Business Management FT
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Knowledge Management (E)

level of course unit

k.A.

Learning outcomes of course unit

The students
• know alternative methods and concepts of how knowledge can be generated from information and how knowledge can be converted into sustainable competitive advantages in order to make business successes or failures measurable.
• can apply the basics of identifying and measuring knowledge in the context of intellectual capital reporting.
• understand the basic knowledge management processes and can apply tools and instruments for knowledge work.
• know how digitization can be used to build a knowledge management system in the company.
• know the connection between digitalization and artificial intelligence.
• know the challenges and possible applications for Artificial Intelligence in business management.
• know how artificial intelligence can be used in knowledge management.

prerequisites and co-requisites

None

course contents

Part A: Knowlege Management
• Characteristics and features of knowledge societies
• Definition of knowledge and knowledge management
• Knowledge under consideration of the resource-based-view and knowledge-based-view
• Knowledge as a core resource in competition
• Knowledge generation, knowledge sharing, knowledge protection
• Identification and measurement of knowledge, intellectual capital reports
• Basics of the learning organization
• Identification and structuring of company-relevant knowledge
• Design of knowledge organizations - tools and processes
• Tools and instruments for knowledge workers

Part B: Artificial Intelligence
• Definition of Artificial Intelligence and the connection to digitalization
• Overview of the development of AI (neural networks, machine learning, deep learning)
• Basic applications of AI in modern business management (e.g. automated learning, analysis of data sets, etc.) and especially in knowledge management (natural language processing, natural question answering, semantic preparation of content, human-machine interaction, etc.)

recommended or required reading

• Deckert, R., & Meyer, E. (2020). Digitalisierung und Künstliche Intelligenz: Kooperation von Menschen und Maschinen aktiv gestalten. Wiesbaden: Springer Verlag.
• Ertel, W. (2021). Grundkurs Künstliche Intelligenz: Eine praxisorientierte Einführung. Wiesbaden: Springer Verlag.
• Hovdar-Stojakovic, I., Steinbacher, H.-P., Situm, M., & Märk, S. (2023). Innovatives Lehren und Lernen mit Blended Learning: Bausteine, Strukturen und Umsetzung in der Organisation. Wiesbaden: Springer Verlag.
• Lehner, F. (2021). Wissensmanagement: Grundlagen, Methoden und technische Unterstützung. München: Carl Hanser Verlag.
• Massingham, P. (2020). Knowledge management: Theory and practice. London, UK: SAGE Publications.
• North, K. (2021). Wissensorientierte Unternehmensführung: Wissensmanagement im digitalen Wandel. Wiesbaden: Springer Verlag.
• Rhem, A. J. (2022). Knowledge management in practice. Boca Raton, FL: CRC Press.

assessment methods and criteria

• Seminar paper and
• Quiz

language of instruction

English

number of ECTS credits allocated

3

eLearning quota in percent

25

course-hours-per-week (chw)

2

planned learning activities and teaching methods

• 25 % of the event is covered by eLearning. A combination between online phases (inductive method for the independent acquisition of knowledge and the practice of tasks) and presence phases (deductive method, in which assistance is given in the learning process and knowledge is imparted via frontal lectures) is used.

semester/trimester when the course unit is delivered

3

name of lecturer(s)

English version will be available soon

course unit code

LEA 3

type of course unit

integrated lecture

mode of delivery

Compulsory

work placement(s)

not applicable

Contact

Situm Mario
Prof. (FH) DDr. Mario Situm, MBA
Director of Studies Business Management
+43 5372 71819 147
Mario.Situmfh-kufstein.ac.at
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