Periodic Reporting for period 3 - TechEvo (Technology Evolution in Regional Economies)
Berichtszeitraum: 2020-03-01 bis 2021-08-31
The creation and accumulation of knowledge are processes at the heart of technological change, economic growth and prosperity. Attention has been directed at aggregate measures of knowledge production in regional and national contexts, but little consideration has been given to the properties, heterogenous nature, and multi-dimensional aspects of knowledge produced in specific places. This leaves open numerous key questions including: How does the nature of knowledge that is produced vary over space, what conditions the scope of scientific and technological advances generated in different locations, and how do these knowledge sets impact the performance of local firms and industries? To date, the way in which specific regional knowledge capabilities influence the evolution of local technology trajectories and thus shape geographies of economic prosperity have not yet been considered systematically.
Cluster initiatives in the past, and more recently research and innovation strategies utilized for smart specialization (RIS3 platform of the European Commission), all suffer from this shortcoming despite their aim to prescribe smart growth policies that are based on place-specific scientific and knowledge core competencies. Thus, empirical evidence that identifies evolutionary patterns of knowledge production and that takes into account the heterogeneity in science-technology trajectories among regions, is critically needed. Due to the lack of appropriate empirics, potential intra- and inter-regional synergies are overlooked, and the likely outcome is that regional innovation strategies only re-enforce existing industry structures while overlooking potential future growth avenues.
The objective of TechEvo is to fill this significant research gap by investigating the long-term evolution of scientific and technological knowledge and expertise in European regions from 1981 to the present. Questions concerning the production, application and diffusion of knowledge are at the centre of the innovation and economic growth literatures and thus novel insights into how the actual type of knowledge produced within specific places shapes the innovative capacity of a locality, and its future technological prospects, are urgently needed. Grounded in the framework of evolutionary economics and the evolutionary economic geography literatures, TechEvo offers ground-breaking insights into how innovative entities and individual inventors and scientists are embedded in social and cognitive local and non-local networks, and how regional knowledge trajectories are shaped through entry, exit, and selection processes. Furthermore, the project develops theories, methods and empirics that significantly advance existing work, push the scientific frontier of innovation research, and deliver a science and technology policy evaluation tool capable of assessing impact.
Cluster initiatives in the past, and more recently research and innovation strategies utilized for smart specialization (RIS3 platform of the European Commission), all suffer from this shortcoming despite their aim to prescribe smart growth policies that are based on place-specific scientific and knowledge core competencies. Thus, empirical evidence that identifies evolutionary patterns of knowledge production and that takes into account the heterogeneity in science-technology trajectories among regions, is critically needed. Due to the lack of appropriate empirics, potential intra- and inter-regional synergies are overlooked, and the likely outcome is that regional innovation strategies only re-enforce existing industry structures while overlooking potential future growth avenues.
The objective of TechEvo is to fill this significant research gap by investigating the long-term evolution of scientific and technological knowledge and expertise in European regions from 1981 to the present. Questions concerning the production, application and diffusion of knowledge are at the centre of the innovation and economic growth literatures and thus novel insights into how the actual type of knowledge produced within specific places shapes the innovative capacity of a locality, and its future technological prospects, are urgently needed. Grounded in the framework of evolutionary economics and the evolutionary economic geography literatures, TechEvo offers ground-breaking insights into how innovative entities and individual inventors and scientists are embedded in social and cognitive local and non-local networks, and how regional knowledge trajectories are shaped through entry, exit, and selection processes. Furthermore, the project develops theories, methods and empirics that significantly advance existing work, push the scientific frontier of innovation research, and deliver a science and technology policy evaluation tool capable of assessing impact.
The ERC Technology Evolution in Regional Economies (TechEvo) project has recently reached its half-way point, marking 30 months since commencing, and by comparison to the initial proposal this ambitious frontier research project is currently ahead of schedule. Over the past two and a half years as is common with large-scale and long-term scientific inquiries, there have been obstacles that needed to be overcome while at the same time new challenges and opportunities have opened up following initial insights. Below, key aspects of the work performed since the inception of the project are highlighted.
Following the proposed workplan, the efforts over the initial 30-month research period mainly centred on Work Packages 1 & 2 (WP#1 & WP#2). Thus, the main focus was on “the knowledge space and technology life-cycles” (WP#1 – initial 16 months), and “knowledge creation, diffusion, and recombination” (WP#2 – subsequent 14 months).
The initial critical task (WP#1) was to establish and develop the core TechEvo patent, science and trademark database (for analysis), as well as the regional database platform that will be complemented throughout the project duration and play a key-role for the development of the objectives in WP#4.
