Simulating Knowledge Dynamics in Innovation Networks by Nigel Gilbert, Petra Ahrweiler, Andreas Pyka

Simulating Knowledge Dynamics in Innovation Networks by Nigel Gilbert, Petra Ahrweiler, Andreas Pyka

By Nigel Gilbert, Petra Ahrweiler, Andreas Pyka

The competitiveness of corporations, areas and nations significantly is determined by the iteration, dissemination and alertness of recent wisdom. sleek innovation examine is challenged through the necessity to include wisdom new release and dissemination approaches into the research on the way to disentangle the complexity of those dynamic approaches. With innovation, even though, powerful uncertainty, nonlinearities and actor heterogeneity develop into crucial components which are at odds with conventional modeling strategies anchored in equilibrium and homogeneity.

This textual content introduces epidermis (Simulation wisdom Dynamics in Innovation Networks), an agent-based simulation version that basically makes a speciality of joint wisdom production and alternate of data in innovation co‐operations and networks. during this context, wisdom is explicitly modeled and never approximated by way of, for example, the extent of accrued R&D funding. the outside process helps functions in several domain names starting from sector-based examine actions in knowledge-intensive industries to the actions of foreign examine consortia engaged in uncomplicated and utilized learn.

Following a common description of the outside version, numerous functions and ameliorations are provided. every one bankruptcy introduces intimately the constitution of the version, the correct methodological issues and the research of simulation effects, whereas recommendations for empirically validating the types’ constitution and results also are mentioned. The publication considers the scope of additional functions and descriptions clients for the improvement of joint modeling strategies.

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Extra resources for Simulating Knowledge Dynamics in Innovation Networks

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Since some firms do not fit neatly into either category, we also asked the strategic analysts at Telenor to indicate roughly how many firms should be allocated to the different categories. 1. While the dynamic character of the industry and use of collaborations are well known, we know relatively little about how firm level strategies and decisions affect the macro-level evolution of inter-firm networks and the capacity of the industry as a whole to generate novelty. Based on the above stylized facts, we develop an agent-based model to explore this relationship further.

5 are roughly the same. This means that the number of capabilities that constitutes a service is about the same, and in turn that the way services are made by firms is not influenced by inter-firm collaboration or innovation strategies. The number of capabilities in a service is then not particularly affected by the change of strategy in scenario 2. When access ISPs change their strategy in scenario 2 and begin to learn from other firms with knowledge areas more unknown to themselves, we observe a higher degree of clustering of capabilities.

43 smaller specialized firms that are more vulnerable to experimentation. On a macrolevel, the interconnection of knowledge resources and the resultant eradication of isolated pockets of knowledge might reduce the network’s potential for generating novelty. On a more general theoretical level, the model results are in line with past ABM analyses on the relationship between firm level strategies and macro-level networks (Gilbert et al. 2001; Ozman 2007, Antonelli and Ferraris 2011), but complements these in one important way.

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