EURACE is a major European attempt to construct an agent-based model of the European economy with a very large population of autonomous, purposive agents interacting in a complicated economic environment. To create it, major advances are needed, in particular in terms of economic modeling and software engineering. In this paper, we describe the general structure of the economic model developed for EURACE and present the Flexible Large-scale Agent Modeling Environment (FLAME) that will be used to describe the agents and run the model on massively parallel supercomputers. Illustrative simulations with a simplified model based on EURACE's labor market module are presented.

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This chapter surveys work dedicated to macroeconomic analysis using an agentbased modeling approach. After a short review of the origins and general characteristics of this approach a systemic comparison of the structure and modeling assumptions of a set of important (families of) agent-based macroeconomic models is provided. The comparison highlights substantial similarities between the different models, thereby identifying what could be considered an emerging common core of macroeconomic agent-based modeling. In the second part of the chapter agent-based macroeconomic research in different domains of economic policy is reviewed.

This paper investigates firms' optimal location choices explicitly accounting for the role of inwards and outwards knowledge spillovers in a dynamic Cournot oligopoly with firms that are heterogeneous in their ability to carry out cost-reducing R&D. Firms can either locate in an industrial cluster or in isolation. Technological spillovers are exchanged between the firms in the cluster. It is shown that a technological leader has an incentive to locate in isolation only if her advantage exceeds a certain threshold, which is increasing in firms' discount rate, in industry dispersion, and in the intensity of knowledge spillovers. Scenarios are identified where although it is optimal for the technological leader to locate in isolation, from a welfare perspective it would be desirable that she locates in the cluster.

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This document provides a description of the modeling assumptions and economic features of the Eurace@Unibi model. Furthermore, the document shows typical patterns of the output generated by this model and compares it to empirically observable stylized facts. The Eurace@Unibi model provides a representation of a closed macroeconomic model with spatial structure. The main objective is to provide a micro-founded macroeconomic model that can be used as a unified framework for policy analysis in different economic policy areas and for the examination of generic macroeconomic research questions. In spite of this general agenda the model has been constructed with certain specific research questions in mind and therefore certain parts of the model, e.g. the mechanisms driving technological change, have been worked out in more detail than others.The purpose of this document is to give an overview over the model itself and its features rather than discussing how insights into particular economic issues can be obtained using the Eurace@Unibi model. The model has been designed as a framework for economic analysis in various domains of economics. A number of economic issues have been examined using (prior versions of) the model (see Dawid et al. (2008) (2010)) and recent extensions of the model have substantially extended its applicability in various economic policy domains, however results of such policy analyses will be reported elsewhere. Whereas the overall modeling approach, the different modeling choices and the economic rationale behind these choices is discussed in some detail in this document, no detailed description of the implementation is given. Such a detailed documentation is provided in the accompanying document Dawid et al. (2011b).

Smart products not only provide novel functionalities, but also may establish new business models, markets, or distribution channels, strengthen relationships with consumers, and/or add smart remote services. While many technical obstacles of such products have already been overcome, the broad market dissemination of smart products still poses some vital managerial challenges for decision makers. In this paper, we outline the technical potential and future trends of smart consumer products, discuss economic challenges in four scopes, namely, preference-based new product development, market analysis, supply chain design, and industry development, and, in particular, we highlight research perspectives for management science in this promising field.