We propose a machine learning approach to identify service robotics technologies within the knowledge space of robotic patents. Apart from analyzing this particular area of knowledge for the first time using machine learning methods, our paper provides two important methodological novelties: (i) We propose a new matching method to distinguish topics belonging to service robotics using descriptions of SR fields provided by the international Federation of Robotics. (ii) We construct a graph of topic interrelations showing which topics appear more often together thus distinguishing between more "general purpose" topics and those which appear more isolated (typically specific application fields). In doing that, we distinguish significant edges by building a null model and conducting a Monte Carlo experiment to assess how likely the edge is to be observed given the structure of the data. The paper offers a series of findings regarding dynamics of the topics over time, the share and position of SR topics in the overall space of knowledge, and the implications of our findings for policy.

Identifying emerging technologies has been of long-standing interest to many scholars and practitioners. Previous studies have introduced methods to capture the concept of emergence from bibliographic records, including the recently proposed Technology Emergence Indicator. This indicator method has shown to be applicable to various technological fields. However, the indicator uses a limited time window, which can overlook the potential long-term evolution of emerging technologies. Moreover, the existing method suffers from interpretability, because it can be difficult to understand the context in which identified emerging terms are used. In the paper of Seokkyun Woo, Jan Youtie, Ingrid Ott and Fenja Scheu (2021) , an improved version of the Technology Emergence Indicator that addresses these issues is proposed. In doing so, emerging topics within the field of autonomous vehicles technologies during the period of 1991-2018 are examined, guided by a proposition about the long-term diffusion of an emerging technology topic.

In order to achieve the convergence objective, the EU relies on integration and policy coordination, supported by substantial (supra-)national budgets. These are used to finance a wide range of government expenditure, for example on education or public security. In a spatial growth model, Ingrid Ott and Susanne Soretz show that, when designing coordination mechanisms and integration, more attention needs to be paid to the extent to which convergence can be achieved as a result of market incentives and the interaction between the public and private sectors.

Thomas Vöhringer was awarded the Fakultätspreis 2020, prize of faculty of economics for his master thesis:

Knowledge Generation and the Speed of Knowledge Obsolescence in the Era of the Digital Transformation.

The faculty of Economic Policy congratulates Thomas Vöhringer for his great achievement.

The joint workshop, originally planned for 19 and 20 March 2020, by the Chair in Economic Policy together with 

ZEW: Economics of Innovation and Industrial Dynamics 

ISI: CC Innovation and Knowledge Economy 

TUB: Chair of Innovation Economics 

will take place at a later time.

The annual convention of the Ausschuss für Regionaltheorie- und Politik des Vereins für Sozialpolitik initially planned for 8.-10. October 2020 is postpoend to October 2021.

Der Lehrstuhl für Wirtschaftspolitik hostet die KIT Working Paper Series in Economics. Die beteiligten Lehrstühle finden Sie hier. Wenn Sie einen Beitrag einreichen möchten, kontaktieren Sie bitte econpapers@wiwi.kit.edu

Donnerstags um 11:45 Uhr findet der Workshop on Economics and Finance statt. Alle Interessierten sind herzlich willkommen!

Mittwochs um 11:30 Uhr findet das Brown Bag Seminar statt. Interessierte sind herzlich willkommen!