The cold chain—temperature-controlled logistics that preserve perishable goods across storage, transport, and distribution—has become central to global food security, pharmaceutical delivery, and pandemic resilience. This paper presents a comprehensive, publication-ready synthesis and original theoretical framework that integrates technological, managerial, and policy perspectives on cold chain performance and innovation. Drawing strictly on the provided body of literature spanning reviews of monitoring technologies, refrigeration engineering, logistics service quality, sustainability performance metrics, hybrid distribution optimization, and machine learning applications, the article articulates a multidisciplinary research agenda and proposes a layered framework for resilient, intelligent cold chain systems. The structured abstract summarizes objectives, methods, key findings, and implications. Methodologically the paper adopts a rigorous integrative-review approach combined with constructive theoretical synthesis: it systematically reinterprets empirical findings and technological trends from existing studies to derive a unified conceptual model and testable propositions. Results synthesize evidence that: (1) recent advances in sensor, telemetry, and data analytics enable real-time, distributed monitoring that materially reduces temperature excursions (Badia-Melis et al., 2018; Zhao et al., 2020); (2) intelligent routing and machine learning can optimize scheduling and reduce spoilage in last-mile and urban distribution (Yu, 2022; Wang et al., 2022); (3) performance measurement and sustainability metrics must be hybridized to capture both service quality and carbon/cost trade-offs (Kilibarda et al., 2016; Liao et al., 2023; Babagolzadeh et al., 2020); and (4) institutional and regulatory guidance—especially for pharmaceuticals and vaccines—remains a binding constraint that shapes operational design (WHO, 2015; WHO, 2021). The discussion interprets these findings, articulates limitations and critical uncertainties, and maps out a future research agenda with prioritized empirical and modeling challenges. The conclusion offers clear managerial recommendations for practitioners seeking to transform legacy refrigerated transport architectures into resilient, data-driven cold chains that balance quality, sustainability, and cost. This work synthesizes extant knowledge while providing specific theoretical contributions: a layered conceptual model of cold-chain intelligence, a set of propositions linking monitoring fidelity to service outcomes, and an interdisciplinary roadmap for integrating refrigeration engineering, data analytics, and policy compliance.

cold chain logistics, temperature-controlled transport, monitoring technologies, intelligent distribution

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