Knowledge Economy

The creation, accumulation and diffusion of knowledge are processes at the heart of technological change and economic growth. Scientific and technological expertise acquired in the past strongly determines future development opportunities, but also sets limitations in this regard. While this applies universally, regardless if considered at the personal, corporate, or spatial level, it is of particular interest in the context of cities and regions given that these entities serve as containers of unique knowledge pools. Guided by evolutionary principles and advanced spatial analysis approaches, and paired with multi-dimensional datasets, this research pillar aims to open up a new research frontier in science and technology studies, as well as to support the development of new planning and forecasting tools for progressive strategic innovation policies that translate in wide-spread advancement and prosperity.


Regional Knowledge Spaces – Entry-Relatedness & Entry-Potential for Technological Change and Growth

This paper aims to uncover the mechanism of how the network properties of regional knowledge spaces contribute to technological change from the perspective of regional knowledge entry-relatedness and regional knowledge entry-potential. Entry-relatedness, which has been previously employed to investigate the technology evolution of regional economies, is advanced by introducing a knowledge gravity model. The entry-potential of a newly acquired regional specialisation has been largely ignored in the relevant literature; surprisingly given the high relevance that is attributed to the recombination potential of new capabilities. In other words, just adding new knowledge domains to a system is not sufficient alone, it really depends on how these fit into the existing system and thus can generate wider economic benefits. Based on an empirical analysis of EU-15 Metro and non-Metro regions from 1981 to 2015, we find that entry-relatedness has a significant negative association with novel inventive activities, while entry-potential has a significant positive association with the development of novel products and processes of economic value. This highlights that regions’ capacity to venture into high-potential areas of technological specialization in the knowledge space outperforms purely relatedness driven diversification that is frequently promoted in the relevant literature.

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Regional knowledge spaces: the interplay of entry‑relatedness and entry‑potential for technological change and growth

Scientific collaboration, research funding, and novelty in scientific knowledge

In this project the focus is on publications' novelty as an indicator of scientific advancement with regard to collaboration and funding patterns. First, we investigate the relationship between collaborations and novelty in publications. Novelty in scientific publications often incorporates new ideas and opportunities from interdisciplinarity across heterogenous research groups to solve practical problems. Interdisciplinarity, which results from scientific collaboration, is believed to bring out new research outputs, and thus it is reasonable to expect some correlations between collaboration and novelty measures. To the best of our knowledge, however, only few studies have examined the relationship between scientific collaborations and novelty. Specifically, we examine collaborations at the country and various sub-national, i.e. regional, as well as the institutional levels. We measure novelty of articles with keywords' information. Finally, we evaluate the role of funding in research novelty.

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Scientific Collaboration, Research Funding, and Novelty in Scientific Knowledge

Artificial Intelligence (AI) – The Creation and Integration of AI Scientific and Technical Knowledge Spaces & Systems

The overall goal of this project is to a) to analyse how AI is integrated into the technical knowledge space of regions, and b) to map the creation of scientific knowledge at the global, national and regional scale, and there especially to show the evolution of AI knowledge and again how embedded it is in regional economies. In particular, we seek to build a comprehensive panel of AI patents and scientific publications. Along these lines, we first use identifying keywords to find every AI patent published in Europe between 1985 and 2013. Succinctly, we query the patent abstracts for n-grams like "Genetic Algorithms" or "Neural Networks." We then use this data to map the patents into regions - at the NUTS2 level - and technological codes - the 4-digits CPCs. And next, we borrow methods from network sciences to measure the embeddedness of AI into each region's knowledge space. In doing so, we find that AI "superstar" regions, where AI output is largest, are also those where it's most embedded into the innovation networks. We continue our project to map the development of AI as indicated in scientific publications. We reuse the keywords to identify AI-related publications in the Web of Science. And we employ the metadata within these publications to map the AI evolution across different scales - i.e., the continental, national, and regional levels. Through this exercise, we once again identify potential AI "hotspots" while also distinguishing between places that lead the development of AI from the onset vis-a-vis those that have managed to catch up over time. Besides, we produce networks that illustrate international collaborative efforts in AI knowledge creation via co-authorship across nations and via the evolution of keywords' co-occurrence across three decades. It is evident how these networks become denser with time and how they differ across regions. Therefore, the project aims to enhance our understanding of where and how AI knowledge emerges. Although the results are still exploratory, the project is the start of a reliable database to answer the big questions about AI systems. In particular, we hope to encourage and assist future research efforts addressing the creation of AI and its consequences.  The project relates to both the ERC TechEvo and SFI SciTechSpace funded research grants.

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OK Computer: the creation and integration of AI in Europe



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Dieter F. Kogler
Francesco Pilla