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ICITIES Report Summary

Project ID: IST-1999-11337
Funded under: FP5-IST
Country: Greece

iCities project book incorporating progress achieved in all workpackages and highlighting results from various deliverables

Information cities project defining issue was the need to respond to the basic question of how the web economy organizes its use of (virtual) space: explain evident concentrations of population and economic activity over the web (information cities) and illuminate fast growth rates obtained by leading web locations. In this project we have modelled the self-reinforcing forces that drive growth and prosperity in the web ecosystem and support the process of formation and evolution of information cities. We show that the strong organization of the web economy around a handful of locations is clearly something that has emerged, not necessarily because of any inherent initial qualities of different web sites (is so different from but rather through self-organization involving various feedback mechanisms.

In fact, the picture that results from our theories and models, based on both, i) appreciative (empirically observing key-Internet players' behaviours) and, ii) formal theorizing (modelling these behaviours within a "built-from-scratch" computational web economy and running multiple experiments) demonstrates that:

All these concentrations of population in particular web locations form and survive because of some form of agglomeration economies (fuelled, in most cases, by informational increasing returns), in which concentration and growth themselves create the favourable environment that supports further or continued concentration and even faster growth. The above conclusion was reached by developing a modelling framework, which can account for both strong patterns of growth obtained in the web economy (concentrations of population and economic activity over the web, and, fast growth rates obtained by leading web locations). Research and development of such a modelling framework was the primary strategic objective of iCities Project.

The developed modelling framework i) follows a "bottom-up" approach: web sites' growth and population agglomeration, emerge endogenously from the behaviour of individual agents (i.e. web sites and Internet visitors) and the various interactions between them, and ii) takes into account the agglomeration economies present in the World Wide Web. In this framework we have developed three particular agent-based models and a simulation infrastructure to satisfy the particular requirements of our models.

First model's starting question is simple: Why cities, information cities, i.e. large agglomerations of people and economic activity emerge in the virtual world, and why web economy exemplifies particularly fast growth rates for its elements. The model provides a sound basis for the dynamics of population concentration in the Web and put forward an explanation to web sites' exceptionally high growth rates, by developing a simulated web economy, with behavioural and economic variables. The model i) reproduces the empirically observed power law distribution of Internet users across web sites, and ii) suggests that the existence of particularly strong, and rapidly formed, agglomeration patterns in the web involves a specific growth process that emerges from various forms of informational increasing returns.

The second model has the main objective to examine evolutionary dynamics in the formation of the web geography and economy by studying an experimental very complex environment. From various model simulations, we have been able to investigate rules of competition and success strategies within this experimental web economy. More precisely, we have obtained fast growth pattern for web leaders (largely depending on the structure of the networks carrying agents' decisions) and co-existence of highly diversified, partially diversified and specialized sites.

The main objective of the third model is to frame the forces that drive the phenomenon of aggregation of merchant web sites (B-to-C) competing in a differentiated electronic market where search cost (costs related to find a good in a differentiated market) for the consumers are independent of their adaptation/transportation cost (when the good they find does not match with their preference).

The simulation infrastructure (large-scale agent-based simulation environment) has been built to provide opportunities for experimentation and progressive formation of global dynamic behaviours. The environment has two versions, a sequential executing on a single workstation, and a parallel executing on a cluster of workstations. Multiple experiments showed scalability and speedup when executed in both clusters of workstations and multiprocessors machine.

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