Geospatial distance in environmental governance networks: metrics, models, and implications.

Josh Redmond


Social networks are almost always embedded in a geographical context - whether between people, or organisations. Whilst telecommunications technologies have the potential to allow for new connections to be made, and connections to be maintained, across significant geographical distances - effects such as propinquity, and exchange of tacit information aided by in person meetings, are presumably aided by being in close physical proximity. However, distance is not a one dimensional measure - and can be represented in a variety of ways: does distance matter because it limits physical access, because it indicates a proxy for ‘place’, or because distance per se imposes some additional constraint on tie formation. There is no consensus on what distance between two network actors means, and is obviously heavily influenced by network context. In the context of environmental governance, geographic distance between governance actors can be a central factor in the overall success of the network - with phenomena such as scalar mismatch being examples of the role that this distance can play. However, despite the fact that distance is acknowledged as being of significant importance in studying network structure, there is no consensus on how distance should be measured, operationalised, or modelled. For any given pair of actors in a network - distance can be represented as a simple euclidean distance, adjusted for road/transportation networks, examined as overlapping pools of use, or instead modelled as travel time. Each of these metrics is different conceptually, and may cause the same method to produce very different results, which should be interpreted differently. Despite this however, there is no consensus on how to model distance in environmental governance networks. This is of particular interest in urban areas, where a strong sense of place may interact with other spatial effects, and where distance and accessibility become somewhat uncoupled thanks to complex transportation networks. This presentation will examine a network of collaboration between environmental stewardship organisations in New York City, demonstrate several different methods for modelling geographic distance and related effects - and use exponential random graph models to compare each distance measure - with the goal of shedding some light on how to improve the modelling of spatial effects in environmental governance networks.

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