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Towards resilient and viable supply chains: a multidimensional model and empirical analysis.

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Title: Towards resilient and viable supply chains: a multidimensional model and empirical analysis.
Authors: Padovano, Antonio1 (AUTHOR) antonio.padovano@unical.it, Ivanov, Dmitry2 (AUTHOR)
Source: International Journal of Production Research. Sep2025, Vol. 63 Issue 17, p6252-6290. 39p.
Subjects: Supply chains, Supply chain management, Empirical research, Design, Structural equation modeling, Field research, Agricultural economics
Abstract: The increasing frequency and severity of disruptions in supply chains (SCs), driven by climate change, geopolitical tensions, and evolving structural dynamics, have heightened the importance of supply chain resilience (SCR) and viability (SCV). This study introduces a comprehensive, three-dimensional framework for SCR and SCV covering product, process, technology, and human-centric perspectives. The framework is empirically validated using structural equation modelling (SEM) based on data from 65 SC experts. We demonstrate how key SC variables align with their latent constructs, operationalising the theoretical concepts of resilience and viability in their integrity. The analysis confirms that network and product resilience and viability are pivotal in driving SC performance, while technology and workforce resilience and viability have a lower direct impact. Using a case study of the cereal SC in the Mediterranean region, we show how to implement our framework providing actionable recommendations for supply chain actors, decision-makers, and policymakers, while offering generalized, practical insights for improving the resilience and viability of agri-food systems. This paper contributes both methodological and practical insights to advancing SCR and SCV theory and practical applications. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Towards resilient and viable supply chains: a multidimensional model and empirical analysis.
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  Data: <searchLink fieldCode="AR" term="%22Padovano%2C+Antonio%22">Padovano, Antonio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> antonio.padovano@unical.it</i><br /><searchLink fieldCode="AR" term="%22Ivanov%2C+Dmitry%22">Ivanov, Dmitry</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Sep2025, Vol. 63 Issue 17, p6252-6290. 39p.
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  Data: <searchLink fieldCode="DE" term="%22Supply+chains%22">Supply chains</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+chain+management%22">Supply chain management</searchLink><br /><searchLink fieldCode="DE" term="%22Empirical+research%22">Empirical research</searchLink><br /><searchLink fieldCode="DE" term="%22Design%22">Design</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Field+research%22">Field research</searchLink><br /><searchLink fieldCode="DE" term="%22Agricultural+economics%22">Agricultural economics</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The increasing frequency and severity of disruptions in supply chains (SCs), driven by climate change, geopolitical tensions, and evolving structural dynamics, have heightened the importance of supply chain resilience (SCR) and viability (SCV). This study introduces a comprehensive, three-dimensional framework for SCR and SCV covering product, process, technology, and human-centric perspectives. The framework is empirically validated using structural equation modelling (SEM) based on data from 65 SC experts. We demonstrate how key SC variables align with their latent constructs, operationalising the theoretical concepts of resilience and viability in their integrity. The analysis confirms that network and product resilience and viability are pivotal in driving SC performance, while technology and workforce resilience and viability have a lower direct impact. Using a case study of the cereal SC in the Mediterranean region, we show how to implement our framework providing actionable recommendations for supply chain actors, decision-makers, and policymakers, while offering generalized, practical insights for improving the resilience and viability of agri-food systems. This paper contributes both methodological and practical insights to advancing SCR and SCV theory and practical applications. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2025.2470350
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      – Code: eng
        Text: English
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        PageCount: 39
        StartPage: 6252
    Subjects:
      – SubjectFull: Supply chains
        Type: general
      – SubjectFull: Supply chain management
        Type: general
      – SubjectFull: Empirical research
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      – SubjectFull: Design
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      – SubjectFull: Structural equation modeling
        Type: general
      – SubjectFull: Field research
        Type: general
      – SubjectFull: Agricultural economics
        Type: general
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            NameFull: Padovano, Antonio
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            NameFull: Ivanov, Dmitry
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            – D: 01
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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