Abstract
A systematic review of previous mobile payment studies revealed that studies mainly focused on consumer adoptions via conducting surveys, yet the low adoption of mobile payment services still exists. Despite a number of studies investigated barriers to mobile payment consumer adoptions, little explanation has been provided without taking ecosystem factors of mobile payment into account. Given the promising future of digital payments, we believe it is more relevant to study the actual usage of e-wallets via a novel approach. The objective of the study is to identify and categorize related themes of usages of e-wallets using big data analytics. With a large dataset of 18,149 user posts extracted from social media platforms, we apply the text mining method to analyze e-wallet users' behaviors. Our major findings are (i) whilst contradicting with user adoption factors (e.g., usefulness), users are attracted to use e-wallets to gain cashback and accumulate reward points; (ii) successful measures for e-wallet business models include a user-friendly interface, promotional campaigns, and customer service with real-time problem-solving; (iii) an intense competition between bank e-wallets and third party e-wallets is compounded with stricter government regulations; (iv) low rates of merchant adoption contribute to the lack of critical mass use of e-wallets. The big data analytics of actual usage of e-wallets produce more relevant and accurate understandings of the mobile payment mechanism. It reflects the complexity of human-computer interactions. This study establishes a predictive model of measuring successful e-wallet business and provides a holistic view of the mobile payment ecosystem with empirical evidence. The business must go beyond consumer adoption, learn actual user behavior, and take consumers’ pulse to achieve a sustainable business model. It is suggested that governments reform and upgrade the monitoring framework to accommodate the development of payment systems.
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