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An Empirical Analysis of Consumption Patterns for Mobile Apps and Web: A Multiple Discrete-Continuous Extreme Value Approach

机译:移动应用程序和Web消费模式的实证分析:多重离散连续极值方法

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Using a unique panel data set detailing individual-level mobile app consumption, this study develops a utility theory-based structural model for multiple discrete/continuous choices in app use. We identify the dynamics and inter-dependencies between mobile apps and jointly quantify consumers' app choice and satiation simultaneously. The results suggest that mobile users' baseline utility is the highest for communication apps, while the lowest for personal financing apps. In addition, users' satiation level is the highest for the personal financing apps and the lowest for the game apps. However, a substantial heterogeneity in baseline utility and satiation is observed across diverse users. Furthermore, both positive and negative correlations exist in the baseline utility and satiation levels of mobile web and app categories. Consequently, the proposed frameworks could open new perspectives for handling large-scale, micro-level data, serving as important resources for big data analytics in general and mobile app analytics in particular.
机译:本研究使用详细描述各个级别移动应用程序消费的唯一面板数据集,为应用程序中的多个离散/连续选择开发了一种基于效用理论的结构模型。我们确定了移动应用之间的动态关系和相互依赖性,并共同量化了消费者对应用的选择和满意度。结果表明,移动用户的基准效用在通信应用程序中最高,而在个人理财应用程序中最低。此外,个人理财应用程序的用户满意度最高,游戏应用程序的用户满意度最低。但是,在不同的用户中观察到基线效用和满意度的实质性异质性。此外,移动网络和应用类别的基准效用和满足程度都存在正相关和负相关。因此,所提出的框架可以为处理大规模,微观级别的数据开辟新的视角,成为一般和特别是移动应用程序分析中大数据分析的重要资源。

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