ICT Revolution, Globalization and Informational Lock-in

We examine a model of social learning in networks following the lines of Bala and Goyal (1998, 2001). As a model of agents’ behaviour we have chosen the model of informational cascades of Bikhchandani et al (1992). Similarly to Bala and Goyal we find that the higher the ’degree of integration’ within the society is, the more likely it is that conformity of actions will arise. However, unlike their results our model suggests that in the presence of informational externalities globalisation of informational flows, expressed in the increasing density of communication channels in a network, may drive down the expected social welfare.Social learning, Cascades, Globalization, Networks

ICT Revolution, Globalization and Informational Lock-in

We examine a model of social learning in networks following the lines of Bala and Goyal (1998, 2001). As a model of agents’ behaviour we have chosen the model of informational cascades of Bikhchandani et al (1992). Similarly to Bala and Goyal we find that the higher the ’degree of integration’ within the society is, the more likely it is that conformity of actions will arise. However, unlike their results our model suggests that in the presence of informational externalities globalisation of informational flows, expressed in the increasing density of communication channels in a network, may drive down the expected social welfare.microeconomics ;

Topological resilience in non-normal networked systems

The network of interactions in complex systems, strongly influences their resilience, the system capability to resist to external perturbations or structural damages and to promptly recover thereafter. The phenomenon manifests itself in different domains, e.g. cascade failures in computer networks or parasitic species invasion in ecosystems. Understanding the networks topological features that affect the resilience phenomenon remains a challenging goal of the design of robust complex systems. We prove that the non-normality character of the network of interactions amplifies the response of the system to exogenous disturbances and can drastically change the global dynamics. We provide an illustrative application to ecology by proposing a mechanism to mute the Allee effect and eventually a new theory of patterns formation involving a single diffusing species

Topological resilience in non-normal networked systems

The network of interactions in complex systems, strongly influences their resilience, the system capability to resist to external perturbations or structural damages and to promptly recover thereafter. The phenomenon manifests itself in different domains, e.g. cascade failures in computer networks or parasitic species invasion in ecosystems. Understanding the networks topological features that affect the resilience phenomenon remains a challenging goal of the design of robust complex systems. We prove that the non-normality character of the network of interactions amplifies the response of the system to exogenous disturbances and can drastically change the global dynamics. We provide an illustrative application to ecology by proposing a mechanism to mute the Allee effect and eventually a new theory of patterns formation involving a single diffusing species