Abdullah's research interests spans three inter-related areas of innovation management and policy. First, he studies emerging technologies and their implications for business strategy and public policy. He is interested in how emerging technologies are developed, governed and commercialised. He was involved in research projects studying i) emergence and growth of graphene-based enterprises around the world, ii) University of Manchester’s commercialisation strategy for the Nobel level success in graphene research, iii) strategies of high growth green goods manufacturing enterprises in the UK, US and China, iv) science and innovation systems transition in China and Russia, v) research and innovation trajectories of quantum technologies, vi) responsible research and innovation in synthetic biology and vii) applications, expectations and concerns for synthetic biology through applying text mining techniques on tweets and website data.
Abdullah’s second research area relates to formulation, evaluation and impact of innovation policy. He studies how government intervention creates impact on innovative businesses and how this impact is evaluated, particularly by employing an evolutionary view of innovation. He was a Co-PI of the Compendium of Effectiveness of Innovation Policy project in which a large team synthesised the evidence on the effectiveness of business innovation support programmes. Furthermore, he has been involved in a number of evaluations of innovation policies as well as large scale projects that collect, analyse and conceptualise evaluations. Building on his PhD research, he is extending his work on the concept of behavioural additionality – persistent evolutionary change in the behaviour of innovative firms due to external triggers such as innovation policy intervention. He is a co-editor of the forthcoming Handbook of Innovation Policy Impact, while he published a number of articles and book chapters on this topic.
His third research area is at the intersection between data and innovation. He utilises data science in studying innovation by developing (“big” and novel) data collection and analysis methods, for instance to identify firms in certain sectors and to study their innovation strategies from unstructured information in their websites. As part of this effort, he published methodological articles and organised two data science and innovation workshops that bring together the community of scholars working on this area. He is also interested in studying data as a driver for innovation. Abdullah has recently been developing a research programme around questions like how data influences the way innovation is created, how public policy supports data-driven innovation and the managerial, economic, social issues related to data-driven innovation and innovation policy.
Dr Abdullah Gök is currently co-supervising PhD researchers working on innovation in the oil industry in Brasil, and commercialisation of synthetic biology. He previously supervised students studying evaluation of innovation policy. Abdullah is interested in supervising further PhD students, any prospective PhD students are encouraged to contact him directly.