Hotel location evaluation: A combination of machine learning tools and web GIS

Yang Yang; Jingyin Tang; Hao Luo; Chun Hung Roberts Law

doi:10.1016/j.ijhm.2015.02.008

Hotel location evaluation: A combination of machine learning tools and web GIS

Yang Yang, Jingyin Tang, Hao Luo, Chun Hung Roberts Law

Research output: Journal article publication › Journal article › Academic research › peer-review

69 Citations (Scopus)

Abstract

The need for a reliable, unbiased, and objective assessment of hotel location has always been important. This study presents a new approach to evaluate potential sites for proposed hotel properties by designing an automated web GIS application: Hotel Location Selection and Analyzing Toolset (HoLSAT). The application uses a set of machine learning algorithms to predict various business success indicators associated with location sites. Using an example of hotel location assessment in Beijing, HoLSAT calculates and visualizes various desirable sites contingent on the specified characteristics of the proposed hotel. The approach shows considerable potential usefulness in the field of hotel location evaluation.

Original language	English
Pages (from-to)	14-24
Number of pages	11
Journal	International Journal of Hospitality Management
Volume	47
DOIs	https://doi.org/10.1016/j.ijhm.2015.02.008
Publication status	Published - 1 May 2015

Keywords

Hotel location
Machine learning
Spatial decision making
Web GIS

ASJC Scopus subject areas

Tourism, Leisure and Hospitality Management
Strategy and Management

More information

10.1016/j.ijhm.2015.02.008

Cite this

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abstract = "The need for a reliable, unbiased, and objective assessment of hotel location has always been important. This study presents a new approach to evaluate potential sites for proposed hotel properties by designing an automated web GIS application: Hotel Location Selection and Analyzing Toolset (HoLSAT). The application uses a set of machine learning algorithms to predict various business success indicators associated with location sites. Using an example of hotel location assessment in Beijing, HoLSAT calculates and visualizes various desirable sites contingent on the specified characteristics of the proposed hotel. The approach shows considerable potential usefulness in the field of hotel location evaluation.",

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AU - Tang, Jingyin

AU - Luo, Hao

AU - Law, Chun Hung Roberts

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AB - The need for a reliable, unbiased, and objective assessment of hotel location has always been important. This study presents a new approach to evaluate potential sites for proposed hotel properties by designing an automated web GIS application: Hotel Location Selection and Analyzing Toolset (HoLSAT). The application uses a set of machine learning algorithms to predict various business success indicators associated with location sites. Using an example of hotel location assessment in Beijing, HoLSAT calculates and visualizes various desirable sites contingent on the specified characteristics of the proposed hotel. The approach shows considerable potential usefulness in the field of hotel location evaluation.

KW - Hotel location

KW - Machine learning

KW - Spatial decision making

KW - Web GIS

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JO - International Journal of Hospitality Management

JF - International Journal of Hospitality Management

ER -

Hotel location evaluation: A combination of machine learning tools and web GIS

Abstract

Keywords

ASJC Scopus subject areas

More information

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