Global Supply Chain Agility Through ERP Systems: A Decision Support Model for Emerging Economies

Year : 2025 | Volume : 15 | Issue : 03 | Page : 31 37
    By

    Sunidhi Chauhan,

  1. Student, Department of Biotech, Chaudhary Charan Singh University, Meerut, Uttar Pradesh, India

Abstract

In today’s highly dynamic and interconnected global markets, supply chain agility—the capacity to sense environmental changes and respond rapidly and effectively—has emerged as a critical success factor. This is particularly significant for firms operating in emerging economies, where market volatility, infrastructural limitations, policy uncertainties, and resource constraints pose persistent challenges. Enterprise Resource Planning (ERP) systems, with their ability to integrate cross-functional processes, centralize data, and provide real-time decision-making support, offer promising avenues to enhance supply chain agility. This review article systematically synthesizes existing literature on supply chain agility, ERP implementation, and their synergistic relationship, especially in the context of emerging markets. It identifies and categorizes key enablers (such as top management support, digital literacy, and cloud-based ERP solutions), barriers (including high implementation costs, resistance to change, and inadequate IT infrastructure), and critical success factors (such as change management, user training, and alignment with strategic objectives). Building on these insights, the article proposes a novel decision support model specifically designed to address the unique constraints and opportunities in emerging economies. The model focuses on four pillars: internal integration (e.g., real-time data sharing across departments), external integration (e.g., supplier and customer collaboration), flexibility (e.g., rapid reconfiguration of processes), and responsiveness (e.g., quick adaptation to market signals), underpinned by digital infrastructure readiness. Real-world and hypothetical case illustrations are presented to demonstrate practical applications. The article concludes with actionable recommendations for industry practitioners aiming to leverage ERP for agile supply chains and offers a future research agenda to guide academic inquiry in this evolving domain.

Keywords: Supply Chain Agility; ERP Systems; Decision Support Model; Emerging Economies; Internal and External Integration; Responsiveness; Flexibility; Digital Infrastructure

[This article belongs to Journal of Production Research & Management ]

How to cite this article:
Sunidhi Chauhan. Global Supply Chain Agility Through ERP Systems: A Decision Support Model for Emerging Economies. Journal of Production Research & Management. 2025; 15(03):31-37.
How to cite this URL:
Sunidhi Chauhan. Global Supply Chain Agility Through ERP Systems: A Decision Support Model for Emerging Economies. Journal of Production Research & Management. 2025; 15(03):31-37. Available from: https://journals.stmjournals.com/joprm/article=2025/view=230933


References

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  2. Patel, B. S., & Sambasivan, M. (2021). A systematic review of the literature on supply chain agility. Management Research Review, 45(2), 236‑260.
  3. Harianto, K. J., Tarigan, Z. J. H., Siagian, H., Basana, S. R., & Jie, F. (2024). The effect of digital ERP implementation, supply chain integration and supply chain flexibility on business performance. International Journal of Data and Network Science, 8(4), 2399‑2414.
  4. Grace T. Pontoh, Aini Indrijawati, Fifi Selvi, Lasri Ningsih, & Dinda Reskiana Putri. (2024). A Systematic Literature Review of ERP and RFID Implementation in Supply Chain Management. (Journal of ???), ISSN 2657‑4950.
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  8. Christopher, M. (2000). The Agile Supply Chain: Competing in Volatile Markets. (Industrial Marketing Management, etc.) — often cited in agility literature.
  9. Boer, L., & Machuca, J. (2015). Organizational capability, information technology, and supply chain agility: An empirical investigation.
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Regular Issue Subscription Review Article
Volume 15
Issue 03
Received 04/11/2025
Accepted 10/11/2025
Published 17/11/2025
Publication Time 13 Days
118

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