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Lecturer(s)
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Petříček Martin, doc. Ing. Ph.D.
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Course content
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Revenue management in services and its importance in the company. Methods of client segmentation. Prediction methods as part of revenue management. Optimization and tools used in revenue management. Current trends in the development of revenue management models.
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Learning activities and teaching methods
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unspecified
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| learning outcomes |
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| Knowledge |
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| Students will gain a deeper understanding of what revenue management means in a service context, particularly in hospitality, and its importance to the business. |
| Students will gain a deeper understanding of what revenue management means in a service context, particularly in hospitality, and its importance to the business. |
| Gain knowledge of different customer segmentation methods and understand how these methods can be applied to effectively manage pricing and capacity. |
| Gain knowledge of different customer segmentation methods and understand how these methods can be applied to effectively manage pricing and capacity. |
| They will learn about various demand forecasting techniques, including the use of neural networks, and understand their use in revenue management. |
| They will learn about various demand forecasting techniques, including the use of neural networks, and understand their use in revenue management. |
| They will gain knowledge of optimization techniques and tools used in revenue management, including their practical application through software support such as the R programming language or statistical software. |
| They will gain knowledge of optimization techniques and tools used in revenue management, including their practical application through software support such as the R programming language or statistical software. |
| They will be kept informed of current trends and innovations in revenue management, enabling them to monitor and adapt to changing needs and trends in the industry. |
| They will be kept informed of current trends and innovations in revenue management, enabling them to monitor and adapt to changing needs and trends in the industry. |
| Skills |
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| Students will be able to analyse data and information to understand customer behaviour and market trends and develop strategies for effective price and capacity management. |
| Students will be able to analyse data and information to understand customer behaviour and market trends and develop strategies for effective price and capacity management. |
| They will gain skills in using specific software tools, such as the R programming language or statistical software, to implement and apply specific revenue management methods. |
| They will gain skills in using specific software tools, such as the R programming language or statistical software, to implement and apply specific revenue management methods. |
| They will be able to clearly present and communicate their ideas, analyses and recommendations in course discussions and presentations. |
| They will be able to clearly present and communicate their ideas, analyses and recommendations in course discussions and presentations. |
| They will be able to apply theoretical concepts and methodologies to real situations in the field of revenue management, which will enable them to gain practical experience. |
| They will be able to apply theoretical concepts and methodologies to real situations in the field of revenue management, which will enable them to gain practical experience. |
| They will be able to critically evaluate different approaches to revenue management and decide on their suitability and effectiveness in specific situations. |
| They will be able to critically evaluate different approaches to revenue management and decide on their suitability and effectiveness in specific situations. |
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Recommended literature
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IVANOV, S. Hotel Revenue Management: From Theory to Practice.. Zangador Research institute, 2014. ISBN 978-954-92786-3-7.
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PHILLIPS, R. L. Pricing and revenue optimization.. Stanford, California: Stanford Business Books, 2021. ISBN 978-1503610002.
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SHMUELI, G. Practical Time Series Forecasting with R: A Hands-On Guide. Axelrod Schnall Publishers, 2016. ISBN 978-0997847918.
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TALLURI, K. T., VAN RYZIN, G. The theory and practice of revenue management.. New York, NY: Springer, 2005. ISBN 978-0387243764.
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WILLIAM, P. F. Nonlinear Optimization ? Models and Applications. Chapman and Hall/CRC, 2021. ISBN 978-0367444150.
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