Exploring user switching intention to central bank digital currency payments

Abstract

With the widespread use of mobile devices, mobile payments have become increasingly popular worldwide. In China, third-party providers such as Alipay and WeChat Pay dominate the mobile payment landscape. However, drawbacks of these systems have gradually surfaced, prompting the development of Central Bank Digital Currency (CBDC) payments, most notably China’s Digital Yuan (e-CNY). Despite its advantages, CBDC adoption remains limited compared with established third-party platforms. This study investigates the factors influencing users’ switching from third-party mobile payments to CBDC payments. Unlike third-party systems, CBDC belongs to the cash category (M0), making it distinct in nature and warranting a tailored research framework. To capture this complexity, the Push-Pull-Mooring (PPM) model was employed, integrated with privacy calculus theory, status quo bias theory, and national identity theory, to construct a comprehensive model of switching intention. Methodologically, a combined approach of partial least squares (PLS), artificial neural networks (ANN), and fuzzy-set qualitative comparative analysis (fsQCA) was adopted. This hybrid strategy enhances robustness and provides nuanced insights into the interplay of causal factors. The findings reveal that privacy concern and trust act as key drivers of users’ intention to switch to CBDC payments, whereas inertia represents a significant barrier. These results enrich theoretical research on CBDC payments and extend the application of the PPM model in a novel financial context. Practically, the study informs policymakers and managers by highlighting the importance of targeted strategies that strengthen trust, address privacy issues, and reduce switching barriers, thereby accelerating CBDC adoption.