nep-net New Economics Papers
on Network Economics
Issue of 2009‒09‒11
three papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. A model of influence in a social network By Michel Grabisch; Agnieszka Rusinowska
  2. "Territorial innovation dynamics: a knowledge based perspective" By Karine Roux; Rani Jeanne Dang; Catherine Thomas; Christian Longhi; D. Talbot
  3. An Interdisciplinary Approach to Coalition Formation By Rudolf Berghammer; Agnieszka Rusinowska; Harrie De Swart

  1. By: Michel Grabisch (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, LIP6 - Laboratoire d'Informatique de Paris 6 - CNRS : UMR7606 - Université Pierre et Marie Curie - Paris VI); Agnieszka Rusinowska (GATE - Groupe d'analyse et de théorie économique - CNRS : UMR5824 - Université Lumière - Lyon II - Ecole Normale Supérieure Lettres et Sciences Humaines)
    Abstract: In this paper, we study a model of influence in a social network. It is assumed that each player has an inclination to say YES or NO which, due to influence of other players, may be different from the decision of the player. The point of departure here is the concept of the Hoede-Bakker index—the notion which computes the overall decisional ‘power' of a player in a social network. The main drawback of the Hoede-Bakker index is that it hides the actual role of the influence function, analyzing only the final decision in terms of success and failure. In this paper, we separate the influence part from the group decision part, and focus on the description and analysis of the influence part. We propose among other descriptive tools a definition of a (weighted) influence index of a coalition upon an individual. Moreover, we consider different influence functions representative of commonly encountered situations. Finally, we propose a suitable definition of a modified decisional power.
    Keywords: Influence function ; Influence index ; Decisional power ; Social network
    Date: 2009
  2. By: Karine Roux (CEREFIGE - Institut National Polytechnique de Lorraine - INPL); Rani Jeanne Dang (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis); Catherine Thomas (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis); Christian Longhi (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis); D. Talbot (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - CNRS : UMR5113 - Université Montesquieu - Bordeaux IV)
    Abstract: A great deal of studies has focused on the role played by geographical location on the emergence and the building of localised learning capacities (Maskell, Malmberg, 1999). In this perspective, empirical studies have demonstrated that innovation dynamics of clusters results from the quality of interactions and coordination inside the cluster as well as interactions with external, often global, networks. In this context, knowledge exchange between firms and institutions are claimed to be the main drivers of spatial agglomeration (Canals et al, 2008). Hence, cluster policies have followed the main idea that geographic proximity facilitates collective innovation in so far as firms can capture knowledge externalities more easily. This idea is in fact very attractive but contains some limits (Suire et Vicente, 2007): if some clusters are successful others seem to decline. Therefore, in order to understand the territorial dynamics of clusters, the analysis of the specific nature of knowledge and information flows within a cluster is crucial. The objective of the paper is to enhance the analysis of the role of cognitive and relational dimensions of interactions on territorial dynamics of innovation. We focus on the key sub process of innovation: knowledge creation, which is above all a social process based on two key complex social mechanisms: the exchange and the combination of knowledge (Nahapiet and Goshal, 1996). We suggest building a theoretical framework that hinges on these two key mechanisms. In this perspective, we mobilise Boisot's I-Space model (Boisot, 1998) for the diffusion and exchange of knowledge and suggest completing the model by introducing the concept of architectural knowledge (Henderson and Clark, 1990) so as to take the complexity of the combination process into consideration. This analysis is conducted through the illustrative analysis of three different case studies. We will draw upon the case of Aerospace Valley Pole of Competitiveness (PoC), The Secured Communicating Solutions PoC, and Fabelor Competence Cluster. The cases show that the existence of architectural knowledge is pivotal to territorial innovation.
    Keywords: Architectural Knowledge, I-Space Model, Territorial Innovation, Geographical Clusters, Knowledge Management
    Date: 2009–07–06
  3. By: Rudolf Berghammer (Computer-Aided Program Development - Institute of Computer Science - Christian-Albrechts-Universität, Kiel); Agnieszka Rusinowska (GATE - Groupe d'analyse et de théorie économique - CNRS : UMR5824 - Université Lumière - Lyon II - Ecole Normale Supérieure Lettres et Sciences Humaines); Harrie De Swart (Faculteit Wijsbegeerte-Logica en taalanalyse - Universiteit van Tilburg)
    Abstract: A stable government is by definition not dominated by any other government. However, it may happen that all governments are dominated. In graph-theoretic terms this means that the dominance graph does not possess a source. In this paper we are able to deal with this case by a clever combination of notions from different fields, such as relational algebra, graph theory and social choice theory, and by using the computer support system RelView for computing solutions and visualizing the results. Using relational algorithms, in such a case we break all cycles in each initial strongly connected component by removing the vertices in an appropriate minimum feedback vertex set. In this way we can choose a government that is as close as possible to being un-dominated. To achieve unique solutions, we additionally apply the majority ranking recently introduced by Balinski and Laraki. The main parts of our procedure can be executed using the RelView tool. Its sophisticated implementation of relations allows to deal with graph sizes that are sufficient for practical applications of coalition formation.
    Keywords: Graph theory; RelView; relational algebra; dominance; stable government
    Date: 2009

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