1. Network characterization of the Entangled Model for sustainability indicators. Analysis of the network properties for scenarios
- Author
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Jesús A. del Río, Jiska Joanneke van Dijk, Pável Vázquez, Henrik Jeldtoft Jensen, and Karla G. Cedano
- Subjects
010504 meteorology & atmospheric sciences ,Economics ,Computer science ,Fundamental Interactions ,Social Sciences ,010501 environmental sciences ,Systems Science ,01 natural sciences ,Sustainable Growth ,Feature (machine learning) ,Multidisciplinary ,Physics ,Economic agents ,Sustainable Development ,Nature-Society Interactions ,Multidisciplinary Sciences ,Physical Sciences ,SIMULATION ,Science & Technology - Other Topics ,Medicine ,System Instability ,TANGLED NATURE ,Algorithms ,Network Analysis ,Research Article ,Computer and Information Sciences ,Mathematical optimization ,General Science & Technology ,Science ,Sustainability Science ,Stability (probability) ,Set (abstract data type) ,Clustering Coefficients ,MD Multidisciplinary ,Humans ,Computer Simulation ,Particle Physics ,0105 earth and related environmental sciences ,Clustering coefficient ,Science & Technology ,STABILITY ,Ecology and Environmental Sciences ,Sustainability science ,Models, Theoretical ,Degree distribution ,Elementary Particle Interactions ,Economic Agents ,Graph Theory ,Sustainability ,Samfunnsvitenskap: 200::Økonomi: 210 [VDP] ,Mathematics - Abstract
Artikkel Policy-makers require strategies to select a set of sustainability indicators that are useful for monitoring sustainability. For this reason, we have developed a model where sustainability indicators compete for the attention of society. This model has shown to have steady situations where a set of sustainability indicators are stable. To understand the role of the network configuration, in this paper we analyze the network properties of the Entangled Sustainability model. We have used the degree distribution, the clustering coefficient, and the interaction strength distribution as main measures. We also analyze the network properties for scenarios compared against randomly generated scenarios. We found that the stable situations show different characteristics from the unstable transitions present in the model. We also found that the complex emergent feature of sustainability shown in the model is an attribute of the scenarios, however, the randomly generated scenarios do not present the same network properties.
- Published
- 2018