Unlocking the future of paytech: exploring biometric payment card adoption patterns

Francisco Liébana‐Cabanillas et al.

Financial Innovation2026https://doi.org/10.1186/s40854-025-00883-9article
AJG 2ABDC B
Weight
0.37

Abstract

With the transition to a cashless society and the evolving regulatory framework governing electronic payments, the advent of novel payment systems has become increasingly apparent. In this context, biometric payment cards have emerged as a promising alternative to enhance security, convenience, and efficiency in electronic transactions. An online questionnaire was administered to a sample of users experienced in mobile payment systems, and structural equation modeling was utilized to identify the variables significantly affecting usage and recommendation. The results confirm the proposed hypotheses, except for those related to social influence and perceived risk. This study provides a unique contribution by investigating the factors influencing the adoption and word-of-mouth (WOM) of biometric payment cards, integrating elements from the unified theory of acceptance and use of technology 2 (UTAUT2), general risk theory, and trust theory. This research is highly relevant for financial institutions, tech companies, marketers and policymakers, as it informs user strategy development for businesses operating within the biometric payment sector and suggests guidelines for enhancing consumer trust and reducing perceived risks associated with biometric payments.

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https://doi.org/https://doi.org/10.1186/s40854-025-00883-9

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@article{francisco2026,
  title        = {{Unlocking the future of paytech: exploring biometric payment card adoption patterns}},
  author       = {Francisco Liébana‐Cabanillas et al.},
  journal      = {Financial Innovation},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1186/s40854-025-00883-9},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.