EFFECTS OF THE INTERACTION OF HETEROGENEOUS RATIONALITIES ON THE INNOVATION OUTPUT OF FIRMS — A MULTI-AGENT-SYSTEM APPROACH

Alexander Kaufmann

Chapter 11 in Industry and Labor Dynamics:The Agent-Based Computational Economics Approach, 2004, pp 222-243 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractMost innovations are the result of contributions from many agents. Not only the firm which eventually commercializes the innovation but also suppliers, service firms, customers, banks, venture capital providers, universities, contract research organizations or technology centres may have participated in this process. Often the collaborating organizations belong to different societal systems like business, science or politics. As a consequence, they face the problem how to deal with the different rationalities of these systems. They have to establish rules and routines how to integrate them in order to avoid conflicts and to benefit from the diversity of rationalities. As far as innovation is concerned there is a lot of evidence that the interaction between different rationalities, especially between the business and science systems, stimulates more advanced or so-called “radical” innovations, Far more ambiguous is the problem of organizing such multi-system based innovation projects. Two basic types of multi-system innovation processes can be distinguished: on the one hand, hybrid organizations which integrate two or more rationalities within the organization and, on the other hand, co-operations and market transactions between single-system based organizations. The aim of the paper is to present the concept of a simple multi-agent system model that simulates the effects of the interaction between the rationalities of the business and science systems on the innovation process of firms and that enables us to compare the two modes of organization — the internal mode of multi-system based hybrid organizations versus the external mode of co-operation or market transaction between single-system based organizations.

Keywords: Simulation; Agent-Based; Computational Economics; Labor; Industrial Dynamics; Innovation; Cluster; Firm Behavior (search for similar items in EconPapers)
Date: 2004
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