The objective of this research is to identify the role of network architecture in influencing individual travel behavior using travel survey data from two urban areas in Florida: Fort Lauderdale and Miami. Various measures of network structure, compiled from existing sources, are used to...

Literature claims for a deeper understanding of which processes shape the evolution of network structures over time. Drawing on the assumption that the “normative ideal” network structure should be understood according to the context in which the network is embedded, we observe collaborative...

In an urban context people travel between places of residence and work destinations via transportation networks. Transportation studies that involve measurements of distances between residence and work locations tend to use Euclidean distances rather than Network distances. This is due to the...

We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents apply a heuristic rule to aggregate predecessors' actions. They weigh these actions according the strengths of their social connections to different predecessors. We show this...

Consider a group of agents embedded in a network, repeatedly playing a game with their neighbors. Each agent acts locally but through the links of the network local decisions percolate to the entire population. Past research shows that such a system converges either to an absorbing state (a...

We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents apply a heuristic rule to aggregate predecessors' actions. They weigh these actions according the strengths of their social connections to different predecessors. We show this...