D 2019

Behavioral Segmentation of Hotel Customers: An Empirical Study

CHALUPA, Štěpán, Jan CHROMÝ and Petr ČECH

Basic information

Original name

Behavioral Segmentation of Hotel Customers: An Empirical Study

Authors

CHALUPA, Štěpán (203 Czech Republic, guarantor, belonging to the institution), Jan CHROMÝ (203 Czech Republic, belonging to the institution) and Petr ČECH (203 Czech Republic, belonging to the institution)

Edition

Granada, Proceedings of the 33rd International Business Information Management Association Conference, p. 2113-2119, 7 pp. 2019

Publisher

International Business Information Management Association

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

50204 Business and management

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

storage medium (CD, DVD, flash disk)

Organization unit

University College Prague – University of International Relations and Institute of Hospitality Management and Economics, Ltd.

ISBN

978-0-9998551-2-6

UT WoS

000503988803057

Keywords in English

Customer segmentation; Cluster Analysis; Marketing Analysis

Tags

International impact, Reviewed
Změněno: 5/3/2020 07:52, Ing. Bc. Jan Chromý, Ph.D.

Abstract

V originále

The paper focuses on the use of cluster analysis for hotel customers’ segmentation and its possible application within the hotel marketing mix. Study works with Two-Step Cluster analysis that allows clustering of quantitative and nominal data. Main results show that using booking window (the period between reservation creation and date of arrival), distribution channel, length of stay (in days) and net room rate to cluster hotel customers into homogenous segments can be beneficial during the process of customer segmentation. Six basic customer segments were identified and lately described mainly by their behaviour in time, and money spends for a single reservation. The paper directly describes the whole methodology of Two-Step Clustering and possible outputs that can be used in revenue management research.
Displayed: 22/11/2024 05:45