At this point the TechEvo database platform is set-up, operational, and a number of key objectives in terms of analysis have been either completed or are ongoing. Without doubt and confirmed by the leading scientific community in data and algorithms for science-technology and innovation studies (ST&I), this is probably the most advanced and comprehensive database for analysing the evolution of regional knowledge production, diffusion and application processes. The principal investigator (PI) of the TechEvo project is involved as a core-organizer of the annual Summer School of Data and Algorithms for ST&I, which provides an annual benchmark for evaluation.
Concerning the key deliverables associated with WP#1 and WP#2, currently there are already 5 manuscripts that have been published, and about a dozen further ones that are under development and forthcoming. In conclusion, at the half-way mark of the TechEvo project (2.5 years) all critical tasks have been successfully completed, and scientific output has well exceeded the proposed key deliverables as specified in the original ERC TechEvo proposal document.
Following the proposed workplan, the efforts over the initial 30-month research period mainly centred on Work Packages 1 & 2 (WP#1 & WP#2). Thus, the main focus was on “the knowledge space and technology life-cycles” (WP#1 – initial 16 months), and “knowledge creation, diffusion, and recombination” (WP#2 – subsequent 14 months).
The initial critical task (WP#1) was to establish and develop the core TechEvo patent, science and trademark database (for analysis), as well as the regional database platform that will be complemented throughout the project duration and play a key-role for the development of the objectives in WP#4.
At this point the TechEvo database platform is set-up, operational, and a number of key objectives in terms of analysis have been either completed or are ongoing. Without doubt and confirmed by the leading scientific community in data and algorithms for science-technology and innovation studies (ST&I), this is probably the most advanced and comprehensive database for analysing the evolution of regional knowledge production, diffusion and application processes. The principal investigator (PI) of the TechEvo project is involved as a core-organizer of the annual Summer School of Data and Algorithms for ST&I, which provides an annual benchmark for evaluation.
Concerning the key deliverables associated with WP#1 and WP#2, currently there are already 5 manuscripts that have been published, and about a dozen further ones that are under development and forthcoming. In conclusion, at the half-way mark of the TechEvo project (2.5 years) all critical tasks have been successfully completed, and scientific output has well exceeded the proposed key deliverables as specified in the original ERC TechEvo proposal document.
To date, the ERC funded Technology Evolution in Regional Economies (TechEvo) project has already surpassed a number of expectations beyond the state of the art. The proposed “knowledge space” methodology is establishing itself as a sound and widely applied empirical tool capable of assessing regional knowledge (scientific and technical) capabilities leading to future growth opportunities, which in turn is much needed for the more effective regional development and innovation policy instruments.
Effectively, based on the knowledge space methodology, it is possible to provide more insightful metrics concerning the present economic structure of a place, while subsequently making it possible to evaluate the future potential of entry and exit of particular sectors. Considerations regarding the life cycle or recombination potential of technologies, for example, further adds to the predictive power of the knowledge space methodology.
A recent TechEvo contribution by Kogler and Whittle (2019) reaches the following conclusions: “the proposed knowledge space methodology has important bearings for the recently proposed Smart Specialization Strategies framework. By taking an evolutionary look at regions in terms of their underlying knowledge structure the expectation is that it is possible to direct investments into realistic development pathways”. (p. 165).
It is expected that TechEvo will continue to offer even further progress beyond the state of the art in the second half of the project. All the results, insights and theoretical and empirical advancements that will result from the TechEvo project by the time it is completed are expected to revolutionize the way regional innovation systems are analysed, and subsequently how strategies and policies utilize regional science-technology and innovation indicators in the development of more effective policy interventions.
Effectively, based on the knowledge space methodology, it is possible to provide more insightful metrics concerning the present economic structure of a place, while subsequently making it possible to evaluate the future potential of entry and exit of particular sectors. Considerations regarding the life cycle or recombination potential of technologies, for example, further adds to the predictive power of the knowledge space methodology.
A recent TechEvo contribution by Kogler and Whittle (2019) reaches the following conclusions: “the proposed knowledge space methodology has important bearings for the recently proposed Smart Specialization Strategies framework. By taking an evolutionary look at regions in terms of their underlying knowledge structure the expectation is that it is possible to direct investments into realistic development pathways”. (p. 165).
It is expected that TechEvo will continue to offer even further progress beyond the state of the art in the second half of the project. All the results, insights and theoretical and empirical advancements that will result from the TechEvo project by the time it is completed are expected to revolutionize the way regional innovation systems are analysed, and subsequently how strategies and policies utilize regional science-technology and innovation indicators in the development of more effective policy interventions.