Zimmermann
Jean-Benoît Zimmermann
Publications
This book continues in a tradition which has developed in the annual Workshops on Economics with Heterogeneous Interacting Agents, (WEHIA). The purpose of that workshop was to analyse situations in which individual agents, who might be different from each other, interact and produce behaviour on the aggregate level which does not correspond to that of the average actor. This rupture with the well-established tradition of the “representative individual” is far from having established a central position in economics. That the relaxation of that assumption and the introduction of heterogeneous individuals might change the relationship between micro behaviour and macro phenomena is clearly spelled out by Forni and Lippi(1997). The modelling of the actual interaction between these individuals has been and remains a challenge. Early analytical attempts to introduce direct and local interaction between agents such as in the pioneering work of Follmer (1974) met with little response and the recent wave of interest associated with the names of Aoki (1996) Durlauf (1997) and Blume (1993) amongst others was twenty years in the making. Yet, the influence of other disciplines such as physics and biology in which complex interactive systems and their analysis play a central role is now making itself felt in economics and the papers in this volume reflect that fact.
This book continues in a tradition which has developed in the annual Workshops on Economics with Heterogeneous Interacting Agents, (WEHIA). The purpose of that workshop was to analyse situations in which individual agents, who might be different from each other, interact and produce behaviour on the aggregate level which does not correspond to that of the average actor. This rupture with the well-established tradition of the “representative individual” is far from having established a central position in economics. That the relaxation of that assumption and the introduction of heterogeneous individuals might change the relationship between micro behaviour and macro phenomena is clearly spelled out by Forni and Lippi(1997). The modelling of the actual interaction between these individuals has been and remains a challenge. Early analytical attempts to introduce direct and local interaction between agents such as in the pioneering work of Follmer (1974) met with little response and the recent wave of interest associated with the names of Aoki (1996) Durlauf (1997) and Blume (1993) amongst others was twenty years in the making. Yet, the influence of other disciplines such as physics and biology in which complex interactive systems and their analysis play a central role is now making itself felt in economics and the papers in this volume reflect that fact.
Diverse approaches of innovation diffusion, in the presence of increasing returns, have been outlined or explored in the recent literature. We propose, four ourselves, to take into account the idea that agents, in the situation to adopt or not an innovation or a new technological standard, are “situated” within a social network, that is the support of influence effects. Our approach aim is here to explore the role of learning processes into the propagation dynamics within a network structure. In a recent model, formally represented by a neural network, we have introduced a relational learning that constitutes a way to set up an endogenous network evolution. We prove the existence of a self organised criticality phenomenon, where some agents acquire key-positions within the network that bring them a strong structural capacity of influence over the whole population of potential adopters. In this paper, we study the way how network auto-organisation can lead, under given conditions, to a critical state characterised by macroscopic effects generated from microscopic impulses at the level of the individual agent. It is the peculiar structure of those critical networks that allow macroscopic “avalanches” to take place, on which the diffusion process is likely to lean. We analyse the way learning leads endogenously to such a critical state and how it strikes against the finite size of the network.
Diverse approaches of innovation diffusion, in the presence of increasing returns, have been outlined or explored in the recent literature. We propose, four ourselves, to take into account the idea that agents, in the situation to adopt or not an innovation or a new technological standard, are “situated” within a social network, that is the support of influence effects. Our approach aim is here to explore the role of learning processes into the propagation dynamics within a network structure. In a recent model, formally represented by a neural network, we have introduced a relational learning that constitutes a way to set up an endogenous network evolution. We prove the existence of a self organised criticality phenomenon, where some agents acquire key-positions within the network that bring them a strong structural capacity of influence over the whole population of potential adopters. In this paper, we study the way how network auto-organisation can lead, under given conditions, to a critical state characterised by macroscopic effects generated from microscopic impulses at the level of the individual agent. It is the peculiar structure of those critical networks that allow macroscopic “avalanches” to take place, on which the diffusion process is likely to lean. We analyse the way learning leads endogenously to such a critical state and how it strikes against the finite size of the network.
[eng] While adopting an approach of innovation diffusion in terms of interacting agents, we emphasise the role of cumulated influence in the context of social networks. We first introduce a cumulative effect in the classical epidemic model which involves a slower starting phase followed by a more pronounced acceleration phase. We then show that the topology of the network affects both equilibrium selection as well the pace of diffusion. Hence the nature of uncertainty characterising the diffusion process is affected by the structure of the network and the distribution of initial adopters.
