Abstract
ABSTRACT Despite the high utilization of mobile payment during the COVID-19 pandemic, this situation may change in the post-pandemic era. Therefore, great value can be derived from determining the significant antecedents of mobile payment continuance intention. This study looks to do so by introducing a Multi-Dimensional Nomological Network of Mobile Payment Continuance. A two-stage Partial Least Square-Structural Equation Modeling and Artificial Neural Network was utilized for the data analysis. The results provided empirical support to establish the overall nomological network. In addition, more than 70% of the variance in continuance intention was captured. Overall, this study provides practitioners with detailed insights to develop strategies for sustainable utilization and academics with a dynamic framework to look into users’ mobile payment continuance intention.
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