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NTU Management Review Vol. 33 No. 3 Dec. 2023

Figure 3 Results of the Research Model Analyses
Note: Value on Path: Standardized Coefficients (β); *p < 0.05, **p < 0.01, ***p < 0.001.

determinants of switching intention, namely social influence, dissatisfaction with the
current health app, and habits, with the path coefficients being 0.258, 0.768, and -0.165 (β
= 0.258, p < 0.001; β = 0.768, p < 0.01; and β = -0.165, p < 0.01), respectively. Therefore,

Hypotheses 2, 3, and 5 are significantly supported. In addition, attractive alternatives
have a path coefficient of 0.108 (β = 0.108, p > 0.05) on the path; it is close to the
minimum criterion of 1.96 for the significance criterion, showing only slight significance.

Even so, Hypotheses 1 is not supported. Moreover, the path coefficient on the path of
procedural switching costs is 0.141 (β = 0.141, p > 0.05), and the result is not significant,
indicating that this independent variable has no effect on the switching intention; therefore,
Hypothesis 4 is not supported. In addition, we can observe the effect of the moderator
in the model. Hypothesis 6 assumes that procedural switching cost will have a negative

moderating effect on dissatisfaction with the current incumbent health app, and the
path coefficient is -0.336 (β = -0.336, p > 0.05). The result is not significant; therefore,
Hypothesis 6 is not supported. To sum up, the overall explanation of variance to switch

is 57.32%, and the analysis supports three hypotheses (H2,3,5) and does not support the
other three hypotheses (H1,4,6). Corresponding to the analysis results, we provide the
following reasons to explain why the users of health apps have switching intentions or are

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