 
• Innovation Management 
• Communities of Practice. 

Strategic Knowledge Management

• KM and Competitive Advantage 
• Knowledge Strategy Development 
• Intellectual Capital Management. 

KM in Specific Contexts

• KM in Public Administration 
• KM in Education 
• KM in Healthcare. 

Knowledge Management and Organizational Culture

• Cultural Barriers to KM 
• Leadership and KM 
• Change Management in KM Initiatives. 

Ethics and Knowledge Management

• Ethical Issues in KM 
• Sustainability and KM. 

Emerging Trends and Challenges in KM

• Digital Transformation and KM 
• Globalization and KM 
• The integration of KM with other business disciplines 
• The evolving role of knowledge managers. 

Mini-Tracks

The impacts of Generative AI on individual, group, and organizational knowledge management

Mini Track Chairs: Dr. Gang LIU & Prof. Jacky F. L. HONG, Business School, Shenzhen Technology University, Faculty of Business Administration, University of Macau

Generative artificial intelligence (GenAI) has transformed the way people approach knowledge management (KM) activities, including knowledge creation, acquisition, sharing, transfer, and retention. The integration of GenAI such as ChatGPT, Auto GPT, Grok-1, etc. into KM activities and practices is a growing area of interest for organizations. However, it is still unclear how GenAI and KM can be effectively synthesized to maximize value generation in both theory and practice.

There are many emerging research topics in this field deserving further exploration. For example, what is the relationship between GenAI and KM? can the application of GenAI improve KM efficiency and performance? What are the limitations and barriers of GenAI application in KM? How can organizations and individuals benefit from GenAI applications? Where should KM go with GenAI? This mini-track encourages researchers to discuss the changes and impacts that GenAI brings to KM as it is applied to individuals, groups, and organizations.

Topics of interest include, but are not limited to:

• GenAI and individual KM, job performance/creativity/decision-making
• GenAI, KM, and group/organizational performance
• GenAI and knowledge creation/sharing/transfer
• GenAI and individual/organizational learning
• Privacy, information security, ethical issues of GenAI in KM
• GenAI and KM in different cultural contexts

Sustainability in Knowledge Management and Advanced Green Policy Strategies

Mini Track Chairs: Prof. Dr. Mustafa Sağsan, European University of Lefke

Knowledge has penetrated green policies to increase sustainable environmental strategies, as an important intangible asset. World ecosystems, artificial intelligence, social governance, innovation, knowledge policy, environmental initiatives, etc. are significant fields that require knowledge management strategies using personalization and codification strategies for green areas. This track aims to evaluate how knowledge management is applied in green policies; including climate change, resource conservation, waste reduction and recycling, biodiversity production, environmental pollution, and green construction. National governments, local governments, organizations, and businesses are responsible for creating green knowledge management strategies to enhance sustainability by supporting different projects. This track invites research on various aspects of green knowledge management.

Topics may include but are not limited to:

• Unified knowledge ecosystems from an artificial intelligence perspective
• Green policy strategies in knowledge management fields
• Behaviour-driven knowledge management in organisations
• Agile knowledge management processes and innovation strategies
• Environmental and social governance in creating national knowledge policies
• Knowledge management practices in sustainable growth strategies for developing and developed countries.

Bridging Knowledge and Project Management for Strategic Success

Mini Track Chair: Professor Emeritus, Dr. Marta Christina Suciu, PhD Supervisor, Economics 1 Doctoral Shool, Dr. Irina Purcarea,  Rennes School of Business, France

Bridging Knowledge and Project Management for Strategic Success intends to explore the connection between knowledge management (KM) and project management (PM) in order to better drive organizational success. Nowadays, organizations increasingly rely on PM and project-based initiatives, where effective and efficient KM strategies and practices become key factors to strategic performance and success. This track aims to examine how integrating KM practices within PM frameworks and methodologies might contribute to the improvement of collaboration, better decision-making, effective risk management, and enhanced project efficiency and effectiveness.

Key topics may include:

• Integrating KM into PM processes
• The role of knowledge sharing in mitigating project risks
• The use of KM tools to capture, organize, and share critical insights across different projects
• Strategies for applying lessons learned to future projects in order to facilitate and drive continuous improvement
• Challenges in integrating KM and PM
• Overcoming knowledge silos in project-based organizations.

