<?xml version="1.0" encoding="UTF-8"?>
<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>03</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Investigation of Effective Indicators in the Implementation of Industry 4.0 Technologies for Improving Warehousing Operations in Chain Stores</ArticleTitle>
    <VernacularTitle>Investigation of Effective Indicators in the Implementation of Industry 4.0 Technologies for Improving Warehousing Operations in Chain Stores</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>14</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>11</Month>
        <Day>01</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The aim of this study is to investigate the effective indicators in the implementation of Industry 4.0 technologies for improving warehousing operations in chain stores. This research is classified as an analytical–software-based study. The study is cross-sectional in nature. In terms of purpose, it is applied research. From the spatial perspective, it is a field study, and the temporal scope of the research is 2025. Since the m-TISM model within the MICMAC technique framework was employed in this study, the statistical population and sample consisted of 15 managers, warehouse management experts, and specialists in the fields of information technology and artificial intelligence, selected through a census method. In this study, convenience sampling was used. The required data were collected using a pairwise comparison questionnaire and analyzed through MICMAC software. The findings obtained from the conducted analyses indicate that multiple indicators should be considered in warehouse management. When applying technology in warehouse management for chain stores, a defined and context-specific indicator system should be established for this domain. This section introduces an implementation indicator system encompassing six critical dimensions: technical, economic, environmental, safety, managerial, and supervisory dimensions. This comprehensive indicator system includes six primary indicators, which are divided into 20 secondary indicators. The results demonstrate that investment cost (economic), operational cost (economic), expected return (economic), personnel safety (safety), pollution control (environmental), and the use of specialized integrated warehouse operations management software (managerial) are among the key indicators for implementing Industry 4.0 technologies to improve warehousing operations in chain stores. A high success rate in exploration is associated with an increased probability of identifying relevant resources, which enhances the implementation of Industry 4.0 technologies. The availability and effectiveness of the required technology are evaluated to ensure that the implementation achieves the research objectives.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Effective Indicators</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Implementation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Industry 4</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Warehousing</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Chain Stores</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalrmde.com/index.php/jrmde/article/download/310/354</ArchiveCopySource>
  </Article>
</ArticleSet>
