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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2027</Year>
        <Month>01</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Quantitative Analysis of the Impact of Digital-Based Business Capability Mechanisms on the Resilience of Online Businesses Based on Structural Equation Modeling</ArticleTitle>
    <VernacularTitle>Quantitative Analysis of the Impact of Digital-Based Business Capability Mechanisms on the Resilience of Online Businesses Based on Structural Equation Modeling</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>13</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2025</Year>
        <Month>12</Month>
        <Day>02</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The present study aimed to quantitatively analyze the impact of digital-based business capability mechanisms on the resilience of online businesses using Structural Equation Modeling (SEM) and the Partial Least Squares (PLS) approach. To this end, the collected data were analyzed using SmartPLS software, and the relationships between digital variables and the business resilience construct were evaluated. Prior to testing the structural model, the quality of the measurement model was assessed through the examination of reliability, validity, and multicollinearity. The results indicated that all Variance Inflation Factor (VIF) values were below 5, demonstrating that the model was free from multicollinearity issues. Reliability analysis showed that Cronbach’s alpha coefficients and Composite Reliability (CR) values for all constructs exceeded 0.70, indicating satisfactory internal consistency of the measurement instrument. Furthermore, the Average Variance Extracted (AVE) values were greater than 0.50, confirming the convergent validity of the constructs. In the structural section, all paths were significant at the 95% confidence level, and the t-statistic values were outside the ±1.96 range. The coefficient of determination (R² = 0.393) for the endogenous constructs, according to the criteria proposed by Chin and Hair, indicated a moderate and acceptable model fit in explaining the resilience of online businesses, such that 39% of the variance in the dependent variables was explained by digital-based business capability mechanisms. The findings further demonstrated that components such as information and communication technology infrastructure, data management and predictive analytics, cybersecurity, scalability capability, digital collaboration, and business model innovation play a significant role in strengthening the flexibility and resilience of online businesses. Overall, the research model demonstrated adequate validity and reliability, and the findings can provide effective guidance for managers seeking to enhance digital competitive advantage.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Digital</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Business Capability</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Online Business Resilience</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Structural Equation Modeling (SEM)</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journalrmde.com/index.php/jrmde/article/download/304/271</ArchiveCopySource>
  </Article>
</ArticleSet>
