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Clustering benefits for upscale urban hotels

Clustering benefits for upscale urban hotels PurposeThe aim of this paper is twofold. First, clustering patterns of urban hotels are explored, and, second, clustering effects on performance for upscale urban hotels are estimated.Design/methodology/approachLocal indicators of spatial association (LISA) were computed using geographic information system (GIS) techniques. Clustering for the entire population of hotels in Madrid was explored visualizing LISA statistics. Then, a system generalized method of moments regression was applied to test a set of hypotheses about the performance effects of LISA statistics for a sample of upscale urban hotels.FindingsTwo significantly distinct types of clusters are identified: dense “cold spots” or clusters containing many low-priced hotels and quiet “hot spots” or clusters only containing a few high-priced hotels. And, estimates confirmed two important results: evidence of adverse selection when clustering and evidence of positive location economies for upscale hotels.Practical implicationsThis study has a number of relevant implications for making better hotel location decisions. Specifically, the paper shows the applicability of GIS to find statistically significant clustering in the data. In the hotel sector, knowing exactly where hotel clustering occurs and of what type is of vital importance.Originality/valueThis paper’s novel application of LISA based on GIS techniques for hotel clustering sheds light on the effects of clustering on performance to convey the subtle nuances of the relationship for upscale urban hotels. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Contemporary Hospitality Management Emerald Publishing

Clustering benefits for upscale urban hotels

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References (69)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0959-6119
DOI
10.1108/IJCHM-10-2015-0583
Publisher site
See Article on Publisher Site

Abstract

PurposeThe aim of this paper is twofold. First, clustering patterns of urban hotels are explored, and, second, clustering effects on performance for upscale urban hotels are estimated.Design/methodology/approachLocal indicators of spatial association (LISA) were computed using geographic information system (GIS) techniques. Clustering for the entire population of hotels in Madrid was explored visualizing LISA statistics. Then, a system generalized method of moments regression was applied to test a set of hypotheses about the performance effects of LISA statistics for a sample of upscale urban hotels.FindingsTwo significantly distinct types of clusters are identified: dense “cold spots” or clusters containing many low-priced hotels and quiet “hot spots” or clusters only containing a few high-priced hotels. And, estimates confirmed two important results: evidence of adverse selection when clustering and evidence of positive location economies for upscale hotels.Practical implicationsThis study has a number of relevant implications for making better hotel location decisions. Specifically, the paper shows the applicability of GIS to find statistically significant clustering in the data. In the hotel sector, knowing exactly where hotel clustering occurs and of what type is of vital importance.Originality/valueThis paper’s novel application of LISA based on GIS techniques for hotel clustering sheds light on the effects of clustering on performance to convey the subtle nuances of the relationship for upscale urban hotels.

Journal

International Journal of Contemporary Hospitality Management – Emerald Publishing

Published: May 8, 2017

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