Ex-Ante Evaluation of Investments in Knowledge, Learning, and Innovation

An Application Example

Authors

DOI:

https://doi.org/10.14512/tatup.26.3.51

Keywords:

innovation networks, knowledge diffusion and transfer, agent-based modeling and simulation, ex-ante policy evaluation

Abstract

Knowledge diffusion in regional innovation systems is considered as a necessary prerequisite to spur innovation and the economic performance of the actors involved. Yet, the conditions under which actors exchange knowledge in an efficient way are still not fully understood. In this paper we apply an agent-based simulation approach designed for ex-ante policy evaluation. The simulation approach and the application example are based on the VISIBLE simulation environment (“Virtual Simulation Lab for the Analysis of Investments in Learning and Education”). We investigate how presumably positive interventions affect the diffusion performance within an empirical network. Our results indicate that policy interventions can even hamper the diffusion properties of some network structures.

References

Axtell, Robert L.; Epstein, Joshua M. (1994): Agent-Based Modeling: Understanding Our Creations. In: The Bulletin of the Santa Fe Institute 9 (2), S. 28–32. Online verfügbar unter http://samoa.santafe.edu/media/bulletin_pdf/Winter1994Bulletin.pdf, zuletzt geprüft am 24. 10. 2017.

Brenner, Thomas; Cantner, Uwe; Graf, Holger (2011): Innovation Networks: Measurement, Performance and Regional Dimensions. In: Industry & Innovation 18 (1), S. 1–5. DOI: https://doi.org/10.1080/13662716.2010.528925

Cantner, Uwe; Graf, Holger (2011): Innovation Networks: Formation, Performance and Dynamics. In: Cristiano Antonelli (Hg.): Handbook on the Economic Complexity of Technological Change. Celtenham: Edward Elgar Publishing, S. 366–394. DOI: https://doi.org/10.4337/9780857930378.00023

Cohen, Wesley M.; Levinthal, Daniel A. (1990): Absorptive Capacity: A New Perspective on Learning and Innovation. In: Administrative Science Quarterly, 35 (1), S. 128–152. DOI: https://doi.org/10.2307/2393553

Cowan, Robin; Jonard, Nicolas (2004): Network Structure and the Diffusion of Knowledge. In: Journal of Economic Dynamics and Control 28 (8), S. 1557–1575. DOI: https://doi.org/10.1016/j.jedc.2003.04.002

Dawid, Herbert (2006): Agent-Based Models of Innovation and Technological Change. In: Leigh Tesfatsion und Kenneth Judd (Hg.): Handbook of Computational Economics II: Agent-Based Computational Economics. Amsterdam: North-Holland, S. 1235–1272. DOI: https://doi.org/10.1016/S1574-0021(05)02025-3

Gilbert, Nigel; Pyka, Andreas; Ahrweiler, Petra (2001): Innovation Networks: A Simulation Approach. In: Journal of Artificial Societies and Social Simulation 4 (3), S. 1–14. Online verfügbar unter http://jasss.soc.surrey.ac.uk/18/4/5.html, zuletzt geprüft am 24. 10. 2017.

Hanusch, Horst; Pyka, Andreas (2007): Elgar Companion to Neo-Schumpeterian Economics. Cheltenham: Edward Elgar Publishing. DOI: https://doi.org/10.4337/9781847207012

Kudic, Muhamed (2015): Innovation Networks in the German Laser Industry: Evolutionary Change, Strategic Positioning, and Firm Innovativeness. Heidelberg: Springer. DOI: https://doi.org/10.1007/978-3-319-07935-6

Mueller, Matthias; Bogner, Kristina; Buchmann, Tobias; Kudic, Muhamed (2017): The Effect of Structural Disparities on Knowledge Diffusion in Networks: An Agent-Based Simulation Model. In: Journal of Economic Interaction and Coordination 12 (3), S. 613–634. DOI: https://doi.org/10.1007/s11403-016-0178-8

Mueller, Matthias; Pyka, Andreas (2017): Economic Behaviour and Agent-Based Modelling. In: Roger Frantz, Shu-Heng Chen, Kurt Dopfer, Floris Heukelom und Shabnam Mousavi (Hg.): Routledge Handbook of Behavioral Economics. Abingdon: Routledge, S. 405–415.

Nooteboom, Bart; van Haverbeke, Wim; Duysters, Geert; Gilsing, Victor; van den Oord, Ad (2007): Optimal Cognitive Distance and Absorptive Capacity. In: Research Policy 36 (7), S. 1016–1034. DOI: https://doi.org/10.1016/j.respol.2007.04.003

Pyka, Andreas; Fagiolo, Giorgio (2007): Agent-Based Modelling: A Methodology for Neo-Schumpeterian Economics. In: Horst Hanusch und Andreas Pyka (Hg.): The Elgar Companion to Neo-Schumpeterian Economics. Cheltenham: Edward Elgar Publishing, S. 467–492.

Starfield, Anthony M. (1990): Qualitative, Rule-Based Modeling. In: Bioscience 40 (8), S. 601–604. DOI: https://doi.org/10.2307/1311300

Wooldridge, Michael; Jennings, Nicholas R. (1995): Intelligent Agents: Theory and Practice. In: The Knowledge Engineering Review 10 (2), S. 115–152. DOI: https://doi.org/10.1017/S0269888900008122

Forschungsdaten:

BMBF – Bundesministerium für Bildung und Forschung (2017): Förderkatalog. Online verfügbar unter http://www.foerderportal.bund.de/foekat, zuletzt geprüft am 01. 06. 2017.

EU – Europäische Kommission (2017): CORDIS. Forschungs- & Entwicklungsinformationsdienst der Gemeinschaft. Online verfügbar unter http://www.cordis.europa.eu, zuletzt geprüft am 01. 06. 2017.

Published

18.12.2017

How to Cite

1.
Müller M, Kudic M, Pyka A. Ex-Ante Evaluation of Investments in Knowledge, Learning, and Innovation: An Application Example. TATuP [Internet]. 2017 Dec. 18 [cited 2024 Mar. 28];26(3):51-7. Available from: https://www.tatup.de/index.php/tatup/article/view/67