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Equitable Green Innovation in Supply Chains Harnessing Machine Learning for Sustainable Development
Abstract
The intersection of equitable innovation, sustainability, and machine learning is transforming global supply chains into efficient, environmentally conscious systems. This chapter explores how machine learning is driving green innovation across various stages of the supply chain, from resource sourcing to final delivery, while ensuring inclusivity and fairness. By leveraging predictive analytics, optimization algorithms, and real-time monitoring, machine learning enables organizations to reduce carbon footprints, minimize waste, and enhance operational efficiency. The chapter also delves into the role of AI in addressing challenges such as ethical sourcing, energy-efficient logistics, and circular economy practices. Case studies highlight successful implementations, demonstrating how equitable machine learning applications can foster sustainable growth and empower marginalized communities. By integrating technology with sustainable practices, this chapter provides a roadmap for achieving a resilient, green, and inclusive supply chain ecosystem
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