Hierarchical Bayesian Evidence on CBDC Adoption: The Case of Indonesia’s Digital Rupiah

This study analyzed accessibility, privacy, transferability, and interest rates related to the adoption of Digital Rupiah, Indonesia’s Central Bank Digital Currency (CBDC), among rural and urban consumers. Findings from a hierarchical Bayesian model show that mobile applications are the main acquisition channel, and enhanced transferability with bank accounts and electronic money boosts consumer utility. However, there are concerns about fully anonymous transactions, differentiated by socio-demographic profiles (age, income, education, and knowledge). Scenario analysis suggests the potential CBDC adoption rate in Indonesia could range from 38% to 55%, influenced by privacy levels and the central bank’s interest rates.