AI-Driven Dynamic Pricing for Sustainable Retail and Food Waste Reduction

The College of Business, Technology and Engineering at Sheffield Hallam University aims to be a leading provider of applied research excellence delivering innovations across business, materials, computing, science, and engineering. This PhD focuses on tackling the challenge of food waste in the UK retail sector caused by demand uncertainty and static pricing. By leveraging AI, particularly reinforcement learning and machine learning, this project will develop a dynamic pricing and inventory optimisation framework that incorporates real-time product freshness and demand variability. You will undertake a design science and data-driven approach, starting with a systematic literature review to inform a conceptual framework. You will design AI models trained on simulated and secondary datasets to learn optimal pricing and inventory policies. Furthermore, you will develop a sensor-enabled case study model in a controlled environment to test freshness-aware pricing decisions. Expected Outcomes This research will advance knowledge in dynamic pricing by introducing a freshness-aware decision framework and operationalise AI models with real-time data integration. You will contribute to academia and industry by providing insights that help retailers reduce food waste while maintaining commercial performance. Why It Matters Aligning with the priorities of sustainable food systems and digital transformation, this project addresses the gap between cutting-edge analytics and practical retail operations. The outcomes promise impactful improvements in economic, environmental, and societal dimensions.

Applicants should hold at least a 1st or 2:1 Honours degree in Computer Science, Artificial Intelligence, Data Science, Operations Research, Logistics, Supply Chain Management, Industrial Engineering, Information Management, Information Science, or a related discipline. English language proficiency equivalent to IELTS 7 with minimum 6.5 in all areas is required for non-native speakers. Applications from individuals underrepresented in postgraduate research are strongly encouraged.

Visit the institution website to register your interest and apply. This PhD is part of a Graduate Teaching Assistantship scheme where successful applicants will undertake teaching duties in addition to their research work.