Intellectual Capital as a Dynamic, Multilevel, and Complex Ecosystem

Mini Track Chair: Prof. Sladjana Cabrilo, PhD ,I-Shou University, Department of International Business Administration, Kaohsiung, Taiwan

Intellectual capital (IC) has predominantly been considered in the literature as a static stock of knowledge-based resources. However, there is an emerging need for a move to recognizing IC as a dynamic (Kianto, 2007), multilevel (Bratianu, 2023), interconnected, and complex IC ecosystem (Konno & Schillaci, 2021; Lin & Edvinsson, 2021; Kianto et al., 2024). This is because a single-level and a snapshot approach to IC research overlooks the dynamic and interdependent nature of IC components and can only provide a limited and retrospective understanding of IC (Kianto et al., 2024). Therefore, it is crucial for future IC research to acknowledge the complex and multilevel nature of the IC ecosystem and explore interconnected IC dimensions at the individual, team, organizational, and institutional levels. Multilevel empirical research seems to be lacking in the IC literature, and could be applied to improve understanding of the complex IC ecosystem.     

Furthermore, there is a mismatch between theory and methods regarding knowledge dynamics and complexity (Bratianu, 2023; Cabrilo et al. 2024). One way to overcome these barriers is to interpret IC as an integrated bundle of knowledge assets and apply a configurational rather than a symmetric approach to IC and its outcomes (Cabrilo & Dahms 2018; Cabrilo et al., 2024). Asymmetrical techniques such as fuzzy-set qualitative comparative analysis (fsQCA) allow us to understand equifinality and causal asymmetry (Kumar et al. 2022); therefore, in the context of dynamic and complex IC ecosystems, they can bring the explanatory power to IC theory and practice (Cabrilo et al., 2024).

This mini-track welcomes diverse research perspectives and a dialogue on the following topics:

• Conceptualizing IC as a Complex Ecosystem - Understanding IC beyond organizations, and exploring complex structure of an IC ecosystem.
• Multilevel Perspectives on IC - Examining how intellectual capital operates across various levels, from individual and team to organizational, inter-organizational, city, and national scales.
• IC Dynamics and Interconnectedness of IC Elements - Exploring dynamic interactions and interdependences between IC elements at different levels of IC ecosystem
• Aligning Theory and Research Method - Discussing the limitations of traditional linear and symmetric approaches and applying new approaches to capture the dynamic and complex nature of IC and its outcomes.

Data-Driven Knowledge Management

Mini Track Chair: Henri Hussinki, Assistant Professor of Business Analytics, LUT University, Lahti, Finland

The past decade has witnessed a surge in organizations’ business analytics (BA) investments and academic literature investigating this area. BA use helps organizations leverage their structured data assets to enhance their processes and generate insights for decision-makers. Organizations that take such an approach are described as data-driven, allowing them to, e.g., increase the degree of business process automation and make more accurate and quicker decisions. With the technological landscape rapidly evolving beyond “traditional” BA, incorporating novel and more capable solutions such as artificial intelligence (AI), it has become paramount for organizations to leverage these technologies to stay competitive. However, most organizations fail to reap the expected return on their BA investments, as they overemphasize the technological aspects and underestimate the role of other key resources, such as human skills and organizational culture. Even though BA literature is flourishing, knowledge management (KM) has not yet been fully integrated into it. This is surprising, as the impact of BA on KM, such as its bolstering effect on an organization’s knowledge base and decision-making support, seems to be likely and worth further research. In addition, the role of KM in establishing suitable organizational conditions for BA utilization is plausible, establishing a potentially reciprocal relationship between KM and BA.

We welcome manuscripts that deal with this above-described contemporary topic, or other similar topics related to KM and data-driven organization.

 Topics of interest include, but are not limited to:

• Data-driven knowledge management in organizations
• AI-driven knowledge management in organizations
• The integration of business analytics into an organization’s knowledge management systems
• Automation and augmentation - leveraging BA in organizations for business value
• Business analytics as a part of an organization’s KM

Important Dates