A Simulation of Strategic Bargainings within a Biotechnology Cluster

A Simulation of Strategic Bargainings within a Biotechnology Cluster

A. Berro (Toulouse University, France) and I. leroux (Le Mans University, France)
DOI: 10.4018/978-1-59140-984-7.ch023
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This chapter introduces artificial life as a means of exploring strategic relations dynamics between firms and local authorities within a local biotechnology cluster. It argues that artificial life, combined with a conception of bioclusters as complex adaptive systems, offers a significant approach to understanding the co-evolution of strategies and the potential vulnerability of such systems. The simulation model involves firms and local government administrations that negotiate to share a quasi-rent, and which, to this end, use strategies that are to a greater or lesser extent sophisticated or opportunistic. The results show that the firms adjust their bargaining strategies according to their assessment of gains which might be collectively generated. The results also bring to light that the local authorities play a regulatory role against opportunism and that they are the key players in local coordination. Stemming from these simulations, the authors develop promising new avenues of theoretical and empirical research.

Key Terms in this Chapter

Path Dependency: Path dependency is the dependence of the outcome of a dynamic process on historical events. So learning process and auto-reinforcement mechanisms lead to the irreversibility of the cluster dynamics.

Clusters: According to the Porter (1998) definition, clusters are geographic concentrations of interconnected companies, specialized suppliers, service providers, firms in related industries, and associated institutions (universities, standards agencies, trade associations) in a particular field that compete but also cooperate. Clusters can be specialized in biotechnology, computing, wine, electronics, and so forth. One of the best known is the Silicon Valley.

Inductive Learning: The agents are individually involved in a cognitive process of problem solving. They learn step by step by experience and they adapt their behaviors according to the different situations previously observed.

Cooperation-Competition: The duality between cooperation and competition is very high within clusters because firms are linked locally both by complementary relations and vigorous competition. This process can contribute to innovation and collective performance. In this case, cooperation and competition can coexist because they are on different dimensions.

Relational Quasi-Rent: The relational quasi-rent is a surplus generated by a cooperation process involving several actors linked by complementarities (firms, institutions). This surplus cannot be appropriated by one actor to the detriment of the others because of its collective nature. So the sharing of the quasi-rent between the participants can be a big problem because no objective criteria exist for sharing it. Thus, opportunist behaviors can often occur such as “hold up” strategies.

Situated Rationality: The situated rationality of an agent is defined as a limited rationality fundamentally linked to the context of interaction. The problem-solving process of each agent takes into account the links with his environment, such as for example the proximity links built with some of the agents involved.

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