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| dc.rights.license |
CC BY |
eng |
| dc.contributor.author |
Chalupa, Štěpán |
cze |
| dc.contributor.author |
Petříček, Martin |
cze |
| dc.date.accessioned |
2025-12-05T09:53:34Z |
|
| dc.date.available |
2025-12-05T09:53:34Z |
|
| dc.date.issued |
2020 |
eng |
| dc.identifier.issn |
2217-8309 |
eng |
| dc.identifier.uri |
http://hdl.handle.net/20.500.12603/1209 |
|
| dc.description.abstract |
Understanding customer behaviour is an essential activity for hotel marketers and revenue managers. This article presents the statistical approach based on the data mining techniques focused on the extraction of valuable insight from big data. Using Two-Step Clustering, four major customers segments were identified, including their characteristics. Their description based on the booked room type, rate plan, booking window, net average room rate and length of stay can help the manager to plan better their activities. |
eng |
| dc.format |
p. 1088-1093 |
eng |
| dc.language.iso |
eng |
eng |
| dc.publisher |
UIKTEN |
eng |
| dc.relation.ispartof |
TEM Journal : Technology, Education, Management, Informatics, volume 9, issue: 3 |
eng |
| dc.subject |
Market segmentation |
eng |
| dc.subject |
cluster analysis |
eng |
| dc.subject |
Two-Step Cluster |
eng |
| dc.subject |
Hospitality marketing |
eng |
| dc.subject |
Revenue Management |
eng |
| dc.title |
Using Customer Characteristics to Manage Marketing and Revenue Management Activities |
eng |
| dc.type |
article |
eng |
| dc.identifier.obd |
43877474 |
eng |
| dc.identifier.doi |
10.18421/TEM93-33 |
eng |
| dc.publicationstatus |
postprint |
eng |
| dc.peerreviewed |
yes |
eng |
| dc.source.url |
https://www.temjournal.com/content/93/TEMJournalAugust_1088_1093.pdf |
cze |
| dc.relation.publisherversion |
https://www.temjournal.com/content/93/TEMJournalAugust_1088_1093.pdf |
eng |
| dc.rights.access |
Open Access |
eng |
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