[fre] En nous situant dans le cadre des modèles interactionnistes de diffusion de l'innovation, nous mettons en évidence le rôle joué par la notion de cumul d'influence dans un contexte de réseaux sociaux. Nous introduisons d'abord un effet de cumul dans le modèle épidémique classique se traduisant par un démarrage plus lent et une phase d'accélération plus marquée. Nous montrons ensuite que la topologie du réseau peut intervenir aussi bien dans la détermination de l'équilibre atteint que dans celle de la vitesse de diffusion. L'issue de la diffusion est ainsi marquée d'une forme d'incertitude qui confère un rôle essentiel à la structure du réseau et à la distribution des adopteurs initiaux.
L\'existence et le développement d\'un pôle, d\'une filière micro-électronique, dans la Haute-Vallée de l\'Arc et dans l\'Aire Métropolotaine Marseillaise, relèvent à tous égards d\'une réalité paradoxale. Si d\'aucuns la voient comme l\'une des manifestations du développement d\'activités de hautes technologies dans le Pays d\'Aix, force est de reconnaître que ce pôle est né et s\'est développé selon une logique...Mots-clés (fr)industriehistoire
No abstract is available for this item.
[eng] Over the last ten years, diffusion models have been improved by including network externalities. We briefly outline the main approaches developed to date and describe the basis of an approach to take account of different interindividual influences in a population. We then present an empirical validation based on two contemporary examples in France. The first is cable television, which is expected to present social utility via mimetic effects. The second example is the fax, which presents strong interindividual externalities. Its utility stems from the possibility for players to use it to communicate with their contacts.
[fre] Les modèles de diffusion se sont enrichis depuis une dizaine d'années par la prise en compte des effets d'externalités de réseau. Après un rapide survol des principales approches développées jusqu'ici, nous exposons les fondements d'une démarche visant à intégrer la différenciation de l'influence interindividuelle au sein d'une population. Nous présentons ensuite un travail de validation empirique sur deux exemples contemporains, en France. Le premier concerne la télévision par câble. Ce produit présente a priori une utilité sociale par effet de mimétisme. Le deuxième exemple concerne le fax. Ce produit comporte de fortes externalités interindividuelles. Son utilité dérive pour l'essentiel de la possibilité pour un agent de communiquer par ce moyen avec les personnes avec lesquelles il est en relation.
The aim of this paper is to lay the foundations of 3 social influence based approach for the diffusion of an innovation or a technological standard. A model built on the principles of a neural network is proposed and a learning procedure is set up, making the network formation endogenous, the strength of connections among agents being determined by their shared histories, Referring to the concept of criticality developed by physicists, it shall be shown that learning, in a social structure, can lead the network to a critical state, called 'learning induced criticality, where some agents are able to exert a macroscopic influence over the network. The distribution of influence spheres' size follows a Pareto law. This approach shows an interesting similatry with that of the social coherence in sociology, whereby individuals within a social structure are led to share a close assessment of a given innovation.
[eng] This paper can be related with the field of network externalities and increasing returns of adoption. We present the foundations of an approach and a model able to take in account the influence of effective relationship between agents onto the adoption-diffusion process of an innovation or a technological standard. Therefore we locate our research at the confluence of network externalities and social networks approaches. A simulation process provides first informations on those network behaviours, while an empirical application on fax diffusion in France bears out the soundness of the method by comparison with the traditional diffusion approach. [fre] Cet article se situe dans le champ des externalités de réseau et des rendements croissants d'adoption. Nous proposons les fondements d'une approche et d'un modèle qui rendent compte de l'influence de la topologie des relations effectives entre les agents sur les mécanismes de l'adoption - diffusion d'une innovation ou d'un standard technologique. Nous situons par conséquent notre démarche au confluent de l'approche des externalités de réseau et de celle des réseaux sociaux. Un travail de simulation permet de donner une première idée de ces comportements « résiliaires », tandis qu'une application empirique sur la diffusion du fax en France confirme l'intérêt de la démarche comparativement à une approche traditionnelle de la diffusion.
