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Technological districts (Science Technology Parks, STPs) with high levels of competitiveness and growth are not easy to establish. Pugh et al (2018) report a 60% failure rate in the UK, while the World Bank (Kelly & Firestone, 2016) report a success rate globally of only 20%.
This work will model factors leading to success or failure of STPs, using comparative data from Sweden and the UK. The methods will be a combination of classical techniques like case-based reasoning but will also feature more econometric techniques including 3D modelling in Maple as well as Markov Chain Monte Carlo methods.
Impact will be high-profile and international in the area of public policy and governmental strategies and relevant to other subjects in the School, like "Smart Cities".
I am a research student at Kingston University, London under Faculty of Science, Engineering and Computing. My research interest is using computer modelling to help organisations and governments build a proper strategic plan when planning for a new STP by examining young ones and comparing them to mature successful ones. I am interested in analysing the success and optimum configuration of business clusters, using an approach based on econometrics, regional studies and innovation management. I did my MSc in Computing from London Metropolitan University and have passed with merit. Last 10 years I have worked as a software programmer and have gained significant experience in data analysis and implement them using programming language to develop reports and application.