CHALUPA, Štěpán and Martin PETŘÍČEK. Understanding customer's online booking intentions using hotel big data analysis. Journal of Vacation Marketing. Sage, 2024, vol. 30, No 1, p. 110-122. ISSN 1356-7667. Available from: https://dx.doi.org/10.1177/13567667221122107.
Other formats:   BibTeX LaTeX RIS
Basic 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
Original language English
Type of outcome Article in a journal
Confidentiality degree is not subject to a state or trade secret
Organization unit University College Prague – University of International Relations and Institute of Hospitality Management and Economics, Ltd.
Doi http://dx.doi.org/10.1177/13567667221122107
UT WoS 000847837600001
Keywords in English Price elasticity of demand, hotel market segmentation, cluster analysis, hospitality marketing, hospitality e-commerce
Tags International impact, Reviewed
Changed by Changed by: Ing. Štěpán Chalupa, Ph.D., učo 10522. Changed: 4/6/2024 09:20.
Abstract
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.
PrintDisplayed: 21/7/2024 20:09