Discontinuity, Nonlinearity, and Complexity
A Dynamic Systems Approach to the Representation of Policy Implementation Processes in a Multi-Actor World
Discontinuity, Nonlinearity, and Complexity 6(3) (2017) 219--245 | DOI:10.5890/DNC.2017.09.001
Dmitry V. Kovalevsky$^{1}$,$^{2}$,$^{3}$, Richard Hewitt$^{4}$,$^{5}$, Cheryl de Boer$^{6}$, Klaus Hasselmann$^{7}$,$^{8}$
$^{1}$ Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht, Fischertwiete 1, 20095 Hamburg, Germany
$^{2}$ Nansen International Environmental and Remote Sensing Centre, 14th Line 7, office 49, Vasilievsky Island, 199034 St. Petersburg, Russia
$^{3}$ Saint Petersburg State University, Universitetskaya emb. 7-9, 199034 St. Petersburg, Russia
$^{4}$ Observatorio para una Cultura del Territorio, C/ Duque de Fern´an N´u˜nez 2, 1, Madrid, 28012, Spain
$^{5}$ James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, Scotland, UK
$^{6}$ University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), P.O Box 6, 7500 AA Enschede, Netherlands
$^{7}$ Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
$^{8}$ Global Climate Forum, Neue Promenade 6, 10178 Berlin, Germany
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Abstract
Implementation of any policy involves negotiation between multiple actors, and is therefore susceptible to a dynamic systems modelling approach. In this paper, we make an attempt to develop a family of dynamic systems models of policy implementation in such a multi-actor world by translating an existing, semi-quantitative, application of two theoretical approaches, Contextual Interaction Theory (CIT) and Participatory Action Research (PAR), into a quantitative dynamic framework. We explore various alternative actor-based dynamic systems for this proposed Participatory Contextual Interaction Theory (PCIT), including linear, piecewise linear, and strongly nonlinear models. Analytical results are supplemented with results of numerical simulations. One of the goals of the modelling exercise is to advance the actor dynamics module in the APoLUS land use cellular automata model; illustrative examples of the incorporation of actor dynamics models developed in the present paper into the computation of APoLUS transition potentials are provided.
Acknowledgments
The research leading to the reported results has received funding from the European Community’s Seventh Framework Programme under Grant Agreement No. 308601 (COMPLEX).
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