<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-statistics-and-management-systems</journal-id>
      <journal-title-group>
        <journal-title> Journal of Statistics and Management Systems</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0014</issn>
      <issn publication-format="print">0972-0510</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JSMS-1153</article-id>
      <title-group>
        <article-title>Using AHP model to evaluate factor influencing mobile banking usage in Indian banks</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Kaur</surname>
            <given-names>Dhillon Lakhwinder</given-names>
          </name>
          <aff>Department of Finance, Amity University, Noida, Uttar Pradesh, India</aff>
        </contrib>
      </contrib-group>
      <volume>26</volume>
      <issue>5</issue>
      <fpage>1005</fpage>
      <lpage>1014</lpage>
      <pub-date date-type="pub">
        <day>25</day>
        <month>09</month>
        <year>2023</year>
      </pub-date>
      <abstract>
        <p>The aim of this work is to develop Analytical Hierarch Model (AHP Model) in identifying the most influencing factor in mobile banking that influences the mobile banking users. The factors are identified through a systematic literature review and data is collected from experts in the banking industry with prior experience in Mobile Banking. Collected data is analyzed through the AHP model where pairwise comparison is done to distribute weights to different factors. An Excel template by Business Performance Management Singapore was utilized to calculate the weights. Through the study, it was found that security-related factors are the most influential factor in mobile banking usage (with weight 0.308). In the Sub criteria, Security, Ease of use, Perceived usefulness, and perceived efficiency were given the highest priority.</p>
      </abstract>
      <kwd-group>
        <kwd>Analytic hierarchy model</kwd>
        <kwd>AHP</kwd>
        <kwd>Mobile banking</kwd>
        <kwd>Pairwise comparison</kwd>
        <kwd>Security</kwd>
        <kwd>User interface</kwd>
        <kwd>Convenience</kwd>
        <kwd>Social inclusion</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
