B_ZM Knowledge Management

University of Finance and Administration
Summer 2026
Extent and Intensity
2/0/0. 3 credit(s). Type of Completion: z (credit).
Teacher(s)
Ing. Mgr. Jaromír Tichý, Ph.D., MBA (seminar tutor)
Guaranteed by
Ing. Mgr. Jaromír Tichý, Ph.D., MBA
Department of Economics and Management – Departments – University of Finance and Administration
Contact Person: Mgr. Markéta Koliášová
Supplier department: Department of Economics and Management – Departments – University of Finance and Administration
Timetable of Seminar Groups
B_ZM/pEKFPH: each odd Tuesday 8:45–9:29 E004, each odd Tuesday 9:30–10:15 E004, each odd Tuesday 10:30–11:14 E004, each odd Tuesday 11:15–12:00 E004, J. Tichý
Prerequisites
No prerequisites are required.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The aim of the Knowledge Management course is to clarify the basic concepts and terms related to knowledge management. To familiarize the student with the necessity of using knowledge management in business practice.
Knowledge Management in modern companies combines the collection and extraction of data and information from systems (from business applications, the Internet, research outputs, etc.) with the development of people's knowledge (through education, increasing practical experience, transferring knowledge and skills between employees, cooperation with R&D departments, higher education institutions, etc.). The strategy for the future success of companies today is the massive development of Industry 4.0 technology (automation, robotization and digitalization), including the application of artificial intelligence and cybernetics. Knowledge management is at the crossroads of people's development, their abilities and interest in continuous education, and information management: Knowledge management is part of the development of people, human resources and the development of their knowledge (emphasis is placed on tacit knowledge). Knowledge management is also part of informatics, information management, data governance, because the acquisition, evaluation, storage and extraction of data is an important part of the strategic management of a business (the emphasis is on explicit knowledge).
Learning outcomes
After successfully completing the course, the student will:
• understand the basic concepts of knowledge management and explain the difference between data, information, knowledge and wisdom in the context of Industry 4.0 and 5.0,
• distinguish between sources and types of knowledge and explain the functioning of knowledge systems,
• analyze the factors influencing the implementation of knowledge management in practice and explain the role of knowledge transfer and new technologies,
• explain the essence of a knowledge-oriented organization and the strategic context of change management,
• explain the principles of adaptation and characterize a learning organization, including adaptive models and strategies,
• describe modern technologies used in Industry 4.0 and 5.0 (ERP systems, IoT, IoE, shared data, virtualization, augmented reality) and evaluate their impacts on knowledge management,
• use basic methods of knowledge modeling and simulation, explain the principles of autonomous robotics and reverse engineering,
• will explain the principles of data collection and processing (Big Data, statistical methods) and evaluate their relevance and cost,
• analyze the performance of knowledge-oriented companies, describe the principles of clusters and knowledge groups,
• clarify the relationship between information and knowledge management and the methodological foundations of system integration,
• critically assess the barriers and paradoxes of knowledge management (e.g. knowledge noise) and suggest ways to overcome them,
• apply the principles of intellectual property protection in the context of knowledge management and evaluate the importance of knowledge as a strategic resource for a company.
Syllabus
  • 1. Introduction to the issue of knowledge management. Definition of the term knowledge management. Data, information, knowledge, wisdom - their importance in the era of Industry 4.0 (marketing, business, services, work, etc.).
  • 2. Knowledge competence and expansion of the concept of knowledge. Sources, properties and types of knowledge. Knowledge and knowledge system.
  • 3. Factors determining the implementation of knowledge management. Knowledge transfer, new technologies - research and development outputs in business practice. Perspectives for combining the academic and application spheres.
  • 4. Strategically oriented management and knowledge-oriented organization. Context of necessary changes.
  • 5. The issue of adaptation and its framework understanding. Adaptive and active human activity. The essence and place of adaptation in business practice. Adaptation and learning organizations (the essence and goals of adaptation and learning in learning organizations; adaptive models; strategies of learning-based organizations).
  • 6. Industry 4.0 technologies with a focus on knowledge management – ​​remote collaboration, enterprise applications, IS, ERP, shared data, RFID, IoT and M2M, Internet of Everything (IoE – Internet of Things, People, Processes and Data).
  • 7. Adaptation and learning algorithms. Introduction to knowledge simulation and modeling. The essence of modeling methods. Autonomous robotics, reverse engineering, shadowing of production, additive manufacturing, augmented reality, virtualization, virtual reality.
  • 8. Learning organizations. Characteristics of a learning organization. Knowledge-driven organizations. System approach to learning. How to proceed in research, statistical methods of data processing, Big Data. Data collection and processing (relevance, validation, costs).
  • 9. Performance management of knowledge-based enterprises. Factors determining the need for management in strategic contexts. Knowledge groups and clusters.
  • 10. The relationship between information and knowledge management. Methodological basis of system integration. Knowledge needs.
  • 11. Paradoxes associated with knowledge management. Knowledge noise. Knowledge barriers.
  • 12. Knowledge and knowledge management as a science. The necessity of an offensive understanding of the role of management. protection of intellectual property.
