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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.
Mondal, Charles and Mellor, Robert B. (2021) Analyses of small and medium-sized science and technology parks show that longer-term growth may depend upon attracting larger partners. International Journal of Management and Enterprise Development, 20(3), pp. 311-328. ISSN (print) 1468-4330
Mondal, Charles, Kussainov, Adilkhan and Mellor, Robert B. (2021) Modelling the number of client firms needed to support a new Science Park and the spacing between new Parks and existing Parks with similar themes. International Journal of Knowledge-Based Development, 12(2), pp. 141-155. ISSN (print) 2040-4468