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

About the Project

Project Description:

The College of Business, Technology and Engineering draws on talents, expertise and facilities across Sheffield Hallam University. The vision is to be the leading provider of applied research excellence delivering business, materials, computing, science and engineering innovations meeting the development needs of industry.

This project is part of a Graduate Teaching Assistantship scheme, in which the successful applicant will undertake certain teaching duties associated with the student experience, in addition to working towards a PhD qualification. They will contribute up to 180 hours of support for research or teaching related activity per academic year. This activity forms part of the scholarship and there is no additional payment.

PhD Research Topic:

The UK retail sector faces a persistent and costly challenge in managing perishable food products, with significant implications for economic performance, environmental sustainability, and supply chain efficiency. Food waste at the retail level is primarily driven by demand uncertainty, limited shelf life, and inflexible pricing and inventory practices. Despite the increasing availability of data, many retailers continue to rely on static markdown strategies that fail to respond dynamically to real-time changes in product freshness and demand. This results in suboptimal decision-making, contributing to avoidable waste and reduced profitability.

This PhD project aims to address these challenges through the development of an integrated, AI-driven framework for dynamic pricing and perishable inventory optimisation. The research will explore how advanced artificial intelligence techniques, particularly reinforcement learning and machine learning, can be leveraged to support real-time pricing and inventory decisions that explicitly account for product freshness, demand variability, and operational constraints.

A key innovation of this project lies in the integration of real-time data from smart technologies into decision-making models. The research will investigate how Internet of Things (IoT) sensors, such as temperature and humidity monitors, can be used to generate proxy indicators of product freshness. These data streams will be incorporated into AI-based pricing algorithms, enabling more responsive and context-aware decision-making. By combining freshness-aware data with predictive demand modelling, the project seeks to develop adaptive pricing strategies that optimise both revenue and waste reduction outcomes.

Methodologically, the project will adopt a design science and data-driven approach. Initial work will involve a systematic review of the literature on perishable inventory management, dynamic pricing, and AI applications in retail. This will inform the development of a conceptual framework linking data inputs, decision models, and operational outcomes. The core of the research will focus on the design and implementation of AI-based models capable of learning optimal pricing and inventory policies under uncertainty. These models will be trained and evaluated using simulated and secondary datasets, reflecting realistic retail scenarios.

To enhance practical relevance, the project will include the development of a small-scale, sensor-enabled case model within a controlled experimental environment. This will demonstrate the feasibility of integrating real-time freshness data into pricing decisions without reliance on large-scale industry infrastructure. The framework will be evaluated through computational experiments and scenario-based analysis, assessing its performance in terms of waste reduction, profitability, and robustness under varying conditions.

The expected contributions of this research are both theoretical and practical. Academically, the project will advance the state of knowledge in dynamic pricing and perishable inventory management by introducing a unified, freshness-aware decision framework. Methodologically, it will demonstrate how AI models can be operationalised using real-time data inputs in applied settings. From an industry perspective, the research will provide actionable insights for retailers seeking to reduce food waste while maintaining commercial performance.

Overall, the project aligns with growing priorities around sustainable food systems and digital transformation. By addressing a critical gap between advanced analytics and real-world retail operations, it has the potential to deliver meaningful impact across economic, environmental, and societal dimensions.

Eligibility

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.

We strongly encourage applications from individuals from groups underrepresented in postgraduate research, including but not limited to women, LGBTQ+, and minoritised ethnic groups.

Information for international applicants

English language requirements of IELTS 7 with a minimum score of 6.5 in all test areas (or equivalent) are mandatory if English is not your first language. Qualifications should have been taken within the last two years. Further information can be found here.

How to apply

To apply for this GTA scholarship, please use our online application form.

You must ensure that you upload:

1. A personal statement (up to 2 pages maximum) detailing your interest in the project and how your experience in academia, industry, research or social activities makes you the best candidate (Please upload this in place of a proposal). We’re looking for evidence of:
   • motivation and curiosity for postgraduate research
   • analytical and technical expertise related to the research proposal
   • ability to communicate clearly
   • planning and organisational skills
   • ability to work independently and collaborate with others
   • commitment to integrity and responsible research
   • resilience to setbacks and challenges
   • where you might contribute to teaching
2. A two page (maximum) CV
3. Two letters of reference, or details of two referees, at least one from an academic and both dated within the last 2 years
4. Copy of your highest degree certificate and transcript. If your degree is not yet awarded then submit a copy of your latest transcript.
5. Non-UK applicants must submit IELTS results (or equivalent) taken in the last two years and a copy of their passport

If you are applying for multiple GTA projects, please clearly list them all in your application. You will need to submit a tailored personal statement for each project.

Application deadline: 07 May 2026

Start date: October 2026

Interviews: TBC

Funding Notes

The GTA scholarship is for 3.5 years of full-time study and provides tuition fees at both the UK (home) and international level plus a maintenance bursary in line with guidance from UK Research and Innovation and the Living Wage Foundation (for illustrative purposes, the Sheffield Hallam University bursary for 25/26 is £22152). GTA scholarships are open to both UK (home) and international applicants.