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Sustainable Supply Chain Practices: A Teaching Framework with Data Science
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Author(s): Gopi Chand Vegineni (Nexsolv, USA)and Venkateswara Rao Anumolu (Independent Researcher, USA)
Copyright: 2025
Pages: 18
Source title:
Integrating AI and Sustainability in Technical and Vocational Education and Training (TVET)
Source Author(s)/Editor(s): Ali Sorayyaei Azar (University of Malaya, Malaysia), Shashi Kant Gupta (Eudoxia Research University, USA), Hamed Taherdoost (Department of Arts, University Canada West, Canada & GUS Institute, Global University Systems, UK & College of Technology and Engineering, Westcliff University, USA & Gisma University of Applied Sciences, Germany & Q Minded, Quark Minded Technology, Canada & Research and Development Department, Hamta Business Corporation, Canada)and Fahima Alhamaty (Harvard Business Review, Kuwait)
DOI: 10.4018/979-8-3373-1142-5.ch012
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Abstract
Sustainable supply chain practices have gained significant attention in recent years, driven by the growing need for businesses to reduce their environmental impact while maintaining operational efficiency. This chapter introduces a teaching framework that integrates data science methodologies to enhance sustainability within supply chains. By leveraging machine learning, predictive analytics, and optimization techniques, the framework enables the identification of key sustainability metrics and the development of data-driven strategies to optimize resource utilization, reduce waste, and minimize carbon footprints
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