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Use of Supply Chain Analytics Technologies in Peru's Agri‐Food Supply Chain: Supporting Agility and Supply Chain Cost Reduction

Author

Listed:
  • Edgar Ramos
  • Zulqurnain Ali
  • Benjamin Hazen
  • Christopher Boone
  • Ginger Miranda
  • Angello Tamayo

Abstract

This research examines how the use of supply chain analytics technologies (USCAT) can increase financial performance by enabling agility and quality management capabilities in the Peruvian coffee supply chain. Using an empirical research approach, we theorize and test a model based on the dynamic capabilities view. We collected survey data from supply chain management experts working in the Peruvian coffee supply chain and used covariance‐based structural equation modeling to test a series of hypotheses. This research supports the relationship between USCAT and improvements in supply chain agility, quality focus, and supply chain cost performance for agri‐food supply chains (AFSC). These findings offer valuable insights for agri‐food businesses, especially in developing economies, suggesting that strategic technological investment can enhance competitiveness and financial sustainability. Stakeholders (scholars and managers alike) operating in developing areas can use the results to motivate and leverage the value of readying themselves and their supply chain partners to participate in current and future supply chain technology‐enabled business opportunities. This research contributes to the literature by providing a unique perspective on the impact of new supply chain technologies in emerging markets, specifically within the Peruvian agri‐food sector, and extends the discourse on technology adoption in global agri‐food supply chains.

Suggested Citation

  • Edgar Ramos & Zulqurnain Ali & Benjamin Hazen & Christopher Boone & Ginger Miranda & Angello Tamayo, 2025. "Use of Supply Chain Analytics Technologies in Peru's Agri‐Food Supply Chain: Supporting Agility and Supply Chain Cost Reduction," Transportation Journal, John Wiley & Sons, vol. 64(2), March.
    • Handle: RePEc:wly:transj:v:64:y:2025:i:2:n:e70007
    DOI: 10.1002/tjo3.70007
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