Course detail

Modern Methods in Economic Decision-making

FP-merDAcad. year: 2020/2021

Subpart 1 – Selected mathematical methods in economic decision-making
1. Approximation of functions: Discrete function, approximation using least squares method
and cubic spline, applications in demand analysis
2. Graph theory: Undirected and directed graphs, weighted graphs, Dijkstra´s algorithm for finding the shortest path Kruskal´s algorithm for finding the minimal spanning tree
3. Fuzzy mathematics: Fuzzy propositions, fuzzy sets, operations on fuzzy sets, applications in economic analysis

Subpart 2 – Advanced methods in strategic decision-making
The course is focused on the following areas: properties and characteristics of successful companies (Framework "7S" factors of successful businesses, case study: Businessman S. Walton - founder of Wall Mart stores). The influence of environment on the company. Basic principles of change processes of the company. Models of planned changes in the company (Levin model, Jaguar model, model Nokia). Change and risk. Types and risk analysis. Measurement of risk. Basic statistical characteristics of risk. Methods of reducing risk in management and its analysis (methods of removing the causes of risk, methods of reducing the effect of the risk). The basis of investment mathematics and methodology of investment decision. Reducing of the risk and evaluation of the investment in personal or corporate investment (case study). The risk connected with the change of the company's strategy including the methodology of the change strategy. Forecasting - tool for reducing the risk in the economic life of the company. Forecasting - tool to reduce risk in the economic life of the company. To acquaint students with selected advanced methods of analysis and economic modeling techniques (fuzzy logic, artificial neural networks, genetic algorithms) by explaining the principles of these theories and their subsequent application to managerial practice. The goal of the course is to familiarize students with some non-standard advanced methods of analysis and modeling techniques in economics and finance in the form of an explanation of the principles of these theories, to learn with these theories and their applications. The knowledge and skills obtain in the course will help to students obtain modern approach to the analysis and modeling of the national economy and private sector organizations, businesses, companies, banks, etc.

Language of instruction

Czech

Number of ECTS credits

0

Mode of study

Not applicable.

Learning outcomes of the course unit

Subpart 1 – Selected mathematical methods in economic decision-making
Development of the ability to describe economic relationships by means of exact tools as a precondition to make economic decisions on advanced level.
Subpart 2 – Advanced methods in strategic decision-making
Written project - creating a model of optimal time management
1. Critical analysis of selected problem (eg project management of production, the project of construction of the house, management of research, etc.).
2. Modeling of the project by suitable method of network analysis (CPM, PERT, etc.).
3. Finding the critical path and its managerial interpretation
4. Extending the duration of noncritical activities to become the part of the critical path, management discussion of this problem
5. Recommendations for the management, including the project risk policy

Prerequisites

The subject knowledge on the MSc studies is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Lectures, consultations in practice

Assesment methods and criteria linked to learning outcomes

Subpart 1 – Selected mathematical methods in economic decision-making
The course continues in summer term of the 1st year of study and is completed with final exam. Classification of partial assessment from winter semester is included in the final exam classification. For the realization of the term assessment is necessary to carry out a written materials containing solutions to the following tasks 1-5:
1.Aproximate a discrete function given at 10 points describing the relation between the price of a good and the quantity demanded using a linear function or parabola or other curve (except hyperbola type) by means of least squares method. For the demand function obtained calculate the price elasticity of demand and give an advice how to change the current price to increase total revenue.
2. Approximate a discrete function given at 5 points by cubic spline.
3. Find the shortest path in a weighted graph with at least with 10 vertices using Dijkstra´s algorithm.
4. Find the minimal spanning tree in a weighted graph with at least 10 vertices using Kruskal´s algorithm.
5.Describe and analyze a real economic situation using one of themes 2, 3 or their combination.

Subpart 2 – Advanced methods in strategic decision-making
1. Clear targeted analysis with conclusions
2. Management views and interpretations of the proposed solution form with the citation conditions.
The work does not exceed 20 pages (additional information can be inserted into Annex)
The course Modern methods in economic decision-making is completed with final exam, that consists of partial exams from Subpart 1 and Subpart 2. The completion of the partial exam from Subpart 1 ( Selected methods in economic decision-making-prof. Mezník) must precede the partial exam from Subpart 2. The overall marking of the whole course is assessed by the garant prof. Rais.

Course curriculum

Syllabus is in accordance with the contents.

Work placements

Not applicable.

Aims

Subpart 1 – Selected mathematical methods in economic decision-making
To provide students with advanced mathematical tools used in economic decision making
Subpart 2 – Advanced methods in strategic decision-making
1. Critically analyze specific situation and propose appropriate decision-making methods
2. To acquaint students with advanced methods of management decisions.
3. Presentation of case studies for strategic decision of the management

Specification of controlled education, way of implementation and compensation for absences

concentration of PhD students, oral exam added by written project

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Jablonský Josef : Operační výzkum. Kvantitativní metody pro ekonomické rozhodování. Praha. Professional Publishing 2002. ISBN 80-86419-23-1. (CS)
ALLEN, R., S., D.: Mathematical Analysis for Economists. St. Martin´s Press, New York 1968 (EN)
JACQUES, I. : Mathematics for Economics and Business. Addison Wesley Publ. Comp., New York 1995 (EN)
MAROŠ, B., MAROŠOVÁ, M. : Základy numerické matematiky. FSI VUT v Brně, Brno 2001 (CS)
MEZNÍK, I. : Úvod do matematické ekonomie pro ekonomy. Akademické nakladatelství CERM, s.r.o., Brno 2011 (CS)
SIMON, C. P.: Mathematics for Economists. W.W. Norton Comp., New York 1994 (EN)
HARARY, F. : Graph Theory . Addison – Wesley, New York 1972 (EN)
MATOUŠEK, J., NEŠETŘIL, J. : Kapitoly z diskrétní matematiky. Nakladatelství Karolinum, Praha 2000 (CS)
MEZNÍK, I. : Diskrétní matematika pro užitou informatiku. Akademické nakladatelství CERM s.r.o., Brno 2013 (CS)
ROSEN, K.H.: Discrete Mathematics and its Applications. Mc Graw-Hill, New York 1999 (EN)
JURA, P.: Základy fuzzy logiky pro řízení a modelování. Nakladatelství VUTIUM VUT v Brně, Brno 2003 (CS)
KAUFMANN, A.: Introduction to the Theory of Fuzzy Subsets. Academic Press, New York 1975 (EN)
NOVÁK,V.: Základy fuzzy modelování. Nakladatelství BEN, Praha 2000 (CS)
ZADEH, L. A.: Fuzzy Sets. Information and Control 8 (1965), 338-353 (EN)
Smejkal,V., Rais,K.: Řízení rizik ve firmách a jiných organizacích. Grada,Praha Publishing, 2013,Čtvrté vydání.Str. 483. (CS)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme DSP-KS Doctoral

    branch DSP-ŘEP-KS , 1. year of study, summer semester, compulsory

  • Programme DSP Doctoral

    branch DSP-ŘEP , 1. year of study, summer semester, compulsory

Type of course unit

 

Seminar

20 hours, optionally

Teacher / Lecturer