Mobile application providers face high user losses because users can easily and often switch to an alternative application. Researchers have recently started to study information technology (IT) switching. However, no studies have concentrated on the unique context of mobile applications. Mobile application switching differs from the switching behavior related to many other IT products and services because of the highlighted role of alternatives, beta versions, updates, reviews, and users’ spontaneous behavior. To address this gap, we develop a mobile-specific model by using a qualitative research approach. As a theoretical contribution, we introduce trialing behavior as a predecessor of switching behavior and present six new behavioral antecedents for them. As practical implications, we suggest ways for mobile application providers and developers to reduce user churn.

Mobile application providers face high user losses because users can easily and often switch to an alternative application. Researchers have recently started to study information technology (IT) switching. However, no studies have concentrated on the unique context of mobile applications. Mobile application switching differs from the switching behavior related to many other IT products and services because of the highlighted role of alternatives, beta versions, updates, reviews, and users’ spontaneous behavior. To address this gap, we develop a mobile-specific model by using a qualitative research approach. As a theoretical contribution, we introduce trialing behavior as a predecessor of switching behavior and present six new behavioral antecedents for them. As practical implications, we suggest ways for mobile application providers and developers to reduce user churn.