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Agents, Attributes and Strategies

We consider the agents in the model to be industrial firms that perform research. In order to do so, each agent is provided with a set of variables, i.e. agent-specific knowledge endowment, strategies and organisational figures. Thus, the agent population is heterogeneous and dynamic with respect to these attributes.

Knowledge Endowment

The knowledge endowment of the agent represents the agent’s dynamic knowledge base during the simulation. It depicts the technological field the agent is currently active in and upon which it may perform research. A subfield category is included taking into account the fact that the agents may differ with respect to their core competencies, activities and operations. Moreover, an expertise level indicates how frequently and how long the agent has successfully conducted research in the research field and subfield. Formally, the knowledge endowment Ki = {ku, k2i, k3i} of agent ai (i = 1, 2, ..., I) is defined as a set of three so-called kenes kji, similar to the concept of Gilbert (1997). The kene kji consists of a technology class Tjm, a subfield Sj and an expertise level Ej with j = 1, 2, 3 and m = 1,2, ..., M. Hence, the knowledge endowment Ki of agent ai is given by

where I and M denote the empirically determined numbers of agents and technology classes. The domains of the subfield Sj 2 {1, 2, ..., 10} and the expertise level Ej 2 {1, 2, ..., 10} are given by definition (i.e. by model design).

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