Identifying hotel competitiveness based on hotel feature ratings

Haiyang Xia, Huy Quan Vu, Qiujun Lan, Rob Law, Gang Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

Identification of hotel competitiveness is crucial for hotel managers in developing effective marketing strategies and promoting their business. A common practice in representing hotel competitiveness is to advertise hotel features with high customer ratings as selling points. However, this approach is ineffective to clearly distinguish top-tier hotels with similar high ratings, while low-tier hotels are disadvantaged because of their low ratings. This study presents a new approach for hotel competitiveness evaluation by identifying the unique aspects that combine multiple features. The proposed approach could distinguish a hotel from its counterparts, rather than rely solely on the high ratings of hotel features. We introduce a data mining technique to automatically discover the distinct aspects of a hotel based on the ratings of hotel features. The proposed method is beneficial to researchers and hotel managers in evaluating hotel competitiveness and identifying critical features that need improvement to considerably attract potential customers.

Original languageEnglish
Pages (from-to)81-100
Number of pages20
JournalJournal of Hospitality Marketing and Management
Volume28
Issue number1
DOIs
Publication statusPublished - 2 Jan 2019

Keywords

  • data mining
  • feature ratings
  • Hotel competitiveness
  • hotel reviews
  • kernel destiny estimation

ASJC Scopus subject areas

  • Management Information Systems
  • Tourism, Leisure and Hospitality Management
  • Marketing

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