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A cluster analysis of text message users based on their demand for text messaging: A behavioral economic approach

机译:基于他们对文本消息的需求的文本消息用户的集群分析:行为经济方法

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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.
机译:本研究的目标是确定集群分析是否可用于根据对文本消息的需求的行为经济指标确定文本消息用户的不同子组。群集分析是一种分析技术,其试图根据所选变量的相似性进行分类案例。与会者完成了一个关于手机使用的问卷和假设的短信需求任务,其中他们表明他们向继续发送短信的额外收费的可能性。对行为经济指数进行了分层集群分析,例如需求强度,需求弹性,断点和最大支出。通过群集分析,我们确定了3个文本消息用户的3个子组。该组的特征在于(a)高强度和低弹性,(b)高强度和培养基弹性,(c)低强度和高弹性。在收敛有效性的演示中,在移动电话使用和短信的各种措施中,亚组在统计上显着和概念上有意义的差异。群集分析是一个有用的工具,用于根据行为指数识别和分析不同的实际有意义的群体,并且可以更有效地提供针对序列的框架。

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