Money for Nothing, Innovation for free? The Role of research funding in research output

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the Faculty of Business and Law, and will be supervised by Dr Ali Sina Onder, Dr Sercan Ozcan and Prof Lester Hunt.

This project aims to investigate the linkage between research funds and scientific outputs. To provide specific recommendations for funding policies and strategies, this study will focus on the UK. To gain a better understanding of how research funding affects research output in a broad set of emerging fields and hence to increase the efficiency of funding, this project proposes to investigate causal linkages between funding related variables (i.e. size, type and frequency of funds) and output related variables (i.e. number, quality and dissemination of outputs).

The work on this project could involve:
-analysing the causal relationship between research funding and (a) the quality of output, (b) patterns of collaboration between co-authors or co-inventors and (c) diffusion and pervasiveness of research

-investigating the extent, efficiency and cost-effectiveness of inter-disciplinary research funding by analysing causal links between researchers’ academic background, impact of their research and the level of funding

-documenting research funding profile and characteristics in the UK and developing a funding policy to increase the efficiency of the funding mechanisms in the UK.

Economics of science and innovation is an emerging field at the crossroads of public economics, labour economics and innovation management. Science and innovation drive long term economic growth and development. Persistent success in science and innovation hinges among other things upon the size and availability of public and private research funds to support scientists’ endeavours. The current literature in this field fails to establish a clear causal relationship between research funding and output.

Considering the gap in the literature, proposed study will make use of targeted text-mining techniques to create a large micro-level databases of research funding and output of British institutes, especially in particular emerging sectors. Specific institutional settings of research funding will be used for establishing causality in a rigorous microeconometric analysis.

Entry requirements
You’ll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements
We welcome applications from highly motivated prospective students with a background in economics, econometrics, information management, or computer science and other relevant disciplines with an interest in the proposed research. Familiarity with data science and bibliometric methods is desirable (not essential). We encourage prospective students to design their own research strategies depending on their interest and core skills.

How to apply
We’d encourage you to contact Dr Ali Sina Onder at [Email Address Removed] to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our online application form (please follow the institution website link to access it). Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.

If you want to be considered for this self-funded PhD opportunity you must quote project code ECFN5100220 when applying.