Abstract
To explore the influencing factors of the adoption of mobile payment systems from the perspective of merchants, this study builds a data analysis model based on three different ensemble learning algorithms, Adaboost model, random forest and XGBoost model, where static social-economic attributes, dynamic trading behavior and clustering effect variables of merchants are used as independent variables. Moreover, this paper establishes the prediction models and analyzes the prediction accuracy of different models. The results of the study indicate that: 1) Merchants in the housing industry, health hospitals and retail industries are more willing to adopt mobile payment systems; 2) The average daily transaction volume and the average amount of each consumer significantly affect the merchant mobile payment adoption behavior; 3) The adoption of mobile payment systems by neighboring merchants significantly positively affected the adoption behavior of merchants; 4) On the basis of the social-economic attributes of merchants, the hit rate and accuracy of the prediction model were greatly improved after adding transaction data.
Highlights
According to different payment methods, mobile payment can be divided into remote payment and near field payment
This study builds analysis model based on three Ensemble learning algorithms: Adaboost, Random Forest, and XGBoost, using social-economic attribute variables, dynamic transaction variables, and clustering effect variables of the merchants as independent variables, researched influencing factors of merchants’ adoption of mobile payment services
The results show that the ensemble learning algorithm significantly improves the prediction accuracy of the model
Summary
According to different payment methods, mobile payment can be divided into remote payment and near field payment. Mobile remote payment refers to a payment method that uses the Internet, telecommunications network, etc. Third-party institutions such as Alipay Wallet and WeChat Pay use the advantages of Internet technology, e-commerce platforms, and social networks to enlarge customer number and business scale. Through the continuous integration of online and offline services, various innovative mobile near-field payment methods (mobile phone flash payment, barcode payment) are increasingly accepted by users, which promotes customer loyalty and expands usage scenarios. The offline retail market based on mobile near field payment has become the focus of competition among major payment companies and financial institutions
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