Competitive Sets for Lodging Properties

Abstract

This article illustrates the differences in the composition, characteristics, and performance evaluation of competitive sets of hotels determined using two methods-the common product type classification scheme and the less commonly used cluster analysis based on average daily rate (ADR) as the clustering variable. The analysis examined annual ADR, occupancy, and revenue per available room (RevPAR) for a group of hotels in a portion of a single U.S. metropolitan market. The comparison of the two methods shows the following: the average variability of ADR and RevPAR is less for the cluster-based competitors than it is for competitor groups determined using product type; most clusters contain a variety of product types (confirming that competition occurs across product types); most product types are categorized into different clusters; and the average RevPAR difference between the particular hotel and its reference competitive group is less for the ADR-cluster-based reference group than it is for the product type reference group, indicating that the performance of hotels within cluster competitive groups is more similar than in product type competitive groups. Comparing competing hotels based on the two methods can provide information regarding the extent of congruence between the hotel's intended competitive position and its position as seen by customers.

The evolution of competitor data collection in the hotel industry and its application to revenue management and pricing

“…Another manager commented that there was so much focus on data that they took the eye off what was actually important in driving revenue and that was delivering customer service. Certainly the competitive market is related not just to firms but also to customers (Kim and Canina, 2011). So by looking purely at competitor movements through data, such as the STAR report, it might be possible to argue that managers are missing out on the richness of other data sources that could lead to customerfocussed, strategic pricing decisions.…”

Harvesting Online Reviews to Identify the Competitor Set in a Service Business: Evidence From the Hotel Industry

“…Competitor identification is, therefore, a vital initial step in market evaluation, service improvement, and strategy development (J. Y. Kim and Canina 2011). As information search is often customers' initial step, at which companies can affect their decision making, it is important to understand how online customers select hotels, especially in the era of big data.…”

Revenue management analysis with competitive sets

“…resource similarity) gauges the extent to which firms exhibit similar production and technological capabilities. Accordingly, the traditional approach in the lodging industry determines competitors along a mixed range of attributes, including hotel type and market segments, among other competing factors (Kim and Canina, 2010). Given the expanded availability of transparent rates and Internet tracking technology, customer-oriented hotels have begun to identify competitors based on their potential customers' consideration set by using clickstream data in which a consumer's search results, views, and purchasing process can be fully tracked (Chatterjee and Wang, 2012;Cross et al, 2009;Li and Netessine, 2012).…”

“…Managers and firms devise comp sets that cover a full range of product classes, including luxury, upper upscale, upscale, upper midscale, midscale, and economy, of other participating hotels (Smith and Zheng, 2011). Despite the broad use and acceptance of ADR and RevPAR as primary comparative measures throughout the lodging industry (Chipkin, 2007; Cross et al, 2009; Enz and Peiró-Signes, 2014; Kim and Canina, 2010), the reliability and integrity of both measures and comp sets has been called into question (e.g. Enz et al, 2001; Slattery, 2002).…”

“…At the same time, it is acknowledged that this comparative method of performance evaluation is not without its drawbacks (e.g. Kim and Canina, 2010). The present study focuses on one potential drawback: the nature of comp set’s membership and specifically on the inclusion/exclusion decision.…”