2020
PRICE ELASTICITY OF DEMAND FOR ACCOMODATION SERVICES – EMPIRICAL APPLICATION IN PRAGUE
PETŘÍČEK, Martin a Štěpán CHALUPAZákladní údaje
Originální název
PRICE ELASTICITY OF DEMAND FOR ACCOMODATION SERVICES – EMPIRICAL APPLICATION IN PRAGUE
Název anglicky
PRICE ELASTICITY OF DEMAND FOR ACCOMODATION SERVICES – EMPIRICAL APPLICATION IN PRAGUE
Autoři
PETŘÍČEK, Martin a Štěpán CHALUPA
Vydání
AD ALTA: JOURNAL OF INTERDISCIPLINARY RESEARCH, HRADEC KRALOVE, MAGNANIMITAS, 2020, 1804-7890
Další údaje
Typ výsledku
Článek v odborném periodiku
Utajení
není předmětem státního či obchodního tajemství
Organizační jednotka
University College Prague – Vysoká škola mezinárodních vztahů a Vysoká škola hotelová a ekonomická s.r.o.
UT WoS
000562038200037
Klíčová slova anglicky
Price Elasticity, Demand, Price Optimization, Consumer Behavior
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 15. 12. 2020 08:00, Ing. Štěpán Chalupa, Ph.D.
V originále
The paper focuses on the issue of measuring price elasticity of demand. Research has available a significant data sample on a daily basis in the segment of accommodation services since 2005 in the Czech Republic. The aim of the paper is to evaluate the development of consumer behaviour (measured by price elasticity) in the monitored segment from 2005 to the year 2017. For the calculation of price elasticity log-log regression analysis is used. The data is available daily, and therefore the resulting elasticity in the article is compared to several levels (working days, weekdays, summer months). One of the primary outputs in the research is that price elasticity is relatively stable in the monitored levels over time but has changed significantly over the long-term period.
Anglicky
The paper focuses on the issue of measuring price elasticity of demand. Research has available a significant data sample on a daily basis in the segment of accommodation services since 2005 in the Czech Republic. The aim of the paper is to evaluate the development of consumer behaviour (measured by price elasticity) in the monitored segment from 2005 to the year 2017. For the calculation of price elasticity log-log regression analysis is used. The data is available daily, and therefore the resulting elasticity in the article is compared to several levels (working days, weekdays, summer months). One of the primary outputs in the research is that price elasticity is relatively stable in the monitored levels over time but has changed significantly over the long-term period.