knowledge transfer

I4S 5/2026: Organizing Work and Securing Expertise Through AI

I4S 5/2026: Organizing Work and Securing Expertise Through AI

How we make industrial work and organizational processes more resilient with AI
Artificial intelligence is transforming knowledge work. Diagnosis, decision-making, and optimization are increasingly shaped by the interaction between humans and AI. As a result, AI proficiency is becoming a competitive factor, although technical expertise—the foundation of industrial performance—must not be lost. This issue explores the potential of AI in manufacturing as well as the skill requirements for AI-based knowledge management.
Application Potentials of Chinese Knowledge Platforms

Application Potentials of Chinese Knowledge Platforms

Digital platforms for knowledge transfer in research and education
Yunhao Su, Martin Braun ORCID Icon
Knowledge drives innovation, which is why digital platforms are increasingly used for knowledge transfer. The People’s Republic of China (PRC) is a global leader in digitalization and digital platforms are central to Chinese knowledge transfer and innovation systems. This study supplements theoretical concepts of knowledge transfer with empirical findings on the (further) development of relevant knowledge platforms. It examines the influence of specific design features on the functionality and quality of digital knowledge platforms. A literature review identifies seven condensed success criteria. Nine leading Chinese knowledge platforms are categorized based on their transfer logic and functional scope. Online survey participants assess the platform-specific manifestations of the identified criteria and highlight potential and areas for improvement in platform-based knowledge transfer.
Industry 4.0 Science | Volume 42 | 2026 | Edition 3 | Pages 84-93
Knowledge Sharing and Transfer in Production Networks

Knowledge Sharing and Transfer in Production Networks

An organizational learning approach
Bernd Scholz-Reiter ORCID Icon, Salima Delhoum
In a production network, teams or companies exchange information and products to create value. The competitive advantage of the team / company relies on that of the network. This paper addresses knowledge management in a production network especially the promotion of knowledge sharing and transfer. This is a substantial issue when, for example, a company comes to leave the network voluntarily or disappears because of natural or man-made catastrophes. In this case, the question remains whether the substituting company can acquire the tacit knowledge needed to fulfil its mission. Consequently, the operation of the network is also an acute issue. The paper proposes a methodology based on organisational and interorganisational learning and develops a learning laboratory that facilitates knowledge sharing and transfer. This lab supports, (a) knowledge sharing through the mental map’s knowledge elicitation of every company’s leader, and (b) knowledge transfer via dedicated learning-based ...
Industrie Management | Volume 23 | 2007 | Edition 4 | Pages 34-36