<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Management and Business Solutions</JournalTitle>
      <Issn>3092-7226</Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2027</Year>
        <Month>03</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Integrated Resource Management and Decision Engineering Model for Manufacturing Industries: A Hybrid Approach in Inflationary Economies</ArticleTitle>
    <VernacularTitle>Integrated Resource Management and Decision Engineering Model for Manufacturing Industries: A Hybrid Approach in Inflationary Economies</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>19</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2026</Year>
        <Month>04</Month>
        <Day>09</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;This paper addresses the critical challenge of manufacturing resource management under inflationary pressures by developing an integrated decision engineering framework. Drawing upon established theories in inventory management, production reliability models, reconfigurable manufacturing systems, and macroeconomics, the proposed hybrid methodological approach combines mathematical optimization, multi-criteria decision-making, system dynamics, and macroeconomic sensitivity analysis within a coherent framework. The model integrates production planning, inventory control, quality management, reliability investments, capacity allocation, and reconfiguration decisions while explicitly considering inflation dynamics through the New Keynesian Phillips Curve framework. The primary contribution lies in bridging the gap between micro-level operational decisions and macro-level inflationary constraints, offering a comprehensive tool for manufacturing decision-makers in unstable economic environments. Numerical analysis using data from the Iranian automotive parts industry demonstrates that the integrated approach achieves 7.2% to 12.1% cost savings compared to sequential decision-making, with reliability and reconfigurability investments gaining significant value as inflation volatility increases. Comprehensive sensitivity analysis with 95% confidence intervals confirms the model's robustness under parameter uncertainty.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Integrated resource management</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">decision engineering</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">reconfigurable manufacturing systems</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">inflationary economies</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">New Keynesian Phillips Curve</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">fuzzy multi</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">objective optimization</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalmbs.com/index.php/jmbs/article/download/376/303</ArchiveCopySource>
  </Article>
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