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coefficients of habits on attractive alternatives, social influence, and dissatisfaction with
the current health app are -0.166, -0.316, and -0.424. (β = -0.166, p > 0.05; β = -0.316, p >
0.05; and β = -0.424, p > 0.05), respectively. The results show that habits as a moderating
variable is more influential than procedural switching cost, but it is still not significant.

6. Implications and Conclusion

6.1 Theoretical Implications

This research provides some novel and meaningful contributions to the literature.
First, previous studies have examined the factors that affect users’ IT/IS switching, such
as Bhattacherjee et al. (2012) and Fan and Suh (2014). These studies separately identify
several key factors, including relative advantage, satisfaction/dissatisfaction, habit,

and switching cost. However, these studies do not use a theoretical basis to discuss the
relevance of these factors, and they only explain the impact of these factors on users’ IT/
IS switching based on superficial reasons. To fill this gap, by applying the PPM model of
migration theory, this study proposes an exterior-interior factor model to explain why users

want to switch from their current health apps to other apps. In order to clearly analyze
the factors affecting switching intention for health apps, this study divides the factors into
positive and negative drivers.
Second, previous research identifies four types of decisions about using health apps,

including abandoning use, limiting use, switching apps, and continuing use (Vaghefi and
Tulu, 2019). However, previous research has not addressed the conditions or antecedents
of the decision on health apps switching. Contrarily, in this study, we propose a research
model that attempts to explain why users have switching intentions of current health apps.

Our results reflect that in addition to known functional conditions, users are also affected
by social influences, (dis)satisfaction and habits, which lead to switching intentions of
health applications. We believe these results fill another gap in previous research.
Third, this study provides new empirical evidence that social influence has an

impact on users’ switching intention. However, sources of social influence with respect to
individuals are from online acquaintances or reviews that ought to be investigated further.
If the decision to switch apps is influenced by online friends, then the relationship types
and roles of online friends should be further explored. However, if it is online reviews that

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