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AI-Driven Route Optimization and Sustainable Logistics: Transforming Stakeholder Perspectives for a Greener Future
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Author(s): Pawan Kumar (Graphic Era University, India), Arvinder Kaur (Chandigarh University, India), Bhupinder Pal Singh Chahal (Yorkville University, Canada)and Pravesh Soti (NIET Business School, Greater Noida, India)
Copyright: 2026
Pages: 20
Source title:
Impact of Generative AI on Food Supply Chain Management
Source Author(s)/Editor(s): Bhupinder Pal Singh Chahal (Yorkville University, Canada), Arokiaraj David (SBS Swiss Business School, RAK, UAE), Amrinder Singh (Jain University, India), Geetika Madaan (Marwadi University, India)and Gurmeet Singh (The University of the South Pacific, Fiji)
DOI: 10.4018/979-8-3693-9856-2.ch006
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Abstract
This chapter examines how generative AI helps the food SCM evolve and aims to improve its efficiency, robustness, and sustainability performance. Using generative AI models, predictive analytics, and digital technologies, the paper identifies the AI's usage, data availability, digital supply chain, and the accuracy of the demand forecast. Therefore, the structured quantitative approach was adopted, and responses were collected on a seven-point Likert scale from 215 participants: financial analysts, market specialists, and other supply chain practitioners. Simple descriptive statistics such as frequency distributions and measures of central tendencies and variability were used as data analysis tools, and hypothesis testing involved basic bivariate correlation coefficients and bootstrapping to make the results conservative and replicable. The study points out how applying AI enhances decision-making, cuts costs and wastes, and can also enhance logistics. It also provides valuable information on developing sustainable and flexible food supply chains in complex contexts.
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