Literature
    required literature
  • ŠIMKOVÁ, Eva a HOFFMANNOVÁ, Martina. Znalostní management v cestovním ruchu: Knowledge management in tourism = Wissensmanagement im Tourismus. Červený Kostelec: Pavel Mervart, 2022. ISBN 978-80-7465-566-1.
  • PILNÝ, Ivan. Digitální ekonomika: žít nebo přežít. V Brně: BizBooks, 2016. ISBN 978-80-265-0481-8.
  • PITRA, Zbyněk a Hana MOHELSKÁ. Management transferu znalostí: od prvního nápadu ke komerčně úspěšné inovaci. Praha: Professional Publishing, 2015. ISBN 978-80-7431-145-1.
  • VEBER, Jaromír. Digitalizace ekonomiky a společnosti: výhody, rizika, příležitosti. V nakladatelství Management Press vydání 1. Praha: Management Press, 2018. ISBN 978-80-7261-554-4.
  • BUJNA, Tomáš. Spojovat či rozdělovat? [organizování, koordinování a sdílení informací]. Praha: Management Press, 2015. ISBN 978-80-7261-278-9.
  • MAŘÍK, Vladimír a KEIL, Robert. Průmysl 4.0: základ ekonomické transformace ČR. V Praze: Management Press, 2024. ISBN 978-80-7261-604-6.
    recommended literature
  • MATOS, F., & ROSA, Á. (Eds.). Proceedings of the 24th European Conference on Knowledge Management (Vol. 24, No. 1). Reading, UK: Academic Conferences and Publishing International, 2023. ISBN 978-1-914587-73-3.
  • BORNEMANN, M. (Ed.). Blue Book on Knowledge Management – 2023. Berlin: KMGN, 2023. ISBN 978-1-914587-74-0.
Teaching methods
Teaching methods Teaching in the full-time form of study will be based on interactive lectures, in which theory will be supplemented with practical examples, based on which the student will form an idea of ​​the actual role of knowledge management (Knowledge Management) for the successful development of a company.
Teaching in the combined study will be carried out in the form of guided group consultations. It assumes continuous preparation of students for guided group consultations, in which the emphasis will be placed on practical applications with the aim of optimal use of knowledge from the given subject in business practice.
If contact teaching and consultations in the personal presence of the student in the full-time and combined forms of study are impossible, the teaching is replaced by a distance form of study (online transmission via MS TEAMS) and self-study.
Lectures
Explanation of the theoretical foundations of knowledge management using visualizations, models and diagrams for a better understanding of the relationships between data, information and knowledge. Presentation of examples from real practice of Czech and foreign companies (e.g. implementation of ERP systems, digitalization of production processes, use of big data in banking, AI in logistics). Analysis of case studies and discussion of successful and unsuccessful examples of knowledge management implementation. Linking theoretical concepts with current trends (Industry 4.0, 5.0, IoT, AI, reverse engineering, circular economy). Continuous assignment of topics for reflection and short tasks that students will work on using examples of specific companies or institutions. Support for self-study through recommended literature, professional articles and e-learning materials available in the IS.
Modern methods (supported by technologies) – motivation, higher interactivity Discussion and reflection – students actively participate in the evaluation of presented examples and formulate their own proposals for applying theory to practice. Collaborative environment (MS Teams) for joint knowledge modeling: knowledge maps, process maps, simple “as-is / to-be” ontologies. Working with data and visualizations: use of open data and corporate reports, creation of mini-dashboards (e.g. Power BI) to demonstrate information and knowledge flows. AI-assisted analysis: safe use of generative AI for summarizing sources, comparing approaches and proposing knowledge-workflows; emphasis on fact-checking. Simulation and “sandbox”: short KM implementation scenarios (deployment of wiki/knowledge base, change of workflow sharing), decision trees with impact evaluation. Micro-learning and “flipped classroom”: short videos/articles. Peer-review and portfolios: shared knowledge map and internal guidelines designs, mutual feedback and iteration; ongoing mini-artifacts (knowledge map, governance checklist, metric design). Knowledge management tools Confluence / Notion / SharePoint for corporate knowledge base prototypes. Ethics and compliance: checklists for information security, intellectual property protection and GDPR; data anonymization in student outputs.
Assessment methods
Conditions for completing the course:
1. Meet the minimum mandatory participation in exercises 75% in full-time study, 50% in guided group consultations in combined study and ISP students. If not met, the student will prepare a substitute seminar paper of at least 10 pages in the BP template. For this paper, the student chooses a topic and has it approved by the teacher. The condition is the use of at least 3 references from the ProQuest database available from IS.VSFS.
2. Prepare a seminar paper, the topic will be published during the course (at least 10 pages in the DP template).
3. The final assessment is in the form of a credit. The credit test will be carried out electronically - by an answer sheet in is.vsfs. The credit test consists of 8 questions (the minimum for obtaining credit is 50% of points).
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is also listed under the following terms Winter 2019, Winter 2020, Summer 2027.
  • Enrolment Statistics (Summer 2026, recent)
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