Defining Competitive Sets of Hotel Brands Through Analysis of Customer Brand Switching

Morgan, Michael S.; Dev, Chekitan S.

doi:10.1300/j150v02n02_06

Cited by 8 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In terms of the consumers' perspective of competitor identification in the lodging market, Yesawich (1987) noted conceptually that substitutability of the properties is a matter of the guests' perception of the hotels in the same market area. Morgan and Dev (1994) identified the competitive set of the hotel brands based on the consumers' perspectives in terms of purpose of stay, satisfaction, and demographic measures.…”

Section: Literature Reviewmentioning

confidence: 99%

Competitive Sets for Lodging Properties

Kim

Canina²

2010

Cornell Hospitality Quarterly

View full text Add to dashboard Cite

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.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Competitive Sets for Lodging Properties

Kim

Canina²

2010

Cornell Hospitality Quarterly

View full text Add to dashboard Cite

show abstract

“…Benchmarking against the competition is a key element in the evaluation of hotel performance (e.g., Buckhiester, 2011; Smith & Zheng, 2011). These comparisons support stakeholders’ short-term operational decisions in activity domains such as marketing and revenue management and are also central for the longer-term strategic decisions of investment, asset management, brand positioning, and product mix (Love et al, 2012; Morgan & Dev, 1994). Specifically, a large and growing number of hotels in the United States, and globally, compare hotel key performance indicators (KPIs) such as the average daily rate (ADR), occupancy, and revenue per available room (RevPAR) with the averages of their competitive sets (compsets) (Chipkin, 2007; Cross et al, 2009; Enz et al, 2014; Kim & Canina, 2011; Schwartz et al, 2017; Watkins, 2017).…”

Section: Introductionmentioning

confidence: 97%

Resource Similarity, Market Commonality, and Spatial Distribution of Hotel Competitive Sets

Schwartz¹,

Webb

2021

Journal of Hospitality & Tourism Research

View full text Add to dashboard Cite

Index scores and competitive sets (compsets) play a critical role in the performance and evaluation of hotels. The reliance on these metrics has drawn skepticism in recent years as competitive sets may be opportunistically chosen, creating bias in performance evaluation. Drawing from the principal–agent theory and the theory of incentives, we explore whether the distance of the competitors chosen for a hotel’s compset influences revenue per available room (RevPAR) index scores. Based on the concepts of resource similarity and market commonality, we develop a novel mathematical model through which we empirically analyze a large dataset of 10,000 compsets. We find evidence that competitor distance influences index performance and that this relationship is bidirectional. Results show that hotels that outperform the competition may use distance to inflate RevPAR indices, while those that underperform may use distance to further reduce scores. These conflicting results may be reflected from the reverse motivations of the stakeholders.

show abstract

“…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). Earlier research has shown that comp sets vary according to consumer measures, including reason(s) for use, frequency of use, price, post-purchase satisfaction, and several demographic variables (Morgan and Dev, 1994). STR, the global leading provider of indices-benchmarking services, currently recommends attributes including price, location, restaurant service, room service, meeting space, complimentary breakfast, loyalty program, full-service amenities, and brand (Li and Netessine, 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Revenue management analysis with competitive sets

Webb

Schwartz

2016

Tourism Economics

View full text Add to dashboard Cite

Growing concerns about the integrity of the revenue per available room index—the lodging industry de facto performance measure—stem from previously published empirical evidence concerning the competitive set’s venerability and from management’s financial incentives to outperform the hotel’s competitive set. This study demonstrates the potential of the decision to include or exclude a hotel in, or from, competitive set averages to bias its performance index. The analysis shows that the bias potential is nonlinear and asymmetric in relation to the subject hotel’s revenues, and uses this revealed asymmetry to prove that when future relative performance levels are uncertain, exclusion tactics is preferred. Finally, the study demonstrates how the relative nature of the performance indicator, coupled with management potential opportunistic inclusion/exclusion competitive set tactics, are detrimental to the perceived desirability of co-opetition strategies.

show abstract

Defining Competitive Sets of Hotel Brands Through Analysis of Customer Brand Switching

Cited by 8 publications

References 15 publications

Competitive Sets for Lodging Properties

Competitive Sets for Lodging Properties

Resource Similarity, Market Commonality, and Spatial Distribution of Hotel Competitive Sets

Revenue management analysis with competitive sets

Contact Info

Product

Resources

About