This study aims to present a taxonomic framework that categorizes hotel loyalty program members on the basis of involvement and a mix of behavioral outcome variables.
The taxonomy is derived through mixture modeling from a sample of 1,395 loyalty program members of two global hotel chains.
Study results suggest the presence of four classes of program members across both hotels. Class members differ with respect to the attitudes they hold, the behaviors they exhibit, and the motivations they have for maintaining membership in the program.
First, the study enhances understanding of member differences that exist within loyalty programs. Second, the study advances understanding of the ways through which loyalty programs can best be managed. Third, the study illustrates the usefulness of mixture modeling as a classificatory tool.
Study results are not generalizable beyond the sample used in deriving them. Further, decisions pertaining to what variables to include in developing a taxonomic framework are critical to its usefulness. The choice to include certain variables as well as their related measures, to the exclusion of others, represents a second limitation.
The study is but the second to empirically categorize loyalty program members, and the first to do so in a services context. Two classes of high‐involvement customers emerge, each with contrasting attitudes and behaviors. Thus, our findings suggest that high levels of involvement invoke the most extreme of customer attitudes and behaviors.
