PETŘÍČEK, Martin a Štěpán CHALUPA. MEASURING PRICE ELASTICITY AND ITS APPLICATION INTO THE REVENUE OPTIMIZATION PROCESS. Online. In 11th INTERNATIONAL CONFERENCE PROCEEDINGS - HOSPITALITY, TOURISM AND EDUCATION. Prague: Institute of Hospitality Management in Prague 8., 2019, s. 87-94. ISBN 978-80-87411-87-2.
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Základní údaje
Originální název MEASURING PRICE ELASTICITY AND ITS APPLICATION INTO THE REVENUE OPTIMIZATION PROCESS
Název anglicky MEASURING PRICE ELASTICITY AND ITS APPLICATION INTO THE REVENUE OPTIMIZATION PROCESS
Autoři PETŘÍČEK, Martin a Štěpán CHALUPA.
Vydání Prague, 11th INTERNATIONAL CONFERENCE PROCEEDINGS - HOSPITALITY, TOURISM AND EDUCATION, od s. 87-94, 8 s. 2019.
Nakladatel Institute of Hospitality Management in Prague 8.
Další údaje
Typ výsledku Stať ve sborníku
Utajení není předmětem státního či obchodního tajemství
Forma vydání elektronická verze "online"
Organizační jednotka University College Prague – Vysoká škola mezinárodních vztahů a Vysoká škola hotelová a ekonomická s.r.o.
ISBN 978-80-87411-87-2
Klíčová slova anglicky Demand, Elasticity, Price
Příznaky Mezinárodní význam, Recenzováno
Změnil Změnil: doc. Ing. Martin Petříček, Ph.D., učo 14750. Změněno: 28. 10. 2019 10:38.
Anotace
The paper focuses on various possibilities of measuring price elasticity of demand with the application of log-log regression analysis. The elasticity measured can be than an input for the optimization process. The critical element of this optimization is the value of the coefficient of price elasticity, which was in the given contribution (for the selected accommodation facility) to the value -0.297, which indicates a price inelastic demand. This approach also has some limitations. It assumes a regression function that is linear in parameters, and also it is only a simple regression. Despite this fact, the results are comparable to other approaches.
Anotace anglicky
The paper focuses on various possibilities of measuring price elasticity of demand with the application of log-log regression analysis. The elasticity measured can be than an input for the optimization process. The critical element of this optimization is the value of the coefficient of price elasticity, which was in the given contribution (for the selected accommodation facility) to the value -0.297, which indicates a price inelastic demand. This approach also has some limitations. It assumes a regression function that is linear in parameters, and also it is only a simple regression. Despite this fact, the results are comparable to other approaches.
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