This project is funded by:
This PhD project aims to revolutionize sustainable supply chain management by integrating blockchain and artificial intelligence (AI) to enhance transparency, traceability, and accountability. In complex, multi-stakeholder supply chains, it is often difficult to verify the origin, environmental impact, and ethical standards of products. Blockchain provides an immutable, decentralised record of each stage in the supply chain, from raw material sourcing to delivery, while AI analyzes this data to predict and verify sustainability metrics, such as carbon footprint, energy use, and waste generation.
Despite the potential of these technologies, implementing them at scale involves key challenges. Supply chain data often exists in disparate systems, making integration complex; there is a need for standardised metrics to ensure data accuracy, and processing data in real time requires robust AI-driven solutions. This project will develop an interoperable blockchain framework to unify supply chain data, employ AI algorithms for accurate sustainability tracking, and deliver real-time insights that support proactive decision-making.
Aligned with the United Nations Sustainable Development Goal (SDG) 12: Responsible Consumption and Production, this research will foster a more sustainable and transparent supply chain system. It will empower suppliers, manufacturers, and consumers to make informed, responsible choices by providing verified environmental data on products. Ultimately, this project will drive the adoption of sustainable practices, encourage transparency across industries, and enable consumers to support environmentally responsible production.
Objectives:
1. Develop an interoperable blockchain framework for seamless data integration across supply chains.
2. Build AI-driven algorithms to ensure accurate, reliable tracking of sustainability metrics.
3. Implement real-time analytics for resource optimisation, reducing waste and energy use.
4. Create consumer-facing transparency tools for verified sustainability information, encouraging responsible consumption.
Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.
We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.
In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.
Appointment will be made on merit.
This project is funded by:
Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance). A Research Training Support Grant (RTSG) of £900 per annum is also available.
These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.
Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.
Due consideration should be given to financing your studies.
1. Dedeoglu, V., Malik, S., Ramachandran, G., Pal, S. and Jurdak, R., 2023. Blockchain meets edge-AI for food supply chain traceability and provenance. In Comprehensive analytical chemistry (Vol. 101, pp. 251-275). Elsevier.
2. Charles, V., Emrouznejad, A. and Gherman, T., 2023. A critical analysis of the integration of blockchain and artificial intelligence for supply chain. Annals of Operations Research, 327(1), pp.7-47.
3. Tsolakis, N., Schumacher, R., Dora, M. and Kumar, M., 2023. Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?. Annals of Operations Research, 327(1), pp.157-210.
4. Khan, M., Parvaiz, G.S., Dedahanov, A.T., Abdurazzakov, O.S. and Rakhmonov, D.A., 2022. The impact of technologies of traceability and transparency in supply chains. Sustainability, 14(24), p.16336.
5. Sunny, J., Undralla, N. and Pillai, V.M., 2020. Supply chain transparency through blockchain-based traceability: An overview with demonstration. Computers & Industrial Engineering, 150, p.106895.
6. Casino, F., Kanakaris, V., Dasaklis, T.K., Moschuris, S., Stachtiaris, S., Pagoni, M. and Rachaniotis, N.P., 2021. Blockchain-based food supply chain traceability: a case study in the dairy sector. International journal of production research, 59(19), pp.5758-5770.
7. Behnke, K. and Janssen, M.F.W.H.A., 2020. Boundary conditions for traceability in food supply chains using blockchain technology. International Journal of Information Management, 52, p.101969.
8. Dwivedi, V., Norta, A., Wulf, A., Leiding, B., Saxena, S. and Udokwu, C., 2021. A formal specification smart-contract language for legally binding decentralized autonomous organizations. IEEE access, 9, pp.76069-76082.
Submission deadline
Monday 24 February 2025
04:00PM
Interview Date
3 April 2025
Preferred student start date
15 September 2025
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