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  <doi_batch_id>aspg-37-4451-1792223298</doi_batch_id>
  <timestamp>20261017074818</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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  <journal>
   <journal_metadata language="en">
    <full_title>Financial Technology and Innovation</full_title>
    <abbrev_title>FinTechI</abbrev_title>
    <issn media_type="electronic">2836-5372</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <journal_volume>
     <volume>5</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>From Mobile Adoption to Payment-Rail Use</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Betul</given_name>
      <surname>Aktas</surname>
      <affiliations>
       <institution>
        <institution_name>Higher Vocational School, Cag University, Mersin, Turkey</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Measures of financial-technology adoption often bundle devices, interfaces, accounts, and the payment instruments themselves, which can end up making the transformation of payment rails look bigger than it really is. In other words, it’s sort of easy to overstate what changed in the underlying payment rails when you mix everything together. This study builds a friction-aware measurement framework that separates instrument adoption, recent use, payment-count share, and the transaction context. We apply the framework to nationally representative, weighted U.S. consumerpayment tables that were available by 31 March 2025. The analysis follows eight payment instruments from 2015 to 2023, and then links their payment-count shares to consumer rankings of acceptance setup, convenience, cost, record keeping, and security. In 2023, credit and debit cards together made up 62.2% of payment transactions, while stored-value mobile-payment applications were below 1%. So widespread mobile-device adoption seems to have meant a change in the payment interface , not a direct replacement of the card and bank-account rails. Also, credit and debit cards show the highest use-depth ratios among recent users. In a two-way fixed-effects model, a one-standard-deviation decline in the convenience rank lines up with an 8.97-percentage-point drop in payment share (p = 0.0047); the other rankings, well, were not independently separable from zero. An expanding-window ridge model didn’t beat a persistence benchmark over 2021–2023, even though it did generate a lower forecast error in 2023. Overall the evidence suggests payment-rail transformation is driven by convenience, behavioral persistence, and transaction context rather than interface adoption only. Finally, the study offers a practical measurement architecture that financial institutions, payment platforms, and regulators can use when they’re trying to check for genuine rail substitution.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <pages>
     <first_page>28</first_page>
     <last_page>34</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">4451</item_number>
    </publisher_item>
    <ai:program name="AccessIndicators">
     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
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     <doi>10.54216/FinTech-I.050204</doi>
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