Tallinn University of Technology, School of Business and Governance, Department of Business Administration offers a 4-year PhD position in business.
Proposed doctoral thesis topic: "Industrial Strategy and Competitiveness Research Using Innovative Data Analytics".
Supervisors: Professor Tarmo Kalvet and Senior Researcher Marek Tiits
A research team working on industrial strategy and competitiveness using innovative data analytical methods and tools is looking for a PhD candidate interested in economic complexity and global value chains. The PhD candidate would join the two on-going international projects, carried out in co-operation with outstanding research partners.
The research group is driven by the understanding that the living standard of nations depends fundamentally on their ability to earn export revenues. The dependence on foreign trade is especially obvious for small(er) economies. However, not all products are the same in terms of their potential to contribute to the increase in living standards. Evolutionary economics maintains that in order to increase living standards, nations and companies should increase the knowledge intensity of products. Research on economic complexity operationalises this by focusing on the ubiquity and relatedness of products, and the analysis of potential pathways for entering more complex product groups. Open-data, big-data, and other novel data science approaches are currently seen as transforming the landscape for business administration, decision-making, socio-economic policy and research.
The objective of the research project is to develop research methods, with a particular focus on advanced data analytics skills to be exploited to conduct improved analysis of global value chains (GVCs), clusters and companies, and to identify and analyse the impact of relevant public policies.
The researcher is expected to contribute to the research project “Economic Complexity, Machine Learning and Economic Policy” (2022-2025). This project advances the state-of-the art by integrating the market demand side of the international trade and considering risks involved in a country’s and companies’ participation in global value chains. Another major novelty is the inclusion of data not generally utilised for such research and the use of explainable machine learning, acknowledged as a crucial feature for the practical deployment of AI models. On the basis of the research, a framework is built on business intelligence, business administration and public services, and on policy support. The above leads to actionable research results on upgrading the competitive advantages and securing the strategic autonomy of the European economies.
As part of the CatChain project (“Catching-Up along the global value chain: business models, determinants and policy implications in the era of the Fourth Industrial Revolution”, 2018-2024), fully funded short term research trips (in total up to 12 months) to Seoul National University (South Korea), University of Malaya (Malaysia), University of Campinas (Brazil) and to our other strategic research partners, are available and highly encouraged.
The researcher will be also part of the H2020 project “Industrial Strategy and Competitiveness Studies at TalTech” (2020-2023). This project develops strategic partnership between TalTech as the beneficiary, and Bocconi University (Italy), Aalto University (Finland) and NESTA (United Kingdom).
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