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<p>The Reserve Bank of India is planning to introduce Central Bank Digital Currency (CBDC) in India. The widespread acceptance of the Unified Payment Interface (UPI) and online transactions could facilitate the adoption of CBDC among Indian users. The adoption of CBDC depends on individuals' intentions. This paper investigates various determinants of behavioral intentions among UPI and online transaction users who adopt CBDC. This study combines the Technology Adoption Model and Innovation Diffusion Theory with new factors such as social influence, awareness, and perceived security to predict how individual’s will adopt CBDC. CBDC uses facial recognition technology and cryptocurrency. The study focuses solely on UPI and online payment users who act as digital innovators residing in Mumbai, India's urban agglomerate and financial hub. A covariance-based structural equation modeling was used to evaluate the relationships among the various constructs. The findings show that perceived ease of use, social influence, and usefulness strongly influence CBDC adoption. Thus, central banks should prioritize these aspects when introducing CBDC to the general public. The findings of the study will help policymakers in designing policies for a smooth transition to CBDC among the common people. The results suggest that the model successfully explained individuals' intentions towards CBDC adoption.</p>

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Pioneering digital finance: determinants of CBDC adoption in the era of FinTech and online payments

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Mohammad Razi-ur-Rahim,
  • Furquan Uddin,
  • Saubia Rahim,
  • Md Billal Hossain

摘要

The Reserve Bank of India is planning to introduce Central Bank Digital Currency (CBDC) in India. The widespread acceptance of the Unified Payment Interface (UPI) and online transactions could facilitate the adoption of CBDC among Indian users. The adoption of CBDC depends on individuals' intentions. This paper investigates various determinants of behavioral intentions among UPI and online transaction users who adopt CBDC. This study combines the Technology Adoption Model and Innovation Diffusion Theory with new factors such as social influence, awareness, and perceived security to predict how individual’s will adopt CBDC. CBDC uses facial recognition technology and cryptocurrency. The study focuses solely on UPI and online payment users who act as digital innovators residing in Mumbai, India's urban agglomerate and financial hub. A covariance-based structural equation modeling was used to evaluate the relationships among the various constructs. The findings show that perceived ease of use, social influence, and usefulness strongly influence CBDC adoption. Thus, central banks should prioritize these aspects when introducing CBDC to the general public. The findings of the study will help policymakers in designing policies for a smooth transition to CBDC among the common people. The results suggest that the model successfully explained individuals' intentions towards CBDC adoption.