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dc.contributor.authorKim, Jin-Young
dc.contributor.authorCanina, Linda
dc.date.accessioned2020-09-10T15:27:05Z
dc.date.available2020-09-10T15:27:05Z
dc.date.issued2009-09-01
dc.identifier.other6535235
dc.identifier.urihttps://hdl.handle.net/1813/71063
dc.description.abstractDespite the importance of accurately identifying a hotel’s competitors, determining those competitors is not a simple task. A common and easily implemented approach is to categorize products in terms of product type, but competition may occur across different types of products depending on how consumers perceive goods as substitutes. As an alternative, we identify the competitive set using cluster analysis based on hotels’ average daily rate (ADR). A cluster analysis of the ADR of 49 hotels in one urban tract in the U.S. found five competitive clusters, in which upscale properties were in some cases competing directly with economy hotels. This analysis indicates that some properties have a discrepancy between their intended product type and their perceived competitive position, based on ADR. By integrating and comparing the results of the two methods for the purpose of performance evaluation, managers, owners, analysts, and investors can ascertain the market position of a hotel as determined by its guests, and make inferences regarding the hotel’s value proposition, property condition, service offerings, and management acumen. In particular, the analysis points out performance benchmarks for hotels that are underperforming their competitive set and those that are outperforming their competitors.
dc.language.isoen_US
dc.rightsRequired Publisher Statement: © Cornell University. This report may not be reproduced or distributed without the express permission of the publisher
dc.subjecthotels
dc.subjectcompetitors
dc.subjectaverage daily rate (ADR)
dc.subjectperformance benchmarking
dc.titleProduct Tiers and ADR Clusters: Integrating Two Methods for Determining Hotel Competitive Sets
dc.typearticle
dc.description.legacydownloadsKim_202009_20Product_20tiers.pdf: 484 downloads, before Aug. 1, 2020.
local.authorAffiliationCanina, Linda: lc29@cornell.edu Cornell University


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