|InterJournal Complex Systems, 1688
|Manuscript Number: |
Submission Date: 2006
|Hypercompetitive environments: an agent based model approach|
Globalisation, technological advances and increasing innovation have created complex and unpredictable climates in which Information Systems (IS) companies must operate. Porter (1991) recognised the lack of new frameworks to deal with hypercompetitive environments, with extreme dynamics and aggressive strategies. Traditional strategy theories and tools, based on static models, can lead to less flexible and more predictable enterprises, and, consequently, more vulnerable to their competitors. Thus, the development of dynamic models accounting internal, external and collective environment factors is crucial to successfully define business strategies. Complex systems approach, based on agent modelling has been proved to be a suitable tool to deal with individual and collective enterprises behaviour, as well as interdependent and non-linear aspects of business strategies, under interconnected and extremely dynamic systems. This paper presents an agent-based model to business strategies definition focused on enterprises operating under high competitive environments, in order to reach comprehension of systemic patterns and short-term forecasting. Local interaction between agents intends to model direct competition between firms operating at the same market segment and the consideration of general environment parameters with impact over all intervenients, provides individual and collective behaviour of IS enterprises. The model simulation has been done according a set of representative economic scenarios and some well known firmsí characteristics, such as flexibility and mobility. Simulations results provided important conclusions concerning the strategic resources distribution, differentiation strategies, asymmetric valorisation of local competition versus wide influence over all intervenients and, at last, polarized strategic investments. Such conclusions should be, in our opinion, verified through model instantiation with real data, to validate assumptions and to sediment key issues, that we believe, will help IS top management in the strategic choice process.
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