Research Methods in Economic Systems of Tourism

Teachers

Included in study programs

Teaching results

In particular, students will acquire the following knowledge:
• The new institutional economic theory and the theory of transaction costs offer evidence of the
application of quantitative methods in the management of tourism enterprises, as it identifies the
source of transaction costs in the existence of imperfect information, the risk of opportunism and
specific assets.
• The student will get acquainted with the basic quantitative and statistical methods needed in
the analysis of economic systems in tourism, including the basics of descriptive, correlation and
regression analysis of cross-sectional data.
• The student theoretically distinguishes the type of data, i.e., he will be able to distinguish between
time, cross-sectional and panel data.
• In addition to basic statistical methods, the student will gain knowledge of the necessary
verification tests, including the possible occurrence of errors.
• The student will gain knowledge about the availability of suitable databases and information
resources.
Upon successful completion of the course, students will acquire the following skills:
• The student obtains data from available sources.
• The student applies basic analytical methods to input data.
• The student will be able to verify, test and reveal the basic methods of cross-sectional data analysis.
• The student will acquire basic skills in predicting time data using extra- and intrapolation methods.
Upon successful completion of the course, students will acquire the following competencies:
• Decision-making in conditions of information uncertainty.
• Analytical competencies.
• Decision-making based on objective data.
• Presentation and communication competencies.

Indicative content

Theoretical background in accordance with the new institutional economic theory and the theory
of transaction costs. Introduction and basics of quantitative and statistical methods, including the
selection of appropriate sources and databases. Descriptive statistics in tabular and graphical form.
Basic processing of time series, including the basics of prediction. Fundamentals of correlation and
regression analysis of cross-sectional data, including their testing, interpretation and presentation.

Support literature

1. LUKÁČIKOVÁ, Adriana, Martin LUKÁČIK a Karol SZOMOLÁNYI. (2022). Úvod do ekonometrie s jazykom R. Bratislava: Letra Edu, 372 s.
2. LUKÁČIKOVÁ, Adriana, Martin LUKÁČIK a Karol SZOMOLÁNYI. (2018). Úvod do ekonometrie s programom Gretl. Bratislava: Letra Edu, 345 s.
3. OKUMUS, Fevzi, S. Mostafa RASOOLIMANESH a Shiva JAHANI, eds. (2023). Cutting Edge Research Methods in Hospitality and Tourism [online]. Emerald Publishing Limited, s. 157-172. DOI: 10.1108/978-1-80455-063-220231010. ISBN 978-1-80455-064-9. Dostupné na internete: https://www.emerald.com/insight/content/doi/10.1108/978-1-80455-063-220231010/full/html
4. STEINHAUSER, Dušan a Ľuboš PAVELKA. (2021). Riadenie rizík v medzinárodnom obchode. Bratislava: Vydavateľstvo EKONÓM, 140 s.
5. STEINHAUSER, Dušan. (2022). Metódy výskumu v ekonomických systémoch cestovného ruchu a medzinárodnom podnikaní. Bratislava: Vydavateľstvo EKONÓM, 83 s.

Syllabus

1. Theoretical introduction and significance of analysis in accordance with the new institutional economic theory and the theory of transaction costs; 2. Introduction to quantitative and statistical methods, types of data, formulation of hypotheses; 3. Selection of information sources and databases; 4. Introduction to statistical and econometric software GRETL, possibilities of MS EXCEL; 5. Preparation of information sources and databases; 6. Descriptive statistics in MS EXCEL, GRETL and PAST programs; 7. Graphic data display options, scatter plots and box plots; 8. Basics of time series analysis, basics of prediction (intra- and extrapolation); 9. Correlation analysis in MS EXCEL, GRETL and PAST programs, basics of cluster analysis in PAST program; 10. Paired regression analysis of cross-sectional data in MS EXCEL and GRETL programs; 11. Multiregression analysis of cross-sectional data in MS EXCEL and GRETL programs; 12. Testing of regression analysis of cross-sectional data in the GRETL program, detection of errors of heteroskedasticity, collinearity, normal distribution of residues, confidence intervals; 13. Interpretation and presentation of results.

Requirements to complete the course

40% semestral project;
60% written exam.

Student workload

Total: workload 3 credits x 26 h = 78 h.
Attendance at seminars: 26 hours
Preparation for seminars: 10 hours
Semester semestral project: 22 hours
Preparation for the exam: 20 hours

Language whose command is required to complete the course

Slovak and English

Date of approval: 03.10.2023

Date of the latest change: 25.10.2023