Empirical Marketing Research
- Credits: 10
- Ending: Examination
- Range: 16sP
- Semester: winter
- Year: 2
- Faculty of Commerce
Teachers
Included in study programs
Teaching results
Knowledge:
The graduate of the course expands his knowledge of the latest trends in marketing research from the perspective of academic work and published empirical research. Through the study of scientific articles, he deepens his overview of currently used scientific methods and the essence of marketing research at present.
Competences:
The graduate is able to read scientific studies and critically evaluate their results. He is able to formulate a research problem into his dissertation, set the main goal and propose methods to meet it.
Skills:
The graduate is able to decide on the choice of method of data collection and their detailed analysis. It will control the methods of data processing and editing. They will be able to independently develop their knowledge in the field of statistical methods and the use of modern software, will understand empirical studies in the field of marketing and will be able to apply them in new areas of their focus.
Indicative content
Marketing research. Quantitative methods. Machine learning and statistical classification.
Support literature
Literatúra:
1. Anderson, D. R. et al. (2018). An introduction to management science: quantitative approach. Boston: Cengage learning.
2. Baumöhl, E., Čvirik, M., Kukura M., Ševčíková, R. (2023). Manažérske rozhodovanie v marketingu. Bratislava: Vydavateľstvo Ekonóm.
3. Hair Jr, J., Page, M., & Brunsveld, N. (2020). Essentials of business research methods. New York: Routledge.
4. Lyócsa, Š., Baumöhl, E., Výrost, T. (2013). Kvantitatívne metódy v ekonómii II. Košice : ELFA, 2013.
5. McDaniel Jr, C., Gates, R. (2018). Marketing research. Hoboken: John Wiley & Sons.
6. Výrost, T., Baumöhl, E., Lyócsa, Š. (2013). Kvantitatívne metódy v ekonómii III. Košice: ELFA.
Články:
1. Baumöhl, E. (2019). Are cryptocurrencies connected to forex? A quantile cross-spectral approach. Finance Research Letters, 29, 363-372.
2. Baumöhl, E., Iwasaki, I., Kočenda, E. (2019). Institutions and determinants of firm survival in European emerging markets. Journal of Corporate Finance, 58, 431-453.
3. Cortez, R. M., Clarke, A. H., Freytag, P. V. (2021). B2B market segmentation: A systematic review and research agenda. Journal of Business Research, 126, 415-428.
4. Di Domenico, G., Sit, J., Ishizaka, A., Nunan, D. (2021). Fake news, social media and marketing: A systematic review. Journal of Business Research, 124, 329-341.
5. Kienzler, M., Kowalkowski, C. (2017). Pricing strategy: A review of 22 years of marketing research. Journal of Business Research, 78, 101-110.
6. Lyócsa, Š., Baumöhl, E., Výrost, T. (2022). YOLO trading: Riding with the herd during the GameStop episode. Finance Research Letters, 46, 102359.
7. Lyócsa, Š., Baumöhl, E., Výrost, T., Molnár, P. (2020). Fear of the coronavirus and the stock markets. Finance Research Letters, 36, 101735.
8. Rust, R. T., Rand, W., Huang, M. H., Stephen, A. T., Brooks, G., Chabuk, T. (2021). Real-time brand reputation tracking using social media. Journal of Marketing, 85(4), 21-43.
9. Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333-339.
10. Vlačić, B., Corbo, L., e Silva, S. C., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187-203.
Syllabus
1. Practical examples of scientific empirical work on selected articles. 2. Linear regression analysis, assumption testing, software support. 3. Cross-sectional data and testing of time series properties. 4. Measures of dependence on average and in quantiles. 5. Panel regression analysis. 6. Basic machine learning techniques, statistical classification, cluster analysis. 7. Experimental and behavioral economics. 8. Preparation and consultations for individual seminar papers.
Requirements to complete the course
40% semester work
60% written exam
Student workload
Workload: 260 hours
Attendance at seminars: 16 hours
Preparation for seminars: 84 hours
Elaboration of a semester project: 60 hours
Preparation for the exam: 100 hours
Language whose command is required to complete the course
Slovak, English
Date of approval: 02.04.2023
Date of the latest change: 17.10.2023