Recent Developments in Advanced Innovation Economics (Lecture)
Module No. 5209-521
Time: Monday 12:00-14:00
Room: HS 6
Short description:
‘Innovation Economics II: Recent Developments in Advanced Innovation Economics’ introduces the master students into the most common methods of modern innovation economics. Due to the high degree of complexity of innovation processes, traditional tools from neoclassical economics quickly reach their limits or are inadequate for the considerations of the particularities of innovation. In innovation economics, the heterogeneity of actors is considered to be an important source for learning and innovation. The concept of a representative firm which optimizes its profits is not suited because of the Knightian uncertainty prevailing all innovation processes. Innovations trigger dynamic processes of entrepreneurship and structural change. The concept of economic equilibrium most often is not suited for the analysis of Schumpeterian competition. For this reason, in innovation economics new tools were developed which allow dealing with heterogeneity, imperfect knowledge, non-linearities, and dynamics. In this course, we will introduce to simulation tools like agent-based models and social network analysis which fulfil, to some extent, the methodological requirements from innovation economics.
Contents:
I. The methodological requirements of modern innovation economics
II. Comprehensive Neo-Schumpeterian Economics
III. Indicator Based Modelling
IV. Simulation Models I: System Dynamics
V. Simulation Models II: Agent-based Models
VI. Responsible Innovation
VII. Social Network Analysis
Literature:
Blok, V. and Lemmens, P. (2015). The emerging concept of responsible innovation. Three reasons why it is questionable and calls for a radical transformation of the concept of innovation. In B.-J. Koops, I. Oosterlaken, H. Romijn, T. Swierstra, & J. van den Hoven (Eds.), Responsible innovation 2: Concepts, approaches, and applications (pp. 19-35). Cham: Springer.
Buchmann, T. and Pyka, A. (2012). Innovation networks. In M. Dietrich & J. Krafft (Eds.), Economics and theory of the firm (pp. 466-484). Cheltenham: Edward Elgar.
Fritsch, M. and Kauffeld-Monz, M. (2008). The impact of network structure on knowledge transfer: An application of social network analysis in the context of regional innovation networks. The Annals of Regional Science, 44, 21-38.
Hanusch, H. and Pyka, A. (2007), The Principles of Neo-Schumpeterian Economics. Cambridge Journal of Economics, 31(2), 275-289.
Macal, C. M. (2016). Everything you need to know about agent-based modelling and simulation. Journal of Simulation, 10(2), 144-156.Saviotti, P. P. and Pyka, A. (2004). Economic development by the creation of new sectors. Journal of Evolutionary Economics, 14(1), 1-35.
Stilgoe, J., Owen, R., and Macnaghten, P. (2013). Developing a framework for responsible innovation. Research Policy, 42(9), 1568-1580.
von Schomberg, R. (2013). A vision of responsible research and innovation. In: R. Owen, J. Bessant, & M. Heintz (Eds.), Responsible innovation: Managing the responsible emergence of science and innovation in society (pp. 51-74). Chichester: Wiley.
Further (recommended but not mandatory) literature on Topics VI & VII is provided on the slides.