Objectives and competences
The course Quantitative techniques in management enables students to formulate business problems that can be solved using quantitative methods, to select and apply appropriate quantitative methods for hypothesis testing, analyzing and interpreting results to solve problems, and to prepare research reports. Using case studies and computer programs, students develop competencies for independent individual and group solving of complex problems in management with selected quantitative methods, with an emphasis on critical valuating and ethical aspects of decision-making.
Content (Syllabus outline)
- Decision theory: basics of decision-making, complex decisions' analysis under complete uncertainty and risk, business and economic study cases. Computer support: Excel
- Multiple criteria decision-making: selected traditional methods based on multi-attribute / utility theory, the Analytic Hierarchy Process, with real-life applications in economics and business. Computer support: Expert Choice
- Statistics in Management: organizing and visualizing data, descriptive statistics, Basic probability and probability distributions, sampling and sampling distributions, Confidence intervals, Fundamentals of Hypothesis testing – selected tests, simple regresion, Statistical Applications in Quality Management.
- Project optimisation: project definition, project planning and scheduling (project duration and cost with CPM), project risk estimate (PERT), project control.
Learning and teaching methods
- interactive lectures
- case studies
- active individual and group work
Intended learning outcomes - knowledge and understanding
Upon successful completition of this course students:
1. Differentiate, select, and apply quantitative methods of statistical analysis and decision-making, as well as appropriate computer programs for collecting, preparing, and analyzing data. (PILO 3a)
2. Use advanced analytical techniques to discover patterns and trends in data, contributing to a better understanding of economic and business phenomena (PILO 2c).
3. Solve complex management problems using advanced multi-criteria decision-making, optimization, and statistical tools and methods, considering the appropriateness of data use and ethical aspects. (PILO 3a, PILO 4c)
4. Identify and resolve ethical dilemmas in expressing judgments on the importance of criteria and in data analysis with a proactive approach and collaboration, ensuring integrity and trust in analytical processes. (PILO 4a)
5. Demonstrate the ability to deeply interpret data and results and their use for informed decision-making. (PILO 1a)
6. Critically synthesize information and recognize the practical value of quantitative processes and methods for decision-making in management. (PILO 2c)
7. Lead and effectively participate in groups, using various approaches to optimize teamwork, resolve conflicts, and promote innovation. (PILO 3c)
8. Apply knowledge and skills to solve managerial problems. (PILO 2a)
9. Demonstrate initiative and a high level of personal responsibility in performing tasks, adhering to ethical, professional and international standards. (PILO 4c)
The PILO label (i.e., Programme Intended Learning Outcomes) defines the contribution of each listed intended learning outcome of a course towards achieving the general and/or subject-specific competencies or learning outcomes acquired through the programme.
Intended learning outcomes - transferable/key skills and other attributes
Upon successful completition of this course students:
1. Differentiate, select, and apply quantitative methods of statistical analysis and decision-making, as well as appropriate computer programs for collecting, preparing, and analyzing data. (PILO 3a)
2. Use advanced analytical techniques to discover patterns and trends in data, contributing to a better understanding of economic and business phenomena (PILO 2c).
3. Solve complex management problems using advanced multi-criteria decision-making, optimization, and statistical tools and methods, considering the appropriateness of data use and ethical aspects. (PILO 3a, PILO 4c)
4. Identify and resolve ethical dilemmas in expressing judgments on the importance of criteria and in data analysis with a proactive approach and collaboration, ensuring integrity and trust in analytical processes. (PILO 4a)
5. Demonstrate the ability to deeply interpret data and results and their use for informed decision-making. (PILO 1a)
6. Critically synthesize information and recognize the practical value of quantitative processes and methods for decision-making in management. (PILO 2c)
7. Lead and effectively participate in groups, using various approaches to optimize teamwork, resolve conflicts, and promote innovation. (PILO 3c)
8. Apply knowledge and skills to solve managerial problems. (PILO 2a)
9. Demonstrate initiative and a high level of personal responsibility in performing tasks, adhering to ethical, professional and international standards. (PILO 4c)
The PILO label (i.e., Programme Intended Learning Outcomes) defines the contribution of each listed intended learning outcome of a course towards achieving the general and/or subject-specific competencies or learning outcomes acquired through the programme.
Readings
Obvezna študijska literature (Compulsory textbooks):
Izbrana poglavja iz:
Salacinski, T., Chrzanowski, J., Chmielewski, T. (2023). Statistical Process Control Using Control Charts with Variable Parameters, Proceses, 11. 2744 (Dosegljivo 6.4.2024 na: https://www.mdpi.com/2227-9717/11/9/2744)
Render, B., Stair, R. M., Hanna, M. E., & Hale, T. S. (2018). Quantitative Analysis For Management (13. izd.). Harlow: Pearson.
Taherdoost, H., Madanchian, M. (2023). Multi-Criteria Decision Making (MCDM) Methods and Concepts. Encyclopedia, 3, 77-87. (Dosegljivo 6. 4. 2024 na: https://www.mdpi.com/2673-8392/3/1/6)
Dodatna študijska literature (Additonal textbooks):
Selected Chapters from:
- Doumpos, M., Figueira, J. R., Greco, S., Zopounidis, C. (2019). New Perspectives in Multiple Criteria Decision Making: Innovative Applications and Case Studies. Cham: Springer.
- Čančer, V. (2023). A hybrid multi-criteria and creative, problemsolving approach, for measuring local values of information technology products. Acta polytechnica Hungarica, 20(2), 205-221. (Dosegljivo 6. 4. 2024 na: http://acta.uni-obuda.hu/Cancer_131.pdf)
Additional information on implementation and assessment • Active participation at lectures and tutorials (20%)
• Written exam (50%)
• Project work (30%)
Active participation at lectures and tutorials - shorter tasks than can be solved within lectures and tutorials and within one week
Written exam - a written exam with tasks covering all major topics. For a positive grade, written exam must be positive. Positive means at least 56 %.
Project work - students create project papers in which they define the economic-business problem, and analyse and solve it with selected quantitative methods.
