Economic and sociological theories increasingly highlight the importance of social networks for the diffusion of technological innovations. However, while it is generally agreed that network structure affects the speed and scale of technology diffusion by offering efficient communication channels for the transfer of information, it seems that current literature does not say whether also the process of diffusion can affect the very structure of the networks on which it occurs. We attempt to address this gap by examining how the spread of a technological innovation influences patterns of dyadic relationships within a large social network and, in turn, how those changes interact with the diffusion process. In this paper we develop a computer simulation applying agent based modeling techniques and use it to inquire about the feedback loop between the number of adopters and diffusion as well as about the extent to which local bandwagon forces reshape entire networks that generate them. Our initial results show, first, the emergence of an interesting phase transition in the speed of technology diffusion and, second, the acquisition of a complex property by the network structure when the stability of social ties, the average number of connections per agent, and certain agent internal characteristics are manipulated.

The Complex Dynamics of Innovation Diffusion and Social Structure: A Simulation Study

SIMONI, MICHELE;
2006

Abstract

Economic and sociological theories increasingly highlight the importance of social networks for the diffusion of technological innovations. However, while it is generally agreed that network structure affects the speed and scale of technology diffusion by offering efficient communication channels for the transfer of information, it seems that current literature does not say whether also the process of diffusion can affect the very structure of the networks on which it occurs. We attempt to address this gap by examining how the spread of a technological innovation influences patterns of dyadic relationships within a large social network and, in turn, how those changes interact with the diffusion process. In this paper we develop a computer simulation applying agent based modeling techniques and use it to inquire about the feedback loop between the number of adopters and diffusion as well as about the extent to which local bandwagon forces reshape entire networks that generate them. Our initial results show, first, the emergence of an interesting phase transition in the speed of technology diffusion and, second, the acquisition of a complex property by the network structure when the stability of social ties, the average number of connections per agent, and certain agent internal characteristics are manipulated.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/24036
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