Knowledge Elicitation

Potentials, Premises, Perspectives

Potentials, Premises, Perspectives

Using LLMs to reinterpret corporate knowledge management
Vanessa Kuks ORCID Icon, Pius Finkel ORCID Icon, Peter Wurster ORCID Icon
Demographic change is exacerbating the shortage of labor and skilled workers in the manufacturing industry, making knowledge management an increasingly important issue in many companies. Collecting and preserving tacit knowledge poses a particular challenge. This study examines the extent to which large language models (LLMs) can provide meaningful support in knowledge gathering through expert interviews. Three experts test and evaluate a personalized chatbot that has been developed using ChatGPT-5. The results of the interview are promising, but the summary shows room for improvement.
Industry 4.0 Science | Volume 41 | Edition 6 | Pages 48-56 | DOI 10.30844/I4SE.25.6.48
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