Traditional approaches to measuring innovation have provided a strong foundation, but they often suffer from limitations such as lack of flexibility, scalability, and real-time responsiveness. Sajad’s dissertation addresses these challenges by proposing novel methodologies based on large-scale data collection and analysis techniques, such as web scraping, text mining, and the use of large language models. These approaches allow researchers and policymakers to complement existing measures with new indicators that offer deeper insights into firm-level innovation, digital transformation, and paradigm-shifting discoveries.
Through a series of case studies, the dissertation demonstrates how novel methodologies can enhance the coverage, accuracy, and contextual relevance of innovation measurement, offering actionable insights for strategic planning, policymaking, and foresight. Beyond methodological advancements, it introduces data-driven indicators and multidimensional frameworks that capture not only the quantity but also the quality, novelty, and impact of innovations, emphasising the practical value of new data tools for continuous monitoring, strategy development, and decision-making in innovation management.
"A hybrid indicators paradigm which integrates the traditional innovation indicators with big data-based metrics to yield deeper theoretical insights into innovation systems across time, space, and networks. The hybrid paradigm, therefore, advocates innovation studies to gain insights previously unattainable through traditional methods alone," Sajad Ashouri notes.
Sajad Ashouri is a Research Scientist at VTT Technical Research Centre of Finland, specialising in business foresight and technology and innovation management. His work focuses on applying advanced data science, artificial intelligence, and generative AI methods to support data-driven decision-making and business analytics. He has extensive expertise in utilizing emerging data sources and analytical techniques for trend forecasting, policy evaluation, and R&D analytics, helping organizations anticipate technological shifts and evaluate the impacts of innovation policies.
Public Defence on Wednesday 14 May
M.Sc. MRes. Sajad Ashouri’s doctoral dissertation in the field of innovation management, titled Developing Scalable and Adaptive Methodologies for Measuring Innovation, will be publicly examined at 12 o'clock on Wednesday 14 May at the Faculty of Management and Business, Tampere University. The venue is Festia building, Auditorium Pieni sali 1 (address: Korkeakoulunkatu 8, Tampere). The Opponent will be Associate Professor Antti Knutas from LUT University, Finland, and Professor Arho Suominen from Tampere University will act as the Custos.