About the Project
The University of Exeter Business School trains world-class researchers who will shape how we understand and respond to the most important societal challenges.
Students receive full funding, which includes a tax-free stipend of £19,000 that covers the 3-year PhD, and a tuition fee waiver. Students are additionally eligible for funding to support their research, development and conference attendance. The scholarship includes a requirement that students work as teaching or research assistants for 23 days (180 hours) a year. This is a valuable part of your training and will ensure that you graduate from the Business School as a highly skilled researcher and educator.
Circular Economy – Improving the UK evidence base through data, modelling and quantification
The total material requirements for the UK economy is over 1bn tonnes p.a. dominated by construction minerals, biomass, fossil fuels and metal ores; approximately 15% higher than 2001. The UK also generates an estimated 200 million tonnes of waste p.a. :12% higher than 2010. Additionally, according to a recent study the production of goods and services are a significant contributor (45%) to carbon emissions. The proportion of resources that are recovered, re-used or recycled after a first use life has been estimated to be <10%, meaning their embodied value and materials are lost, whilst placing increasing demand and pressure on virgin materials and scarce resources. This linear take-make-dispose approach to economic growth is widely recognised as being non-sustainable and a different model is required.
The CE is a simple, yet compelling framework based on a set of clear principles that decouple resources from economic growth through innovation and entrepreneurship. Analysis has indicated that scaling up circularity provides a multi-billion economic opportunity, driving up resource productivity, driving down material costs, improving resource security and reducing negative externalities and their human and environmental costs. In the wake of COVID-19 there is a significant opportunity for a more sustainable and resilient recovery that can ‘Build Back Better’. Recent reports propose that moving to a more CE can provide an essential element of the UK’s recovery plan, delivering increased clean growth, net jobs, higher resilience and regenerate natural capital.
To drive a CE at scale across value chains in the UK requires a systematic and systemic approach including: the future design of materials, components, products, services and infrastructure business models that promote access and performance over ownership; closed loop and reverse logistics and whole system enablers and innovation, including the use of data, emerging technologies and behaviour change.
There is now a need for improved modelling, scientific evidence and quantification of CE interventions to enable more effective decision-making, prioritisation and implementation. Specifically, there is a need for: metrics and KPIs for framing and measuring successful CE implementation; identification of the right data to measure CE performance at different levels (material flows, supply chain, reverse logistics, design, operations); forecasting methods and quantification of business models to support buy-in and decision making within organisations and governmental bodies and industry-specific CE indicators to inform prioritisation of investment and research.
This PhD will (1) select and develop modelling approaches, and data sets quantify, evaluate and prioritise different CE value creation options and interventions at a variety of scales, compared to business as usual, via well-researched case examples, modelling and scenario analysis, and (2) track the aggregate progress and contribution towards one or more pivotal UK resource or sector related to policy commitments such as nett zero and targets to inform policy and industrial user needs.
The framework for the research is to (1) theorise and synthesise an underlying taxonomy and conceptual design of the modelling and data framework; (2) build, test and validate a rapid, agile and iterative implementation and data population of the models and sub models to quantify outcomes and impacts; (3) Co-ordinate a CE metrics and indicator for institutionalizing and embedding data, evidence and analysis to one or more industrial sector or strategic resource flow to be agreed.
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