Detailed Information on Publication Record
2024
Understanding customer's online booking intentions using hotel big data analysis
CHALUPA, Štěpán and Martin PETŘÍČEKBasic information
Original name
Understanding customer's online booking intentions using hotel big data analysis
Authors
CHALUPA, Štěpán and Martin PETŘÍČEK
Edition
Journal of Vacation Marketing, Sage, 2024, 1356-7667
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Confidentiality degree
není předmětem státního či obchodního tajemství
Organization unit
University College Prague – University of International Relations and Institute of Hospitality Management and Economics, Ltd.
UT WoS
000847837600001
Keywords in English
Price elasticity of demand, hotel market segmentation, cluster analysis, hospitality marketing, hospitality e-commerce
Tags
International impact, Reviewed
Změněno: 4/6/2024 09:20, Ing. Štěpán Chalupa, Ph.D.
Abstract
V originále
The presented article focuses on the issue of customer segmentation in the hospitality industry and its use for price optimisation. To identify the market segments article uses the Two-Step cluster analysis. The analysis was based on the seven variables (length of stay, average room rate, distribution channel, reservation day, day of arrival, lead time and payment conditions). Six clusters were identified as following segments: Corporates, Early Bird Bookers, Last Minute Bookers, Product Seekers, Values Seekers and Last Minute Bookers. To optimise the price for these segments, article works with the coefficient of price elasticity of demand for the presented market segments. The price elasticity of demand is measured by the log-log regression analysis. Data were colected from the four-star hotel in Prague, Czech Republic and analysis is based on more than 9000 transactions. Last minute bookers segment was the only one with the positive coefficient of price elasticity and has the lowest value of lead time (9,27 in average). Product seekers have the highest coefficient of price elasticity (−3,413) and highest average room rate (3573 CZK in average). Early bird bookers, Long time stayers, Corporates and Value seekers was identified as pricely inelastic.