2017
DOI: 10.1016/j.ifacol.2017.08.1139
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Structural Effects and Aggregation in a Social-Network Model of Natural Resource Consumption

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Cited by 7 publications
(4 citation statements)
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“…Family members, neighbours, friends, colleagues, superiors and experienced individuals known by a person may influence that person to be more aware of a product or service. Members of a cohesive group are likely to be more aware of each other's opinions due to efficiency in communicating opinions among themselves (Friedkin, 2006). In investigating the respondents' awareness of energy conservation, for example, Nolan et al (2008) found that neighbours have the strongest effect.…”
Section: Social Influencementioning
confidence: 99%
“…Family members, neighbours, friends, colleagues, superiors and experienced individuals known by a person may influence that person to be more aware of a product or service. Members of a cohesive group are likely to be more aware of each other's opinions due to efficiency in communicating opinions among themselves (Friedkin, 2006). In investigating the respondents' awareness of energy conservation, for example, Nolan et al (2008) found that neighbours have the strongest effect.…”
Section: Social Influencementioning
confidence: 99%
“…This section describes the system model of interest and its coupled resource and consumption dynamics. The model was first presented in [10] and subsequently studied in [17], [19], [20]. For full details on the environmental and social-psychological foundations of the model, we refer the reader to the sources mentioned above.…”
Section: Background and Network Modelmentioning
confidence: 99%
“…Note that this assumption is the same used in defining homogeneous consumer networks in [5]. Below, the networklevel dynamics will be derived by considering the new state variables z = log x and u = n i=1 y i .…”
Section: A Transformed Leaderless Aggregate Dynamicsmentioning
confidence: 99%
“…This paper studies the behavior of a consumption network under the assumption that it is leaderless: that one agent will not drive the social network component of the model more than any other agent in the network. This assumption allows an aggregation of individual state nodes [5], facilitating an understanding of the system-level behavior. Discussing a consuming population in aggregate is a common tool for the study of resource consumer social networks [19] and allows for the design of actions taken to change behavior, which often happen at the community level [18].…”
Section: Introductionmentioning
confidence: 99%