Article Details
  • Published Online:
    April  2026
  • Product Name:
    The IUP Journal of Management Research
  • Product Type:
    Article
  • Product Code:
    IJMR050426
  • DOI:
    10.71329/IUPJMR/2026.25.2.101-118
  • Author Name:
    Kunal Mishra and Balaji Setty
  • Availability:
    YES
  • Subject/Domain:
    Management
  • Download Format:
    PDF
  • Pages:
    101-118
Volume 25, Issue 2, April -June 2026
Agentic AI for ESG-Aligned Supply Chain Resilience in Apparel SMEs: A Multi-Agent Framework and Illustrative Simulation
Abstract

This study has developed a Value-Based Agentic AI Framework (VBAF) for risk management and ESG compliance in apparel small and medium enterprises (SMEs). A PRISMA 2020-guided systematic literature review synthesizing 93 peer-reviewed sources (2016-2025) was conducted. Thematic coding in NVivo 14, supplemented by VOSviewer bibliometric clustering, identifies seven research gaps: agentic autonomy, multi-agent coordination, risk sensing, ESG-value alignment, SME implementation barriers, digital infrastructure deficits, and theoretical fragmentation. VBAF embeds ESG utility constraints directly within agent decision functions through six design propositions calibrated to SME resource profiles. An illustrative NetLogo agent-based simulation across 20 production ticks demonstrates VBAF achieving 92% on-time delivery against a reactive baseline of 68% under severe cascade disruption, with 18% reduction in simulated emissions and 75% mitigation of modeled shortfall events. The framework integrates Value-Sensitive Design, Socio-Technical Resilience Theory, and Resource Dependence Theory, offering a phased deployment roadmap operable within sub-$2,000 monthly budgets.

Introduction

Global supply chains have become structurally more fragile over the past decade. The Covid-19 pandemic severed approximately 70% of tier-2 apparel linkages and amplified bullwhip effects by factors of four to twelve within highly seasonal supply chains (Ivanov, 2022). The 2021 Suez Canal blockage halted an estimated $9.6 bn in daily trade, exposing how tightly coupled production networks can cascade a single node failure across the entire system (Pournader et al., 2020).