The goal of this study was to determine whether cluster analysis could be used to identify distinct subgroups of text message users based on behavioral economic indices of demand for text messaging. Cluster analysis is an analytic technique that attempts to categorize cases based on similarities across selected variables. Participants completed a questionnaire about mobile phone usage and a hypothetical texting demand task in which they indicated their likelihood of paying an extra charge to continue to send text messages. A hierarchical cluster analysis was conducted on behavioral economic indices, such as demand intensity, demand elasticity, breakpoint, and the maximum expenditure. With the cluster analysis, we identified 3 subgroups of text message users. The groups were characterized by (a) high intensity and low elasticity, (b) high intensity and medium elasticity, and (c) low intensity and high elasticity. In a demonstration of convergent validity, there were statistically significant and conceptually meaningful differences across the subgroups in various measures of mobile phone use and text messaging. Cluster analysis is a useful tool for identifying and profiling distinct, practically meaningful groups based on behavioral indices and could provide a framework for targeting interventions more efficiently.
All Science Journal Classification (ASJC) codes
- Experimental and Cognitive Psychology
- Behavioral Neuroscience